We propose novel methods for the analysis of survival data arising from studies of organ failure patients. The organ failure setting yields data structures to which existing univariate and multivariate survival analysis methods cannot be applied to address many questions of great interest to clinicians, health policy makers and patients. The issues addressed by the proposed methods are general, in that they will have wide applicability outside the organ replacement setting. There is currently great interest in quantifying the survival benefit of organ transplantation and, correspondingly, this proposal is targeted strongly in that direction.
In Aim 1 we propose semiparametric methods to quantify the effect of an experimental time-dependent therapy relative to conventional therapy on mean time until failure. Methods developed in Aim 1 will be used to quantify the benefit of expanded criteria donor kidney transplantation relative to conventional therapy.
In Aim 2, we develop semiparametric methods to predict patient-specific differences between post-treatment and treatment-free mean lifetime. These predictions are intended to be the basis of a score to replace the current system for prioritizing patients wait listed for liver transplantation. We also propose methods for estimating the marginal effect of a time-dependent treatment on mean lifetime, obtained by averaging over the patient- specific estimates used in the proposed score.
In Aim 3, we develop and evaluate semiparametric methods to make covariate-adjusted comparisons of gap time survival distributions. The methods proposed in Aim3 will be used to compare mean lifetime of first and second kidney transplants, in order to assess the value of repeat kidney transplantation.
We propose novel methods for the analysis of survival data arising from studies of organ failure patients. There is currently great interest in quantifying the survival benefit of organ transplantation and, correspondingly, this proposal is targeted strongly in that direction.
|Sharma, Pratima; Goodrich, Nathan P; Schaubel, Douglas E et al. (2017) National assessment of early hospitalization after liver transplantation: Risk factors and association with patient survival. Liver Transpl 23:1143-1152|
|Shu, Xu; Schaubel, Douglas E (2017) Methods for Contrasting Gap Time Hazard Functions: Application to Repeat Liver Transplantation. Stat Biosci 9:470-488|
|Gong, Qi; Schaubel, Douglas E (2017) Estimating the average treatment effect on survival based on observational data and using partly conditional modeling. Biometrics 73:134-144|
|Sharma, Pratima; Shu, Xu; Schaubel, Douglas E et al. (2016) Propensity score-based survival benefit of simultaneous liver-kidney transplant over liver transplant alone for recipients with pretransplant renal dysfunction. Liver Transpl 22:71-9|
|Goodrich, Nathan P; Schaubel, Douglas E; Smith, Abigail R et al. (2016) National Assessment of Hospitalization Rates for Incident End-Stage Renal Disease After Liver Transplantation. Transplantation 100:2115-21|
|Fan, Ludi; Schaubel, Douglas E (2016) Comparing center-specific cumulative incidence functions. Lifetime Data Anal 22:17-37|
|Shu, Xu; Schaubel, Douglas E (2016) Semiparametric methods to contrast gap time survival functions: Application to repeat kidney transplantation. Biometrics 72:525-34|
|Gong, Qi; Schaubel, Douglas E (2015) Semiparametric Contrasts of Cumulative Pre-Treatment Mortality in the Presence of Dependent Censoring. Stat Biosci 7:245-261|
|Sharma, Pratima; Schaubel, Douglas E; Goodrich, Nathan P et al. (2015) Serum sodium and survival benefit of liver transplantation. Liver Transpl 21:308-13|
|Smith, Abigail R; Schaubel, Douglas E (2015) Time-dependent prognostic score matching for recurrent event analysis to evaluate a treatment assigned during follow-up. Biometrics 71:950-9|
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