Pharmaceutical Industry

1. Efficacy: Manipulation of Pharma Sponsored Study Results
   1. Background
      1. Pharmaceutical companies have decades of work, billions of dollars of potential sales hinging on study results
      2. Newly introduced drugs are typically backed by studies that overestimate benefit and underestimate risk
         1. Lexchin (2003) BMJ 326(7400): 1167 +PMID:12775614 [PubMed]
         2. Schott (2010) Dtsch Arztebl Int 107(16):279-85 +PMID:20467553 [PubMed]
         3. Schott (2010) Dtsch Arztebl Int 107(17):295-301 +PMID:20490338 [PubMed]
   2. Methods of data manipulation
      1. Negative studies are not published
         1. Pharmaceutical supported studies with negative results are eliminated
         2. Journals are pressured not to publish Independent studies with negative results
            1. Tsai (2003) Int J Health Serv 33(4): 751–768 +PMID:14758858 [PubMed]
      2. Adverse outcomes are suppressed in published reports
         1. http://www.breggin.com/antidepressant-drugs-resources/Breggin2006a-Paxil-GSK-Sepcial-Report-Part-I.pdf
      3. Control group manipulation
         1. Limit the Placebo Effect (patients can infer that they are not taking the active drug)
      4. Statistical manipulation
         1. Pharma employs talented biostatisticians
      5. Selective study duration
         1. Limit trial duration to time where toxicity is not yet evident, and effects have not yet dissipated
2. Resources
   1. Goldacre (2014) Bad Pharma
      1. Paid link to Amazon.com (ISBN 0865478066)
3. References
   1. Lin and Paradis in Herbert (2018) EM:Rap 18(9): 7-8