Mugdha Gokhale1,2, John B Buse3, Christina DeFilippo Mack1,4, Michele Jonsson Funk1, Jennifer Lund1, Ross J Simpson3, Til Stürmer1. 1. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapell Hill, NC, USA. 2. Real World Evidence & Epidemiology, GlaxoSmithKline, Collegeville, PA, USA. 3. Department of Medicine, University of North Carolina School of Medicine, Chapell Hill, NC, USA. 4. Real-World and Late Phase Research, Quintiles, Research Triangle Park, NC, USA.
Abstract
OBJECTIVE: In recent years, second-line diabetes treatment with dipeptidyl peptidase-4 inhibitors (DPP-4i) increased with a corresponding decrease in thiazolidinediones (TZDs). Using hospitalization for heart failure (HF) as a positive control outcome, we explored the use of calendar time as an instrumental variable (IV) and compared this approach to an active comparator new-user study. METHODS: We identified DPP-4i or TZD initiators after a 6-month washout using Medicare claims 2006-2013. The IV was defined as a binary variable comparing initiators during October 2010 to December 2013 (postperiod) versus January 2008 to May 2010 (preperiod). We examined IV strength and estimated risk differences (RDs) for HF using Kaplan-Meier curves, which were compared with propensity score (PS)-weighted RD for DPP-4i versus TZD. RESULTS: The IV compared 22 696 initiators (78% DPP-4i) in the postperiod versus 20 283 initiators (38% DPP-4i) in the preperiod, resulting in 40% compliance. The active-comparator (PS-weighted) approach compared 26 198 DPP-4i and 18 842 TZD initiators. Covariate balance across IV levels was slightly better than across treatments (standardized difference, 3% vs 4.5%). The 1- and 2-year local average treatment effects of RD of HF per 100 patients in the "compliers" (95% confidence intervals) were -0.62 (-0.99 to -0.25) and -0.88 (-1.46 to -0.25). Corresponding PS-weighted results were -0.20 (-0.33 to -0.05) and -0.18 (-0.30 to 0.03). CONCLUSION: Both approaches indicated lesser risk of HF hospitalizations among DPP-4i vs TZD initiators. The magnitude of the estimated effects may differ due to differences in the target populations and assumptions. Calendar time can be leveraged as an IV when market dynamics lead to profound changes in treatments.
OBJECTIVE: In recent years, second-line diabetes treatment with dipeptidyl peptidase-4 inhibitors (DPP-4i) increased with a corresponding decrease in thiazolidinediones (TZDs). Using hospitalization for heart failure (HF) as a positive control outcome, we explored the use of calendar time as an instrumental variable (IV) and compared this approach to an active comparator new-user study. METHODS: We identified DPP-4i or TZD initiators after a 6-month washout using Medicare claims 2006-2013. The IV was defined as a binary variable comparing initiators during October 2010 to December 2013 (postperiod) versus January 2008 to May 2010 (preperiod). We examined IV strength and estimated risk differences (RDs) for HF using Kaplan-Meier curves, which were compared with propensity score (PS)-weighted RD for DPP-4i versus TZD. RESULTS: The IV compared 22 696 initiators (78% DPP-4i) in the postperiod versus 20 283 initiators (38% DPP-4i) in the preperiod, resulting in 40% compliance. The active-comparator (PS-weighted) approach compared 26 198 DPP-4i and 18 842 TZD initiators. Covariate balance across IV levels was slightly better than across treatments (standardized difference, 3% vs 4.5%). The 1- and 2-year local average treatment effects of RD of HF per 100 patients in the "compliers" (95% confidence intervals) were -0.62 (-0.99 to -0.25) and -0.88 (-1.46 to -0.25). Corresponding PS-weighted results were -0.20 (-0.33 to -0.05) and -0.18 (-0.30 to 0.03). CONCLUSION: Both approaches indicated lesser risk of HF hospitalizations among DPP-4i vs TZD initiators. The magnitude of the estimated effects may differ due to differences in the target populations and assumptions. Calendar time can be leveraged as an IV when market dynamics lead to profound changes in treatments.
Authors: Mugdha Gokhale; Stacie B Dusetzina; Virginia Pate; Danielle S Chun; John B Buse; Til Stürmer; Emily W Gower Journal: Diabetes Care Date: 2020-07-08 Impact factor: 19.112