Burgess COMMENTARY

Peter Burgess

Gmail Peter Burgess [e-drug] WHO Pharmacovigilance Indicators: practical manual for assessment of PV systems (2) 1 message Donald W. Light Jr. Fri, Sep 4, 2015 at 9:56 PM Reply-To: Essential Drugs in English To: Essential Drugs in English E-DRUG: WHO Pharmacovigilance Indicators: practical manual for assessment of PV systems (2) -------------------------------------------------------------------------------------------- These look like good indicators; but note how the model of 'lifecycle monitoring' has accompanied more and more new medicines being approved faster on weaker and even dubious evidence that they offer advantages to patients over existing medications. For evidence, see the BMJ editorial this spring, 'Why do cancer drugs get such an easy ride?' See the forthcoming pair of articles and editorial in the BMJ in a few weeks. The risks of serious harm rises sharply with faster reviews, a trade-off between generating revenues faster for the companies that pay for the regulatory reviews and the number of patients hospitalized, dying, or put at serious risk. Postmarket vigilance tacitly supports this Faustian bargain. No evidence supports the claims that modernized vigilance can or will work. For a deep worry, see Moore and Furberg's assessment: http://link.springer.com/article/10.1007%2Fs40264-015-0305-9#page-1 About 90 percent of the medicines that the FDA and EMA approve, so that companies can start spending billions to turn doctors heads towards prescribing, are found to provide few or no advantages. At the same time, based on chart reviews of hospitalized patients, prescription drugs are a major cause of illness, hospitalizations, and deaths. See http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2282014 A good manual for the assessment of pharmacovigilance systems is just what industry wants, after flooding markets with minor variations under-tested for safety that have new patents to protect high prices. What patients and their doctors need is scientifically rigorous testing (not biased trial designs) before approval that new medicines are clinically advantageous for patients. Then pharmacovigilance can monitor for remaining rare or delayed problems. This is my opinion, at least. Don Light For a series of analyses in top journals, see pharmamyths.net 'Donald W. Light Jr.' _______________________________________________ E-Drug, an e-forum on essential drugs, is moderated by a team of international experts, and hosted by the FHI360-SATELLIFE Center for Health Information and Technology (www.healthnet.org). To subscribe: e-drug-join@healthnet.org To unsubscribe: e-drug-leave@healthnet.org To discuss (subscribers only): e-drug@healthnet.org For help: e-drug-owner@healthnet.org For archives: www.essentialdrugs.org/edrug/archives.php SSRN-id2282014-Institutional-Corruption-and-the-Myth-of-Safe-and-Effective-Drugs

Drug Safety July 2015, Volume 38, Issue 7, pp 601-610 Electronic Health Data for Postmarket Surveillance: A Vision Not Realized Thomas J. Moore , Curt D. Furberg Abstract

What has been learned about electronic health data as a primary data source for regulatory decisions regarding the harms of drugs? Observational studies with electronic health data for postmarket risk assessment can now be conducted in Europe and the US in patient populations numbering in the tens of millions compared with a few hundred patients in a typical clinical trial. With standard protocols, results can be obtained in a few months; however, extensive research published by scores of investigators has illuminated the many obstacles that prevent obtaining robust, reproducible results that are reliable enough to be a primary source for drug safety decisions involving the health and safety of millions of patients. The most widely used terminology for coding patient interactions with medical providers for payment has proved ill-suited to identifying the adverse effects of drugs. Directly conflicting results were reported in otherwise similar patient health databases, even using identical event definitions and research methods. Evaluation of some accepted statistical methods revealed systematic bias, while others appeared to be unreliable. When electronic health data studies detected no drug risk, there were no robust and accepted standards to judge whether the drug was unlikely to cause the adverse effect or whether the study was incapable of detecting it. Substantial investment and careful thinking is needed to improve the reliability of risk assessments based on electronic health data, and current limitations need to be fully understood.