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Kidney Week

Abstract: TH-PO431

Evaluation of Tolvaptan Effect in Autosomal Dominant Polycystic Kidney Disease (ADPKD) Using Inverse Probability of Censoring Weighting for Long-Term Extension Data

Session Information

Category: Genetic Diseases of the Kidneys

  • 1201 Genetic Diseases of the Kidneys: Cystic

Authors

  • Jiang, Huan, Otsuka America Pharmaceutical Inc, Princeton, New Jersey, United States
  • Zhang, Zhen, Otsuka America Pharmaceutical Inc, Princeton, New Jersey, United States
Background

In long-term extension (LTE) clinical trials switching treatment arms is common among placebo participants. Inverse Probability of Censoring Weighting (IPCW) was invented to recreate balanced treatment arms by assigning weights to patients without switching. Another possible issue is no comparators exist during LTE trials, leading to bias in comparisons between treatments when including LTE data. In this research, we aim to create a control group for treatment comparison and determine whether IPCW decreases bias raised from crossover in LTE data.

Methods

Using data from TEMPO 3:4 trial and its LTE TEMPO 4:4, we created a control group for placebo druing LTE, calculated weights using IPCW, and conducted analyses: 1) estimation of time to end stage kidney disease (ESKD) using Cox regression models; (2) estimation of average decline in eGFR between placebo and tolvaptan using mixed-effects models.

Results

IPCW method performed well in reducing errors from unbalanced treatment arms and determining effectiveness of tolvaptan with a decreased hazard ratio(HR) in Model 1(0.17 with 95% CI (0.05, 0.54)) compared to HRs estimated in Model 2, which ignored crossover and analyzed as intention-to-treat (ITT) (0.38 with 95% CI (0.20, 0.75)) and Model 3, a time-varying Cox regression model (0.22 with 95% CI (0.09, 0.56)) (Table 1). Cox regression models were adjusted by baseline age, eGFR, creatinine, sex, race, PKD diagnosed before age 35, and TKVs over time. It also adjusted biases well in Model 4 (-4.22 ml/min/1.73 m2 per year for placebo; -2.93 ml/min/1.73 m2 per year for tolvaptan) on average eGFR decline, compared to Model 5, which excluded placebo patients from LTE and longer years were used to estimate tolvaptan effects, and Model 6 using ITT method mentioned in Model 2 (Table 2). Mixed-effects models were used without adjustment.

Conclusion

In Cox regression and mixed-effects models, IPCW reduced bias in estimating long-term effects from crossover after creating a control group for placebo patients.

Funding

  • Commercial Support – Otsuka Pharmaceutical Development & Commercialization, Inc.