Friday Foolery #51 Statistically Funny

1 06 2012

Epidemiologists, people working in the EBM field and, above all, statisticians are said to have no sense of humor.*

Hilda Bastian is a clear exception to this rule.

I met Hilda a few years ago at a Cochrane colloquium. At that time she was working as a consumer advocate in Australia. Nowadays she is editor and curator of PubMed Health. According to her Twitter Bio (she tweets as @hildabast) she is (still) “Interested in effective communication as well as effective health care”. She also writes important articles, like “Seventy-Five Trials and Eleven Systematic Reviews a Day: How Will We Ever Keep Up? (PLOS 2010), reviewed at this blog.

Today I learned she also has a great creative talent in cartoon drawing, in the field of …  yeah… EBM, epidemiology & statistics.

Below is one of her cartoons, which fits in well with a recent post in the BMJ by Ray Moynihan, retweeted by Hilda: Preventing overdiagnosis: how to stop harming the healthy. In her post she refers to another article: Overdiagnosis in cancer (JNCI 2010), saying:

“Finding and aggressively treating non-symptomatic disease that would never have made people sick, inventing new conditions and re-defining the thresholds for old ones: will there be anyone healthy left at all?”

I invite you to go and visit Hilda’s blog Statistically funny (Commenting on the science of unbiased health research with cartoons) and to enjoy her cartoons, that are often inspired by recent publications in the field.

* My post #NotSoFunny #16: ridiculing RCTs and EBM even led David Rind to sigh that “EBM folks are not necessarily known for their great senses of humor”. (so I’m no exception to the rule ;)





The Scatter of Medical Research and What to do About it.

18 05 2012

ResearchBlogging.orgPaul Glasziou, GP and professor in Evidence Based Medicine, co-authored a new article in the BMJ [1]. Similar to another paper [2] I discussed before [3] this paper deals with the difficulty for clinicians of staying up-to-date with the literature. But where the previous paper [2,3] highlighted the mere increase in number of research articles over time, the current paper looks at the scatter of randomized clinical trials (RCTs) and systematic reviews (SR’s) accross different journals cited in one year (2009) in PubMed.

Hofmann et al analyzed 7 specialties and 9 sub-specialties, that are considered the leading contributions to the burden of disease in high income countries.

They followed a relative straightforward method for identifying the publications. Each search string consisted of a MeSH term (controlled  term) to identify the selected disease or disorders, a publication type [pt] to identify the type of study, and the year of publication. For example, the search strategy for randomized trials in cardiology was: “heart diseases”[MeSH] AND randomized controlled trial[pt] AND 2009[dp]. (when searching “heart diseases” as a MeSH, narrower terms are also searched.) Meta-analysis[pt] was used to identify systematic reviews.

Using this approach Hofmann et al found 14 343 RCTs and 3214 SR’s published in 2009 in the field of the selected (sub)specialties. There was a clear scatter across journals, but this scatter varied considerably among specialties:

“Otolaryngology had the least scatter (363 trials across 167 journals) and neurology the most (2770 trials across 896 journals). In only three subspecialties (lung cancer, chronic obstructive pulmonary disease, hearing loss) were 10 or fewer journals needed to locate 50% of trials. The scatter was less for systematic reviews: hearing loss had the least scatter (10 reviews across nine journals) and cancer the most (670 reviews across 279 journals). For some specialties and subspecialties the papers were concentrated in specialty journals; whereas for others, few of the top 10 journals were a specialty journal for that area.
Generally, little overlap occurred between the top 10 journals publishing trials and those publishing systematic reviews. The number of journals required to find all trials or reviews was highly correlated (r=0.97) with the number of papers for each specialty/ subspecialty.”

Previous work already suggested that this scatter of research has a long tail. Half of the publications is in a minority of papers, whereas the remaining articles are scattered among many journals (see Fig below).

Click to enlarge en see legends at BMJ 2012;344:e3223 [CC]

The good news is that SRs are less scattered and that general journals appear more often in the top 10 journals publishing SRs. Indeed for 6 of the 7 specialties and 4 of the 9 subspecialties, the Cochrane Database of Systematic Reviews had published the highest number of systematic reviews, publishing between 6% and 18% of all the systematic reviews published in each area in 2009. The bad news is that even keeping up to date with SRs seems a huge, if not impossible, challenge.

In other words, it is not sufficient for clinicians to rely on personal subscriptions to a few journals in their specialty (which is common practice). Hoffmann et al suggest several solutions to help clinicians cope with the increasing volume and scatter of research publications.

  • a central library of systematic reviews (but apparently the Cochrane Library fails to fulfill such a role according to the authors, because many reviews are out of date and are perceived as less clinically relevant)
  • registry of planned and completed systematic reviews, such as prospero. (this makes it easier to locate SRs and reduces bias)
  • Synthesis of Evidence and synopses, like the ACP-Jounal Club which summarizes the best evidence in internal medicine
  • Specialised databases that collate and critically appraise randomized trials and systematic reviews, like www.pedro.org.au for physical therapy. In my personal experience, however, this database is often out of date and not comprehensive
  • Journal scanning services like EvidenceUpdates from mcmaster.ca), which scans over 120 journals, filters articles on the basis of quality, has practising clinicians rate them for relevance and newsworthiness, and makes them available as email alerts and in a searchable database. I use this service too, but besides that not all specialties are covered, the rating of evidence may not always be objective (see previous post [4])
  • The use of social media tools to alert clinicians to important new research.

Most of these solutions are (long) existing solutions that do not or only partly help to solve the information overload.

I was surprised that the authors didn’t propose the use of personalized alerts. PubMed’s My NCBI feature allows to create automatic email alerts on a topic and to subscribe to electronic tables of contents (which could include ACP journal Club). Suppose that a physician browses 10 journals roughly covering 25% of the trials. He/she does not need to read all the other journals from cover to cover to avoid missing one potentially relevant trial. Instead it is far more efficient to perform a topic search to filter relevant studies from journals that seldom publish trials on the topic of interest. One could even use the search of Hoffmann et al to achieve this.* Although in reality, most clinical researchers will have narrower fields of interest than all studies about endocrinology and neurology.

At our library we are working at creating deduplicated, easy to read, alerts that collate table of contents of certain journals with topic (and author) searches in PubMed, EMBASE and other databases. There are existing tools that do the same.

Another way to reduce the individual work (reading) load is to organize journals clubs or even better organize regular CATs (critical appraised topics). In the Netherlands, CATS are a compulsory item for residents. A few doctors do the work for many. Usually they choose topics that are clinically relevant (or for which the evidence is unclear).

The authors shortly mention that their search strategy might have missed  missed some eligible papers and included some that are not truly RCTs or SRs, because they relied on PubMed’s publication type to retrieve RCTs and SRs. For systematic reviews this may be a greater problem than recognized, for the authors have used meta-analyses[pt] to identify systematic reviews. Unfortunately PubMed has no publication type for systematic reviews, but it may be clear that there are many more systematic reviews that meta-analyses. Possibly systematical reviews might even have a different scatter pattern than meta-analyses (i.e. the latter might be preferentially included in core journals).

Furthermore not all meta-analyses and systematic reviews are reviews of RCTs (thus it is not completely fair to compare MAs with RCTs only). On the other hand it is a (not discussed) omission of this study, that only interventions are considered. Nowadays physicians have many other questions than those related to therapy, like questions about prognosis, harm and diagnosis.

I did a little imperfect search just to see whether use of other search terms than meta-analyses[pt] would have any influence on the outcome. I search for (1) meta-analyses [pt] and (2) systematic review [tiab] (title and abstract) of papers about endocrine diseases. Then I subtracted 1 from 2 (to analyse the systematic reviews not indexed as meta-analysis[pt])

Thus:

(ENDOCRINE DISEASES[MESH] AND SYSTEMATIC REVIEW[TIAB] AND 2009[DP]) NOT META-ANALYSIS[PT]

I analyzed the top 10/11 journals publishing these study types.

This little experiment suggests that:

  1. the precise scatter might differ per search: apparently the systematic review[tiab] search yielded different top 10/11 journals (for this sample) than the meta-analysis[pt] search. (partially because Cochrane systematic reviews apparently don’t mention systematic reviews in title and abstract?).
  2. the authors underestimate the numbers of Systematic Reviews: simply searching for systematic review[tiab] already found appr. 50% additional systematic reviews compared to meta-analysis[pt] alone
  3. As expected (by me at last), many of the SR’s en MA’s were NOT dealing with interventions, i.e. see the first 5 hits (out of 108 and 236 respectively).
  4. Together these findings indicate that the true information overload is far greater than shown by Hoffmann et al (not all systematic reviews are found, of all available search designs only RCTs are searched).
  5. On the other hand this indirectly shows that SRs are a better way to keep up-to-date than suggested: SRs  also summarize non-interventional research (the ratio SRs of RCTs: individual RCTs is much lower than suggested)
  6. It also means that the role of the Cochrane Systematic reviews to aggregate RCTs is underestimated by the published graphs (the MA[pt] section is diluted with non-RCT- systematic reviews, thus the proportion of the Cochrane SRs in the interventional MAs becomes larger)

Well anyway, these imperfections do not contradict the main point of this paper: that trials are scattered across hundreds of general and specialty journals and that “systematic reviews” (or meta-analyses really) do reduce the extent of scatter, but are still widely scattered and mostly in different journals to those of randomized trials.

Indeed, personal subscriptions to journals seem insufficient for keeping up to date.
Besides supplementing subscription by  methods such as journal scanning services, I would recommend the use of personalized alerts from PubMed and several prefiltered sources including an EBM search machine like TRIP (www.tripdatabase.com/).

*but I would broaden it to find all aggregate evidence, including ACP, Clinical Evidence, syntheses and synopses, not only meta-analyses.

**I do appreciate that one of the co-authors is a medical librarian: Sarah Thorning.

References

  1. Hoffmann, Tammy, Erueti, Chrissy, Thorning, Sarah, & Glasziou, Paul (2012). The scatter of research: cross sectional comparison of randomised trials and systematic reviews across specialties BMJ, 344 : 10.1136/bmj.e3223
  2. Bastian, H., Glasziou, P., & Chalmers, I. (2010). Seventy-Five Trials and Eleven Systematic Reviews a Day: How Will We Ever Keep Up? PLoS Medicine, 7 (9) DOI: 10.1371/journal.pmed.1000326
  3. How will we ever keep up with 75 trials and 11 systematic reviews a day (laikaspoetnik.wordpress.com)
  4. Experience versus Evidence [1]. Opioid Therapy for Rheumatoid Arthritis Pain. (laikaspoetnik.wordpress.com)




Can Guidelines Harm Patients?

2 05 2012

ResearchBlogging.orgRecently I saw an intriguing “personal view” in the BMJ written by Grant Hutchison entitled: “Can Guidelines Harm Patients Too?” Hutchison is a consultant anesthetist with -as he calls it- chronic guideline fatigue syndrome. Hutchison underwent an acute exacerbation of his “condition” with the arrival of another set of guidelines in his email inbox. Hutchison:

On reviewing the level of evidence provided for the various recommendations being offered, I was struck by the fact that no relevant clinical trials had been carried out in the population of interest. Eleven out of 25 of the recommendations made were supported only by the lowest levels of published evidence (case reports and case series, or inference from studies not directly applicable to the relevant population). A further seven out of 25 were derived only from the expert opinion of members of the guidelines committee, in the absence of any guidance to be gleaned from the published literature.

Hutchison’s personal experience is supported by evidence from two articles [2,3].

One paper published in the JAMA 2009 [2] concludes that ACC/AHA (American College of Cardiology and the American Heart Association) clinical practice guidelines are largely developed from lower levels of evidence or expert opinion and that the proportion of recommendations for which there is no conclusive evidence is growing. Only 314 recommendations of 2711 (median, 11%) are classified as level of evidence A , thus recommendation based on evidence from multiple randomized trials or meta-analyses.  The majority of recommendations (1246/2711; median, 48%) are level of evidence C, thus based  on expert opinion, case studies, or standards of care. Strikingly only 245 of 1305 class I recommendations are based on the highest level A evidence (median, 19%).

Another paper, published in Ann Intern Med 2011 [3], reaches similar conclusions analyzing the Infectious Diseases Society of America (IDSA) Practice Guidelines. Of the 4218 individual recommendations found, only 14% were supported by the strongest (level I) quality of evidence; more than half were based on level III evidence only. Like the ACC/AHH guidelines only a small part (23%) of the strongest IDSA recommendations, were based on level I evidence (in this case ≥1 randomized controlled trial, see below). And, here too, the new recommendations were mostly based on level II and III evidence.

Although there is little to argue about Hutchison’s observations, I do not agree with his conclusions.

In his view guidelines are equivalent to a bullet pointed list or flow diagram, allowing busy practitioners to move on from practice based on mere anecdote and opinion. It therefore seems contradictory that half of the EBM-guidelines are based on little more than anecdote (case series, extrapolation from other populations) and opinion. He then argues that guidelines, like other therapeutic interventions, should be considered in terms of balance between benefit and risk and that the risk  associated with the dissemination of poorly founded guidelines must also be considered. One of those risks is that doctors will just tend to adhere to the guidelines, and may even change their own (adequate) practice  in the absence of any scientific evidence against it. If a patient is harmed despite punctilious adherence to the guideline-rules,  “it is easy to be seduced into assuming that the bad outcome was therefore unavoidable”. But perhaps harm was done by following the guideline….

First of all, overall evidence shows that adherence to guidelines can improve patient outcome and provide more cost effective care (Naveed Mustfa in a comment refers to [4]).

Hutchinson’s piece is opinion-based and rather driven by (understandable) gut feelings and implicit assumptions, that also surround EBM in general.

  1. First there is the assumption that guidelines are a fixed set of rules, like a protocol, and that there is no room for preferences (both of the doctor and the patient), interpretations and experience. In the same way as EBM is often degraded to “cookbook medicine”, EBM guidelines are turned into mere bullet pointed lists made by a bunch of experts that just want to impose their opinions as truth.
  2. The second assumption (shared by many) is that evidence based medicine is synonymous with “randomized controlled trials”. In analogy, only those EBM guideline recommendations “count” that are based on RCT’s or meta-analyses.

Before I continue, I would strongly advice all readers (and certainly all EBM and guideline-skeptics) to read this excellent and clearly written BJM-editorial by David Sackett et al. that deals with misconceptions, myths and prejudices surrounding EBM : Evidence based medicine: what it is and what it isn’t [5].

Sackett et al define EBM as “the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients” [5]. Sackett emphasizes that “Good doctors use both individual clinical expertise and the best available external evidence, and neither alone is enough. Without clinical expertise, practice risks becoming tyrannised by evidence, for even excellent external evidence may be inapplicable to or inappropriate for an individual patient. Without current best evidence, practice risks becoming rapidly out of date, to the detriment of patients.”

Guidelines are meant to give recommendations based on the best available evidence. Guidelines should not be a set of rules, set in stone. Ideally, guidelines have gathered evidence in a transparent way and make it easier for the clinicians to grasp the evidence for a certain procedure in a certain situation … and to see the gaps.

Contrary to what many people think, EBM is not restricted to randomized trials and meta-analyses. It involves tracking down the best external evidence there is. As I explained in #NotSoFunny #16 – Ridiculing RCTs & EBM, evidence is not an all-or-nothing thing: RCT’s (if well performed) are the most robust, but if not available we have to rely on “lower” evidence (from cohort to case-control to case series or expert opinion even).
On the other hand RCT’s are often not even suitable to answer questions in other domains than therapy (etiology/harm, prognosis, diagnosis): per definition the level of evidence for these kind of questions inevitably will be low*. Also, for some interventions RCT’s are not appropriate, feasible or too costly to perform (cesarean vs vaginal birth; experimental therapies, rare diseases, see also [3]).

It is also good to realize that guidance, based on numerous randomized controlled trials is probably not or limited applicable to groups of patients who are seldom included in a RCT: the cognitively impaired, the patient with multiple comorbidities [6], the old patient [6], children and (often) women.

Finally not all RCTs are created equal (various forms of bias; surrogate outcomes; small sample sizes, short follow-up), and thus should not all represent the same high level of evidence.*

Thus in my opinion, low levels of evidence are not per definition problematic. Even if they are the basis for strong recommendations. As long as it is clear how the recommendations were reached and as long as these are well underpinned (by whatever evidence or motivation). One could see the exposed gaps in evidence as a positive thing as it may highlight the need for clinical research in certain fields.

There is one BIG BUT: my assumption is that guidelines are “just” recommendations based on exhaustive and objective reviews of existing evidence. No more, no less. This means that the clinician must have the freedom to deviate from the recommendations, based on his own expertise and/or the situation and/or the patient’s preferences. The more, when the evidence on which these strong recommendations are based is ‘scant’. Sackett already warned for the possible hijacking of EBM by purchasers and managers (and may I add health insurances and governmental agencies) to cut the costs of health care and to impose “rules”.

I therefore think it is odd that the ACC/AHA guidelines prescribe that Class I recommendations SHOULD be performed/administered even if they are based on level C recommendations (see Figure).

I also find it odd that different guidelines have a different nomenclature. The ACC/AHA have Class I, IIa, IIb and III recommendations and level A, B, C evidence where level A evidence represents sufficient evidence from multiple randomized trials and meta-analyses, whereas the strength of recommendations in the IDSA guidelines includes levels A through C (OR D/E recommendations against use) and quality of evidence ranges from level I through III , where I indicates evidence from (just) 1 properly randomized controlled trial. As explained in [3] this system was introduced to evaluate the effectiveness of preventive health care interventions in Canada (for which RCTs are apt).

Finally, guidelines and guideline makers should probably be more open for input/feedback from people who apply these guidelines.

————————————————

*the new GRADE (Grading of Recommendations Assessment, Development, and Evaluation) scoring system taking into account good quality observational studies as well may offer a potential solution.

Another possibly relevant post at this blog: The Best Study Design for … Dummies

Taken from a summary of an ACC/AHA guideline at http://guideline.gov/
Click to enlarge.

References

  1. Hutchison, G. (2012). Guidelines can harm patients too BMJ, 344 (apr18 1) DOI: 10.1136/bmj.e2685
  2. Tricoci P, Allen JM, Kramer JM, Califf RM, & Smith SC Jr (2009). Scientific evidence underlying the ACC/AHA clinical practice guidelines. JAMA : the journal of the American Medical Association, 301 (8), 831-41 PMID: 19244190
  3. Lee, D., & Vielemeyer, O. (2011). Analysis of Overall Level of Evidence Behind Infectious Diseases Society of America Practice Guidelines Archives of Internal Medicine, 171 (1), 18-22 DOI: 10.1001/archinternmed.2010.482
  4. Menéndez R, Reyes S, Martínez R, de la Cuadra P, Manuel Vallés J, & Vallterra J (2007). Economic evaluation of adherence to treatment guidelines in nonintensive care pneumonia. The European respiratory journal : official journal of the European Society for Clinical Respiratory Physiology, 29 (4), 751-6 PMID: 17005580
  5. Sackett, D., Rosenberg, W., Gray, J., Haynes, R., & Richardson, W. (1996). Evidence based medicine: what it is and what it isn’t BMJ, 312 (7023), 71-72 DOI: 10.1136/bmj.312.7023.71
  6. Aylett, V. (2010). Do geriatricians need guidelines? BMJ, 341 (sep29 3) DOI: 10.1136/bmj.c5340




Experience versus Evidence [1]. Opioid Therapy for Rheumatoid Arthritis Pain.

5 12 2011

ResearchBlogging.orgRheumatoid arthritis (RA) is a chronic auto-immune disease, which causes inflammation of the joints that eventually leads to progressive joint destruction and deformity. Patients have swollen, stiff and painful joints.  The main aim of treatment is to reduce swelling  and inflammation, to alleviate pain and stiffness and to maintain normal joint function. While there is no cure, it is important to properly manage pain.

The mainstays of therapy in RA are disease-modifying anti-rheumatic drugs (DMARDs) and non-steroidal anti-inflammatory drugs (NSAIDs). These drugs primarily target inflammation. However, since inflammation is not the only factor that causes pain in RA, patients may not be (fully) responsive to treatment with these medications.
Opioids are another class of pain-relieving substance (analgesics). They are frequently used in RA, but their role in chronic cancer pain, including RA, is not firmly established.

A recent Cochrane Systematic Review [1] assessed the beneficial and harmful effects of opioids in RA.

Eleven studies (672 participants) were included in the review.

Four studies only assessed the efficacy of  single doses of different analgesics, often given on consecutive days. In each study opioids reduced pain (a bit) more than placebo. There were no differences in effectiveness between the opioids.

Seven studies between 1-6 weeks in duration assessed 6 different oral opioids either alone or combined with non-opioid analgesics.
The only strong opioid investigated was controlled-release morphine sulphate, in a single study with 20 participants.
Six studies compared an opioid (often combined with an non-opioid analgesic) to placebo. Opioids were slightly better than placebo in improving patient reported global impression of clinical change (PGIC)  (3 studies, 324 participants: relative risk (RR) 1.44, 95% CI 1.03 to 2.03), but did not lower the  number of withdrawals due to inadequate analgesia in 4 studies.
Notably none of the 11 studies reported the primary and probably more clinical relevant outcome “proportion of participants reporting ≥ 30% pain relief”.

On the other hand adverse events (most commonly nausea, vomiting, dizziness and constipation) were more frequent in patients receiving opioids compared to placebo (4 studies, 371 participants: odds ratio 3.90, 95% CI 2.31 to 6.56). Withdrawal due to adverse events was  non-significantly higher in the opioid-treated group.

Comparing opioids to other analgesics instead of placebos seems more relevant. Among the 11 studies, only 1 study compared an opioid (codeine with paracetamol) to an NSAID (diclofenac). This study found no difference in efficacy or safety between the two treatments.

The 11 included studies were very heterogeneous (i.e. different opioid studied, with or without concurrent use of non-opioid analgesics, different outcomes measured) and the risk of bias was generally high. Furthermore, most studies were published before 2000 (less optimal treatment of RA).

The authors therefore conclude:

In light of this, the quantitative findings of this review must be interpreted with great caution. At best, there is weak evidence in favour of the efficacy of opioids for the treatment of pain in patients with RA but, as no study was longer than six weeks in duration, no reliable conclusions can be drawn regarding the efficacy or safety of opioids in the longer term.

This was the evidence, now the opinion.

I found this Cochrane Review via an EvidenceUpdates email alert from the BMJ Group and McMaster PLUS.

EvidenceUpdate alerts are meant to “provide you with access to current best evidence from research, tailored to your own health care interests, to support evidence-based clinical decisions. (…) All citations are pre-rated for quality by research staff, then rated for clinical relevance and interest by at least 3 members of a worldwide panel of practicing physicians”

I usually don’t care about the rating, because it is mostly 5-6 on a scale of 7. This was also true for the current SR.

There is a more detailed rating available (when clicking the link, free registration required). Usually, the newsworthiness of SR’s scores relatively low. (because it summarizes ‘old’ studies?). Personally I would think that the relevance and newsworthiness would be higher for the special interest group, pain.

But the comment of the first of the 3 clinical raters was most revealing:

He/she comments:

As a Palliative care physician and general internist, I have had excellent results using low potency opiates for RA and OA pain. The palliative care literature is significantly more supportive of this approach vs. the Cochrane review.

Thus personal experience wins from evidence?* How did this palliative care physician assess effectiveness? Just give a single dose of an opiate? How did he rate the effectiveness of the opioids? Did he/she compare it to placebo or NSAID (did he compare it at all?), did he/she measure adverse effects?

And what is “The palliative care literature”  the commenter is referring to? Apparently not this Cochrane Review. Apparently not the 11 controlled trials included in the Cochrane review. Apparently not the several other Cochrane reviews on use of opioids for non-chronic cancer pain, and not the guidelines, syntheses and synopsis I found via the TRIP-database. All conclude that using opioids to treat non-cancer chronic pain is supported by very limited evidence, that adverse effects are common and that long-term use may lead to opioid addiction.

I’m sorry to note that although the alerting service is great as an alert, such personal ratings are not very helpful for interpreting and *true* rating of the evidence.

I would rather prefer a truly objective, structured critical appraisal like this one on a similar topic by DARE (“Opioids for chronic noncancer pain: a meta-analysis of effectiveness and side effects”)  and/or an objective piece that puts the new data into clinical perspective.

*Just to be clear, the own expertise and opinions of experts are also important in decision making. Rightly, Sackett [2] emphasized that good doctors use both individual clinical expertise and the best available external evidence. However, that doesn’t mean that one personal opinion and/or preference replaces all the existing evidence.

References 

  1. Whittle SL, Richards BL, Husni E, & Buchbinder R (2011). Opioid therapy for treating rheumatoid arthritis pain. Cochrane database of systematic reviews (Online), 11 PMID: 22071805
  2. Sackett DL, Rosenberg WM, Gray JA, Haynes RB, & Richardson WS (1996). Evidence based medicine: what it is and what it isn’t. BMJ (Clinical research ed.), 312 (7023), 71-2 PMID: 8555924
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Evidence Based Point of Care Summaries [2] More Uptodate with Dynamed.

18 10 2011

ResearchBlogging.orgThis post is part of a short series about Evidence Based Point of Care Summaries or POCs. In this series I will review 3 recent papers that objectively compare a selection of POCs.

In the previous post I reviewed a paper from Rita Banzi and colleagues from the Italian Cochrane Centre [1]. They analyzed 18 POCs with respect to their “volume”, content development and editorial policy. There were large differences among POCs, especially with regard to evidence-based methodology scores, but no product appeared the best according to the criteria used.

In this post I will review another paper by Banzi et al, published in the BMJ a few weeks ago [2].

This article examined the speed with which EBP-point of care summaries were updated using a prospective cohort design.

First the authors selected all the systematic reviews signaled by the American College of Physicians (ACP) Journal Club and Evidence-Based Medicine Primary Care and Internal Medicine from April to December 2009. In the same period the authors selected all the Cochrane systematic reviews labelled as “conclusion changed” in the Cochrane Library. In total 128 systematic reviews were retrieved, 68 from the literature surveillance journals (53%) and 60 (47%) from the Cochrane Library. Two months after the collection started (June 2009) the authors did a monthly screen for a year to look for potential citation of the identified 128 systematic reviews in the POCs.

Only those 5 POCs were studied that were ranked in the top quarter for at least 2 (out of 3) desirable dimensions, namely: Clinical Evidence, Dynamed, EBM Guidelines, UpToDate and eMedicine. Surprisingly eMedicine was among the selected POCs, having a rating of “1″ on a scale of 1 to 15 for EBM methodology. One would think that Evidence-based-ness is a fundamental prerequisite  for EBM-POCs…..?!

Results were represented as a (rather odd, but clear) “survival analysis” ( “death” = a citation in a summary).

Fig.1 : Updating curves for relevant evidence by POCs (from [2])

I will be brief about the results.

Dynamed clearly beated all the other products  in its updating speed.

Expressed in figures, the updating speed of Dynamed was 78% and 97% greater than those of EBM Guidelines and Clinical Evidence, respectively. Dynamed had a median citation rate of around two months and EBM Guidelines around 10 months, quite close to the limit of the follow-up, but the citation rate of the other three point of care summaries (UpToDate, eMedicine, Clinical Evidence) were so slow that they exceeded the follow-up period and the authors could not compute the median.

Dynamed outperformed the other POC’s in updating of systematic reviews independent of the route. EBM Guidelines and UpToDate had similar overall updating rates, but Cochrane systematic reviews were more likely to be cited by EBM Guidelines than by UpToDate (odds ratio 0.02, P<0.001). Perhaps not surprising, as EBM Guidelines has a formal agreement with the Cochrane Collaboration to use Cochrane contents and label its summaries as “Cochrane inside.” On the other hand, UpToDate was faster than EBM Guidelines in updating systematic reviews signaled by literature surveillance journals.

Dynamed‘s higher updating ability was not due to a difference in identifying important new evidence, but to the speed with which this new information was incorporated in their summaries. Possibly the central updating of Dynamed by the editorial team might account for the more prompt inclusion of evidence.

As the authors rightly point out, slowness in updating could mean that new relevant information is ignored and could thus affect the validity of point of care information services”.

A slower updating rate may be considered more important for POCs that “promise” to “continuously update their evidence summaries” (EBM-Guidelines) or to “perform a continuous comprehensive review and to revise chapters whenever important new information is published, not according to any specific time schedule” (UpToDate). (see table with description of updating mechanisms )

In contrast, Emedicine doesn’t provide any detailed information on updating policy, another reason that it doesn’t belong to this list of best POCs.
Clinical Evidence, however, clearly states, We aim to update Clinical Evidence reviews annually. In addition to this cycle, details of clinically important studies are added to the relevant reviews throughout the year using the BMJ Updates service.” But BMJ Updates is not considered in the current analysis. Furthermore, patience is rewarded with excellent and complete summaries of evidence (in my opinion).

Indeed a major limitation of the current (and the previous) study by Banzi et al [1,2] is that they have looked at quantitative aspects and items that are relatively “easy to score”, like “volume” and “editorial quality”, not at the real quality of the evidence (previous post).

Although the findings were new to me, others have recently published similar results (studies were performed in the same time-span):

Shurtz and Foster [3] of the Texas A&M University Medical Sciences Library (MSL) also sought to establish a rubric for evaluating evidence-based medicine (EBM) point-of-care tools in a health sciences library.

They, too, looked at editorial quality and speed of updating plus reviewing content, search options, quality control, and grading.

Their main conclusion is that “differences between EBM tools’ options, content coverage, and usability were minimal, but that the products’ methods for locating and grading evidence varied widely in transparency and process”.

Thus this is in line with what Banzi et al reported in their first paper. They also share Banzi’s conclusion about differences in speed of updating

“DynaMed had the most up-to-date summaries (updated on average within 19 days), while First Consult had the least up to date (updated on average within 449 days). Six tools claimed to update summaries within 6 months or less. For the 10 topics searched, however, only DynaMed met this claim.”

Table 3 from Shurtz and Foster [3] 

Ketchum et al [4] also conclude that DynaMed the largest proportion of current (2007-2009) references (170/1131, 15%). In addition they found that Dynamed had the largest total number of references (1131/2330, 48.5%).

Yes, and you might have guessed it. The paper of Andrea Ketchum is the 3rd paper I’m going to review.

I also recommend to read the paper of the librarians Shurtz and Foster [3], which I found along the way. It has too much overlap with the Banzi papers to devote a separate post to it. Still it provides better background information then the Banzi papers, it focuses on POCs that claim to be EBM and doesn’t try to weigh one element over another. 

References

  1. Banzi, R., Liberati, A., Moschetti, I., Tagliabue, L., & Moja, L. (2010). A Review of Online Evidence-based Practice Point-of-Care Information Summary Providers Journal of Medical Internet Research, 12 (3) DOI: 10.2196/jmir.1288
  2. Banzi, R., Cinquini, M., Liberati, A., Moschetti, I., Pecoraro, V., Tagliabue, L., & Moja, L. (2011). Speed of updating online evidence based point of care summaries: prospective cohort analysis BMJ, 343 (sep22 2) DOI: 10.1136/bmj.d5856
  3. Shurtz, S., & Foster, M. (2011). Developing and using a rubric for evaluating evidence-based medicine point-of-care tools Journal of the Medical Library Association : JMLA, 99 (3), 247-254 DOI: 10.3163/1536-5050.99.3.012
  4. Ketchum, A., Saleh, A., & Jeong, K. (2011). Type of Evidence Behind Point-of-Care Clinical Information Products: A Bibliometric Analysis Journal of Medical Internet Research, 13 (1) DOI: 10.2196/jmir.1539
  5. Evidence Based Point of Care Summaries [1] No “Best” Among the Bests? (laikaspoetnik.wordpress.com)
  6. How will we ever keep up with 75 Trials and 11 Systematic Reviews a Day? (laikaspoetnik.wordpress.com
  7. UpToDate or Dynamed? (Shamsha Damani at laikaspoetnik.wordpress.com)
  8. How Evidence Based is UpToDate really? (laikaspoetnik.wordpress.com)

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Evidence Based Point of Care Summaries [1] No “Best” Among the Bests?

13 10 2011

ResearchBlogging.orgFor many of today’s busy practicing clinicians, keeping up with the enormous and ever growing amount of medical information, poses substantial challenges [6]. Its impractical to do a PubMed search to answer each clinical question and then synthesize and appraise the evidence. Simply, because busy health care providers have limited time and many questions per day.

As repeatedly mentioned on this blog ([6-7]), it is far more efficient to try to find aggregate (or pre-filtered or pre-appraised) evidence first.

Haynes ‘‘5S’’ levels of evidence (adapted by [1])

There are several forms of aggregate evidence, often represented as the higher layers of an evidence pyramid (because they aggregate individual studies, represented by the lowest layer). There are confusingly many pyramids, however [8] with different kinds of hierarchies and based on different principles.

According to the “5S” paradigm[9] (now evolved to 6S -[10]) the peak of the pyramid are the ideal but not yet realized computer decision support systems, that link the individual patient characteristics to the current best evidence. According to the 5S model the next best source are Evidence Based Textbooks.
(Note: EBM and textbooks almost seem a contradiction in terms to me, personally I would not put many of the POCs somewhere at the top. Also see my post: How Evidence Based is UpToDate really?)

Whatever their exact place in the EBM-pyramid, these POCs are helpful to many clinicians. There are many different POCs (see The HLWIKI Canada for a comprehensive overview [11]) with a wide range of costs, varying from free with ads (e-Medicine) to very expensive site licenses (UpToDate). Because of the costs, hospital libraries have to choose among them.

Choices are often based on user preferences and satisfaction and balanced against costs, scope of coverage etc. Choices are often subjective and people tend to stick to the databases they know.

Initial literature about POCs concentrated on user preferences and satisfaction. A New Zealand study [3] among 84 GPs showed no significant difference in preference for, or usage levels of DynaMed, MD Consult (including FirstConsult) and UpToDate. The proportion of questions adequately answered by POCs differed per study (see introduction of [4] for an overview) varying from 20% to 70%.
McKibbon and Fridsma ([5] cited in [4]) found that the information resources chosen by primary care physicians were seldom helpful in providing the correct answers, leading them to conclude that:

“…the evidence base of the resources must be strong and current…We need to evaluate them well to determine how best to harness the resources to support good clinical decision making.”

Recent studies have tried to objectively compare online point-of-care summaries with respect to their breadth, content development, editorial policy, the speed of updating and the type of evidence cited. I will discuss 3 of these recent papers, but will review each paper separately. (My posts tend to be pretty long and in-depth. So in an effort to keep them readable I try to cut down where possible.)

Two of the three papers are published by Rita Banzi and colleagues from the Italian Cochrane Centre.

In the first paper, reviewed here, Banzi et al [1] first identified English Web-based POCs using Medline, Google, librarian association websites, and information conference proceedings from January to December 2008. In order to be eligible, a product had to be an online-delivered summary that is regularly updated, claims to provide evidence-based information and is to be used at the bedside.

They found 30 eligible POCs, of which the following 18 databases met the criteria: 5-Minute Clinical Consult, ACP-Pier, BestBETs, CKS (NHS), Clinical Evidence, DynaMed, eMedicine,  eTG complete, EBM Guidelines, First Consult, GP Notebook, Harrison’s Practice, Health Gate, Map Of Medicine, Micromedex, Pepid, UpToDate, ZynxEvidence.

They assessed and ranked these 18 point-of-care products according to: (1) coverage (volume) of medical conditions, (2) editorial quality, and (3) evidence-based methodology. (For operational definitions see appendix 1)

From a quantitive perspective DynaMed, eMedicine, and First Consult were the most comprehensive (88%) and eTG complete the least (45%).

The best editorial quality of EBP was delivered by Clinical Evidence (15), UpToDate (15), eMedicine (13), Dynamed (11) and eTG complete (10). (Scores are shown in brackets)

Finally, BestBETs, Clinical Evidence, EBM Guidelines and UpToDate obtained the maximal score (15 points each) for best evidence-based methodology, followed by DynaMed and Map Of Medicine (12 points each).
As expected eMedicine, eTG complete, First Consult, GP Notebook and Harrison’s Practice had a very low EBM score (1 point each). Personally I would not have even considered these online sources as “evidence based”.

The calculations seem very “exact”, but assumptions upon which these figures are based are open to question in my view. Furthermore all items have the same weight. Isn’t the evidence-based methodology far more important than “comprehensiveness” and editorial quality?

Certainly because “volume” is “just” estimated by analyzing to which extent 4 random chapters of the ICD-10 classification are covered by the POCs. Some sources, like Clinical Evidence and BestBets (scoring low for this item) don’t aim to be comprehensive but only “answer” a limited number of questions: they are not textbooks.

Editorial quality is determined by scoring of the specific indicators of transparency: authorship, peer reviewing procedure, updating, disclosure of authors’ conflicts of interest, and commercial support of content development.

For the EB methodology, Banzi et al scored the following indicators:

  1. Is a systematic literature search or surveillance the basis of content development?
  2. Is the critical appraisal method fully described?
  3. Are systematic reviews preferred over other types of publication?
  4. Is there a system for grading the quality of evidence?
  5. When expert opinion is included is it easily recognizable over studies’ data and results ?

The  score for each of these indicators is 3 for “yes”, 1 for “unclear”, and 0 for “no” ( if judged “not adequate” or “not reported.”)

This leaves little room for qualitative differences and mainly relies upon adequate reporting. As discussed earlier in a post where I questioned the evidence-based-ness of UpToDate, there is a difference between tailored searches and checking a limited list of sources (indicator 1.). It also matters whether the search is mentioned or not (transparency), whether it is qualitatively ok and whether it is extensive or not. For lists, it matters how many sources are “surveyed”. It also matters whether one or both methods are used… These important differences are not reflected by the scores.

Furthermore some points may be more important than others. Personally I find step 1 the most important. For what good is appraising and grading if it isn’t applied to the most relevant evidence? It is “easy” to do a grading or to copy it from other sources (yes, I wouldn’t be surprised if some POCs are doing this).

On the other hand, a zero for one indicator can have too much weight on the score.

Dynamed got 12 instead of the maximum 15 points, because their editorial policy page didn’t explicitly describe their absolute prioritization of systematic reviews although they really adhere to that in practice (see comment by editor-in-chief  Brian Alper [2]). Had Dynamed received the deserved 15 points for this indicator, they would have had the highest score overall.

The authors further conclude that none of the dimensions turned out to be significantly associated with the other dimensions. For example, BestBETs scored among the worst on volume (comprehensiveness), with an intermediate score for editorial quality, and the highest score for evidence-based methodology.  Overall, DynaMed, EBM Guidelines, and UpToDate scored in the top quartile for 2 out of 3 variables and in the 2nd quartile for the 3rd of these variables. (but as explained above Dynamed really scored in the top quartile for all 3 variables)

On basis of their findings Banzi et al conclude that only a few POCs satisfied the criteria, with none excelling in all.

The finding that Pepid, eMedicine, eTG complete, First Consult, GP Notebook, Harrison’s Practice and 5-Minute Clinical Consult only obtained 1 or 2 of the maximum 15 points for EBM methodology confirms my “intuitive grasp” that these sources really don’t deserve the label “evidence based”. Perhaps we should make a more strict distinction between “point of care” databases as a point where patients and practitioners interact, particularly referring to the context of the provider-patient dyad (definition by Banzi et al) and truly evidence based summaries. Only few of the tested databases would fit the latter definition. 

In summary, Banzi et al reviewed 18 Online Evidence-based Practice Point-of-Care Information Summary Providers. They comprehensively evaluated and summarized these resources with respect to coverage (volume) of medical conditions, editorial quality, and (3) evidence-based methodology. 

Limitations of the study, also according to the authors, were the lack of a clear definition of these products, arbitrariness of the scoring system and emphasis on the quality of reporting. Furthermore the study didn’t really assess the products qualitatively (i.e. with respect to performance). Nor did it take into account that products might have a different aim. Clinical Evidence only summarizes evidence on the effectiveness of treatments of a limited number of diseases, for instance. Therefore it scores bad on volume while excelling on the other items. 

Nevertheless it is helpful that POCs are objectively compared and it may help as starting point for decisions about acquisition.

References (not in chronological order)

  1. Banzi, R., Liberati, A., Moschetti, I., Tagliabue, L., & Moja, L. (2010). A Review of Online Evidence-based Practice Point-of-Care Information Summary Providers Journal of Medical Internet Research, 12 (3) DOI: 10.2196/jmir.1288
  2. Alper, B. (2010). Review of Online Evidence-based Practice Point-of-Care Information Summary Providers: Response by the Publisher of DynaMed Journal of Medical Internet Research, 12 (3) DOI: 10.2196/jmir.1622
  3. Goodyear-Smith F, Kerse N, Warren J, & Arroll B (2008). Evaluation of e-textbooks. DynaMed, MD Consult and UpToDate. Australian family physician, 37 (10), 878-82 PMID: 19002313
  4. Ketchum, A., Saleh, A., & Jeong, K. (2011). Type of Evidence Behind Point-of-Care Clinical Information Products: A Bibliometric Analysis Journal of Medical Internet Research, 13 (1) DOI: 10.2196/jmir.1539
  5. McKibbon, K., & Fridsma, D. (2006). Effectiveness of Clinician-selected Electronic Information Resources for Answering Primary Care Physicians’ Information Needs Journal of the American Medical Informatics Association, 13 (6), 653-659 DOI: 10.1197/jamia.M2087
  6. How will we ever keep up with 75 Trials and 11 Systematic Reviews a Day? (laikaspoetnik.wordpress.com)
  7. 10 + 1 PubMed Tips for Residents (and their Instructors) (laikaspoetnik.wordpress.com)
  8. Time to weed the (EBM-)pyramids?! (laikaspoetnik.wordpress.com)
  9. Haynes RB. Of studies, syntheses, synopses, summaries, and systems: the “5S” evolution of information services for evidence-based healthcare decisions. Evid Based Med 2006 Dec;11(6):162-164. [PubMed]
  10. DiCenso A, Bayley L, Haynes RB. ACP Journal Club. Editorial: Accessing preappraised evidence: fine-tuning the 5S model into a 6S model. Ann Intern Med. 2009 Sep 15;151(6):JC3-2, JC3-3. PubMed PMID: 19755349 [free full text].
  11. How Evidence Based is UpToDate really? (laikaspoetnik.wordpress.com)
  12. Point_of_care_decision-making_tools_-_Overview (hlwiki.slais.ubc.ca)
  13. UpToDate or Dynamed? (Shamsha Damani at laikaspoetnik.wordpress.com)

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#FollowFriday #FF @DrJenGunter: EBM Sex Health Expert Wielding the Lasso of Truth

19 08 2011

If you’re on Twitter you probably seen the #FF or #FollowFriday phenomenon. FollowFriday is a way to recommend people on Twitter to others. For at least 2 reasons: to acknowledge your favorite tweople and to make it easier for your followers to find new interesting people.

However, some #FollowFriday tweet-series are more like a weekly spam. Almost 2 years ago I blogged about the misuse of FF-recommendations and I gave some suggestions to do #FollowFriday the right way: not by sheer mentioning many people in numerous  tweets, but by recommending one or a few people a time, and explaining why this person is so awesome to follow.

Twitter Lists are also useful tools for recommending people (see post). You could construct lists of your favorite Twitter people for others to follow. I have created a general FollowFridays list, where I list all the people I have recommended in a #FF-tweet and/or post.

In this post I would like to take up the tradition of highlighting the #FF favs at my blog. .

This FollowFriday I recommend:  

Jennifer Gunter

Jennifer Gunter (@DrJenGunter at Twitter), is a beautiful lady, but she shouldn’t be tackled without gloves, for she is a true defender of evidence-based medicine and wields the lasso of truth.

Her specialty is OB/GYN. She is a sex health expert. No surprise, many tweets are related to this topic, some very serious, some with a humorous undertone. And there can be just fun (re)tweets, like:

LOL -> “@BackpackingDad: New Word: Fungry. Full-hungry. “I just ate a ton of nachos, but hot damn am I fungry for those Buffalo wings!””

Dr Jen Gunter has a blog Dr. Jen Gunther (wielding the lasso of truth). 

Again we find the same spectrum of posts, mostly in the field of ob/gyn. You need not be an ob/gyn nor an EBM expert to enjoy them. Jen’s posts are written in plain language, suitable for anyone to understand (including patients).

Some titles:

In addition, There are also hilarious posts like “Cosmo’s sex position of the day proves they know nothing about good sex or women“,where she criticizes Cosmo for tweeting impossible sex positions (“If you’re over 40, I dare you to even GET into that position! “), which she thinks were created by one of the following:

A) a computer who has never had sex and is not programmed to understand how the female body bends.
B) a computer programmer who has never has sex and has no understanding of how the female body bends.
C) a Yogi master/Olympic athlete.

Sometimes the topic is blogging. Jen is a fierce proponent of medical blogging. She sees it as a way to “promote” yourself as a doctor, to learn from your readers and to “contribute credible content drowns out garbage medical information” (true) and as an ideal platform to deliver content to your patients and like-minded medical professionals. (great idea)

Read more at:

You can follow Jen at her Twitter-account (http://twitter.com/#!/DrJenGunter) and/or you can follow my lists. She is on:  ebm-cochrane-sceptics and the followfridays list.

Of course you can also take a subscription to her blog http://drjengunter.wordpress.com/

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RIP Statistician Paul Meier. Proponent not Father of the RCT.

14 08 2011

This headline in Boing Boing caught my eye today:  RIP Paul Meier, father of the randomized trial

Not surprisingly, I knew that Paul Meier (with Kaplan) introduced the Kaplan-Meier estimator (1958), a very important tool for measuring how many patients survive a medical treatment. But I didn’t know he was “father of the randomized trial”….

But is he really?:Father of the randomized trial and “probably best known for the introduction of randomized trials into the evaluation of medical treatments”, as Boing Boing states?

Boing Boing’s very short article is based on the New York Times article: Paul Meier, Statistician Who Revolutionized Medical Trials, Dies at 87. According to the NY Times “Dr. Meier was one of the first and most vocal proponents of what is called “randomization.” 

Randomization, the NY-Times explains, is:

Under the protocol, researchers randomly assign one group of patients to receive an experimental treatment and another to receive the standard treatment. In that way, the researchers try to avoid unintentionally skewing the results by choosing, for example, the healthier or younger patients to receive the new treatment.

(for a more detailed explanation see my previous posts The best study designs…. for dummies and #NotSoFunny #16 – Ridiculing RCTs & EBM)

Meier was a very successful proponent, that is for sure. According to Sir Richard Peto, (Dr. Meier) “perhaps more than any other U.S. statistician, was the one who influenced U.S. drug regulatory agencies, and hence clinical researchers throughout the U.S. and other countries, to insist on the central importance of randomized evidence.”

But an advocate need not be a father, for advocates are seldom the inventors/creators. A proponent is more of a nurse, a mentor or a … foster-parent.

Is Meier the true father/inventor of the RCT? And if not, who is?

Googling “Father of the randomized trial” won’t help, because all 1.610  hits point to Dr. Meier…. thanks to Boing Boing careless copying.

What I read so far doesn’t point at one single creator. And the RCT wasn’t just suddenly there. It started with comparison of treatments under controlled conditions. Back in 1753, the British naval surgeon James Lind published his famous account of 12 scurvy patients, “their cases as similar as I could get them” noting that “the most sudden and visible good effects were perceived from the uses of the oranges and lemons and that citrus fruit cured scurvy [3]. The French physician Pierre Louis and Harvard anatomist Oliver Wendell Holmes (19th century) were also fierce proponents of supporting conclusions about the effectiveness of treatments with statistics, not subjective impressions.[4]

But what was the first real RCT?

Perhaps the first real RCT was The Nuremberg salt test (1835) [6]. This was possibly not only the first RCT, but also the first scientific demonstration of the lack of effect of a homeopathic dilution. More than 50 visitors of a local tavern participated in the experiment. Half of them received a vial  filled with distilled snow water, the other half a vial with ordinary salt in a homeopathic C30-dilution of distilled snow water. None of the participants knew whether he got the “actual medicine or not” (blinding). The numbered vials were coded and the code was broken after the experiment (allocation concealment).

The first publications of RCT’s were in the field of psychology and agriculture. As a matter of fact one other famous statistician, Ronald A. Fisher  (of the Fisher’s exact test) seems to play a more important role in the genesis and popularization of RCT’s than Meier, albeit in agricultural research [5,7]. The book “The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century” describes how Fisher devised a randomized trial at the spot to test the contention of a lady that she could taste the difference between tea into which milk had been poured and tea that had been poured into milk (almost according to homeopathic principles) [7]

According to Wikipedia [5] the published (medical) RCT appeared in the 1948 paper entitled “Streptomycin treatment of pulmonary tuberculosis”. One of the authors, Austin Bradford Hill, is (also) credited as having conceived the modern RCT.

Thus the road to the modern RCT is long, starting with the notions that experiments should be done under controlled conditions and that it doesn’t make sense to base treatment on intuition. Later, experiments were designed in which treatments were compared to placebo (or other treatments) in a randomized and blinded fashion, with concealment of allocation.

Paul Meier was not the inventor of the RCT, but a successful vocal proponent of the RCT. That in itself is commendable enough.

And although the Boing Boing article was incorrect, and many people googling for “father of the RCT” will find the wrong answer from now on, it did raise my interest in the history of the RCT and the role of statisticians in the development of science and clinical trials.
I plan to read a few of the articles and books mentioned below. Like the relatively lighthearted “The Lady Tasting Tea” [7]. You can envision a book review once I have finished reading it.

Note added 15-05 13.45 pm:

Today a more accurate article appeared in the Boston Globe (“Paul Meier; revolutionized medical studies using math”), which does justice to the important role of Dr Meier in the espousal of randomization as an essential element in clinical trials. For that is what he did.

Quote:

Dr. Meier published a scathing paper in the journal Science, “Safety Testing of Poliomyelitis Vaccine,’’ in which he described deficiencies in the production of vaccines by several companies. His paper was seen as a forthright indictment of federal authorities, pharmaceutical manufacturers, and the National Foundation for Infantile Paralysis, which funded the research for a polio vaccine.

  1. RIP Paul Meier, father of the randomized trial (boingboing.net)
  2. Paul Meier, Statistician Who Revolutionized Medical Trials, Dies at 87 (nytimes.com)
  3. M L Meldrum A brief history of the randomized controlled trial. From oranges and lemons to the gold standard. Hematology/ Oncology Clinics of North America (2000) Volume: 14, Issue: 4, Pages: 745-760, vii PubMed: 10949771  or see http://www.mendeley.com
  4. Fye WB. The power of clinical trials and guidelines,and the challenge of conflicts of interest. J Am Coll Cardiol. 2003 Apr 16;41(8):1237-42. PubMed PMID: 12706915. Full text
  5. http://en.wikipedia.org/wiki/Randomized_controlled_trial
  6. Stolberg M (2006). Inventing the randomized double-blind trial: The Nuremberg salt test of 1835. JLL Bulletin: Commentaries on the history of treatment evaluation (www.jameslindlibrary.org).
  7. The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century Peter Cummings, MD, MPH, Jama 2001;286(10):1238-1239. doi:10.1001/jama.286.10.1238  Book Review.
    Book by David Salsburg, 340 pp, with illus, $23.95, ISBN 0-7167-41006-7, New York, NY, WH Freeman, 2001.
  8. Kaptchuk TJ. Intentional ignorance: a history of blind assessment and placebo controls in medicine. Bull Hist Med. 1998 Fall;72(3):389-433. PubMed PMID: 9780448. abstract
  9. The best study design for dummies/ (http://laikaspoetnik.wordpress.com: 2008/08/25/)
  10. #Notsofunny: Ridiculing RCT’s and EBM (http://laikaspoetnik.wordpress.com: 2010/02/01/)
  11. RIP Paul Meier : Research Randomization Advocate (mystrongmedicine.com)
  12. If randomized clinical trials don’t show that your woo works, try anthropology! (scienceblogs.com)
  13. The revenge of “microfascism”: PoMo strikes medicine again (scienceblogs.com)




Kaleidoscope 2: 2010 wk 31

8 08 2010

Almost a year ago I started a new series Kaleidoscope, with a “kaleidoscope” of facts, findings, views and news gathered over the last 1-2 weeks.
It never got beyond the first edition. Perhaps the introduction of this Kaleidoscope was to overwhelming & dazzling: lets say it was very rich in content. Or as
Andrew Spong tweeted: “Part cornucopia, part cabinet of wonders, it’s @laikas Kaleidoscope 2009 wk 47″

This is  a reprise in a (somewhat) “shorter” format. Lets see how it turns out.

This edition will concentrate on Social Media (Blogging, Twitter Google Wave). I fear that I won’t keep my promise, if I deal with more topics.

Medical Grand Rounds and News from the Blogosphere

Life in the Fast Lane is the host of this weeks Grand Rounds. This edition is truly terrific, if not terrifying. Not only does it contain “killer posts”, each medblogger has also been coupled to its preferred deadly Aussie critter.
Want to know how a full time ER-doctor/educator/textbook author/blogger/editor /health search engine director manages to complete work-related tasks …when the kids are either at school or asleep(!), then read this recent interview with Mike Cadogan, the founder of Life in the Fast Lane.

Don’t forget to submit your medical blog post to next weeks Grand Rounds over at Dispatch From Second Base. Instructions and theme details can be found on the post “You are invited to Grand Rounds!“ (update here).

And certainly don’t forget to submit your post related to medical information to the MedLibs Round (about medical information) here. More details can be found at Laika’s MedLibLog and at Highlight Health, the host of the upcoming Edition.
(sorry, writing this post took longer than I thought: you have one day left for submission)

Dr Shock of the blog with the same name advises us to submit good quality, easy-to-understand posts dealing with science, environment or medicine to Scientia Pro Publica via the blog carnival submission form.

There is a new on-line science blogging community – Scientopia, till now mostly consisting of bloggers who left Scienceblogs after (but not because of) Pepsigate. New members can only be added to the collective by invitation (?). Obviously, pepsi-researchers will not be invited, but it remains to be seen who will…  Hopefully it doesn’t become an elitist club.
Virginia Heffernan (NY-Times) has an outspoken opinion about the (ex-) sciencebloggers, illustrated by this one-liner

“ScienceBlogs has become Fox News for the religion-baiting, peak-oil crowd.”

Although I don’t appreciate the ranting-style of some of the blogs myself (the sub-“South Park” blasphemy style of PZ Myers, as Virginia puts it). I don’t think most Scienceblogs deserve to be labelled as “preoccupied with trivia, name-calling and saber rattling”.
See balanced responses at: NeurodojoNeuron Culture & Neuroanthropology (anything with neuro- makes sense, I guess).
Want to understand more about ScienceBlogs and why it was such a terrific community, then read Bora Z’s (rather long) ScienceBlog farewell post.

Oh.. and there is yet another new science blogging platform: http://www.labspaces.net/, that has evolved from a science news aggregator . It looks slick.

Social Media

Speaking about Twitter, did you know that  Twitter reached its 20 billionth tweet over the weekend, a milestone that came just a few months after hitting the 10 billion tweet mark!? (read more in the Guardian)

Well and if you have no idea WHAT THE FUCK IS MY SOCIAL MEDIA “STRATEGY”? you might click the link to get some (new) ideas. You probably need to refresh the site a couple of times to find the right answer.

First-year medical school and master’s of medicine students of Stanford University will receive an i-pad at the start of the year. The extremely tech-savvy Students do appreciate the gift:

“Especially in medicine, we’re using so many different resources, including all the syllabuses and slides. I’m able to pull them up and search them whenever I need to. It’s a fantastic idea.”

Good news for Facebook friends: VoIP giant Vonage has just introduced a new iPhone, iPod touch and Android app that allows users to call their Facebook friends for free (Mashable).

It was a shock – or wasn’t it – that Google pulled the plug on Google Wave (RRW), after being available to the general public for only 78 days?  The unparalleled tool that “could change the web”, but was too complex to be understood. Here are some thoughts why Google wave failed.  Since much of the Code is open source, ambitious developers may pick up where Google left.

Votes down for the social media site Digg.com: an undercover investigation has exposed that a group of influential conservative members were involved in censorship, deliberately trying to ban progressives, by “burying them” (voting down), which effectively means these progressives don’t get enough “digs” to reach the front page where most users spend their time.

Votes up for Healthcare Social Media Europe (#HCSMEU), which just celebrated its first birthday.

Miscellanous

A very strange move: a journal has changed a previously stated conclusion of a previously published paper after a Reuters Health story about serious shortcomings in the report. Read more about it at Gary Schwitzer’s HealthNewsReview Blog.

Finally for the EBM-addicts among us: The Center of Evidence Based Medicine released a new (downloadable) Levels of Evidence Table. At the CEBM-blog they stress that hierarchies of evidence have been somewhat inflexibly used, but are essentially a heuristic, or short-cut to finding the likely best evidence. At first sight the new Table looks simpler, and more easy to use.

Are you a Twitter user? Tweet this!





PubMed versus Google Scholar for Retrieving Evidence

8 06 2010

ResearchBlogging.orgA while ago a resident in dermatology told me she got many hits out of PubMed, but zero results out of TRIP. It appeared she had used the same search for both databases: alopecea areata and diphenciprone (a drug with a lot of synonyms). Searching TRIP for alopecea (in the title) only, we found a Cochrane Review and a relevant NICE guideline.

Usually, each search engine has is its own search and index features. When comparing databases one should compare “optimal” searches and keep in mind for what purpose the search engines are designed. TRIP is most suited to search aggregate evidence, whereas PubMed is most suited to search individual biomedical articles.

Michael Anders and Dennis Evans ignore this “rule of the thumb” in their recent paper “Comparison of PubMed and Google Scholar Literature Searches”. And this is not the only shortcoming of the paper.

The authors performed searches on 3 different topics to compare PubMed and Google Scholar search results. Their main aim was to see which database was the most useful to find clinical evidence in respiratory care.

Well quick guess: PubMed wins…

The 3 respiratory care topics were selected from a list of systematic reviews on the Website of the Cochrane Collaboration and represented in-patient care, out-patient care, and pediatrics.

The references in the three chosen Cochrane Systematic Reviews served as a “reference” (or “golden”) standard. However, abstracts, conference proceedings, and responses to letters were excluded.

So far so good. But note that the outcome of the study only allows us to draw conclusions about interventional questions, that seek to find controlled clinical trials. Other principles may apply to other domains (diagnosis, etiology/harm, prognosis ) or to other types of studies. And it certainly doesn’t apply to non-EBM-topics.

The authors designed ONE search for each topic, by taking 2 common clinical terms from the title of each Cochrane review connected by the Boolean operator “AND” (see Table, ” ” are not used). No synonyms were used and the translation of searches in PubMed wasn’t checked (luckily the mapping was rather good).

“Mmmmm…”

Topic

Search Terms

Noninvasive positive-pressure ventilation for cardiogenic pulmonary edema “noninvasive positive-pressure ventilation” AND “pulmonary edema”
Self-management education and regular practitioner review for adults with asthma “asthma” AND “education”
Ribavirin for respiratory syncytial virus “ribavirin” AND “respiratory syncytial virus”

In PubMed they applied the narrow methodological filter, or Clinical Query, for the domain therapy.
This prefab search strategy (randomized controlled trial[Publication Type] OR (randomized[Title/Abstract] AND controlled[Title/Abstract] AND trial[Title/Abstract]), developed by Haynes, is suitable to quickly detect the available evidence (provided one is looking for RCT’s and doesn’t do an exhaustive search). (see previous posts 2, 3, 4)

Google Scholar, as we all probably know, does not have such methodological filters, but the authors “limited” their search by using the Advanced option and enter the 2 search terms in the “Find articles….with all of the words” space (so this is a boolean “AND“) and they limited it the search to the subject area “Medicine, Pharmacology, and Veterinary Science”.

They did a separate search for publications that were available at their library, which has limited value for others, subscriptions being different for each library.

Next they determined the sensitivity (the number of relevant records retrieved as a proportion of the total number of records in the gold standard) and the precision or positive predictive value, the  fraction of returned positives that are true positives (explained in 3).

Let me guess: sensitivity might be equal or somewhat higher, and precision is undoubtedly much lower in Google Scholar. This is because (in) Google Scholar:

  • you can often search full text instead of just in the abstract, title and (added) keywords/MeSH
  • the results are inflated by finding one and the same references cited in many different papers (that might not directly deal with the subject).
  • you can’t  limit on methodology, study type or “evidence”
  • there is no automatic mapping and explosion (which may provide a way to find more synonyms and thus more relevant studies)
  • has a broader coverage (grey literature, books, more topics)
  • lags behind PubMed in receiving updates from MEDLINE

Results: PubMed and Google Scholar had pretty much the same recall, but for ribavirin and RSV the recall was higher in PubMed, PubMed finding 100%  (12/12) of the included trials, and Google Scholar 58% (7/12)

No discussion as to the why. Since Google Scholar should find the words in titles and abstracts of PubMed I repeated the search in PubMed but only in the title, abstract field, so I searched ribavirin[tiab] AND respiratory syncytial virus[tiab]* and limited it with the narrow therapy filter: I found 26 papers instead of 32. These titles were missing when I only searched title and abstract (between brackets: [relevant MeSH (reason why paper was found), absence of abstract (thus only title and MeSH) and letter], bold: why terms in title abstract are not found)

  1. Evaluation by survival analysis on effect of traditional Chinese medicine in treating children with respiratory syncytial viral pneumonia of phlegm-heat blocking Fei syndrome.
    [MesH:
    Respiratory Syncytial Virus Infections/]
  2. Ribavarin in ventilated respiratory syncytial virus bronchiolitis: a randomized, placebo-controlled trial.
    [MeSH:
    Respiratory Syncytial Virus Infections/ - [NO ABSTRACT, LETTER]
  3. Study of interobserver reliability in clinical assessment of RSV lower respiratory illness.
    [MeSH:Respiratory Syncytial Virus Infections*]
  4. Ribavirin for severe RSV infection. N Engl J Med.
    [MeSH: Respiratory Syncytial Viruses
    [NO ABSTRACT, LETTER]
  5. Stutman HR, Rub B, Janaim HK. New data on clinical efficacy of ribavirin.
    MeSH: Respiratory Syncytial Viruses
    [NO ABSTRACT]
  6. Clinical studies with ribavirin.
    MeSH: Respiratory Syncytial Viruses
    [NO ABSTRACT]

Three of the papers had the additional MeSH respiratory syncytial virus and the three others respiratory syncytial virus infections. Although not all papers (2 comments/letters) may be relevant, it illustrates why PubMed may yield results, that are not retrieved by Google Scholar (if one doesn’t use synonyms)

In Contrast to Google Scholar, PubMed translates the search ribavirin AND respiratory syncytial virus so that the MeSH-terms “ribavirin”, “respiratory syncytial viruses”[MeSH Terms] and (indirectly) respiratory syncytial virus infection”[MeSH] are also found.

Thus in Google Scholar articles with terms like RSV and respiratory syncytial viral pneumonia (or lack of specifications, like clinical efficacy) could have been missed with the above-mentioned search.

The other result of the study (the result section comprises 3 sentences) is that “For each individual search, PubMed had better precision”.

The Precision was 59/467 (13%) in PubMed and 57/80,730 (0.07%)  in Google Scholar (p<0.001)!!
(note: they had to add author names in the Google Scholar search to find the papers in the haystack ;)

Héhéhé, how surprising. Well why would it be that no clinician or librarian would ever think of using Google Scholar as the primary, let alone the only, source to search for medical evidence?
It should also ring a bell, that [QUOTE**]:
In the Cochrane reviews the researchers retrieved information from multiple databases, including MEDLINE, the Cochrane Airways Group trial register (derived from MEDLINE)***, CENTRAL, EMBASE, CINAHL, DARE, NHSEED, the Acute Respiratory Infections Group’s specialized register, and LILACS… “
Note
Google Scholar isn’t mentioned as a source! Google Scholar is only recommendable to search for work citing (already found) relevant articles (this is called forward searching), if one hasn’t access to Web of Science or SCOPUS. Thus only to catch the last fish.

Perhaps the paper could have been more interesting if the authors had looked at any ADDED VALUE of Google Scholar, when exhaustively searching for evidence. Then it would have been crucial to look for grey literature too, (instead of excluding it), because this could be a possible strong point for Google Scholar. Furthermore one could have researched if forward searching yielded extra papers.

The specificity of PubMed is attributed to the used therapy-narrow filter, but the vastly lower specificity of Google Scholar is also due to the searching in the full text, including the reference lists.

For instance, searching for ribavirin AND respiratory syncytial virus in PubMed yields 523 hits. This can be reduced to 32 hits when applying the narrow therapy filter. This means a reduction by a factor of 16.
Yet a similar search in Google Scholar yield
4,080 hits. Thus without the filter there is still an almost 8 times higher yield from Google Scholar than from PubMed.

That evokes another  research idea: what would have happened if randomized (OR randomised) would have been added to the Google Scholar search? Would this have increased the specificity? In case of the above search it lowers the yield with a factor 2, and the first hits look very relevant.

It is really funny but the authors bring down their own conclusion that “These results are important because efficient retrieval of the best available scientific evidence can inform respiratory care protocols, recommendations for clinical decisions in individual patients, and education, while minimizing information overload.” by saying elsewhere that “It is unlikely that users consider more than the first few hundred search results, so RTs who conduct literature searches with Google Scholar on these topics will be much less likely to find references cited in Cochrane reviews.”

Indeed no one would take it into ones head to try to find the relevant papers out of those 4,080 hits retrieved. So what is this study worth from a practical point of view?

Well anyway, as you can ask for the sake of asking you can research for the sake of researching. Despite being an EBM-addict I prefer a good subjective overview on this topic over a weak scientific, quasi-evidence based, research paper.

Does this mean Google Scholar is useless? Does it mean that all those PhD’s hooked on Google Scholar are wrong?

No, Google Scholar serves certain purposes.

Just like the example of PubMed and TRIP, you need to know what is in it for you and how to use it.

I used Google Scholar when I was a researcher:

  • to quickly find a known reference
  • to find citing papers
  • to get an idea of how much articles have been cited/ find the most relevant papers in a quick and dirty way (i.e. by browsing)
  • for quick and dirty searches by putting words string between brackets.
  • to search full text. I used quite extensive searches to find out what methods were used (for instance methods AND (synonym1 or syn2 or syn3)). An interesting possibility is to do a second search for only the last few words (in a string). This will often reveal the next words in the sentence. Often you can repeat this trick, reading a piece of the paper without need for access.

If you want to know more about the pros and cons of Google Scholar I recommend the recent overview by the expert librarian Dean Giustini: “Sure Google Scholar is ideal for some things” [7]“. He also compiled a “Google scholar bibliography” with ~115 articles as of May 2010.

Speaking of librarians, why was the study performed by PhD RRT (RN)’s and wasn’t the university librarian involved?****

* this is a search string and more strict than respiratory AND syncytial AND virus
**
abbreviations used instead of full (database) names
*** this is wrong, a register contains references to controlled clinical trials from EMBASE, CINAHL and all kind of  databases in addition to MEDLINE.
****other then to read the manuscript afterwards.

References

  1. Anders ME, & Evans DP (2010). Comparison of PubMed and Google Scholar Literature Searches. Respiratory care, 55 (5), 578-83 PMID: 20420728
  2. This Blog: http://laikaspoetnik.wordpress.com/2009/11/26/adding-methodological-filters-to-myncbi/
  3. This Blog: http://laikaspoetnik.wordpress.com/2009/01/22/search-filters-1-an-introduction/
  4. This Blog: http://laikaspoetnik.wordpress.com/2009/06/30/10-1-pubmed-tips-for-residents-and-their-instructors/
  5. NeuroDojo (2010/05) Pubmed vs Google Scholar? [also gives a nice overview of pros and cons]
  6. GenomeWeb (2010/05/10) Content versus interface at the heart of Pubmed versus Scholar?/ [response to 5]
  7. The Search principle Blog (2010/05) Sure Google Scholar is ideal for some things.




An Evidence Pyramid that Facilitates the Finding of Evidence

20 03 2010

Earlier I described that there are so many search- and EBM-pyramids that it is confusing. I described  3 categories of pyramids:

  1. Search Pyramids
  2. Pyramids of EBM-sources
  3. Pyramids of EBM-levels (levels of evidence)

In my courses where I train doctors and medical students how to find evidence quickly, I use a pyramid that is a mixture of 1. and 2. This is a slide from a 2007 course.

This pyramid consists of 4 layers (from top down):

  1. EBM-(evidence based) guidelines.
  2. Synopses & Syntheses*: a synopsis is a summary and critical appraisal of one article, whereas synthesis is a summary and critical appraisal of a topic (which may answer several questions and may cover many articles).
  3. Systematic Reviews (a systematic summary and critical appraisal of original studies) which may or may not include a meta-analysis.
  4. Original Studies.

The upper 3 layers represent “Aggregate Evidence”. This is evidence from secondary sources, that search, summarize and critically appraise original studies (lowest layer of the pyramid).

The layers do not necessarily represent the levels of evidence and should not be confused with Pyramids of EBM-levels (type 3). An Evidence Based guideline can have a lower level of evidence than a good systematic review, for instance.
The present pyramid is only meant to lead the way in the labyrinth of sources. Thus, to speed up to process of searching. The relevance and the quality of evidence should always be checked.

The idea is:

  • The higher the level in the pyramid the less publications it contains (the narrower it becomes)
  • Each level summarizes and critically appraises the underlying levels.

I advice people to try to find aggregate evidence first, thus to drill down (hence the drill in the Figure).

The advantage: faster results, lower number to read (NNR).

During the first courses I gave, I just made a pyramid in Word with the links to the main sources.

Our library ICT department converted it into a HTML document with clickable links.

However, although the pyramid looked quite complex, not all main evidence sources were included. Plus some sources belong to different layers. The Trip Database for instance searches sources from all layers.

Our ICT-department came up with a much better looking and better functioning 3-D pyramid, with databases like TRIP in the sidebar.

Moving the  mouse over a pyramid layer invokes a pop-up with links to the databases belonging to that layer.

Furthermore the sources included in the pyramid differ per specialty. So for the department Gynecology we include POPLINE and MIDIRS in the lowest layer, and the RCOG and NVOG (Dutch) guidelines in the EBM-guidelines layer.

Together my colleagues and I decide whether a source is evidence based (we don’t include UpToDate for instance) and where it  belongs. Each clinical librarian (we all serve different departments) then decides which databases to include. Clients can give suggestions.

Below is a short You Tube video showing how this pyramid can be used. Because of the rather poor quality, the video is best to be viewed in full screen mode.
I have no audio (yet), so in short this is what you see:

Made with Screenr:  http://screenr.com/8kg

The pyramid is highly appreciated by our clients and students.

But it is just a start. My dream is to visualize the entire pathway from question to PICO, checklists, FAQs and database of results per type of question/reason for searching (fast question, background question, CAT etc.).

I’m just waiting for someone to fulfill the technical part of this dream.

————–

*Note that there may be different definitions as well. The top layers in the 5S pyramid of Bryan Hayes are defined as follows: syntheses & synopses (succinct descriptions of selected individual studies or systematic reviews, such as those found in the evidence-based journals), summaries, which integrate best available evidence from the lower layers to develop practice guidelines based on a full range of evidence (e.g. Clinical Evidence, National Guidelines Clearinghouse), and at the peak of the model, systems, in which the individual patient’s characteristics are automatically linked to the current best evidence that matches the patient’s specific circumstances and the clinician is provided with key aspects of management (e.g., computerised decision support systems).

Begin with the richest source of aggregate (pre-filtered) evidence and decline in order to to decrease the number needed to read: there are less EBM guidelines than there are Systematic Reviews and (certainly) individual papers.




#NotSoFunny #16 – Ridiculing RCTs & EBM

1 02 2010

I remember it well. As a young researcher I presented my findings in one of my first talks, at the end of which the chair killed my work with a remark, that made the whole room of scientists laugh, but was really beside the point. My supervisor, a truly original and very wise scientist, suppressed his anger. Afterwards, he said: “it is very easy ridiculing something that isn’t a mainstream thought. It’s the argument that counts. We will prove that we are right.” …And we did.

This was not my only encounter with scientists who try to win the debate by making fun of a theory, a finding or …people. But it is not only the witty scientist who is to *blame*, it is also the uncritical audience that just swallows it.

I have similar feelings with some journal articles or blog posts that try to ridicule EBM – or any other theory or approach. Funny, perhaps, but often misunderstood and misused by “the audience”.

Take for instance the well known spoof article in the BMJ:

“Parachute use to prevent death and major trauma related to gravitational challenge: systematic review of randomised controlled trials”

It is one of those Christmas spoof articles in the BMJ, meant to inject some medical humor into the normally serious scientific literature. The spoof parachute article pretends to be a Systematic Review of RCT’s  investigating if parachutes can prevent death and major trauma. Of course, no such trial has been done or will be done: dropping people at random with and without a parachute to proof that you better jump out of a plane with a parachute.

I found the article only mildly amusing. It is so unrealistic, that it becomes absurd. Not that I don’t enjoy absurdities at times, but  absurdities should not assume a live of their own.  In this way it doesn’t evoke a true discussion, but only worsens the prejudice some people already have.

People keep referring to this 2003 article. Last Friday, Dr. Val (with whom I mostly agree) devoted a Friday Funny post to it at Get Better Health: “The Friday Funny: Why Evidence-Based Medicine Is Not The Whole Story”.* In 2008 the paper was also discussed by Not Totally Rad [3]. That EBM is not the whole story seems pretty obvious to me. It was never meant to be…

But lets get specific. Which assumptions about RCT’s and SR’s are wrong, twisted or put out of context? Please read the excellent comments below the article. These often put the finger on the spot.

1. EBM is cookbook medicine.
Many define EBM as “make clinical decisions based on a synthesis of the best available evidence about a treatment.” (i.e. [3]). However, EBM is not cookbook medicine.

The accepted definition of EBM  is “the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients” [4]. Sacket already emphasized back in 1996:

Good doctors use both individual clinical expertise and the best available external evidence, and neither alone is enough. Without clinical expertise, practice risks becoming tyrannised by evidence, for even excellent external evidence may be inapplicable to or inappropriate for an individual patient. Without current best evidence, practice risks becoming rapidly out of date, to the detriment of patients.


2. RCT’s are required for evidence.

Although a well performed RCT provides the “best” evidence, RCT’s are often not appropriate or indicated. That is especially true for domains other than therapy. In case of prognostic questions the most appropriate study design is usually an inception cohort. A RCT for instance can’t tell whether female age is a prognostic factor for clinical pregnancy rates following IVF: there is no way to randomize for “age”, or for “BMI”. ;)

The same is true for etiologic or harm questions. In theory, the “best” answer is obtained by RCT. However RCT’s are often unethical or unnecessary. RCT’s are out of the question to address whether substance X causes cancer. Observational studies will do. Sometimes cases provide sufficient evidence. If a woman gets hepatic veno-occlusive disease after drinking loads of a herbal tea the finding of  similar cases in the literature may be sufficient to conclude that the herbal tea probably caused the disease.

Diagnostic accuracy studies also require another study design (cross-sectional study, or cohort).

But even in the case of  interventions, we can settle for less than a RCT. Evidence is not present or not, but exists on a hierarchy. RCT’s (if well performed) are the most robust, but if not available we have to rely on “lower” evidence.

BMJ Clinical Evidence even made a list of clinical questions unlikely to be answered by RCT’s. In this case Clinical Evidence searches and includes the best appropriate form of evidence.

  1. where there are good reasons to think the intervention is not likely to be beneficial or is likely to be harmful;
  2. where the outcome is very rare (e.g. a 1/10000 fatal adverse reaction);
  3. where the condition is very rare;
  4. where very long follow up is required (e.g. does drinking milk in adolescence prevent fractures in old age?);
  5. where the evidence of benefit from observational studies is overwhelming (e.g. oxygen for acute asthma attacks);
  6. when applying the evidence to real clinical situations (external validity);
  7. where current practice is very resistant to change and/or patients would not be willing to take the control or active treatment;
  8. where the unit of randomisation would have to be too large (e.g. a nationwide public health campaign); and
  9. where the condition is acute and requires immediate treatment.
    Of these, only the first case is categorical. For the rest the cut off point when an RCT is not appropriate is not precisely defined.

Informed health decisions should be based on good science rather than EBM (alone).

Dr Val [2]: “EBM has been an over-reliance on “methodolatry” - resulting in conclusions made without consideration of prior probability, laws of physics, or plain common sense. (….) Which is why Steve Novella and the Science Based Medicine team have proposed that our quest for reliable information (upon which to make informed health decisions) should be based on good science rather than EBM alone.

Methodolatry is the profane worship of the randomized clinical trial as the only valid method of investigation. This is disproved in the previous sections.

The name “Science Based Medicine” suggests that it is opposed to “Evidence Based Medicine”. At their blog David Gorski explains: “We at SBM believe that medicine based on science is the best medicine and tirelessly promote science-based medicine through discussion of the role of science and medicine.”

While this may apply to a certain extent to quack or homeopathy (the focus of SBM) there are many examples of the opposite: that science or common sense led to interventions that were ineffective or even damaging, including:

As a matter of fact many side-effects are not foreseen and few in vitro or animal experiments have led to successful new treatments.

At the end it is most relevant to the patient that “it works” (and the benefits outweigh the harms).

Furthermore EBM is not -or should not be- without consideration of prior probability, laws of physics, or plain common sense. To me SBM and EBM are not mutually exclusive.

Why the example is bullshit unfair and unrealistic

I’ll leave it to the following comments (and yes the choice is biased) [1]

Nibu A George,Scientist :

First of all generalizing such reports of some selected cases and making it a universal truth is unhealthy and challenging the entire scientific community. Secondly, the comparing the parachute scenario with a pure medical situation is unacceptable since the parachute jump is rather a physical situation and it become a medical situation only if the jump caused any physical harm to the person involved.

Richard A. Davidson, MD,MPH:

This weak attempt at humor unfortunately reinforces one of the major negative stereotypes about EBM….that RCT’s are required for evidence, and that observational studies are worthless. If only 10% of the therapies that are paraded in front of us by journals were as effective as parachutes, we would have much less need for EBM. The efficacy of most of our current therapies are only mildly successful. In fact, many therapies can provide only a 25% or less therapeutic improvement. If parachutes were that effective, nobody would use them.
While it’s easy enough to just chalk this one up to the cliche of the cantankerous British clinician, it shows a tremendous lack of insight about what EBM is and does. Even worse, it’s just not funny.

Aviel Roy-Shapira, Senior Staff Surgeon

Smith and Pell succeeded in amusing me, but I think their spoof reflects a common misconception about evidence based medicine. All too many practitioners equate EBM with randomized controlled trials, and metaanalyses.
EBM is about what is accepted as evidence, not about how the evidence is obtained. For example, an RCT which shows that a given drug lowers blood pressure in patients with mild hypertension, however well designed and executed, is not acceptable as a basis for treatment decisions. One has to show that the drug actually lowers the incidence of strokes and heart attacks.
RCT’s are needed only when the outcome is not obvious. If most people who fall from airplanes without a parachute die, this is good enough. There is plenty of evidence for that.

EBM is about using outcome data for making therapeutic decisions. That data can come from RCTs but also from observation

Lee A. Green, Associate Professor

EBM is not RCTs. That’s probably worth repeating several times, because so often both EBM’s detractors and some of its advocates just don’t get it. Evidence is not binary, present or not, but exists on a heirarchy (Guyatt & Rennie, 2001). (….)
The methods and rigor of EBM are nothing more or less than ways of correcting for our
imperfect perceptions of our experiences. We prefer, cognitively, to perceive causal connections. We even perceive such connections where they do not exist, and we do so reliably and reproducibly under well-known sets of circumstances. RCTs aren’t holy writ, they’re simply a tool for filtering out our natural human biases in judgment and causal attribution. Whether it’s necessary to use that tool depends upon the likelihood of such bias occurring.

Scott D Ramsey, Associate Professor

Parachutes may be a no-brainer, but this article is brainless.

Unfortunately, there are few if any parallels to parachutes in health care. The danger with this type of article is that it can lead to labeling certain medical technologies as “parachutes” when in fact they are not. I’ve already seen this exact analogy used for a recent medical technology (lung volume reduction surgery for severe emphysema). In uncontrolled studies, it quite literally looked like everyone who didn’t die got better. When a high quality randomized controlled trial was done, the treatment turned out to have significant morbidity and mortality and a much more modest benefit than was originally hypothesized.

Timothy R. Church, Professor

On one level, this is a funny article. I chuckled when I first read it. On reflection, however, I thought “Well, maybe not,” because a lot of people have died based on physicians’ arrogance about their ability to judge the efficacy of a treatment based on theory and uncontrolled observation.

Several high profile medical procedures that were “obviously” effective have been shown by randomized trials to be (oops) killing people when compared to placebo. For starters to a long list of such failed therapies, look at antiarrhythmics for post-MI arrhythmias, prophylaxis for T. gondii in HIV infection, and endarterectomy for carotid stenosis; all were proven to be harmful rather than helpful in randomized trials, and in the face of widespread opposition to even testing them against no treatment. In theory they “had to work.” But didn’t.

But what the heck, let’s play along. Suppose we had never seen a parachute before. Someone proposes one and we agree it’s a good idea, but how to test it out? Human trials sound good. But what’s the question? It is not, as the author would have you believe, whether to jump out of the plane without a parachute or with one, but rather stay in the plane or jump with a parachute. No one was voluntarily jumping out of planes prior to the invention of the parachute, so it wasn’t to prevent a health threat, but rather to facilitate a rapid exit from a nonviable plane.

Another weakness in this straw-man argument is that the physics of the parachute are clear and experimentally verifiable without involving humans, but I don’t think the authors would ever suggest that human physiology and pathology in the face of medication, radiation, or surgical intervention is ever quite as clear and predictable, or that non-human experience (whether observational or experimental) would ever suffice.

The author offers as an alternative to evidence-based methods the “common sense” method, which is really the “trust me, I’m a doctor” method. That’s not worked out so well in many high profile cases (see above, plus note the recent finding that expensive, profitable angioplasty and coronary artery by-pass grafts are no better than simple medical treatment of arteriosclerosis). And these are just the ones for which careful scientists have been able to do randomized trials. Most of our accepted therapies never have been subjected to such scrutiny, but it is breathtaking how frequently such scrutiny reveals problems.

Thanks, but I’ll stick with scientifically proven remedies.

parachute experiments without humans

* on the same day as I posted Friday Foolery #15: The Man who pioneered the RCT. What a coincidence.

** Don’t forget to read the comments to the article. They are often excellent.

Photo Credits

ReferencesResearchBlogging.org

  1. Smith, G. (2003). Parachute use to prevent death and major trauma related to gravitational challenge: systematic review of randomised controlled trials BMJ, 327 (7429), 1459-1461 DOI: 10.1136/bmj.327.7429.1459
  2. The Friday Funny: Why Evidence-Based Medicine Is Not The Whole Story”. (getbetterhealth.com) [2010.01.29]
  3. Call for randomized clinical trials of Parachutes (nottotallyrad.blogspot.com) [08-2008]
  4. Sackett DL, Rosenberg WM, Gray JA, Haynes RB, & Richardson WS (1996). Evidence based medicine: what it is and what it isn’t. BMJ (Clinical research ed.), 312 (7023), 71-2 PMID: 8555924
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are very well edged off




#Cochrane Colloquium 2009: Better Working Relationship between Cochrane and Guideline Developers

19 10 2009

singapore CCLast week I attended the annual Cochrane Colloquium in Singapore. I will summarize some of the meetings.

Here is a summary of an interesting (parallel) special session: Creating a closer working relationship between Cochrane and Guideline Developers. This session was brought together as a partnership between the Guidelines International Network (G-I-N) and The Cochrane Collaboration to look at the current experience of guideline developers and their use of Cochrane reviews (see abstract).

Emma Tavender of the EPOC Australian Satellite, Australia reported on the survey carried out by the UK Cochrane Centre to identify the use of Cochrane reviews in guidelines produced in the UK ) (not attended this presentation) .

Pwee Keng Ho, Ministry of Health, Singapore, is leading the Health Technology Assessment (HTA) and guideline development program of the Singapore Ministry of Health. He spoke about the issues faced as a guideline developer using Cochrane reviews or -in his own words- his task was: “to summarize whether guideline developers like Cochrane Systematic reviews or not” .

Keng Ho presented the results of 3 surveys of different guideline developers. Most surveys had very few respondents: 12-29 if I remember it well.

Each survey had approximately the same questions, but in a different order. On the face of it, the 3 surveys gave the same picture.

Main points:

  • some guideline developers are not familiar with Cochrane Systematic Reviews
  • others have no access to it.
  • of those who are familiar with the Cochrane Reviews and do have access to it, most found the Cochrane reviews useful and reliable. (in one survey half of the respondents were neutral)
  • most importantly they actually did use the Cochrane reviews for most of their guidelines.
  • these guideline developers also used the Cochrane methodology to make their guidelines (whereas most physicians are not inclined to use the exhaustive search strategies and systematic approach of the Cochrane Collaboration)
  • An often heard critique of Guideline developers concerned the non-comprehensive coverage of topics by Cochrane Reviews. However, unlike in Western countries, the Singapore minister of Health mentioned acupuncture and herbs as missing topics (for certain diseases).

This incomplete coverage caused by a not-demand driven choice of subjects was a recurrent topic at this meeting and a main issue recognized by the entire Cochrane Community. Therefore priority setting of Cochrane Systematic reviews is one of the main topics addressed at this Colloquium and in the Cochrane Strategic review.

Kay Dickersin of the US Cochrane Center, USA, reported on the issues raised at the stakeholders meeting held in June 2009 in the US (see here for agenda) on whether systematic reviews can effectively inform guideline development, with a particular focus on areas of controversy and debate.

The Stakeholder summit concentrated on using quality SR’s for guidelines. This is different from effectiveness research, for which the Institute of Medicine (IOM) sets the standards: local and specialist guidelines require a different expertise and approach.

All kinds of people are involved in the development of guidelines, i.e. nurses, consumers, physicians.
Important issues to address, point by point:

  • Some may not understand the need to be systematic
  • How to get physicians on board: they are not very comfortable with extensive searching and systematic work
  • Ongoing education, like how-to workshops, is essential
  • What to do if there is no evidence?
  • More transparency; handling conflicts of interest
  • Guidelines differ, including the rating of the evidence. Almost everyone in the Stakeholders meeting used GRADE to grade the evidence, but not as it was originally described. There were numerous variations on the same theme. One question is whether there should be one system or not.
  • Another -recurrent- issue was that Guidelines should be made actionable.

Here are podcasts covering the meeting

Gordon Guyatt, McMaster University, Canada, gave  an outline of the GRADE approach and the purpose of ‘Summary of Findings’ tables, and how both are perceived by Cochrane review authors and guideline developers.

Gordon Guyatt, whose magnificent book ” Users’ Guide to the Medical Literature”  (JAMA-Evidence) lies at my desk, was clearly in favor of adherence to the original Grade-guidelines. Forty organizations have adopted these Grade Guidelines.

Grade stands for “Grading of Recommendations Assessment, Development and Evaluation”  system. It is used for grading evidence when submitting a clinical guidelines article. Six articles in the BMJ are specifically devoted to GRADE (see here for one (full text); and 2 (PubMed)). GRADE not only takes the rigor of the methods  into account, but also the balance between the benefits and the risks, burdens, and costs.

Suppose  a guideline would recommend  to use thrombolysis to treat disease X, because a good quality small RCTs show thrombolysis to be slightly but significantly more effective than heparin in this disease. However by relying on only direct evidence from the RCT’s it isn’t taken into account that observational studies have long shown that thrombolysis enhances the risk of massive bleeding in diseases Y and Z. Clearly the risk of harm is the same in disease X: both benefits and harms should be weighted.
Guyatt gave several other examples illustrating the importance of grading the evidence and the understandable overview presented in the Summary of Findings Table.

Another issue is that guideline makers are distressingly ready to embrace surrogate endpoints instead of outcomes that are more relevant to the patient. For instance it is not very meaningful if angiographic outcomes are improved, but mortality or the recurrence of cardiovascular disease are not.
GRADE takes into account if indirect evidence is used: It downgrades the evidence rating.  Downgrading also occurs in case of low quality RCT’s or the non-trade off of benefits versus harms.

Guyatt pleaded for uniform use of GRADE, and advised everybody to get comfortable with it.

Although I must say that it can feel somewhat uncomfortable to give absolute rates to non-absolute differences. These are really man-made formulas, people agreed upon. On the other hand it is a good thing that it is not only the outcome of the RCT’s with respect to benefits (of sometimes surrogate markers) that count.

A final remark of Guyatt: ” Everybody makes the claim they are following evidence based approach, but you have to learn them what that really means.”
Indeed, many people talk about their findings and/or recommendations being evidence based, because “EBM sells well”, but upon closer examination many reports are hardly worth the name.

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UpToDate or Dynamed?

5 07 2009

Guest author: Shamsha Damani (@shamsha) ;
Submission for the July Medlib’s Round

Doctors and other healthcare providers are busy folks. They often don’t have time to go through all the primary literature, find the best evidence, critique it and apply it to their patients in real-time. This is where point-of-care resources shine and make life a bit easier. There are several such tools out there, but the two that I use on a regular basis are UpToDate and DynaMed. There are others like InfoPoems, ACP’s PIER, MD Consult and BMJ’s Point of Care. I often get asked which ones are the best to use and why. The librarian answer to this question: depends on what you are looking for! Not a fair answer I admit, so I wanted to highlight some pros and cons of UpToDate and DynaMed to help you better determine what route to take the next time you find yourself in need of a quick answer to a clinical question.

UpToDate

Pros:

  • Comprehensive coverage
  • Easy-to-read writing style
  • The introduction of grading the evidence is certainly very welcome!

Cons:

  • Expensive
  • Conflict of interest policy a bit perplexing
  • Search feature could use a makeover
  • Remote access at a high premium
  • Not accessible via smart phones
  • They didn’t come to MLA’09 this year and medical librarians felt snubbed (ok, that is not a con, just an observation!)

DynaMed

Pros:

  • Bulleted format is easy to read
  • Remote access part of subscription
  • No conflict of interest with authors
  • A lot of the evidence is graded
  • Accessible on PDAs (iPhones and Blackberries included!)

Cons:

  • The user interface is a bit 1990s and could use a makeover
  • The coverage is not as extensive yet, though they keep adding more topics

A lot has been written about UpToDate and DynaMed, both in PubMed as well as on various blogs. Jacqueline also did a fabulous post of the evidence-based-ness of UpToDate not too long ago. I used to think that I should pick one and stick to it, but have recently found myself re-thinking this attitude. I think that we need to keep in mind that these are point-of-care tools and should not be utilized as one’s only source of information. Use the tool to get an idea about current evidence and combine it with your own clinical judgment when needed at point-of-care. If suspicious, look up the primary literature the good old way by using MEDLINE or other such databases. A point-of-care database will get you started; however, it is not meant to be a one-stop-shop.

I can almost hear people saying: so which one do you prefer anyways? That’s like asking me if I prefer Coke or Pepsi. My honest answer: both! (databases as well as beverages!). So what is a busy clinician to do? If you have access to both (or more), spend some time playing with them and see which one you like. Everyone has a different searching and learning style and it is sometimes a matter of preference. DynaMed’s concise structure may be appealing to newbies, whereas seasoned clinicians may prefer UpToDate’s narrative approach. Based on my very unscientific observation of Twitter conversations, it appears that clinicians in general prefer UpToDate whereas librarians prefer DynaMed. Could this be because UpToDate markets heavily to clinicians and snubs librarians? Or could it be the price? Or could it be the age-old debate on what is evidence? I don’t know the answer, partly because I find it all a bit too political. I’ve seen healthcare providers often use Google or Wikipedia for medical answers, which is quite sad. If you are using either UpToDate or DynaMed (or another similar product), you have already graduated to the big leagues and are a true EBM player! So relax and don’t feel like you have to pick a side. I find myself using both on a regular basis; the degree of success I have with each can be gauged by my daily Twitter feed!

Shamsha Damani








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