DEBIASED LASSO FOR STRATIFIED COX MODELS WITH APPLICATION TO THE NATIONAL KIDNEY TRANSPLANT DATA

• 成果类型: Article
• 署名作者: Xia, Lu; Nan, Bin; Li, Yi
• 署名单位: University of Michigan System; University of Michigan; University of California System; University of California Irvine
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/23-AOAS1775
• 发表日期: 2023
• 页码: 3550-3569
• 关键词: PROPORTIONAL HAZARDS MODEL; recipient age; confidence-intervals; graft failure; variable selection; RISK; survival; parameters; mortality

摘要

The Scientific Registry of Transplant Recipients (SRTR) system has be -come a rich resource for understanding the complex mechanisms of graft failure after kidney transplant, a crucial step for allocating organs effectively and implementing appropriate care. As transplant centers that treated patients might strongly confound graft failures, Cox models stratified by centers can eliminate their confounding effects. Also, since recipient age is a proven non-modifiable risk factor, a common practice is to fit models separately by recipient age groups. The moderate sample sizes, relative to the number of covariates, in some age groups may lead to biased maximum stratified partial like-lihood estimates and unreliable confidence intervals, even when samples still outnumber covariates. To draw reliable inference on a comprehensive list of risk factors measured from both donors and recipients in SRTR, we propose a debiased lasso approach via quadratic programming for fitting stratified Cox models. We establish asymptotic properties and verify via simulations that our method produces consistent estimates and confidence intervals with nominal coverage probabilities. Accounting for nearly 100 confounders in SRTR, the debiased method detects that the graft failure hazard nonlinearly increases with donor's age among all recipient age groups and that organs from older donors more adversely impact the younger recipients. Our method also delineates the associations between graft failure and many risk factors such as recipients' primary diagnoses (e.g., polycystic disease, glomerular disease, and diabetes) and donor-recipient mismatches for human leukocyte antigen loci across recipient age groups. These results may inform the refinement of donor-recipient matching criteria for stakeholders.