Transplantation · 2019
Evaluation of Accepting Kidneys of Varying Quality for Transplantation or Expedited Placement With Decision Trees.
Оценочное исследованиеСтатьяПоддержка NIH: внешняя программаПоддержка службы здравоохранения СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Kilambi Vikram, Bui Kevin, Hazen Gordon B, Friedewald John J, Ladner Daniela P, Kaplan Bruce, Mehrotra Sanjay
Аннотация
BACKGROUND: Underutilization of marginal-quality kidneys for transplantation produced ideas of expediting kidney placement for populations with decreased opportunities of receiving transplants. Such policies can be less efficacious for specific individuals and should be scrutinized until the decision-making for accepting marginal-quality organs, which has relied on experiential judgment, is better understood at the individual level. There exist rigorous tools promoting personalized decisions with useful and objective information.
METHODS: This article introduces a decision-tree methodology that analyzes a patient's dilemma: to accept a kidney offer now or reject it. The methodology calculates the survival benefit of accepting a kidney given a certain quality now and the survival benefit of rejecting it. Survival benefit calculation accounts for patients' and donors' characteristics and transplant centers' and organ procurement organizations' performances and incorporates patients' perceived transplant and dialysis utilities. Valuations of rejecting an offer are contingent on future opportunities and subject to uncertainty in the timing of successive kidney offers and their quality and donor characteristics.
RESULTS: The decision tree was applied to a realistic patient profile as a demonstration. The tool was tested on 1000 deceased-donor kidney offers in 2016. Evaluating up to 1 year of future offers, the tool attains 61% accuracy, with transplant utility of 1.0 and dialysis utility of 0.5. The accuracy reveals potential bias in kidney offer acceptance/rejection at transplant centers.
CONCLUSIONS: The decision-tree tool presented could aid personalized transplant decision-making in the future by providing patients with calculated, individualized survival benefits between accepting and rejecting a kidney offer.
METHODS: This article introduces a decision-tree methodology that analyzes a patient's dilemma: to accept a kidney offer now or reject it. The methodology calculates the survival benefit of accepting a kidney given a certain quality now and the survival benefit of rejecting it. Survival benefit calculation accounts for patients' and donors' characteristics and transplant centers' and organ procurement organizations' performances and incorporates patients' perceived transplant and dialysis utilities. Valuations of rejecting an offer are contingent on future opportunities and subject to uncertainty in the timing of successive kidney offers and their quality and donor characteristics.
RESULTS: The decision tree was applied to a realistic patient profile as a demonstration. The tool was tested on 1000 deceased-donor kidney offers in 2016. Evaluating up to 1 year of future offers, the tool attains 61% accuracy, with transplant utility of 1.0 and dialysis utility of 0.5. The accuracy reveals potential bias in kidney offer acceptance/rejection at transplant centers.
CONCLUSIONS: The decision-tree tool presented could aid personalized transplant decision-making in the future by providing patients with calculated, individualized survival benefits between accepting and rejecting a kidney offer.