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Activity Number:
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473
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Type:
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Contributed
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Date/Time:
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Wednesday, August 9, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #307213 |
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Title:
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Using Marginal Structural Model To Adjust for Post-Discontinuation Chemotherapy in Cancer Clinical Trials
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Author(s):
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Yanping Wang*+ and Jim Symanowski
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Companies:
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Eli Lilly and Company and Eli Lilly and Company
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Address:
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Lilly Corporate Center, Indianapolis, IN, 46285,
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Keywords:
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causal inference ; survival analysis ; cancer clinical trials
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Abstract:
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Comparison of survival between treatment arms in randomized cancer clinical trials is often complicated by post-discontinuation chemotherapy (PDC). We need to adjust for the effect of PDC so the estimated treatment arm effects have the desired causal interpretation. Methods such as the time-dependent proportional hazards model may not properly adjust for post-randomization therapy and may produce biased results. Alternatively, the marginal structural model (MSM) proposed by Robins has the potential to reduce or remove the bias. Because the results of the MSM are appropriately adjusted for potential effects of PDC, the isolated effect of experimental treatment on overall survival can be estimated with less or no bias. We applied this approach to Phase III cancer clinical trials and compared the results with those from the time-dependent proportional hazards model.
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