Elizabeth M Garry1,2, John B Buse3, Mugdha Gokhale1,4, Jennifer L Lund1, Matthew E Nielsen1,5, Virginia Pate1, Til Stürmer1. 1. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. 2. Science, Aetion Inc., Boston, Massachusetts. 3. Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina. 4. Real World Evidence and Epidemiology, GlaxoSmithKline, Collegeville, Pennsylvania. 5. Urologic Oncology, University of North Carolina School of Medicine, Chapel Hill, North Carolina.
Abstract
AIM: The aim of the study was to empirically demonstrate the effect of varying study designs when evaluating the safety of pioglitazone in treating bladder cancer. METHODS: We identified Medicare beneficiaries above 65 years of age with diabetes between 2008 and 2015 and with classified exposure (at least two claims within 180 days) to glucose-lowering drugs (GLD), pioglitazone or another drug. The effects of varying the following study design parameters on bladder cancer risk were assessed: use of a new vs existing drug, choice of referent (all non-users and users of GLDs, non-insulin GLDs and DPP-4s) and whether or not censoring accounted for treatment change. We used the Cox proportional hazards model to obtain adjusted HRs and 95% CIs. RESULTS: We included 1,510,212 patients classified as pioglitazone users (N = 135,188) or non-users (N = 1,375,024). Users had more diabetic complications than non-users, but fewer than insulin users. The HR ranged from 1.10 (1.01-1.20) to 1.13 (0.99-1.29) when censoring ignored treatment change, suggesting a weak association or none between pioglitazone and bladder cancer, probably under-estimating risk. However, the HR was 1.20 (1.01-1.42) when cohorts were restricted to new users, censored upon treatment change, and when DPP-4 was used as the referent, suggesting an increased risk of bladder cancer associated with pioglitazone. CONCLUSIONS: The continued demand for new GLDs indicates the need for more robust observational methods to improve the value of generating real-world evidence in equipping clinicians to make informed prescribing decisions. Although there is no one-size-fits-all approach, we recommend active comparator new user study designs that compare therapeutically equivalent drugs and account for treatment changes during follow-up to present the least biased comparative safety estimates.
AIM: The aim of the study was to empirically demonstrate the effect of varying study designs when evaluating the safety of pioglitazone in treating bladder cancer. METHODS: We identified Medicare beneficiaries above 65 years of age with diabetes between 2008 and 2015 and with classified exposure (at least two claims within 180 days) to glucose-lowering drugs (GLD), pioglitazone or another drug. The effects of varying the following study design parameters on bladder cancer risk were assessed: use of a new vs existing drug, choice of referent (all non-users and users of GLDs, non-insulin GLDs and DPP-4s) and whether or not censoring accounted for treatment change. We used the Cox proportional hazards model to obtain adjusted HRs and 95% CIs. RESULTS: We included 1,510,212 patients classified as pioglitazone users (N = 135,188) or non-users (N = 1,375,024). Users had more diabetic complications than non-users, but fewer than insulin users. The HR ranged from 1.10 (1.01-1.20) to 1.13 (0.99-1.29) when censoring ignored treatment change, suggesting a weak association or none between pioglitazone and bladder cancer, probably under-estimating risk. However, the HR was 1.20 (1.01-1.42) when cohorts were restricted to new users, censored upon treatment change, and when DPP-4 was used as the referent, suggesting an increased risk of bladder cancer associated with pioglitazone. CONCLUSIONS: The continued demand for new GLDs indicates the need for more robust observational methods to improve the value of generating real-world evidence in equipping clinicians to make informed prescribing decisions. Although there is no one-size-fits-all approach, we recommend active comparator new user study designs that compare therapeutically equivalent drugs and account for treatment changes during follow-up to present the least biased comparative safety estimates.
Authors: Ronac Mamtani; Kevin Haynes; Warren B Bilker; David J Vaughn; Brian L Strom; Karen Glanz; James D Lewis Journal: J Natl Cancer Inst Date: 2012-08-09 Impact factor: 13.506
Authors: Elizabeth M Garry; John B Buse; Jennifer L Lund; Virginia Pate; Til Stürmer Journal: Diabetes Obes Metab Date: 2017-08-08 Impact factor: 6.577
Authors: James D Lewis; Assiamira Ferrara; Tiffany Peng; Monique Hedderson; Warren B Bilker; Charles P Quesenberry; David J Vaughn; Lisa Nessel; Joseph Selby; Brian L Strom Journal: Diabetes Care Date: 2011-04 Impact factor: 19.112
Authors: Pasi Korhonen; Edith M Heintjes; Rachael Williams; Fabian Hoti; Solomon Christopher; Maila Majak; Leanne Kool-Houweling; Helen Strongman; Marie Linder; Paul Dolin; Shahram Bahmanyar Journal: BMJ Date: 2016-08-16