Q:Find (in the literature or on Internet) a story on clinical trials fraud. What factors could have played a significant roll in order to detect fraud in your story?
Fraud in breast cancer study;
Doctor lied on data for decade.
Chicago Tribune, 13 March 1994
A 1989 New England Journal of Medicine article on breast cancer therapy presented findings from a study directed by Fisher. Recurrence rates for cancer after lumpectomy and radiation were compared with rates following mastectomy.
The study involved 5,000 patients at nearly 500 medical centers. The recurrence rates were found to be essentially the same, leading many women to opt for the less disfiguring lumpectomy and radiation treatment.
This article reported that Federal investigators discovered that one of the principal collaborators, Dr.
Roger Poisson at the University of Montreal, enrolled at least 100 of his cancer patients who were not eligible for the study and falsified their records to make them appear eligible.
It is suggested that Poisson was not trying to affect the outcome but only wanted to appear good at
recruiting patients, in order to improve his chances for continued financial support. Poisson contributed about 16% of the patients to the 1989 study.
The organizers of the study privately assured investigators nearly two years ago that the fraud did
not affect the results of any of their findings. Fisher promised to publish a re-analysis of the data.
Later news articles reported that Federal health officials have commissioned three statisticians to
analyze the study independently and to give their report in two weeks. Fisher is now expected to give his own analysis to the New England Journal of Medicine within the next two weeks.
Factors that played a significant role in order to detect fraud:
1) Checking the patient ID cards and papers played a vital role in catching the fraud.
2)The dates of prohibited medication use altered or suppressed. The subject was treated, but it was not put in chart or on the CRF. So interviewing the patients thoroughly payed an important role in identifying patients who had antibiotic treatments but not reported in CRF.