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How to smell a rat: Examples of scientific and regulatory failure in medicine

How to smell a rat: Examples of scientific and regulatory failure in medicine. Dr Aubrey Blumsohn Presentation at Radstats British Library, London 24 February 2012. Nature of science – and how we define scientific fraud. Data – and access to data. Regulators (watchdogs).

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How to smell a rat: Examples of scientific and regulatory failure in medicine

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  1. How to smell a rat: Examples of scientific and regulatory failure in medicine Dr Aubrey Blumsohn Presentation at RadstatsBritish Library, London 24 February 2012

  2. Nature of science – and how we define scientific fraud

  3. Data – and access to data

  4. Regulators (watchdogs)

  5. Individual responsibility in science

  6. Science Data Regulators Individual responsibility

  7. History • Einstein • Insanity: doing the same thing over and over again and expecting different results.

  8. What is Science? • UK Science Council (2009) • Spent a year working out a new definition of science. • Claim as the first "official definition of science" ever published. • “Science is the pursuit of knowledge and understanding of the natural and social world following a systematic methodology based on evidence”

  9. What is Science? – Mertonian Norms • Communalism • Everyone can see what’s going on • Universalism • Doing of it not restricted to special people • Disinterestedness • An arms length attitude. • Skepticism (Organized Skepticism) - • Claims exposed to critical scrutiny. Awkward questions.Merton, Robert K. (1973), "The Normative Structure of Science",

  10. Science demands awkward people It takes all sorts of people

  11. Example 1: “Mr Nobody”and Journal of the American Medical Association (JAMA)

  12. Letter #1 to JAMA

  13. Letter #2 To BMJ

  14. Scientific deception- and its mis-definition

  15. The Classics • William Summerlin (Sloan Kettering, 1984) - faked transplantation experiments in white mice by blackening patches of their skin with a pen • Vijay Soman (Yale, 1980) a diabetologist - wrote 12 papers based on invented data. His co-author Felig had to resign

  16. The Classics • Robert Slutsky (Radiologist, University of California). Published 137 papers between 1978 and 1985 -- one every 20 days. Many faked. • John Darsee (Cardiologist, Harvard, 1981). Observed falsifying data. His boss, Eugene Braunwald ignored the problem. Later investigations discovered more than a 100 fraudulent papers

  17. In these odd cases, the stories, as told, usually minimise the involvement of senior colleagues, University administrators, Hospitals and regulatory bodies who hid the misconduct before it was eventually exposed

  18. The impression • The choice of cases implicitly defines what we mean by scientific fraud/misconduct • Fraud is rare • It involves a particular type of activity (painting a mouse) • Usually involves an aberrant (male) acting alone (or duping otherwise honourable collaborators) “Problems of scientific misconduct are rare - the product of psychopathic behaviour’ originating in temporarily deranged minds” President of the National Academy of Sciences (at Congressional Hearings)

  19. And the solution • Is to create yet more procedures and guidance • And for Universities to create robust, secret, legalistic procedures to investigate these rare rogues

  20. Only one problem. As Arnold Schwarzenegger once said:“it's bullshit—all of it”

  21. The reality • Not rare • Scientific misconduct often not an individual activity – but a group activity (or involves group collusion)

  22. Group-think • Hannah Arendt (1965) • "rule by nobody". • No single individual feels responsible for what is ultimately done. • Indeed many people have gone to great lengths to make sure that this exact state of affairs achieved • Legislators • Ethics Committees • Trade bodies • Regulators • System designers responsible for fraud?

  23. The reality • The offender is often not a lone white male psychopath • Corporate fraud

  24. The reality • Corporation acting at the University interface

  25. The reality • or a journal editor

  26. The reality • or a regulator …. • or government itself

  27. The mechanisms also differ • The mechanism of misconduct is also usually not direct fabrication of findings but something far more nuanced

  28. Defining pornography • "hard-core pornography" was hard to define, but "I know it when I see it“Potter Stewart(Associate Justice of the US Supreme Court)

  29. Misconduct • Misconduct is nothing to do with the correctness of conclusion • To err is human, and scientific!!! • It has to do with behaviours • Behaviours which could disturb the scientific record • Not binary • We need to get away from ludicrous discussion about restrictive definitions and start discussing behaviours • Openly

  30. Example 2: The fearful junior • Approached by a Junior Doctor • In order to gain her pathology registration she had to submit her dissertation • She could not write up her dissertation or prepare the main area of work for publication because her supervisor had made this impossible – for years….. • She could only present the secondary aspects • The work involved looking at physiological changes in healthy volunteers randomised to atorvastatin or placebo • The study showed that atorvastatin induced a diabetes like state • Her supervisor was funded by the manufacturer of atorvastatin

  31. Example 3: Does Seroquel cause diabetes and weight gain

  32. But there was a cloud on the horizon. The F.D.A. was beginning to look into the issue of Diabetes in patients on Atypical Antipsychotics and wrote to Astrazeneca

  33. Then somebody noticed the obvious that they had more than just 18 months of data in these subjects

  34. Example 4 – Famovir and Herpes • Famvir is used for treatment of herpes zoster • There was a nine year delay before partial publication of findings which had adverse implications for the sponsor

  35. What are data? Data is not the same as representation of that data

  36. Getting a hamburger when what you need is the original cow

  37. Example 5: Vioxx APPROVE Trial New York Times May 31, 2006

  38. Look at the language Merck & Co. acknowledged that it misidentified a statistical method Merck has contended that the study shows The company said in a statement yesterday Merck has insisted that its 18-month argument holds up while outside scientists have cast doubt on the company's interpretation. Merck research chief Peter Kim said the company stood by its analysis

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