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27 junio, 2013

Is psychotherapy for depression any better than a sugar pill?

By James Coyne PhDplacebo.We now know  that estimates of the efficacy of antidepressants that were once readily accepted were exaggerated. Sure, the estimates came from meta analyses of the carefully searched published literature, but that literature was skewed to make antidepressants look better than they were. Pharmaceutical companies had withheld publication of negative and weak trials and they had selectively promoted positive trials, even buying reprints to distribute journal articles that reported them. Some worried that these sometimes huge purchases gave journals an added incentive for the journals to participate in the confirmatory bias.
A much more balanced perspective on how well antidepressants worked was contained in reports submitted to the Food and Drug Administration (FDA). Since 1997 Drug Approval Packages had been available for download by anyone. For drugs approved before then, reports were available on request. But no one had yet made effective use of these reports in a published evaluation of the efficacy of antidepressants. Either those who were potentially interested in doing so did not know how to gain access or they had been discouraged by what had been the FDA’s notoriously slow response to such requests.fda-logo
Erick Turner once worked for the FDA, but is now a Veterans Administration Health System psychiatrist. He made use of these data in a provocative paper. Whereas the published literature up until then suggested that almost all randomized trials involving antidepressants were positive, the FDA records he obtained revealed that only half were positive. He found that data submitted to the FDA that was positive was 12 times more likely to end up published than negative trials. So, just as many suspected, but could not quantify, there was a considerable bias going on in the evidence being made available to clinicians and policymakers. Turner re-analyzed the data concerning the efficacy of antidepressants, and found that when the suppressed FDA data were included, the effect size (mean standardized difference) dropped from 0.41 to 0.31. Turner did not claim that antidepressants lacked efficacy in comparison to pill placebos, but he did point out that previous estimates of their advantage were exaggerated.
Turner is a cautious, understated guy. As I noted in another blog post, Rich Bonin, a CBS Morning News producer approached him to appear in a segment about whether antidepressants were no more effective than sugar pills.  By Turner’s account, his careful explanation of his work left the CBS producer thinking out loud with his co-producer about whether they should proceed with the story, “or is it too murky…Is it good murky, or is it just murky?”
The producer resolved his dilemma by leaving Turner out of the program. Better a dramatic even if inaccurate message rather than a “murky” one.
60 minutesIrving Kirsch, a psychologist conducted analyses on four of the 12 antidepressants Turner had analyzed, and obtained essentially the same result, an effect size of 0.32. But Kirsch had much more of a flair for grabbing media attention than Turner did, and some would say much more of a flair for hyperbole. Kirsch had already become well known for his relentless declarations that the differences between antidepressants and a placebo pill were trivial. As in the 60 Minutes segment from which Turner was excluded:
Irving Kirsch: The difference between the effect of a placebo and the effect of an antidepressant is minimal for most people.
Lesley Stahl: So you’re saying if they took a sugar pill, they’d have the same effect?
Irving Kirsch: They’d have almost as large an effect and whatever difference there would be would be clinically insignificant.
Kirsch based his claims on the arbitrary requirement that in order to be clinically significant, an effect size has to be 0.50 and the differences between an antidepressant and a pill placebo on the rating scale that the FDA required, the Hamilton Rating Scale for Depression, had to be three points. This standard had previously surfaced in evaluations by the UK’s National Institute for Clinical Excellence  (NICE), but had already been abandoned by the time Kirsch made his claims. I asked Simon Gilbody, a respected British psychiatrist who does lots of meta-analyses what he thought of the now rejected NICE criterion of 0.50 as a sharp boundary between effective and ineffective treatments. He said
“I never believe any study these days which finds an ES > 0.5. it usually means the science is wrong and we haven’t found the bias(es) just yet.”
What would an effect size of 0.5 represent? It would indicate that the mean of the treatment group is at the 69th percentile of the control group and that the non-overlap is 33%.
Turner may not have made it to CBS 60 Minutes, but he had been invited to discuss in BMJ the differences between his and Kirsch’s interpretation of getting basically the same results. In a previous blog post, I commented on what Turner said.
He noted that the NICE criterion of an effect size of 0.5 had been taken from Jacob Cohen’s designation of it as “medium”, but Cohen himself had distanced himself from  his own designation of effect sizes as “small,” “medium,” or “large” with “The values chosen had no more reliable a basis than my own intuition.” Turner suggested that Cohen would undoubtedly have rejected NICE’s rigid distinction of 0.5 as a categorical cutoff between ineffective versus effective treatments. Indeed, Cohen who is now deceased, offered no hint that he would have welcomed becoming the arbiter of categorical judgments of clinical significance and famously lampooned the categorical p<.05 for deciding the world is flat rather than round.
Turner went on:
It seems unfair that pharmacological, and not psychotherapeutic, treatment has become the usual first line approach to depression merely for economic reasons. But before we embrace any treatment as first line, it is prudent to ask whether its efficacy is beyond question. For psychotherapy trials, there is no equivalent of the FDA whose records we can examine, so how can we be sure that selective publication is not occurring here as well?
In hindsight, Turner’s challenge has become particularly important now that Ben Goldacre has caused such a stir about hidden pharmaceutical trials. Goldacre showed that Pharma had successfully promoted the drug reboxetine, as safe and effective as an antidepressant, when data withheld from publication actually indicated it was dangerous for some people and, on average, ineffective. Does psychotherapy have a problem with hidden trials? In a future blog post, I will demonstrate that indeed it does.
But more immediately, Turner left me puzzling about what if we apply the same requirement of an effect size of 0.50 to comparisons between psychotherapy and pill placebo. Fair is fair. If we’re going to judge antidepressants as no better than a sugar pill, what if psychotherapy was no better than a sugar pill by the same standard?
Kirsch attracted a lot of attention, especially among those who already wanted to believe that antidepressants were ineffective and maybe even dangerous – the growing anti-psychiatry crowd that had almost become mainstream, but also clinical psychologists who were frustrated with their declining role in treating all the depression that was now being detected in primary care. When I raised in blog posts the issue that Kirsch’s interpretation of the uselessness of antidepressants might also be extended to the uselessness of psychotherapy, something none of us wanted to do, I found my blogs attacked by trolls and spammed repeatedly, even with praise for what Scientology had done for psychiatry. This was not the first time and I am sure it will not be the last in which I hit on an emotional issue in which the opposing sides were invoking “evidence”, but really did not want to look more closely to see whether the evidence actually supported their views.
Nonetheless, I became determined to put the issue of psychotherapy versus pill placebo to an empirical test. I recruited Erick Turner, but also Pim Cuijpers who had an excellent database about psychotherapy for depression that he constantly updated with citation alerts and renewed searches. You can find a list of the meta analyses he has produced here. We assembled a writing team that included Erick, Pim, and myself, but also David Mohr, Stefan Hofmann, Gerhard Andersson, and Matthias Berking. We did a fresh search of the literature, Pim performed the meta analysis, and together the group drafted the manuscript that became the 2013 Psychological Medicine article that I am now going to discuss.
The Question We Asked.
We asked whether if we integrated all of the available data that we could find, would psychotherapy be more effective than pill placebo.
Facing the Criticism That We Should Not Have Even Done This Meta-Analysis
When we first sent our manuscript out for review, the reviewers were critical about our even having undertaken this meta-analysis. Our responding to this criticism in revising the paper strengthened it. The basic criticism concerned a lack of blindness for either clinicians administering psychotherapy versus pill placebo or to their patients receiving it. In double-blind pharmaceutical trials, clinicians and patients can both see that the patients are given a pill, but they don’t know whether it
s an antidepressant or a placebo, because both are kept in the dark. On the other hand, in a comparison between psychotherapy and pill placebo, it’s obvious which treatment patients are being given. There is lots of room for bias to creep into the study in the form of patients having a strong preference for one treatment or the other and that influencing their response either by skewing the answers they give in assessments or even in having them a more positive expectation about one treatment affecting their actual response.
Elements of the bias are present even in comparisons of psychotherapy and antidepressants. In an earlier study, my colleagues and I showed that over half of patients enrolling in a study in improving the care for depression in primary care would have preferred psychotherapy to the antidepressants, and those with a strong preference did less well with the antidepressant. The bias is present any time you compare psychotherapy to a pill, and so it’s not exactly equivalent to comparing an active treatment contained in a pill in an inert one, especially when neither the clinician nor the patient knows which pill is which. The reviewers were correct that in important ways psychotherapy versus pill placebo comparisons were different then antidepressants versus pill placebo comparisons.
If so, why do the meta-analysis? Because it allowed us to address important policy issues. Policymakers, clinicians, and patient/consumers were making decisions based on arguments that the difference between antidepressants and pill placebo were trivial, and jumping to the conclusion that therefore psychotherapy would be a more effective treatment. We wanted to put that judgment to a test.
A pill placebo condition is not a sugar pill
I phrased the title of this blog post to parallel a lot of the discussions that have gone on about antidepressants versus pill placebos. But I should be clear that a lot more goes into the effect size calculated for such a trial. Patients receiving either treatment benefit from the expectation that they are getting an active treatment and there is a lot of attention that goes on in terms of an active clinical management protocol in which patients are regularly being asked about how well they are doing and provided a lot of social support. These nonspecific factors can then themselves lead to substantial improvement, but in a clinical trial data provided to all conditions. So, the effect size that is calculated takes into account both conditions having this advantage.
This brings us to a point that is not well understood in lots of popular discussions of how well treatments work.. We often talk about efficacy in terms of effect sizes, but we need to keep in mind that effect sizes do not characterize a treatment, but rather a comparison of treatments in a particular context. So, when we are discussing a pill placebo condition, this a lot more involved in producing the effect size than the pill itself, namely, the comparison condition and the context in which the treatment and control condition were administered.
It’s sad that many antidepressants are prescribed in routine depression care in the community without the support and follow-up that patients enrolled in a clinical trial get with their active clinical management. Instead, patients in routine care are simply given their prescription and sent off, often without anyone checking in on them further. When their prescriptions need refilling, that can be accomplished simply with a telephone call to the prescribing physician’s office, without anybody asking how they are doing or whether they require adjustments in dosage or changing medications. Studies show that about 50% of patients prescribed antidepressant require such an inquiry and possible adjustment or different treatment to get any effect.
I wouldn’t be surprised if the benefits of getting an antidepressant in the context of primary care are less than the benefits obtained from getting a pill placebo within the support and attention of a clinical trial. For that matter, many patients getting non-evidence-based psychotherapy in the community can come back month after month without any formal assessment of whether they are getting any benefit. But these are stories for another time.
We went into our meta-analysis fully expecting that psychotherapy might not perform as well as some would like when compared to a pill placebo. As we said in the published article,
Because pill placebo more plausibly controls for positive expectations, support and attention, it is conceivable that this approach will lead to effect sizes that are smaller than those historically found using waitlist and no-treatment control conditions. This would have important implications for clinical and policy decisions concerning provision of psychotherapy versus antidepressants for depression. Because earlier research based on head-to-head comparisons of psychotherapy and pharmacotherapy have found that their effects on depression are comparable (Cuijpers et al., 2008), our hypothesis is that the effect size of psychotherapy is comparable to that of pharmacotherapy, i.e. about g = 0.3 (Turner et al., 2008).
So, rather than 0.5 that Kirsch had proposed has a cutoff for a nontrivial difference, we anticipated that psychotherapy versus pill placebo would be about the same as antidepressants versus placebo. The effect size we anticipated, would indicate that patients getting either psychotherapy or antidepressants would be at the 62nd percentile of those getting a pill placebo and the non-overlap between either of the two active treatments and a pill placebo would be 21%.
What We Found.
We had the requirement that any study that we included had to rely on a standardized assessment of depression such as the Beck Depression Inventory or Hamilton Depression Rating Scale. An exhaustive search only revealed 10 randomized trials that yielded comparisons between psychotherapy and pill placebo. That
s because researchers typically do not use pill placebo as the comparison condition for psychotherapy. Rather, they are more interested in comparing psychotherapy to an antidepressant and a placebo condition is there only to establish that the antidepressant was effectively delivered. That would be shown in an antidepressant/pill placebo difference. So, we were taking advantage of comparisons that were not necessarily intended by investigators.
At the end of clinical trials, the effect size for psychotherapy compared to pill placebo was g = 0.25 [what does this mean?]. If we translate that into practical terms of Number Needed to Treat (NNT), 7.14 psychotherapy patients had to be treated in order to get assured of getting one who did better than getting a pill placebo. Patients in the psychotherapy conditions scored 2.66 points lower on the Hamilton depression rating scale than those assigned to pill placebo. These differences are well within the range of the differences found between antidepressants and pill placebo in the FDA registered trials.
Essentially, when compared to pill placebo, psychotherapy did as well or, if you’d like, as poorly as an antidepressant. So, inferring that psychotherapy is the preferred treatment based simply on the basis of the small differences between antidepressants and pill placebos is not warranted.
The FDA data on which both Erick Turner and Irving Kirsch drew did not include psychotherapy conditions. Thanks to the regulatory requirements of the FDA, we can be assured that there are not many trials being hidden. But we cannot make that assumption about psychotherapy trials because psychotherapy investigators do not consistently register their trials, and can simply leave unpublished trials in which the psychotherapy does not perform well. Add to that that much psychotherapy is conducted by persons who would benefit from a positive result in terms of either their academic career or selling of their treatment on the workshop circuit. There are well-known strong investigator allegiance effects so that it isunusual for published clinical trials to obtain results counter to the interest of the investigators.
Thus, it may have been a draw between the effects observed for psychotherapy versus pill placebo in a meta-analyses versus the effects observed in other meta-analyses of data obtained from the FDA concerning antidepressants versus pill placebos. But our analyses may have overestimated the advantages of psychotherapy.
Elsewhere, I referred to the controversies about antidepressants as being part of the “antidepressant wars.” Combatants in these wars have given a lot of attention to the lack of strong differences between antidepressants and pill placebo. But I think both sides should recognize that neither psychotherapy nor meidcation have the efficacy that we would like to obtain from them in treating depression, especially when they are ineffectively delivered in routine care in the community. Some have pointed out that the efficacy of neither treatment has greatly changed in the past 50 years. Pharmaceutical companies have stopped investing large amounts of money in research seeking to discover new treatments for depression. Similarly, Pim Cuijpers has shown that past research strongly indicates that no one active psychotherapy treatment for depression is consistently superior to its evidence-based alternatives, and so there
s little reason to expect there is some breakthrough treatment on the horizon. We are stuck trying to do the best we can with existing treatments and improving upon their in adequate delivery in the community. If anywhere, for now at least, that is where progress is to be made.
Acknowledgments: Some of my co-authors on the Psychological Medicine provided extremely helpful feedback on earlier drafts of this post, Stefan Hofmann, Gerhard Andersson, and Matthias Berking, but especially Erick Turner. However, the views expressed here do not necessarily express theirs.
My interest in pursuing a comparison between psychotherapy and pill placebos developed has I worked on earlier blog posts on the efficacy of antidepressants. I drew liberally from these earlier blog posts in writing this one, among them 1, 2, 3

22 febrero, 2012

Transmissible H5N1 - If they publish, wil we perish ?


BioMed Central Blog 

TUESDAY FEB 21, 2012

Two influenza research papers remain suspended in press since the US government’s request for their redaction, made on the recommendation of the National Science Advisory Board for Biosecurity (NSABB) late last year. Were this to be upheld, it would be an unprecedented example of censorship of the scientific literature, justified as a necessary measure to protect against bioterror. A comment published in BMC Biology by Peter Doherty and Paul Thomas counters this justification, arguing that although the work raises legitimate safety concerns, full publication of these studies would not add significantly to the vanishingly small risk that influenza might be effectively harnessed to nefarious ends.  By contrast, Doherty and Thomas see it as imperative that the research community continue to investigate, without undue impediment, how highly pathogenic avian influenza might adapt to become transmissible in mammals, so that we are better able to monitor and counter the significant risk that this might happen naturally, without any human design or intent.

The arguments against censorship would seem to be gaining momentum. Last week the World Health Organization convened a meeting which brought together a group of influenza researchers and global public health experts with key players: the lead authors of the two papers, representatives of those who funded the work, editors from the journals concerned (Science and Nature), and Paul Keim, chairman of the NSABB. Keim stood by the original recommendation for redaction and the balance of reasoning behind it, but the workability of  making the full data available on a “need to know” basis was questioned, and a consensus reached that it would be better to delay publication of the papers until safety concerns were addressed and they could be published in full.

A second outcome of last week’s meeting is an extension of the voluntary moratorium on research to create and study transmissible strains of avian influenza, pending the further discussion of how safety issues should be dealt with. The virus already created in Ron Fouchier’s laboratory was obtained by serial passage in ferrets, is transmitted through the air between their cages, and is highly pathogenic so biosafety issues are an obvious concern; the study demonstrates that such adaptation can occur, could thus occur in nature, and identifies a specific pathway of mutation by which it can occur. The virus created by Yoshihiro Kawaoka is no more pathogenic in ferrets than the H1N1 2009 pandemic virus from which it was derived, but instead of H1, it bears the H5 haemagglutinin molecule of avian H5NA. Both studies show that H5-bearing viruses can be transmissible in mammals and therefore pose a risk to be monitored, and against which we should prepare.

Penelope Austin

19 septiembre, 2011

Porque la mayoria de los resultados de investigacion publicados son falsos?

Existe una creciente preocupación de que los resultados de investigación más recientes publicados son falsos. La probabilidad de que una reivindicación de la investigación es cierto puede depender de la energía y el sesgo del estudio, el número de otros estudios sobre la misma cuestión, y, más importante, la proporción de fieles a ninguna relación entre las relaciones investigado en cada campo científico. En este marco, un hallazgo de investigación es menos probable que sea cierto cuando los estudios realizados en el campo son más pequeños, cuando son más pequeños tamaños del efecto, cuando existe un número mayor y menor prueba de preselección de las relaciones, donde existe una mayor flexibilidad en los diseños, definiciones, resultados, y los modos de análisis, cuando los intereses financieros y de otro no es mayor y los prejuicios, y cuando más equipos están involucrados en un campo científico a la caza de la significación estadística. Las simulaciones muestran que la mayoría de los diseños de estudio y configuración, sean más probable que los resultados de una investigación sean más falsos que verdaderos. Además, para muchos campos científicos actuales, los resultados de la investigación puede ser a menudo una medición simplemente precisa de la tendencia imperante. En este ensayo, se discuten las implicaciones de estos problemas para la realización e interpretación de la investigación.
El articulo completo puede encontrarse en http://dx.doi.org/10.1371/journal.pmed.0020124

Why Most Published Research Findings Are False. by: John P. A. Ioannidis

Ioannidis JPA. Why Most Published Research Findings Are False. PLoS Med. 2005 August;2(8):e124
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27 junio, 2011

How should systematic reviews consider evidence on harms?

Montage of images used to illustrate mission o...Image via Wikipedia
Systematic reviews that attempt to assess the risk of harms (adverse effects) associated with specific therapies should consider a broad range of study designs, including both systematic reviews and observational studies. These are the findings of a new study, led by Su Golder of the Centre for Reviews and Dissemination, University of York, UK published in PLoS Medicine.
WaldenU.edu/University
There is increasing focus on the importance of using rigorous methods to assess the effectiveness and harms associated with the use of  and other therapies, and recognition of the role of systematic reviews in this process. A uses predefined, explicit methods to find and appraise all relevant evidence to answer a specific question in healthcare. However, there has been considerable debate as to whether systematic reviews should use evidence from randomized controlled trials or observational studies (or both) in order to collect all the relevant evidence on risk of harms. Some groups have argued that observational studies may produce biased estimates of harm, while randomized trials may be too small to generate useful data on the risk of rare adverse effects.
In the study, Golder and colleagues identified systematic reviews that had compared the risk of specific harms in evidence from versus the evidence from observational studies. They found that there was no difference on average in the estimates produced by these two approaches. The authors conclude: "Instead of restricting the analysis to certain study designs, it may be preferable for systematic reviewers of  to evaluate a broad range of studies that can help build a complete picture of any potential harm and improve the generalisability of the review without loss of validity."
More information: Golder S, Loke YK, Bland M (2011) Meta-analyses of Adverse Effects Data Derived from Randomised Controlled Trials as Compared to Observational Studies: Methodological Overview. PLoS Med 8(5): e1001026.doi:10.1371/journal.pmed.1001026
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14 noviembre, 2009

Porque la mayoria de los resultados de investigacion publicados son falsos?

Existe una creciente preocupación de que los resultados de investigación más recientes publicados son falsos. La probabilidad de que una reivindicación de la investigación es cierto puede depender de la energía y el sesgo del estudio, el número de otros estudios sobre la misma cuestión, y, más importante, la proporción de fieles a ninguna relación entre las relaciones investigado en cada campo científico. En este marco, un hallazgo de investigación es menos probable que sea cierto cuando los estudios realizados en el campo son más pequeños, cuando son más pequeños tamaños del efecto, cuando existe un número mayor y menor prueba de preselección de las relaciones, donde existe una mayor flexibilidad en los diseños, definiciones, resultados, y los modos de análisis, cuando los intereses financieros y de otro no es mayor y los prejuicios, y cuando más equipos están involucrados en un campo científico a la caza de la significación estadística. Las simulaciones muestran que la mayoría de los diseños de estudio y configuración, sean más probable que los resultados de una investigación sean más falsos que verdaderos. Además, para muchos campos científicos actuales, los resultados de la investigación puede ser a menudo una medición simplemente precisa de la tendencia imperante. En este ensayo, se discuten las implicaciones de estos problemas para la realización e interpretación de la investigación.
El articulo completo puede encontrarse en http://dx.doi.org/10.1371/journal.pmed.0020124

Why Most Published Research Findings Are False. by: John P. A. Ioannidis

Ioannidis JPA. Why Most Published Research Findings Are False. PLoS Med. 2005 August;2(8):e124

18 octubre, 2008

Riesgo de Rofecoxib se mantiene luego de mas de un año de discontinuar su uso

El riesgo cardiaco de Vioxx se mantuvo mucho tiempo después de suspender su uso

Según los expertos, otros analgésicos AINE también podrían ser peligrosos

 

Reinberg S, Healthday 13/10/08

 

 

Cuando el analgésico Vioxx fue retirado del mercado en 2004 debido a las preocupaciones de que incrementaba el riesgo de ataque cardiaco, accidente cerebrovascular y muerte, muchos supusieron que suspender el medicamento acabaría con el riesgo.

Sin embargo, un estudio reciente halla que "el riesgo aumentó en cerca de dos veces y se mantuvo durante cerca de un año", señaló el Dr. Robert Bresalier, coautor y profesor de medicina del Centro oncológico M. D. Anderson de Houston.

"La buena noticia es que, después de un año, el riesgo pareció volver a la normalidad", dijo.

Sin embargo, los investigadores del estudio y otros expertos también consideran que el uso a largo plazo de la mayoría de los analgésicos de esta clase que no son aspirina, llamados antiinflamatorios no esteroideos (AINE), también aumentan el riesgo de ataque cardiaco, accidente cerebrovascular y muerte del usuario en alguna medida.

Entre los AINE también se encuentran los inhibidores de la cox-2, como los ahora descontinuados Vioxx y Bextra, al igual que el aún disponible Celebrex. Esos medicamentos se dirigen a la enzima ciclooxigenasa 2 (cox-2), que tiene que ver con la inflamación.

Entre los AINE también se encuentran algunos medicamentos antiinflamatorios menos dirigidos, como ibuprofeno (Advil, Motrin) o naproxeno (Aleve).

El informe aparece en la edición en línea del 14 de octubre de The Lancet.

Para el estudio, el grupo de Bresalier le dio seguimiento a personas que habían participado en el ensayo internacional APPROVe, que comparó Vioxx con un placebo durante tres años en un intento por determinar si el medicamento podría reducir la recurrencia de pólipos cancerosos en el colon. El ensayo se suspendió prematuramente en 2004 por un aumento en el riesgo de ataque cardiaco y accidente cerebrovascular.

Los investigadores del nuevo estudio lograron ponerse en contacto con el 84 por ciento de las cerca de 2,600 personas que habían participado en el ensayo.

Hallaron que un año después de descontinuar Vioxx, los antiguos usuarios todavía tenían un riesgo 79 por ciento mayor de ataque cardiaco, accidente cerebrovascular o muerte en comparación con los que recibieron un placebo.

El hallazgo coincide con el mayor riesgo observado durante el ensayo, en donde las probabilidades de problemas cardiovasculares fueron de más del doble para los que tomaron Vioxx. Para pacientes individuales, el riesgo de ataque cardiaco o accidente cerebrovascular se duplicó durante el año siguiente a haber suspendido el medicamento. Los investigadores anotaron que el incremento en el riesgo de muerte fue de 31 por ciento, comparado con los que habían tomado un placebo.

El grupo de Bresalier sí halló que Vioxx pudo reducir la recurrencia de pólipos en el colon, pero este beneficio se debía sospesar con el aumento en el riesgo cardiovascular, dijeron.

Bresalier sospecha que el uso a largo plazo de AINE que no son aspirinas puede aumentar las probabilidades de problemas cardiovasculares hasta cierto punto.

"Información similar se ha hecho evidente para algunos de los otros inhibidores de la cox 2", anotó. "De hecho, parece ser un efecto de clase para la mayoría, si no para todos los AINE. Hay un riesgo dependiente de la dosis también con Celebrex, cuya magnitud no fue muy distinta de la de Vioxx", dijo.

Bresalier considera que ciertos pacientes no deberían tomar dosis elevadas de estos medicamentos durante un periodo largo. "SI usted tiene antecedentes de enfermedad cardiovascular, hablar con su médico para comprender los riesgos y beneficios relativos. Si usted es alguien que realmente necesita tomar estos medicamentos por dolor crónico o artritis grave, tenga en cuenta los problemas. Pero usted no debe tener miedo de tomar estos medicamentos si los necesita", dijo.

Para las personas que toman estos medicamentos solo de manera intermitente, por ejemplo para el alivio del dolor a corto plazo, el riesgo es mínimo, aseguró Bresalier. "Eso no significa que si usted toma una o dos pastillas tendrá un ataque cardiaco. Para la gran mayoría de las personas que toman estos medicamentos, se trata de medicamentos muy buenos y seguros", dijo.

El Dr. Eric J. Topol, director del Instituto de ciencia transnacional Scripps y director académico de Scripps Health de La Jolla, California, no se sorprendió de que el riesgo de ataque cardiaco y accidente cerebrovascular continuara incluso luego de suspender Vioxx.

"Lo que esto hace es ayudar a demostrar aún más no solo el riesgo de Vioxx, sino la duración temporal", señaló Topol. "Ahora, disponemos de datos contundentes de que el riesgo se extiende un año después de suspender el medicamento", aseguró.

Sin embargo, Topol, uno de los primeros en alertar acerca de Vioxx, no está seguro de que éste sea un efecto de clase de todos los inhibidores de la cox 2.

"Siempre ha habido una señal de que [el riesgo] fue peor con Vioxx que con otros inhibidores de la cox 2. Se desconoce si otros medicamentos como Celebrex también la tenían. Eso no se ha demostrado en estudios sobre Celebrex. Pero hay que ser sospechoso, sobre todo debido a que las dosis elevadas de Celebrex están en riesgo de ataque cardiaco y accidente cerebrovascular. Sin embargo, nunca ha habido un estudio que demuestre que ese sea un problema duradero", dijo.

En respuesta al estudio de The Lancet, Merck, fabricante de Vioxx, emitió la siguiente declaración: "Merck considera que este análisis retrospectivo con datos limites de un estudio terminado prematuramente debe ser interpretado cuidadosamente y en el contexto del resto de la información del programa de desarrollo clínico extensivo de Vioxx


el resumen del articulo 
Baron JA, Sandler RS, Bresalier RS et al. Cardiovascular events associated with rofecoxib: final analysis of the APPROVe trial. Lancet 2008; Oct 14
The Lancet DOI:10.1016/S0140-6736(08)61490-7

disponible en 
http://www.thelancet.com/journals/lancet/article/PIIS0140673608614907/abstract?iseop=true

Traduccion: Martin Cañas

14 octubre, 2008

Ethical and Practical Issues Associated with Aggregating Databases

The goal of “personalized medicine” relies upon defining the genetic variation responsible for disease susceptibility and response to therapy [1]. For most common human diseases, the contribution of a single sequence variant to disease susceptibility is typically small, and can only be detected with data from large numbers of people [2]. Practically, this necessitates collaboration among investigators who either have DNA and phenotypic information previously collected, or have access to populations from which to recruit participants. It also requires that data be shared among the collaborators. Modern bioinformatics platforms have the capacity to combine datasets and store them for re-analysis. This is scientifically advantageous since it makes possible studies with enhanced validity in a cost-effective fashion. However, this data storage can complicate the already vexing practical, scientific, and ethical issues associated with gene and tissue banks. Research participants' data may have been collected without authorization that meets today's standards for informed consent. Research participants may not have consented to participation in genetics research in general, to inclusion in genetics databases specifically, or to use of their samples in genetic analyses that were unanticipated, unknown, or nonexistent at the time samples were collected [3]. Participants who consented to the collection of their data for use in a particular study, or inclusion in a particular database, may not have consented to “secondary uses” of those data for unrelated research, or use by other investigators or third parties [4]. There is concern that institutional review boards (IRBs) or similar bodies will not approve of the formation of aggregated databases or will limit the types of studies that can be done with them, even if those studies are believed by others to be appropriate, since there is a lack of consensus about how to deal with re-use of data in this manner...............leer mas en PLoS Medicine.

Ethical and Practical Issues Associated with Aggregating Databases

By Richard Wheeler (Zephyris) 2007. Lambda rep...Image via WikipediaThe goal of “personalized medicine” relies upon defining the genetic variation responsible for disease susceptibility and response to therapy [1]. For most common human diseases, the contribution of a single sequence variant to disease susceptibility is typically small, and can only be detected with data from large numbers of people [2]. Practically, this necessitates collaboration among investigators who either have DNA and phenotypic information previously collected, or have access to populations from which to recruit participants. It also requires that data be shared among the collaborators. Modern bioinformatics platforms have the capacity to combine datasets and store them for re-analysis. This is scientifically advantageous since it makes possible studies with enhanced validity in a cost-effective fashion. However, this data storage can complicate the already vexing practical, scientific, and ethical issues associated with gene and tissue banks. Research participants' data may have been collected without authorization that meets today's standards for informed consent. Research participants may not have consented to participation in genetics research in general, to inclusion in genetics databases specifically, or to use of their samples in genetic analyses that were unanticipated, unknown, or nonexistent at the time samples were collected [3]. Participants who consented to the collection of their data for use in a particular study, or inclusion in a particular database, may not have consented to “secondary uses” of those data for unrelated research, or use by other investigators or third parties [4]. There is concern that institutional review boards (IRBs) or similar bodies will not approve of the formation of aggregated databases or will limit the types of studies that can be done with them, even if those studies are believed by others to be appropriate, since there is a lack of consensus about how to deal with re-use of data in this manner............read more inn PLoS Medicine.

Ethical and Practical Issues Associated with Aggregating Databases

The goal of “personalized medicine” relies upon defining the genetic variation responsible for disease susceptibility and response to therapy [1]. For most common human diseases, the contribution of a single sequence variant to disease susceptibility is typically small, and can only be detected with data from large numbers of people [2]. Practically, this necessitates collaboration among investigators who either have DNA and phenotypic information previously collected, or have access to populations from which to recruit participants. It also requires that data be shared among the collaborators. Modern bioinformatics platforms have the capacity to combine datasets and store them for re-analysis. This is scientifically advantageous since it makes possible studies with enhanced validity in a cost-effective fashion. However, this data storage can complicate the already vexing practical, scientific, and ethical issues associated with gene and tissue banks. Research participants' data may have been collected without authorization that meets today's standards for informed consent. Research participants may not have consented to participation in genetics research in general, to inclusion in genetics databases specifically, or to use of their samples in genetic analyses that were unanticipated, unknown, or nonexistent at the time samples were collected [3]. Participants who consented to the collection of their data for use in a particular study, or inclusion in a particular database, may not have consented to “secondary uses” of those data for unrelated research, or use by other investigators or third parties [4]. There is concern that institutional review boards (IRBs) or similar bodies will not approve of the formation of aggregated databases or will limit the types of studies that can be done with them, even if those studies are believed by others to be appropriate, since there is a lack of consensus about how to deal with re-use of data in this manner...............leer mas en PLoS Medicine.

30 agosto, 2008

Un mapa humanizado de las enfermedades

El proyecto ha creado 600 mapamundis que reflejan las desigualdades mundiales

Crear los mapas de las desigualdades. Es la idea de un grupo de científicos que, a base de cartogramas y algoritmos, ha intentado representar los estados en proporción al dinero que emplea cada uno en gasto sanitario, al número de muertes infantiles que ocurren dentro de su territorio o a la incidencia de diferentes enfermedades. Se trata de humanizar los clásicos atlas y de ser capaces de ver la realidad para poder así actuar.

"Tú puedes decirlo, puedes probarlo, puedes tabularlo, pero sólo cuando lo ves es cuando golpea tu hogar", así comienza un artículo que publica la revista 'PLoS Medicine' y en el que se da cuenta de los detalles de una iniciativa a la que se le puede poner el adjetivo de humanitaria. "Dibujar imágenes también es una forma de emplear nuestra imaginación para ayudar a comprender la extensión y situación de las desigualdades del mundo en salud", explica el profesor Danny Dorling de la Universidad de Sheffield, Reino Unido.

Este científico elaboró el proyecto 'Worldmapper' junto con otros colaboradores del Grupo de Investigación de las Desigualdades Sociales y Espaciales de dicha universidad y con otros científicos procedentes del Centro para el Estudio de Sistemas Complejos de la Universidad de Michigan, en Estados Unidos. Se trata de dar un giro a las ilustraciones que se han venido utilizando desde hace siglos para mostrar la anatomía humana y para representar el mundo.

Para ello han utilizado mapas, algoritmos y datos de la Organización Mundial de la Salud (OMS) y otras agencias de Naciones Unidas, para hacer visible, entre otras enfermedades, la distribución global de la malaria.
Mapas más humanos

Con un mapa convencional donde se mostrara los países afectados por esta infección, "daría la impresión de que la distribución de los episodios clínicos de 'Plasmodium falciparum' (el parásito causante de la malaria) se confina a una pequeña proporción de la superficie de la tierra". Sin embargo, si se tiene en cuenta el número de casos, la representación es totalmente diferente. "La malaria es una enfermedad de personas, no de terrenos", declara el profesor Dorling.

Es por este motivo, por el que el mapa mundial que muestra los casos de malaria representa África como un gran globo hinchado y Europa como un minúsculo hilo. En cambio, cuando se muestra el dinero que emplea cada país al gasto sanitario, el mapa cambia, y el mundo desarrollado se muestra en formas agigantadas mientras que los países pobres se desinflan como una pelota.

"Nuevas formas de representar el mundo y las personas pueden cambiar a ambos y la forma en cómo los vemos, posiblemente para mejor. La tradicional anatomía ilustrativa, como la cartografía científica, puede deshumanizar [...] Los mapas del Worldmapper son parte de un intento mucho más amplio para ver y pensar de forma diferente", afirma el informe.

En la web http://www.worldmapper.org están disponibles los mapas y datos de cada una de las 600 nuevas representaciones que han desarrollado desde el año 2006.

"Podríamos hacer mucho más. Sin embargo, creo que lo más importante son las nuevas formas de pensamiento que podemos abrigar a partir de redibujar las imágenes de la anatomía humana de nuestro planeta de esta manera. ¿Qué necesitamos para ser capaces de ver, y por tanto para poder actuar?", concluye Dorling.