Promoting Utilization of Kidneys by Improving Patient Level Decision Making

通过改善患者决策来促进肾脏的利用

• 批准号: 9019712
• 负责人: Sanjay Mehrotra
• 金额: $ 18.96万
• 依托单位: NORTHWESTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9019712
• 关键词: Accounting; Address; Affect; Age; Biometry; Biopsy; Blood typing procedure; Cause of Death; Cessation of life; Characteristics; Chronic; Complex; Cost Savings; Creatinine; Data; Decision Making; Decision Trees; Diabetes Mellitus; Dialysis procedure; Disease; Elements; End stage renal failure; Ethnic Origin; Future; Graft Survival; HLA Antigens; Handedness; Health; Health Care Costs; Height; Hepatitis C; Hypertension; Individual; Ischemia; Kidney; Kidney Transplantation; Knowledge; Machine Learning; Measures; Medicare; Methodology; Modeling; Morbidity - disease rate; Nature; Organ; Organ Model; Pancreas; Patients; Process; Quality of life; Recording of previous events; Registries; Research; Resources; Serum; System; Techniques; Time; Transplant Recipients; Transplantation; Uncertainty; United States; Waiting Lists; Weight; base; clinical decision-making; cost; improved; improved outcome; indexing; individual patient; neglect; programs; statistics; survival outcome; time use

 DESCRIPTION (provided by applicant): Promoting Utilization of Kidneys by Improving Organ Acceptance Decision Making Only 15,652 of nearly 109,000 waitlisted patients for kidney transplant (KT) received one in 2014. More than six thousand died while waiting for a KT and more than two thousand became too sick to be transplanted. Patient survival, quality of life, and morbidity is significantly worse for those who remain on dialysis. The majority of kidneys that are transplanted are recovered from deceased donors. In 2014, while 12,664 kidneys were recovered for KT, 2,272 were discarded - most frequently due to being of marginal or low quality. Many of the discarded kidneys are believed to confer smaller survival gains than other procured kidneys. Previous studies show that the marginal kidneys offer survival benefits with respect to remaining on dialysis, but neglect quantification of these benefits to an individual patient. These studies ignore two major issues: (i) the low c-statistics of one and three year post-transplant patient and graft survival models; and (ii) dynamics of the organ offers and the current point based priority system for the waitlisted patients. Given these facts, from a decision maker's perspective, accepting or rejecting a low quality organ is not necessarily a well informed choice. The proposed research takes a comprehensive approach in developing a survival model incorporating time on dialysis, recipient characteristics, transplant center characteristics, and donated kidney characteristics. It proposes to apply techniques from biostatistics and machine learning to improve model accuracy. The research further aims to quantify the dynamics of kidney availability of different quality organs, and model future kidney offers as a stochastic decision tree. The proposed computational engine for estimating the survival benefits of accepting or rejecting an offer will be transformative in clinical decision making. Moreover, th successful completion of the proposed research will provide a highly reliable approach to support kidney acceptance/rejection decisions. The research will be carried out by a trans- disciplinary team with expert knowledge in the transplant allocation system, decision methodologies, and clinical decision making. The research team will incorporate input from an external advisory board consisting of leaders and key stakeholders in kidney and pancreas transplant programs.