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




What Did Deep DNA Sequencing of Traditional Chinese Medicines (TCMs) Really Reveal?

30 04 2012

ResearchBlogging.orgA recent study published in PLOS genetics[1] on a genetic audit of Traditional Chinese Medicines (TCMs) was widely covered in the news. The headlines are a bit confusing as they said different things. Some headlines say “Dangers of Chinese Medicine Brought to Light by DNA Studies“, others that Bear and Antelope DNA are Found in Traditional Chinese Medicine, and still others more neutrally: Breaking down traditional Chinese medicine.

What have Bunce and his group really done and what is the newsworthiness of this article?

doi:info:doi/10.1371/journal.pgen.1002657.g001

Photos from 4 TCM samples used in this study doi/10.1371/journal.pgen.1002657.g001

The researchers from the the Murdoch University, Australia,  have applied Second Generation, high-throughput sequencing to identify the plant and animal composition of 28 TCM samples (see Fig.). These TCM samples had been seized by Australian Customs and Border Protection Service at airports and seaports across Australia, because they contravened Australia’s international wildlife trade laws (Part 13A EPBC Act 1999).

Using primers specific for the plastid trnL gene (plants) and the mitochondrial 16S ribosomal RNA (animals), DNA of sufficient quality was obtained from 15 of the 28 (54%) TCM samples. The resultant 49,000 amplicons (amplified sequences) were analyzed by high-throughput sequencing and compared to reference databases.

Due to better GenBank coverage, the analysis of vertebrate DNA was simpler and less ambiguous than the analysis of the plant origins.

Four TCM samples – Saiga Antelope Horn powder, Bear Bile powder, powder in box with bear outline and Chu Pak Hou Tsao San powder were found to contain DNA from known CITES- (Convention on International Trade in Endangered Species) listed species. This is no real surprise, as the packages were labeled as such.

On the other hand some TCM samples, like the “100% pure” Saiga Antilope powder, were “diluted” with  DNA from bovids (i.e. goats and sheep), deer and/or toads. In 78% of the samples, animal DNA was identified that had not been clearly labeled as such on the packaging.

In total 68 different plant families were detected in the medicines. Some of the TCMs contained plants of potentially toxic genera like Ephedra and Asarum. Ephedra contains the sympathomimetic ephedrine, which has led to many, sometimes fatal, intoxications, also in Western countries. It should be noted however, that pharmacological activity cannot be demonstrated by DNA-analysis. Similarly, certain species of Asarum (wild ginger) contain the nephrotoxic and carcinogenic aristolochic acid, but it would require further testing to establish the presence of aristolochia acid in the samples positive for Asarum. Plant DNA assigned to other potentially toxic, allergic (nuts, soy) and/or subject to CITES regulation were also recovered. Again, other gene regions would need to be targeted, to reveal the exact species involved.

Most newspapers emphasized that the study has brought to light “the dangers of TCM”

For this reason The Telegraph interviewed an expert in the field, Edzard Ernst, Professor of Complementary Medicine at the University of Exeter. Ernst:

“The risks of Chinese herbal medicine are numerous: firstly, the herbs themselves can be toxic; secondly, they might interact with prescription drugs; thirdly, they are often contaminated with heavy metals; fourthly, they are frequently adulterated with prescription drugs; fifthly, the practitioners are often not well trained, make unsubstantiated claims and give irresponsible, dangerous advice to their patients.”

Ernst is right about the risks. However, these adverse effects of TCM have long been known. Fifteen years ago I happened to have written a bibliography about “adverse effects of herbal medicines*” (in Dutch, a good book on this topic is [2]). I did exclude interactions with prescription drugs, contamination with heavy metals and adulteration with prescription drugs, because the events (publications in PubMed and EMBASE) were to numerous(!). Toxic Chinese herbs mostly caused acute toxicity by aconitine, anticholinergic (datura, atropa) and podophyllotoxin intoxications. In Belgium 80 young women got nephropathy (kidney problems) after attending a “slimming” clinic because of mixup of Stephania (chinese: fangji) with Aristolochia fanghi (which contains the toxic aristolochic acid). Some of the women later developed urinary tract cancer.

In other words, toxic side effects of herbs including chinese herbs are long known. And the same is true for the presence of (traces of) endangered species in TCM.

In a media release the complementary health council (CHC) of Australia emphasized that the 15 TCM products featured in this study were rogue products seized by Customs as they were found to contain prohibited and undeclared ingredients. The CHC emphasizes the proficiency of rigorous regulatory regime around complementary medicines, i.e. all ingredients used in listed products must be on the permitted list of ingredients. However, Australian regulations do not apply to products purchased online from overseas.

Thus if the findings are not new and (perhaps) not applicable to most legal TCM, then what is the value of this paper?

The new aspect is the high throughput DNA sequencing approach, which allows determination of a larger number of animal and plant taxa than would have been possible through morphological and/or biochemical means. Various TCM-samples are suitable: powders, tablets, capsules, flakes and herbal teas.

There are also some limitations:

  1. DNA of sufficient quality could only be obtained from appr. half of the samples.
  2. Plants sequences could often not be resolved beyond the family level. Therefore it could often not be established whether an endangered of toxic species was really present (or an innocent family member).
  3. Only DNA sequences can be determined, not pharmacological activity.
  4. The method is at best semi-quantitative.
  5. Only plant and animal ingredients are determined, not contaminating heavy metals or prescription drugs.

In the future, species assignment (2) can be improved with the development of better reference databases involving multiple genes and (3) can be solved by combining genetic (sequencing) and metabolomic (for compound detection) approaches. According to the authors this may be a cost-effective way to audit TCM products.

Non-technical approaches may be equally important: like convincing consumers not to use medicines containing animal traces (not to speak of  endangered species), not to order  TCM online and to avoid the use of complex, uncontrolled TCM-mixes.

Furthermore, there should be more info on what works and what doesn’t.

*including but not limited to TCM

References

  1. Coghlan ML, Haile J, Houston J, Murray DC, White NE, Moolhuijzen P, Bellgard MI, & Bunce M (2012). Deep Sequencing of Plant and Animal DNA Contained within Traditional Chinese Medicines Reveals Legality Issues and Health Safety Concerns. PLoS genetics, 8 (4) PMID: 22511890 (Free Full Text)
  2. Adverse Effects of Herbal Drugs 2 P. A. G. M. De Smet K. Keller R. Hansel R. F. Chandler, Paperback. Springer 1993-01-15. ISBN 0387558004 / 0-387-55800-4 EAN 9780387558004
  3. DNA may weed out toxic Chinese medicine (abc.net.au)
  4. Bedreigde beren in potje Lucas Brouwers, NRC Wetenschap 14 april 2012, bl 3 [Dutch]
  5. Dangers in herbal medicine (continued) – DNA sequencing to hunt illegal ingredients (somethingaboutscience.wordpress.com)
  6. Breaking down traditional Chinese medicine. (green.blogs.nytimes.com)
  7. Dangers of Chinese Medicine Brought to Light by DNA Studies (news.sciencemag.org)
  8. Chinese herbal medicines contained toxic mix (cbc.ca)
  9. Screen uncovers hidden ingredients of Chinese medicine (Nature News)
  10. Media release: CHC emphasises proficiency of rigorous regulatory regime around complementary medicines (http://www.chc.org.au/)




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)

Related articles (automatically generated)





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)

Related articles (automatically generated)





FUTON Bias. Or Why Limiting to Free Full Text Might not Always be a Good Idea.

8 09 2011

ResearchBlogging.orgA few weeks ago I was discussing possible relevant papers for the Twitter Journal Club  (Hashtag #TwitJC), a succesful initiative on Twitter, that I have discussed previously here and here [7,8].

I proposed an article, that appeared behind a paywall. Annemarie Cunningham (@amcunningham) immediately ran the idea down, stressing that open-access (OA) is a pre-requisite for the TwitJC journal club.

One of the TwitJC organizers, Fi Douglas (@fidouglas on Twitter), argued that using paid-for journals would defeat the objective that  #TwitJC is open to everyone. I can imagine that fee-based articles could set a too high threshold for many doctors. In addition, I sympathize with promoting OA.

However, I disagree with Annemarie that an OA (or rather free) paper is a prerequisite if you really want to talk about what might impact on practice. On the contrary, limiting to free full text (FFT) papers in PubMed might lead to bias: picking “low hanging fruit of convenience” might mean that the paper isn’t representative and/or doesn’t reflect the current best evidence.

But is there evidence for my theory that selecting FFT papers might lead to bias?

Lets first look at the extent of the problem. Which percentage of papers do we miss by limiting for free-access papers?

survey in PLOS by Björk et al [1] found that one in five peer reviewed research papers published in 2008 were freely available on the internet. Overall 8,5% of the articles published in 2008 (and 13,9 % in Medicine) were freely available at the publishers’ sites (gold OA).  For an additional 11,9% free manuscript versions could be found via the green route:  i.e. copies in repositories and web sites (7,8% in Medicine).
As a commenter rightly stated, the lag time is also important, as we would like to have immediate access to recently published research, yet some publishers (37%) impose an access-embargo of 6-12 months or more. (these papers were largely missed as the 2008 OA status was assessed late 2009).

PLOS 2009

The strength of the paper is that it measures  OA prevalence on an article basis, not on calculating the share of journals which are OA: an OA journal generally contains a lower number of articles.
The authors randomly sampled from 1.2 million articles using the advanced search facility of Scopus. They measured what share of OA copies the average researcher would find using Google.

Another paper published in  J Med Libr Assoc (2009) [2], using similar methods as the PLOS survey examined the state of open access (OA) specifically in the biomedical field. Because of its broad coverage and popularity in the biomedical field, PubMed was chosen to collect their target sample of 4,667 articles. Matsubayashi et al used four different databases and search engines to identify full text copies. The authors reported an OA percentage of 26,3 for peer reviewed articles (70% of all articles), which is comparable to the results of Björk et al. More than 70% of the OA articles were provided through journal websites. The percentages of green OA articles from the websites of authors or in institutional repositories was quite low (5.9% and 4.8%, respectively).

In their discussion of the findings of Matsubayashi et al, Björk et al. [1] quickly assessed the OA status in PubMed by using the new “link to Free Full Text” search facility. First they searched for all “journal articles” published in 2005 and then repeated this with the further restrictions of “link to FFT”. The PubMed OA percentages obtained this way were 23,1 for 2005 and 23,3 for 2008.

This proportion of biomedical OA papers is gradually increasing. A chart in Nature’s News Blog [9] shows that the proportion of papers indexed on the PubMed repository each year has increased from 23% in 2005 to above 28% in 2009.
(Methods are not shown, though. The 2008 data are higher than those of Björk et al, who noticed little difference with 2005. The Data for this chart, however, are from David Lipman, NCBI director and driving force behind the digital OA archive PubMed Central).
Again, because of the embargo periods, not all literature is immediately available at the time that it is published.

In summary, we would miss about 70% of biomedical papers by limiting for FFT papers. However, we would miss an even larger proportion of papers if we limit ourselves to recently published ones.

Of course, the key question is whether ignoring relevant studies not available in full text really matters.

Reinhard Wentz of the Imperial College Library and Information Service already argued in a visionary 2002 Lancet letter[3] that the availability of full-text articles on the internet might have created a new form of bias: FUTON bias (Full Text On the Net bias).

Wentz reasoned that FUTON bias will not affect researchers who are used to comprehensive searches of published medical studies, but that it will affect staff and students with limited experience in doing searches and that it might have the same effect in daily clinical practice as publication bias or language bias when doing systematic reviews of published studies.

Wentz also hypothesized that FUTON bias (together with no abstract available (NAA) bias) will affect the visibility and the impact factor of OA journals. He makes a reasonable cause that the NAA-bias will affect publications on new, peripheral, and under-discussion subjects more than established topics covered in substantive reports.

The study of Murali et al [4] published in Mayo Proceedings 2004 confirms that the availability of journals on MEDLINE as FUTON or NAA affects their impact factor.

Of the 324 journals screened by Murali et al. 38.3% were FUTON, 19.1%  NAA and 42.6% had abstracts only. The mean impact factor was 3.24 (±0.32), 1.64 (±0.30), and 0.14 (±0.45), respectively! The authors confirmed this finding by showing a difference in impact factors for journals available in both the pre and the post-Internet era (n=159).

Murali et al informally questioned many physicians and residents at multiple national and international meetings in 2003. These doctors uniformly admitted relying on FUTON articles on the Web to answer a sizable proportion of their questions. A study by Carney et al (2004) [5] showed  that 98% of the US primary care physicians used the Internet as a resource for clinical information at least once a week and mostly used FUTON articles to aid decisions about patient care or patient education and medical student or resident instruction.

Murali et al therefore conclude that failure to consider FUTON bias may not only affect a journal’s impact factor, but could also limit consideration of medical literature by ignoring relevant for-fee articles and thereby influence medical education akin to publication or language bias.

This proposed effect of the FFT limit on citation retrieval for clinical questions, was examined in a  more recent study (2008), published in J Med Libr Assoc [6].

Across all 4 questions based on a research agenda for physical therapy, the FFT limit reduced the number of citations to 11.1% of the total number of citations retrieved without the FFT limit in PubMed.

Even more important, high-quality evidence such as systematic reviews and randomized controlled trials were missed when the FFT limit was used.

For example, when searching without the FFT limit, 10 systematic reviews of RCTs were retrieved against one when the FFT limit was used. Likewise when searching without the FFT limit, 28 RCTs were retrieved and only one was retrieved when the FFT limit was used.

The proportion of missed studies (appr. 90%) is higher than in the studies mentioned above. Possibly this is because real searches have been tested and that only relevant clinical studies  have been considered.

The authors rightly conclude that consistently missing high-quality evidence when searching clinical questions is problematic because it undermines the process of Evicence Based Practice. Krieger et al finally conclude:

“Librarians can educate health care consumers, scientists, and clinicians about the effects that the FFT limit may have on their information retrieval and the ways it ultimately may affect their health care and clinical decision making.”

It is the hope of this librarian that she did a little education in this respect and clarified the point that limiting to free full text might not always be a good idea. Especially if the aim is to critically appraise a topic, to educate or to discuss current best medical practice.

References

  1. Björk, B., Welling, P., Laakso, M., Majlender, P., Hedlund, T., & Guðnason, G. (2010). Open Access to the Scientific Journal Literature: Situation 2009 PLoS ONE, 5 (6) DOI: 10.1371/journal.pone.0011273
  2. Matsubayashi, M., Kurata, K., Sakai, Y., Morioka, T., Kato, S., Mine, S., & Ueda, S. (2009). Status of open access in the biomedical field in 2005 Journal of the Medical Library Association : JMLA, 97 (1), 4-11 DOI: 10.3163/1536-5050.97.1.002
  3. WENTZ, R. (2002). Visibility of research: FUTON bias The Lancet, 360 (9341), 1256-1256 DOI: 10.1016/S0140-6736(02)11264-5
  4. Murali NS, Murali HR, Auethavekiat P, Erwin PJ, Mandrekar JN, Manek NJ, & Ghosh AK (2004). Impact of FUTON and NAA bias on visibility of research. Mayo Clinic proceedings. Mayo Clinic, 79 (8), 1001-6 PMID: 15301326
  5. Carney PA, Poor DA, Schifferdecker KE, Gephart DS, Brooks WB, & Nierenberg DW (2004). Computer use among community-based primary care physician preceptors. Academic medicine : journal of the Association of American Medical Colleges, 79 (6), 580-90 PMID: 15165980
  6. Krieger, M., Richter, R., & Austin, T. (2008). An exploratory analysis of PubMed’s free full-text limit on citation retrieval for clinical questions Journal of the Medical Library Association : JMLA, 96 (4), 351-355 DOI: 10.3163/1536-5050.96.4.010
  7. The #TwitJC Twitter Journal Club, a new Initiative on Twitter. Some Initial Thoughts. (laikaspoetnik.wordpress.com)
  8. The Second #TwitJC Twitter Journal Club (laikaspoetnik.wordpress.com)
  9. How many research papers are freely available? (blogs.nature.com)




PubMed’s Higher Sensitivity than OVID MEDLINE… & other Published Clichés.

21 08 2011

ResearchBlogging.orgIs it just me, or are biomedical papers about searching for a systematic review often of low quality or just too damn obvious? I’m seldom excited about papers dealing with optimal search strategies or peculiarities of PubMed, even though it is my specialty.
It is my impression, that many of the lower quality and/or less relevant papers are written by clinicians/researchers instead of information specialists (or at least no medical librarian as the first author).

I can’t help thinking that many of those authors just happen to see an odd feature in PubMed or encounter an unexpected  phenomenon in the process of searching for a systematic review.
They think: “Hey, that’s interesting” or “that’s odd. Lets write a paper about it.” An easy way to boost our scientific output!
What they don’t realize is that the published findings are often common knowledge to the experienced MEDLINE searchers.

Lets give two recent examples of what I think are redundant papers.

The first example is a letter under the heading “Clinical Observation” in Annals of Internal Medicine, entitled:

“Limitations of the MEDLINE Database in Constructing Meta-analyses”.[1]

As the authors rightly state “a thorough literature search is of utmost importance in constructing a meta-analysis. Since the PubMed interface from the National Library of Medicine is a cornerstone of many meta-analysis,  the authors (two MD’s) focused on the freely available PubMed” (with MEDLINE as its largest part).

The objective was:

“To assess the accuracy of MEDLINE’s “human” and “clinical trial” search limits, which are used by authors to focus literature searches on relevant articles.” (emphasis mine)

O.k…. Stop! I know enough. This paper should have be titled: “Limitation of Limits in MEDLINE”.

Limits are NOT DONE, when searching for a systematic review. For the simple reason that most limits (except language and dates) are MESH-terms.
It takes a while before the indexers have assigned a MESH to the papers and not all papers are correctly (or consistently) indexed. Thus, by using limits you will automatically miss recent, not yet, or not correctly indexed papers. Whereas it is your goal (or it should be) to find as many relevant papers as possible for your systematic review. And wouldn’t it be sad if you missed that one important RCT that was published just the other day?

On the other hand, one doesn’t want to drown in irrelevant papers. How can one reduce “noise” while minimizing the risk of loosing relevant papers?

  1. Use both MESH and textwords to “limit” you search, i.e. also search “trial” as textword, i.e. in title and abstract: trial[tiab]
  2. Use more synonyms and truncation (random*[tiab] OR  placebo[tiab])
  3. Don’t actively limit but use double negation. Thus to get rid of animal studies, don’t limit to humans (this is the same as combining with MeSH [mh]) but safely exclude animals as follows: NOT animals[mh] NOT humans[mh] (= exclude papers indexed with “animals” except when these papers are also indexed with “humans”).
  4. Use existing Methodological Filters (ready-made search strategies) designed to help focusing on study types. These filters are based on one or more of the above-mentioned principles (see earlier posts here and here).
    Simple Methodological Filters can be found at the PubMed Clinical Queries. For instance the narrow filter for Therapy not only searches for the Publication Type “Randomized controlled trial” (a limit), but also for randomized, controlled ànd  trial  as textwords.
    Usually broader (more sensitive) filters are used for systematic reviews. The Cochrane handbook proposes to use the following filter maximizing precision and sensitivity to identify randomized trials in PubMed (see http://www.cochrane-handbook.org/):
    (randomized controlled trial [pt] OR controlled clinical trial [pt] OR randomized [tiab] OR placebo [tiab] OR clinical trials as topic [mesh: noexp] OR randomly [tiab] OR trial [ti]) NOT (animals [mh] NOT humans [mh]).
    When few hits are obtained, one can either use a broader filter or no filter at all.

In other words, it is a beginner’s mistake to use limits when searching for a systematic review.
Besides that the authors publish what should be common knowledge (even our medical students learn it) they make many other (little) mistakes, their precise search is difficult to reproduce and far from complete. This is already addressed by Dutch colleagues in a comment [2].

The second paper is:

PubMed had a higher sensitivity than Ovid-MEDLINE in the search for systematic reviews [3], by Katchamart et al.

Again this paper focuses on the usefulness of PubMed to identify RCT’s for a systematic review, but it concentrates on the differences between PubMed and OVID in this respect. The paper starts with  explaining that PubMed:

provides access to bibliographic information in addition to MEDLINE, such as in-process citations (..), some OLDMEDLINE citations (….) citations that precede the date that a journal was selected for MEDLINE indexing, and some additional life science journals that submit full texts to PubMed Central and receive a qualitative review by NLM.

Given these “facts”, am I exaggerating when I am saying that the authors are pushing at an open door when their main conclusion is that PubMed retrieved more citations overall than Ovid-MEDLINE? The one (!) relevant article missed in OVID was a 2005 study published in a Japanese journal that MEDLINE started indexing in 2007. It was therefore in PubMed, but not in OVID MEDLINE.

An important aspect to keep in mind when searching OVID/MEDLINE ( I have earlier discussed here and here). But worth a paper?

Recently, after finishing an exhaustive search in OVID/MEDLINE, we noticed that we missed a RCT in PubMed, that was not yet available in OVID/MEDLINE.  I just added one sentence to the search methods:

Additionally, PubMed was searched for randomized controlled trials ahead of print, not yet included in OVID MEDLINE. 

Of course, I could have devoted a separate article to this finding. But it is so self-evident, that I don’t think it would be worth it.

The authors have expressed their findings in sensitivity (85% for Ovid-MEDLINE vs. 90% for PubMed, 5% is that ONE paper missing), precision and  number to read (comparable for OVID-MEDLINE and PubMed).

If I might venture another opinion: it looks like editors of medical and epidemiology journals quickly fall for “diagnostic parameters” on a topic that they don’t understand very well: library science.

The sensitivity/precision data found have little general value, because:

  • it concerns a single search on a single topic
  • there are few relevant papers (17- 18)
  • useful features of OVID MEDLINE that are not available in PubMed are not used. I.e. Adjacency searching could enhance the retrieval of relevant papers in OVID MEDLINE (adjacency=words searched within a specified maximal distance of each other)
  • the searches are not comparable, nor are the search field commands.

The latter is very important, if one doesn’t wish to compare apples and oranges.

Lets take a look at the first part of the search (which is in itself well structured and covers many synonyms).
First part of the search - Click to enlarge
This part of the search deals with the P: patients with rheumatoid arthritis (RA). The authors first search for relevant MeSH (set 1-5) and then for a few textwords. The MeSH are fine. The authors have chosen to use Arthritis, rheumatoid and a few narrower terms (MeSH-tree shown at the right). The authors have taken care to use the MeSH:noexp command in PubMed to prevent the automatic explosion of narrower terms in PubMed (although this is superfluous for MesH terms having no narrow terms, like Caplan syndrome etc.).

But the fields chosen for the free text search (sets 6-9) are not comparable at all.

In OVID the mp. field is used, whereas all fields or even no fields are used in PubMed.

I am not even fond of the uncontrolled use of .mp (I rather search in title and abstract, remember we already have the proper MESH-terms), but all fields is even broader than .mp.

In general a .mp. search looks in the Title, Original Title, Abstract, Subject Heading, Name of Substance, and Registry Word fields. All fields would be .af in OVID not .mp.

Searching for rheumatism in OVID using the .mp field yields 7879 hits against 31390 hits when one searches in the .af field.

Thus 4 times as much. Extra fields searched are for instance the journal and the address field. One finds all articles in the journal Arthritis & Rheumatism for instance [line 6], or papers co-authored by someone of the dept. of rheumatoid surgery [line 9]

Worse, in PubMed the “all fields” command doesn’t prevent the automatic mapping.

In PubMed, Rheumatism[All Fields] is translated as follows:

“rheumatic diseases”[MeSH Terms] OR (“rheumatic”[All Fields] AND “diseases”[All Fields]) OR “rheumatic diseases”[All Fields] OR “rheumatism”[All Fields]

Oops, Rheumatism[All Fields] is searched as the (exploded!) MeSH rheumatic diseases. Thus rheumatic diseases (not included in the MeSH-search) plus all its narrower terms! This makes the entire first part of the PubMed search obsolete (where the authors searched for non-exploded specific terms). It explains the large difference in hits with rheumatism between PubMed and OVID/MEDLINE: 11910 vs 6945.

Not only do the authors use this .mp and [all fields] command instead of the preferred [tiab] field, they also apply this broader field to the existing (optimized) Cochrane filter, that uses [tiab]. Finally they use limits!

Well anyway, I hope that I made my point that useful comparison between strategies can only be made if optimal strategies and comparable  strategies are used. Sensitivity doesn’t mean anything here.

Coming back to my original point. I do think that some conclusions of these papers are “good to know”. As a matter of fact it should be basic knowledge for those planning an exhaustive search for a systematic review. We do not need bad studies to show this.

Perhaps an expert paper (or a series) on this topic, understandable for clinicians, would be of more value.

Or the recognition that such search papers should be designed and written by librarians with ample experience in searching for systematic reviews.

NOTE:
* = truncation=search for different word endings; [tiab] = title and abstract; [ti]=title; mh=mesh; pt=publication type

Photo credit

The image is taken from the Dragonfly-blog; here the Flickr-image Brain Vocab Sketch by labguest was adapted by adding the Pubmed logo.

References

  1. Winchester DE, & Bavry AA (2010). Limitations of the MEDLINE database in constructing meta-analyses. Annals of internal medicine, 153 (5), 347-8 PMID: 20820050
  2. Leclercq E, Kramer B, & Schats W (2011). Limitations of the MEDLINE database in constructing meta-analyses. Annals of internal medicine, 154 (5) PMID: 21357916
  3. Katchamart W, Faulkner A, Feldman B, Tomlinson G, & Bombardier C (2011). PubMed had a higher sensitivity than Ovid-MEDLINE in the search for systematic reviews. Journal of clinical epidemiology, 64 (7), 805-7 PMID: 20926257
  4. Search OVID EMBASE and Get MEDLINE for Free…. without knowing it (laikaspoetnik.wordpress.com 2010/10/19/)
  5. 10 + 1 PubMed Tips for Residents (and their Instructors) (laikaspoetnik.wordpress.com 2009/06/30)
  6. Adding Methodological filters to myncbi (laikaspoetnik.wordpress.com 2009/11/26/)
  7. Search filters 1. An Introduction (laikaspoetnik.wordpress.com 2009/01/22/)




HOT TOPIC: Does Soy Relieve Hot Flashes?

20 06 2011

ResearchBlogging.orgThe theme of the Upcoming Grand Rounds held at June 21th (1st day of the Summer) at Shrink Rap is “hot”. A bit far-fetched, but aah you know….shrinks“. Of course they hope  assume  that we will express Weiner-like exhibitionism at our blogs. Or go into spicy details of hot sexpectations or other Penis Friday NCBI-ROFL posts. But no, not me, scientist and librarian to my bone marrow. I will stick to boring, solid science and will do a thorough search to find the evidence. Here I will discuss whether soy really helps to relieve hot flashes (also called hot flushes).

…..As illustrated by this HOT picture, I should post as well…..

(CC from Katy Tresedder, Flickr):

Yes, many menopausal women plagued by hot flashes take their relief  in soy or other phytoestrogens (estrogen-like chemicals derived from plants). I know, because I happen to have many menopausal women in my circle of friends who prefer taking soy over estrogen. They rather not take normal hormone replacement therapy, because this can have adverse effects if taken for a longer time. Soy on the other hand is considered a “natural remedy”, and harmless. Probably physiological doses of soy (food) are harmless and therefore a better choice than the similarly “natural” black cohosh, which is suspected to give liver injury and other adverse effects.

But is soy effective?

I did a quick search in PubMed and found a Cochrane Systematic Review from 2007 that was recently edited with no change to the conclusions.

This review looked at several phytoestrogens that were offered in several ways, as: dietary soy (9x) (powder, cereals, drinks, muffins), soy extracts (9x), red clover extracts (7x, including Promensil (5x)), Genistein extract , Flaxseed, hop-extract  and a Chinese medicinal herb.

Thirty randomized controlled trials with a total of 2730 participants met the inclusion criteria: the participants were women in or just before their menopause complaining of vasomotor symptoms (thus having hot flashes) for at least 12 weeks. The intervention was a food or supplement with high levels of phytoestrogens (not any other herbal treatment) and this was compared with placebo, no treatment or hormone replacement therapy.

Only 5 trials using the red clover extract Promensil were homogenous enough to combine in a meta-analysis. The effect on one outcome (incidence of hot flashes) is shown below. As can be seen at a glance, Promensil had no significant effect, whether given in a low (40 mg/day) or a higher (80 mg/day) dose. This was also true for the other outcomes.

The other phytoestrogen interventions were very heterogeneous with respect to dose, composition and type. This was especially true for the dietary soy treatment. Although some of the trials showed a positive effect of phytoestrogens on hot flashes and night sweats, overall, phytoestrogens were no better than the comparisons.

Most trials were small,  of short duration and/or of poor quality. Fewer than half of the studies (n=12) indicated that allocation had been concealed from the trial investigators.

One striking finding was that there was a strong placebo effect in most trials with a reduction in frequency of hot flashes ranging from 1% to 59% .

I also found another systematic review in PubMed by Bolaños R et al , that limited itself only to soy. Other differences with the Cochrane Systematic Review (besides the much simpler search ;) ) were: inclusion of more recently published clinical trials, no inclusion of unpublished studies and less strict exclusion on basis of low methodological quality. Furthermore, genestein was (rightly) considered as a soy product.

The group of studies that used soy dietary supplement showed the highest heterogeneity. Overall, the results “showed a significant tendency(?)  in favor of soy. Nevertheless the authors conclude (similar to the Cochrane authors), that  it is still difficult to establish conclusive results given the high heterogeneity found in the studies. (but apparently the data could still be pooled?)

References

  • Lethaby A, Marjoribanks J, Kronenberg F, Roberts H, Eden J, & Brown J. (2007). Phytoestrogens for vasomotor menopausal symptoms Cochrane Database of Systematic Reviews (4) : 10.1002/14651858.CD001395.pub3.
  • Bolaños R, Del Castillo A, & Francia J (2010). Soy isoflavones versus placebo in the treatment of climacteric vasomotor symptoms: systematic review and meta-analysis. Menopause (New York, N.Y.), 17 (3), 660-6 PMID: 20464785







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