Assessing positive outcomes of phase III trials

[Celebration]

http://www.physorg.com/news/2010-12-positive-outcomes-phase-iii-trials.html

Randomized phase III studies should be designed to find out whether a new drug or treatment makes a meaningful difference in patients' survival or quality of life, according to a commentary published online December 3rd in The Journal of the National Cancer Institute. Instead, most trials now are designed to detect a statistically significant difference between treatment and control groups, which may not be clinically meaningful, write Alberto Ocana, M.D., Ph.D. and Ian F. Tannock, M.D., Ph.D., of Princess Margaret Hospital in Toronto.

Regulatory agencies such as the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMEA) approve drugs usually based on statistically significant results of randomized phase III trials comparing a new, investigational drug with standard treatment. Ocana and Tannock note that pharmaceutical companies have typically sponsored clinical trials that are large enough to detect statistically significant differences in survival. But these differences are often trivial, they say. For instance, the trial that led to approval of erlotinib (Tarceva) for pancreatic cancer found that patients who took the drug had a median survival just 10 days longer than patients in the control group. However, the difference was statistically significant, and the drug was approved.

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Lee goes on to argue for the adoption of the Bayesian approach in contrast to the more conventional frequentist approach. "Statistics in medicine has passed through its infancy and childhood. As it moves into its adolescence, the growing pains of reconciling frequentist and Bayesian views continue," he writes. In his view, though, the "roadblocks" of the Bayesian approach, namely the notion of subjectivity and computation difficulty, have been overcome.

"The Bayesian approach is complementary to and can provide a superior alternative to the frequentist paradigm," Lee writes. "I encourage medical researchers to have an open mind, learn more about Bayesian methods, and apply them to provide a more accurate statistical assessment of the results in clinical trials."

[MannyGoldstein]

1. Cost per added quality-adjusted life year

Best means of comparison, I think.