BMC Medicine (Aug 2020)

Compassionate drug (mis)use during pandemics: lessons for COVID-19 from 2009

  • Amanda M. Rojek,
  • Genevieve E. Martin,
  • Peter W. Horby

DOI
https://doi.org/10.1186/s12916-020-01732-5
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 10

Abstract

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Abstract Background New emerging infections have no known treatment. Assessing potential drugs for safety and efficacy enables clinicians to make evidence-based treatment decisions and contributes to overall outbreak control. However, it is difficult to launch clinical trials in the unpredictable environment of an outbreak. We conducted a bibliometric systematic review for the 2009 influenza pandemic to determine the speed and quality of evidence generation for treatments. This informs approaches to high-quality evidence generation in this and future pandemics. Methods We searched PubMed for all clinical data (including clinical trial, observational and case series) describing treatment for patients with influenza A(H1N1)pdm09 and ClinicalTrials.gov for research that aimed to enrol patients with the disease. Results Thirty-three thousand eight hundred sixty-nine treatment courses for patients hospitalised with A(H1N1)pdm09 were detailed in 160 publications. Most were retrospective observational studies or case series. Five hundred ninety-two patients received treatment (or placebo) as participants in a registered interventional clinical trial with results publicly available. None of these registered trial results was available during the timeframe of the pandemic, and the median date of publication was 213 days after the Public Health Emergency of International Concern ended. Conclusion Patients were frequently treated for pandemic influenza with drugs not registered for this indication, but rarely under circumstances of high-quality data capture. The result was a reliance on use under compassionate circumstances, resulting in continued uncertainty regarding the potential benefits and harms of anti-viral treatment. Rapid scaling of clinical trials is critical for generating a quality evidence base during pandemics.

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