This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 360
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #309056
Title: Using Statistical Concepts to Determine Risk Level of Randomized Clinical Trials That Compare Two Noninvestigational Therapies
Author(s): Martin L. Lesser and Nina E. Kohn*+
Companies: Feinstein Institute for Medical Research
Address: Biostatistics Unit, Manhasset, NY, 11030,
Keywords: research risk assessment ; randomized trials ; IRB

Statistical thinking can help decide if a randomized clinical trial (RCT) can be considered no more than minimal risk (MR) even if the therapies (tx) do include risks. A study is MR if the risks are not greater than those ordinarily encountered in daily life or routine medical procedures. We argue: A RCT comparing 2 commonly used non-investigational tx's, may not increase risk above MR. Let T1, T2 be 2 tx's with risk benefit ratios (RBR) RB1, RB2. Assume a patient (pt) receives T1 or T2 with probabilities p,1-p outside of the RCT (p="community" prob of T1 usage). The expected "community" RBR is r=p*RB1+(1-p)*RB2. In a RCT where v=prob(pt is randomized to T1), the expected RCT RBR is R=v*RB1+(1-v)*RB2. Assuming tx's encountered by a pt are considered "routine" for that pt and are, therefore, considered MR, then, by subjectively comparing r and R, an IRB can decide if the RCT is MR.

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