Of Mice and Men Again: New Genomic Study Helps Explain why Mouse Models of Acute Inflammation do not Work in Men

25 02 2013

ResearchBlogging.org

This post is update after a discussion at Twitter with @animalevidence who pointed me at a great blog post at Speaking of Research ([19], a repost of [20], highlighting the shortcomings of the current study using just one single inbred strain of mice (C57Bl6)  [2013-02-26]. Main changes are in blue

A recent paper published in PNAS [1] caused quite a stir both inside and outside the scientific community. The study challenges the validity of using mouse models to test what works as a treatment in humans. At least this is what many online news sources seem to conclude: “drug testing may be a waste of time”[2], “we are not mice” [3, 4], or a bit more to the point: mouse models of inflammation are worthless [5, 6, 7].

But basically the current study looks only at one specific area, the area of inflammatory responses that occur in critically ill patients after severe trauma and burns (SIRS, Systemic Inflammatory Response Syndrome). In these patients a storm of events may eventually lead to organ failure and death. It is similar to what may occur after sepsis (but here the cause is a systemic infection).

Furthermore the study only uses one single approach: it compares the gene response patterns in serious human injuries (burns, trauma) and a human model partially mimicking these inflammatory diseases (human healthy volunteers receiving  a low dose endotoxin) with the corresponding three animal models (burns, trauma, endotoxin).

And, as highlighted by Bill Barrington of “Understand Nutrition” [8], the researchers have only tested the gene profiles in one single strain of mice: C57Bl6 (B6 for short). If B6 was the only model used in practice this would be less of a problem. But according to Mark Wanner of the Jackson Laboratory [19, 20]:

 It is now well known that some inbred mouse strains, such as the C57BL/6J (B6 for short) strain used, are resistant to septic shock. Other strains, such as BALB and A/J, are much more susceptible, however. So use of a single strain will not provide representative results.

The results in itself are very clear. The figures show at a glance that there is no correlation whatsoever between the human and B6 mouse expression data.

Seok and 36 other researchers from across the USA  looked at approximately 5500 human genes and their mouse analogs. In humans, burns and traumatic injuries (and to a certain extent the human endotoxin model) triggered the activation of a vast number of genes, that were not triggered in the present C57Bl6 mouse models. In addition the genomic response is longer lasting in human injuries. Furthermore, the top 5 most activated and most suppressed pathways in human burns and trauma had no correlates in mice. Finally, analysis of existing data in the Gene Expression (GEO) Database showed that the lack of correlation between mouse and human studies was also true for other acute inflammatory responses, like sepsis and acute infection.

This is a high quality study with interesting results. However, the results are not as groundbreaking as some media suggest.

As discussed by the authors [1], mice are known to be far more resilient to inflammatory challenge than humans*: a million fold higher dose of endotoxin than the dose causing shock in humans is lethal to mice.* This, and the fact that “none of the 150  candidate agents that progressed to human trials has proved successful in critically ill patients” already indicates that the current approach fails.

[This is not entirely correct the endotoxin/LPS dose in mice is 1000–10,000 times the dose required to induce severe disease with shock in humans [20] and mice that are resilient to endotoxin may still be susceptible to infection. It may well be that the endotoxin response is not a good model for the late effects of  sepsis]

The disappointing trial results have forced many researchers to question not only the usefulness of the current mouse models for acute inflammation [9,10; refs from 11], but also to rethink the key aspects of the human response itself and the way these clinical trials are performed [12, 13, 14]. For instance, emphasis has always been on the exuberant inflammatory reaction, but the subsequent immunosuppression may also be a major contributor to the disease. There is also substantial heterogeneity among patients [13-14] that may explain why some patients have a good prognosis and others haven’t. And some of the initially positive results in human trials have not been reproduced in later studies either (benefit of intense glucose control and corticosteroid treatment) [12]. Thus is it fair to blame only the mouse studies?

dick mouse

dick mouse (Photo credit: Wikipedia)

The coverage by some media is grist to the mill of people who think animal studies are worthless anyway. But one cannot extrapolate these findings to other diseases. Furthermore, as referred to above, the researchers have only tested the gene profiles in one single strain of mice: C57Bl6, meaning that “The findings of Seok et al. are solely applicable to the B6 strain of mice in the three models of inflammation they tested. They unduly generalize these findings to mouse models of inflammation in general. [8]“

It is true that animal studies, including rodent studies, have their limitations. But what are the alternatives? In vitro studies are often even more artificial, and direct clinical testing of new compounds in humans is not ethical.

Obviously, the final proof of effectiveness and safety of new treatments can only be established in human trials. No one will question that.

A lot can be said about why animal studies often fail to directly translate to the clinic [15]. Clinical disparities between the animal models and the clinical trials testing the treatment (like in sepsis) are one reason. Other important reasons may be methodological flaws in animal studies (i.e. no randomization, wrong statistics) and publication bias: non-publication of “negative” results appears to be prevalent in laboratory animal research.[15-16]. Despite their shortcomings, animal studies and in vitro studies offer a way to examine certain aspects of a process, disease or treatment.

In summary, this study confirms that the existing (C57Bl6) mouse model doesn’t resemble the human situation in the systemic response following acute traumatic injury or sepsis: the genomic response is entirely different, in magnitude, duration and types of changes in expression.

The findings are not new: the shortcomings of the mouse model(s) were long known. It remains enigmatic why the researchers chose only one inbred strain of mice, and of all mice only the B6-strain, which is less sensitive to endotoxin, and only develop acute kidney injury (part of organ failure) at old age (young mice were used) [21]. In this paper from 2009 (!) various reasons are given why the animal models didn’t properly mimic the human disease and how this can be improved. The authors stress that:

the genetically heterogeneous human population should be more accurately represented by outbred mice, reducing the bias found in inbred strains that might contain or lack recessive disease susceptibility loci, depending on selective pressures.” 

Both Bill Barrington [8] and Mark Wanner [18,19] propose the use of “diversity outbred cross or collaborative cross mice that  provide additional diversity.” Indeed, “replicating genetic heterogeneity and critical clinical risk factors such as advanced age and comorbid conditions (..) led to improved models of sepsis and sepsis-induced AKI (acute kidney injury). 

The authors of the PNAS paper suggest that genomic analysis can aid further in revealing which genes play a role in the perturbed immune response in acute inflammation, but it remains to be seen whether this will ultimately lead to effective treatments of sepsis and other forms of acute inflammation.

It also remains to be seen whether comprehensive genomic characterization will be useful in other disease models. The authors suggest for instance,  that genetic profiling may serve as a guide to develop animal models. A shotgun analyses of gene expression of thousands of genes was useful in the present situation, because “the severe inflammatory stress produced a genomic storm affecting all major cellular functions and pathways in humans which led to sufficient perturbations to allow comparisons between the genes in the human conditions and their analogs in the murine models”. But rough analysis of overall expression profiles may give little insight in the usefulness of other animal models, where genetic responses are more subtle.

And predicting what will happen is far less easy that to confirm what is already known….

NOTE: as said the coverage in news and blogs is again quite biased. The conclusion of a generally good Dutch science  news site (the headline and lead suggested that animal models of immune diseases are crap [6]) was adapted after a critical discussion at Twitter (see here and here), and a link was added to this blog post). I wished this occurred more often….
In my opinion the most balanced summaries can be found at the science-based blogs: ScienceBased Medicine [11] and NIH’s Director’s Blog [17], whereas “Understand Nutrition” [8] has an original point of view, which is further elaborated by Mark Wanner at Speaking of Research [19] and Genetics and your health Blog [20]

References

  1. Seok, J., Warren, H., Cuenca, A., Mindrinos, M., Baker, H., Xu, W., Richards, D., McDonald-Smith, G., Gao, H., Hennessy, L., Finnerty, C., Lopez, C., Honari, S., Moore, E., Minei, J., Cuschieri, J., Bankey, P., Johnson, J., Sperry, J., Nathens, A., Billiar, T., West, M., Jeschke, M., Klein, M., Gamelli, R., Gibran, N., Brownstein, B., Miller-Graziano, C., Calvano, S., Mason, P., Cobb, J., Rahme, L., Lowry, S., Maier, R., Moldawer, L., Herndon, D., Davis, R., Xiao, W., Tompkins, R., , ., Abouhamze, A., Balis, U., Camp, D., De, A., Harbrecht, B., Hayden, D., Kaushal, A., O’Keefe, G., Kotz, K., Qian, W., Schoenfeld, D., Shapiro, M., Silver, G., Smith, R., Storey, J., Tibshirani, R., Toner, M., Wilhelmy, J., Wispelwey, B., & Wong, W. (2013). Genomic responses in mouse models poorly mimic human inflammatory diseases Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1222878110
  2. Drug Testing In Mice May Be a Waste of Time, Researchers Warn 2013-02-12 (science.slashdot.org)
  3. Susan M Love We are not mice 2013-02-14 (Huffingtonpost.com)
  4. Elbert Chu  This Is Why It’s A Mistake To Cure Mice Instead Of Humans 2012-12-20(richarddawkins.net)
  5. Derek Low. Mouse Models of Inflammation Are Basically Worthless. Now We Know. 2013-02-12 (pipeline.corante.com)
  6. Elmar Veerman. Waardeloos onderzoek. Proeven met muizen zeggen vrijwel niets over ontstekingen bij mensen. 2013-02-12 (wetenschap24.nl)
  7. Gina Kolata. Mice Fall Short as Test Subjects for Humans’ Deadly Ills. 2013-02-12 (nytimes.com)

  8. Bill Barrington. Are Mice Reliable Models for Human Disease Studies? 2013-02-14 (understandnutrition.com)
  9. Raven, K. (2012). Rodent models of sepsis found shockingly lacking Nature Medicine, 18 (7), 998-998 DOI: 10.1038/nm0712-998a
  10. Nemzek JA, Hugunin KM, & Opp MR (2008). Modeling sepsis in the laboratory: merging sound science with animal well-being. Comparative medicine, 58 (2), 120-8 PMID: 18524169
  11. Steven Novella. Mouse Model of Sepsis Challenged 2013-02-13 (http://www.sciencebasedmedicine.org/index.php/mouse-model-of-sepsis-challenged/)
  12. Wiersinga WJ (2011). Current insights in sepsis: from pathogenesis to new treatment targets. Current opinion in critical care, 17 (5), 480-6 PMID: 21900767
  13. Khamsi R (2012). Execution of sepsis trials needs an overhaul, experts say. Nature medicine, 18 (7), 998-9 PMID: 22772540
  14. Hotchkiss RS, Coopersmith CM, McDunn JE, & Ferguson TA (2009). The sepsis seesaw: tilting toward immunosuppression. Nature medicine, 15 (5), 496-7 PMID: 19424209
  15. van der Worp, H., Howells, D., Sena, E., Porritt, M., Rewell, S., O’Collins, V., & Macleod, M. (2010). Can Animal Models of Disease Reliably Inform Human Studies? PLoS Medicine, 7 (3) DOI: 10.1371/journal.pmed.1000245
  16. ter Riet, G., Korevaar, D., Leenaars, M., Sterk, P., Van Noorden, C., Bouter, L., Lutter, R., Elferink, R., & Hooft, L. (2012). Publication Bias in Laboratory Animal Research: A Survey on Magnitude, Drivers, Consequences and Potential Solutions PLoS ONE, 7 (9) DOI: 10.1371/journal.pone.0043404
  17. Dr. Francis Collins. Of Mice, Men and Medicine 2013-02-19 (directorsblog.nih.gov)
  18. Tom/ Mark Wanner Why mice may succeed in research when a single mouse falls short (2013-02-15) (speakingofresearch.com) [repost, with introduction]
  19. Mark Wanner Why mice may succeed in research when a single mouse falls short (2013-02-13/) (http://community.jax.org) %5Boriginal post]
  20. Warren, H. (2009). Editorial: Mouse models to study sepsis syndrome in humans Journal of Leukocyte Biology, 86 (2), 199-201 DOI: 10.1189/jlb.0309210
  21. Doi, K., Leelahavanichkul, A., Yuen, P., & Star, R. (2009). Animal models of sepsis and sepsis-induced kidney injury Journal of Clinical Investigation, 119 (10), 2868-2878 DOI: 10.1172/JCI39421




Why Publishing in the NEJM is not the Best Guarantee that Something is True: a Response to Katan

27 10 2012

ResearchBlogging.orgIn a previous post [1] I reviewed a recent  Dutch study published in the New England Journal of Medicine (NEJM [2] about the effects of sugary drinks on the body mass index of school children.

The study got widely covered by the media. The NRC, for which the main author Martijn Katan works as a science columnist,  columnist, spent  two full (!) pages on the topic -with no single critical comment-[3].
As if this wasn’t enough, the latest column of Katan again dealt with his article (text freely available at mkatan.nl)[4].

I found Katan’s column “Col hors Catégorie” [4] quite arrogant, especially because he tried to belittle a (as he called it) “know-it-all” journalist who criticized his work  in a rivaling newspaper. This wasn’t fair, because the journalist had raised important points [5, 1] about the work.

The piece focussed on the long road of getting papers published in a top journal like the NEJM.
Katan considers the NEJM as the “Tour de France” among  medical journals: it is a top achievement to publish in this paper.

Katan also states that “publishing in the NEJM is the best guarantee something is true”.

I think the latter statement is wrong for a number of reasons.*

  1. First, most published findings are false [6]. Thus journals can never “guarantee”  that published research is true.
    Factors that  make it less likely that research findings are true include a small effect size,  a greater number and lesser preselection of tested relationships, selective outcome reporting, the “hotness” of the field (all applying more or less to Katan’s study, he also changed the primary outcomes during the trial[7]), a small study, a great financial interest and a low pre-study probability (not applicable) .
  2. It is true that NEJM has a very high impact factor. This is  a measure for how often a paper in that journal is cited by others. Of course researchers want to get their paper published in a high impact journal. But journals with high impact factors often go for trendy topics and positive results. In other words it is far more difficult to publish a good quality study with negative results, and certainly in an English high impact journal. This is called publication bias (and language bias) [8]. Positive studies will also be more frequently cited (citation bias) and will more likely be published more than once (multiple publication bias) (indeed, Katan et al already published about the trial [9], and have not presented all their data yet [1,7]). All forms of bias are a distortion of the “truth”.
    (This is the reason why the search for a (Cochrane) systematic review must be very sensitive [8] and not restricted to core clinical journals, but even include non-published studies: for these studies might be “true”, but have failed to get published).
  3. Indeed, the group of Ioannidis  just published a large-scale statistical analysis[10] showing that medical studies revealing “very large effects” seldom stand up when other researchers try to replicate them. Often studies with large effects measure laboratory and/or surrogate markers (like BMI) instead of really clinically relevant outcomes (diabetes, cardiovascular complications, death)
  4. More specifically, the NEJM does regularly publish studies about pseudoscience or bogus treatments. See for instance this blog post [11] of ScienceBased Medicine on Acupuncture Pseudoscience in the New England Journal of Medicine (which by the way is just a review). A publication in the NEJM doesn’t guarantee it isn’t rubbish.
  5. Importantly, the NEJM has the highest proportion of trials (RCTs) with sole industry support (35% compared to 7% in the BMJ) [12] . On several occasions I have discussed these conflicts of interests and their impact on the outcome of studies ([13, 14; see also [15,16] In their study, Gøtzsche and his colleagues from the Nordic Cochrane Centre [12] also showed that industry-supported trials were more frequently cited than trials with other types of support, and that omitting them from the impact factor calculation decreased journal impact factors. The impact factor decrease was even 15% for NEJM (versus 1% for BMJ in 2007)! For the journals who provided data, income from the sales of reprints contributed to 3% and 41% of the total income for BMJ and The Lancet.
    A recent study, co-authored by Ben Goldacre (MD & science writer) [17] confirms that  funding by the pharmaceutical industry is associated with high numbers of reprint ordersAgain only the BMJ and the Lancet provided all necessary data.
  6. Finally and most relevant to the topic is a study [18], also discussed at Retractionwatch[19], showing that  articles in journals with higher impact factors are more likely to be retracted and surprise surprise, the NEJM clearly stands on top. Although other reasons like higher readership and scrutiny may also play a role [20], it conflicts with Katan’s idea that  “publishing in the NEJM is the best guarantee something is true”.

I wasn’t aware of the latter study and would like to thank drVes and Ivan Oranski for responding to my crowdsourcing at Twitter.

References

  1. Sugary Drinks as the Culprit in Childhood Obesity? a RCT among Primary School Children (laikaspoetnik.wordpress.com)
  2. de Ruyter JC, Olthof MR, Seidell JC, & Katan MB (2012). A trial of sugar-free or sugar-sweetened beverages and body weight in children. The New England journal of medicine, 367 (15), 1397-406 PMID: 22998340
  3. NRC Wim Köhler Eén kilo lichter.NRC | Zaterdag 22-09-2012 (http://archief.nrc.nl/)
  4. Martijn Katan. Col hors Catégorie [Dutch], (published in de NRC,  (20 oktober)(www.mkatan.nl)
  5. Hans van Maanen. Suiker uit fris, De Volkskrant, 29 september 2012 (freely accessible at http://www.vanmaanen.org/)
  6. Ioannidis, J. (2005). Why Most Published Research Findings Are False PLoS Medicine, 2 (8) DOI: 10.1371/journal.pmed.0020124
  7. Changes to the protocol http://clinicaltrials.gov/archive/NCT00893529/2011_02_24/changes
  8. Publication Bias. The Cochrane Collaboration open learning material (www.cochrane-net.org)
  9. de Ruyter JC, Olthof MR, Kuijper LD, & Katan MB (2012). Effect of sugar-sweetened beverages on body weight in children: design and baseline characteristics of the Double-blind, Randomized INtervention study in Kids. Contemporary clinical trials, 33 (1), 247-57 PMID: 22056980
  10. Pereira, T., Horwitz, R.I., & Ioannidis, J.P.A. (2012). Empirical Evaluation of Very Large Treatment Effects of Medical InterventionsEvaluation of Very Large Treatment Effects JAMA: The Journal of the American Medical Association, 308 (16) DOI: 10.1001/jama.2012.13444
  11. Acupuncture Pseudoscience in the New England Journal of Medicine (sciencebasedmedicine.org)
  12. Lundh, A., Barbateskovic, M., Hróbjartsson, A., & Gøtzsche, P. (2010). Conflicts of Interest at Medical Journals: The Influence of Industry-Supported Randomised Trials on Journal Impact Factors and Revenue – Cohort Study PLoS Medicine, 7 (10) DOI: 10.1371/journal.pmed.1000354
  13. One Third of the Clinical Cancer Studies Report Conflict of Interest (laikaspoetnik.wordpress.com)
  14. Merck’s Ghostwriters, Haunted Papers and Fake Elsevier Journals (laikaspoetnik.wordpress.com)
  15. Lexchin, J. (2003). Pharmaceutical industry sponsorship and research outcome and quality: systematic review BMJ, 326 (7400), 1167-1170 DOI: 10.1136/bmj.326.7400.1167
  16. Smith R (2005). Medical journals are an extension of the marketing arm of pharmaceutical companies. PLoS medicine, 2 (5) PMID: 15916457 (free full text at PLOS)
  17. Handel, A., Patel, S., Pakpoor, J., Ebers, G., Goldacre, B., & Ramagopalan, S. (2012). High reprint orders in medical journals and pharmaceutical industry funding: case-control study BMJ, 344 (jun28 1) DOI: 10.1136/bmj.e4212
  18. Fang, F., & Casadevall, A. (2011). Retracted Science and the Retraction Index Infection and Immunity, 79 (10), 3855-3859 DOI: 10.1128/IAI.05661-11
  19. Is it time for a Retraction Index? (retractionwatch.wordpress.com)
  20. Agrawal A, & Sharma A (2012). Likelihood of false-positive results in high-impact journals publishing groundbreaking research. Infection and immunity, 80 (3) PMID: 22338040

——————————————–

* Addendum: my (unpublished) letter to the NRC

Tour de France.
Nadat het NRC eerder 2 pagina’ s de loftrompet over Katan’s nieuwe studie had afgestoken, vond Katan het nodig om dit in zijn eigen column dunnetjes over te doen. Verwijzen naar je eigen werk mag, ook in een column, maar dan moeten wij daar als lezer wel wijzer van worden. Wat is nu de boodschap van dit stuk “Col hors Catégorie“? Het beschrijft vooral de lange weg om een wetenschappelijke studie gepubliceerd te krijgen in een toptijdschrift, in dit geval de New England Journal of Medicine (NEJM), “de Tour de France onder de medische tijdschriften”. Het stuk eindigt met een tackle naar een journalist “die dacht dat hij het beter wist”. Maar ach, wat geeft dat als de hele wereld staat te jubelen? Erg onsportief, omdat die journalist (van Maanen, Volkskrant) wel degelijk op een aantal punten scoorde. Ook op Katan’s kernpunt dat een NEJM-publicatie “de beste garantie is dat iets waar is” valt veel af te dingen. De NEJM heeft inderdaad een hoge impactfactor, een maat voor hoe vaak artikelen geciteerd worden. De NEJM heeft echter ook de hoogste ‘artikelterugtrekkings’ index. Tevens heeft de NEJM het hoogste percentage door de industrie gesponsorde klinische trials, die de totale impactfactor opkrikken. Daarnaast gaan toptijdschriften vooral voor “positieve resultaten” en “trendy onderwerpen”, wat publicatiebias in de hand werkt. Als we de vergelijking met de Tour de France doortrekken: het volbrengen van deze prestigieuze wedstrijd garandeert nog niet dat deelnemers geen verboden middelen gebruikt hebben. Ondanks de strenge dopingcontroles.




#EAHIL2012 CEC 2: Visibility & Impact – Library’s New Role to Enhance Visibility of Researchers

4 07 2012

This week I’m blogging at (and mostly about) the 13th EAHIL conference in Brussels. EAHIL stands for European Association for Health Information and Libraries.

The second Continuing Education Course (CEC) I followed was given by Tiina Heino and Katri Larmo of the Terkko Meilahti Campus Library at the University of Helsinki in Finland.

The full title of the course was Visibility and impact – library’s new role: How the library can support the researcher to get visibility and generate impact to researcher’s work. You can read the abstract here.

The hands-on workshop mainly concentrated on the social bookmarking sites ConnoteaMendeley and Altmetric.

Furthermore we got information on CiteULike, ORCID,  Faculty of 1000 Posters and Pinterest. Also services developed in Terkko, such as ScholarChart and TopCited Articles, were shortly demonstrated.

What I especially liked in the hands on session is that the tutors had prepared a wikispace with all the information and links on the main page ( https://visibility2012.wikispaces.com) and a separate page for each participant to edit (here is my page). You could add links to your created accounts and embed widgets for Mendeley.

There was sufficient time to practice and try the tools. And despite the great number of participants there was ample room for questions (& even for making a blog draft ;)).

The main message of the tutors is that the process of publishing scientific research doesn’t end at publishing the article: it is equally important what happens after the research has been published. Visibility and impact in the scientific community and in the society are  crucial  for making the research go forward as well as for getting research funding and promoting the researcher’s career. The Fig below (taken from the presentation) visualizes this process.

The tutors discussed ORCID, Open Researcher and contributor ID, that will be introduced later this year. It is meant to solve the author name ambiguity problem in scholarly communication by central registry of unique identifiers for each author (because author names can’t be used to reliably identify all scholarly author). It will be possible for authors to create, manage and share their ORCID record without membership fee. For further information see several publications and presentations by Martin Fenner. I found this one during the course while browsing Mendeley.

Once published the author’s work can be promoted using bookmarking tools, like CiteULike, Connotea and Mendeley. You can easily registrate for Connotea and Mendeley using your Facebook account. These social bookmarking tools are also useful for networking, i.e. to discover individuals and groups with the same field of interest. It is easy to synchronize your Mendeley with your CiteULike account.

Mendeley is available in a desktop and a web version. The web version offers a public profile for researchers, a catalog of documents, and collaborative groups (the cloud of Mendeley). The desktop version of Mendeley is specially suited for reference management and organizing your PDF’s. That said Mendeley seems most suitable for serendipitous use (clicking and importing a reference you happen to see and like) and less useful for managing and deduplicating large numbers of records, i.e. for a systematic review.
Also (during the course) it was not possible to import several PubMed records at once in either CiteULike or Mendeley.

What stroke me when I tried Mendeley is that there were many small or dead groups. A search for “cochrane”  for instance yielded one large group Cochrane QES Register, owned by Andrew Booth, and 3 groups with one member (thus not really a group), with 0 (!) to 6 papers each! It looks like people are trying Mendeley and other tools just for a short while. Indeed, most papers I looked up in PubMed were not bookmarked at all. It makes you wonder how widespread the use of these bookmarking tools is. It probably doesn’t help that there are so many tools with different purposes and possibilities.

Another tool that we tried was Altmetric. This is a free bookmarklet on scholarly articles which allows you to track the conversations around scientific articles online. It shows the tweets, blogposts, Google+ and Facebook mentions, and the numbers of bookmarks on Mendeley, CiteULike and Connotea.

I tried the tool on a paper I blogged about , ie. Seventy-Five Trials and Eleven Systematic Reviews a Day: How Will We Ever Keep Up?

The bookmarklet showed the tweets and the blogposts mentioning the paper.

Indeed altmetrics did correctly refer to my blog (even to 2 posts).

I liked altmetrics*, but saying that it is suitable for scientific metrics is a step too far. For people interested in this topic I would like to refer -again- to a post of Martin Fenner on altmetrics (in general).  He stresses that “usage metrics”  has its limitations because of its proness  to “gaming” (cheating).

But the current workshop didn’t address the shortcomings of the tools, for it was meant as a first practical acquaintance with the web 2.0 tools.

For the other tools (Faculty of 1000 Posters, Pinterest) and the services developed in Terkko, such as ScholarChart and TopCited Articles,  see the wikipage and the presentation:

*Coincidentally I’m preparing a post on handy chrome extensions to look for tweets about a webpage. Altmetric is another tool which seems very suitable for this purpose

Related articles





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)




Friday Foolery #49: The Shortest Abstract Ever! [2]

30 03 2012

In a previous Friday Foolery post I mentioned what I thought was the shortest abstract ever.

 “Probably not”.

But a reader (Trollface”pointed out in a comment that there was an even shorter (and much older) abstract of a paper in the Bulletin of the Seismological Society of America. It was published in 1974.

The abstract simply says: Yes.

It could only be beaten by an abstract saying: “No”, “!”, “?” or a blank one.





Jeffrey Beall’s List of Predatory, Open-Access Publishers, 2012 Edition

19 12 2011

Perhaps you remember that I previously wrote [1] about  non-existing and/or low quality scammy open access journals. I specifically wrote about Medical Science Journals of  the http://www.sciencejournals.cc/ series, which comprises 45 titles, none of which having published any article yet.

Another blogger, David M [2] also had negative experiences with fake peer review invitations from sciencejournals. He even noticed plagiarism.

Later I occasionally found other posts about open access spam, like the post of Per Ola Kristensson [3] (specifically about Bentham, Hindawi and InTech OA publishers), of Peter Murray-Rust [4] ,a chemist interested in OA (about spam journals and conferences, specifically about Scientific Research Publishing) and of Alan Dove PhD [5] (specifically about The Journal of Computational Biology and Bioinformatics Research (JCBBR) published by Academic Journals).

But now it appears that there is an entire list of “Predatory, Open-Access Publishers”. This list was created by Jeffrey Beall, academic librarian at the University of Colorado Denver. He just updated the list for 2012 here (PDF-format).

According to Jeffrey predatory, open-access publishers

are those that unprofessionally exploit the author-pays model of open-access publishing (Gold OA) for their own profit. Typically, these publishers spam professional email lists, broadly soliciting article submissions for the clear purpose of gaining additional income. Operating essentially as vanity presses, these publishers typically have a low article acceptance threshold, with a false-front or non-existent peer review process. Unlike professional publishing operations, whether subscription-based or ethically-sound open access, these predatory publishers add little value to scholarship, pay little attention to digital preservation, and operate using fly-by-night, unsustainable business models.

Jeffrey recommends not to do business with the following (illegitimate) publishers, including submitting article manuscripts, serving on editorial boards, buying advertising, etc. According to Jeffrey, “there are numerous traditional, legitimate journals that will publish your quality work for free, including many legitimate, open-access publishers”.

(For sake of conciseness, I only describe the main characteristics, not always using the same wording; please see the entire list for the full descriptions.)

Watchlist: Publishers, that may show some characteristics of  predatory, open-access publisher
  • Hindawi Way too many journals than can be properly handled by one publisher
  • MedKnow Publications vague business model. It charges for the PDF version
  • PAGEPress many dead links, a prominent link to PayPal
  • Versita Open paid subscription for print form. ..unclear business model

An asterisk (*) indicates that the publisher is appearing on this list for the first time.

How complete and reliable is this list?

Clearly, this list is quite exhaustive. Jeffrey did a great job listing  many dodgy OA journals. We should watch (many) of these OA publishers with caution. Another good thing is that the list is updated annually.

(http://www.sciencejournals.cc/ described in my previous post is not (yet) on the list ;)  but I will inform Jeffrey).

Personally, I would have preferred a distinction between real bogus or spammy journals and journals that seem to have “too many journals to properly handle” or that ask (too much ) money for subscription/from the author. The scientific content may still be good (enough).

Furthermore, I would rather see a neutral description of what is exactly wrong about a journal. Especially because “Beall’s list” is a list and not a blog post (or is it?). Sometimes the description doesn’t convince me that the journal is really bogus or predatory.

Examples of subjective portrayals:

  • Dove Press:  This New Zealand-based medical publisher boasts high-quality appearing journals and articles, yet it demands a very high author fee for publishing articles. Its fleet of journals is large, bringing into question how it can properly fulfill its promise to quickly deliver an acceptance decision on submitted articles.
  • Libertas Academia “The tag line under the name on this publisher’s page is “Freedom to research.” It might better say “Freedom to be ripped off.” 
  • Hindawi  .. This publisher has way too many journals than can be properly handled by one publisher, I think (…)

I do like funny posts, but only if it is clear that the post is intended to be funny. Like the one by Alan Dove PhD about JCBBR.

JCBBR is dedicated to increasing the depth of research across all areas of this subject.

Translation: we’re launching a new journal for research that can’t get published anyplace else.

The journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence in this subject area.

We’ll take pretty much any crap you excrete.

Hattip: Catherine Arnott Smith, PhD at the MedLib-L list.

  1. I Got the Wrong Request from the Wrong Journal to Review the Wrong Piece. The Wrong kind of Open Access Apparently, Something Wrong with this Inherently… (laikaspoetnik.wordpress.com)
  2. A peer-review phishing scam (blog.pita.si)
  3. Academic Spam and Open Access Publishing (blog.pokristensson.com)
  4. What’s wrong with Scholarly Publishing? New Journal Spam and “Open Access” (blogs.ch.cam.ac.uk)
  5. From the Inbox: Journal Spam (alandove.com)
  6. Beall’s List of Predatory, Open-Access Publishers. 2012 Edition (http://metadata.posterous.com)
  7. Silly Sunday #42 Open Access Week around the Globe (laikaspoetnik.wordpress.com)




Friday Foolery #44. The Shortest Abstract Ever?

2 12 2011

This is the shortest abstract I’ve ever seen:

“probably not”

With many thanks to Michelynn McKnight, PhD, AHIP, Associate Professor, School of Library and Information Science, Louisiana State University, who put it on the MEDLIB-L listserv, saying :  “Not exactly structured …. but a great laugh!”

According to Zemanta (articles related to this post) Future Twit also blogged about it.

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