Geographic Variation in Non-HCC MELD Exceptions and Its Effect on Liver Transplant Waitlist Outcomes

非 HCC MELD 例外的地理差异及其对肝移植等候名单结果的影响

• 批准号: 10598104
• 负责人: Robert M. Cannon
• 金额: $ 16.13万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10598104
• 关键词: Accounting; Address; Area; Award; Communities; Country; County; Cox Proportional Hazards Models; Data; Diagnosis; Disparity; Distant; Equity; Face; Fostering; Funding; Geographic Locations; Geography; Goals; Growth; Health; Health Service Area; Knowledge; Laboratories; Literature; Liver; Location; Mentors; Methods; Modeling; Outcome; Paint; Patients; Play; Policies; Population; Predictive Factor; Prevalence; Regional Disease; Regression Analysis; Research; Research Personnel; Rest; Risk; Risk Estimate; Role; Running; Rural Appalachia; Scientist; Side; Standardization; Surgeon; System; Techniques; Testing; Training; Transplantation; Variant; Waiting Lists; advanced simulation; analytical method; career; differences in access; disparity reduction; end stage liver disease; geographic difference; geographic disparity; health care availability; high risk; liver transplantation; mortality; mortality risk; novel; personalized approach; role model; simulation; social health determinants

Summary: Geographic variation in model for end stage liver disease (MELD) scores at transplant across donation service areas has fueled a major policy debate over allocation of donor livers. An important caveat to this perceived disparity is the focus on allocation MELD, in which patients with lower calculated MELD scores may be assigned a higher score if their calculated MELD is thought to underestimate the risk of waitlist mortality. Analysis of calculated MELD at transplant demonstrates much less variation between regions. Some high allocation MELD regions actually have low calculated MELD scores relative to the rest of the country. The different pictures painted by allocation versus calculated MELD scores highlight the critical role MELD exception points play in geographic differences in access to transplantation. A national liver review board was recently implemented to impose national standardization of MELD exception scores in an effort to mitigate geographic disparity. A potential flaw in this strategy is the assumption that the risk of mortality associated with a given MELD score or exception diagnosis is the same across geographic areas. We know that social determinants of health and access to care vary widely across the country, however, and that these differences have a significant impact on health outcomes. Imposing a geographically uniform MELD exception scoring policy that does not account for these important differences may have the unintended effect of overestimating the risk of waitlist mortality for exception patients in some regions while underestimating that risk in others, thus worsening geographic disparity rather than mitigating it. I hypothesize that significant geographic variation exists in the prevalence and appropriateness of MELD exceptions scores at the county level, and that appropriate adjustment to MELD exception scores based on a candidate’s location will mitigate geographic disparity in liver transplant waitlist mortality. Despite abundant literature on geographic disparity in liver transplantation, few studies actually apply formal geospatial analysis to geographically based questions facing the field. I propose to utilize such techniques to accomplish the following unique aims: (1) determine the prevalence and appropriateness of MELD exceptions on a county level and diagnose the presence of geographic clusters where these exceptions provide an inappropriate advantage to transplant candidates with MELD exception scores; (2) determine adjusted MELD exception scores which would equalize waitlist mortality risk between exception and non-exception patients in each geographic area; and (3) simulate waitlist outcomes under an alternative allocation scenario where MELD exception points are assigned according to geographic region as determined in Aim 2. This study will provide a more granular and personalized approach to the estimation of waitlist mortality. The mentoring and training afforded by this award will foster my growth as an investigator by allowing me to focus on building an expertise in geospatial analysis and advanced simulation, advancing my long-term career goal of research independence as a surgeon-scientist with R01 funding.

摘要：终末期肝病（MELD）模型在移植时评分的地理差异