miércoles, 23 de octubre de 2013

Restoring invisible and abandoned trials: a call for people to publish the findings | BMJ

texto completo original:
Restoring invisible and abandoned trials: a call for people to publish the findings | BMJ

Vergüenza ética: Ensayos clínicos invisibles y abandonados


No se puede menos que pensar en las personas, los seres humanos, que participaron en estos ensayos clínicos invisibilizados y abandonados. La industria farmacéutica ¿puede seguir teniendo el cinismo de apelar al altruísmo para incrementar el reclutamiento?

Restoring invisible and abandoned trials: a call for people to publish the findings
BMJ 2013; 346 doi: http://dx.doi.org/10.1136/bmj.f2865 (Published 13 June 2013)
Cite this as: BMJ 2013;346:f2865
“Two basic problems of representation are driving growing concerns about relying on published research to reflect the truth. The first is no representation (invisibility), which occurs when a trial remains unpublished years after completion. The second is distorted representation (distortion), which occurs when publications in medical journals present a biased or misleading description of the design, conduct, or results of a trial. Both go against the fundamental scientific and ethical responsibility that all research on humans be used to advance knowledge and are symptomatic of a general culture of data secrecy. The end result is that the healthcare, biomedical research, and policy communities may, despite best intentions and best practices, end up drawing scientifically invalid conclusions based on only those parts of the evidence base they can see.
Autores
  1. Peter Doshi, postdoctoral fellow1,
  2. Kay Dickersin, professor, director234,
  3. David Healy, professor of psychiatry5,
  4. S Swaroop Vedula, postdoctoral fellow6,
  5. Tom Jefferson, researcher7

Restoring invisible and abandoned trials: a call for people to publish the findings

BMJ2013;346doi: http://dx.doi.org/10.1136/bmj.f2865(Published 13 June 2013)
Cite this as:BMJ2013;346:f2865

  1. Peter Doshi, postdoctoral fellow1,
  2. Kay Dickersin, professor, director234,
  3. David Healy, professor of psychiatry5,
  4. S Swaroop Vedula, postdoctoral fellow6,
  5. Tom Jefferson, researcher7
Author Affiliations
  1. Correspondence to: P Doshi, Reed Hall West, Room 201-C, 1620 McElderry Street, Baltimore, MD 21205, USA pdoshi@post.harvard.edu
  • Accepted 5 April 2013
Unpublished and misreported studies make it difficult to determine the true value of a treatment. Peter Doshi and colleagues call for sponsors and investigators of abandoned studies to publish (or republish) and propose a system for independent publishing if sponsors fail to respond
Well designed and well performed randomised controlled trials are considered to provide the most reliable evidence on the effects of health related interventions. However, the credibility of findings from individual trials and from summaries of trials examining a similar research question (that is, systematic reviews and meta-analyses) has been undermined by numerous reporting biases in the published medical literature.1 2 3 4 5 6 7 8 9 10 11 12 13 14 Reporting biases are often difficult to detect, but have the potential to discredit earnest efforts towards evidence based decision making.
Two basic problems of representation are driving growing concerns about relying on published research to reflect the truth.10 15 The first is no representation (invisibility), which occurs when a trial remains unpublished years after completion. The second is distorted representation (distortion), which occurs when publications in medical journals present a biased or misleading description of the design, conduct, or results of a trial.1 6 10 14 Both go against the fundamental scientific and ethical responsibility that all research on humans be used to advance knowledge and are symptomatic of a general culture of data secrecy. The end result is that the healthcare, biomedical research, and policy communities may, despite best intentions and best practices, end up drawing scientifically invalid conclusions based on only those parts of the evidence base they can see.

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