Developing cystic fibrosis lung transplant referral criteria using predictors of 2-year mortality
Developing cystic fibrosis lung transplant referral criteria using predictors of 2-year mortality
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DOI：
10.1164/rccm.200202-087oc
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发表时间：
2002-12-15
影响因子：
24.7
通讯作者：
Aitken, ML
中科院分区：
文献类型：
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作者：
Mayer-Hamblett, N;Rosenfeld, M;Aitken, ML
我们研究的第一个目标是建立一个模型，确定囊性纤维化(CF)患者两年死亡率的最佳临床预测因素，以帮助选择合适的肺移植候选人。使用多变量Logistic回归分析，我们发现年龄、身高、FEV1、呼吸道微生物学、因肺部恶化而住院的次数和家庭静脉注射抗生素疗程的次数都是1996年囊性纤维化基金会国家患者登记中6岁或以上的14,572名患者2年内死亡率的重要预测因素。第二个目标是比较我们的模型用于指导肺移植转诊时的诊断准确性，以及广泛使用的FEV1预测低于30%的标准的诊断准确性。令人惊讶的是，这个从现有的关于CF患者的最大数据收集中得出的非常合适的模型并没有提供比更简单的FEV1标准更好的诊断准确性。两者都有很高的阴性预测值(分别为98%和97%)，但只有中等的阳性预测值(分别为33%和28%)。无论是基于多变量Logistic模型的移植转诊决策，还是基于FEV1预测低于30%的标准，都可能导致较高的过早转诊。CIF患者的短期死亡率需要更好的临床预测指标。
The first objective of our study was to develop a model identifying the best clinical predictors of 2-year mortality among patients with cystic fibrosis (CF), to assist in selection of appropriate candidates for lung transplantation. Using multivariate logistic regression, we found that age, height, FEV1, respiratory microbiology, number of hospitalizations for pulmonary exacerbations, and number of home intravenous antibiotic courses were all significant predictors of 2-year mortality among 14,572 patients in the Cystic Fibrosis Foundation National Patient Registry who were 6 years of age or older in 1996. The second objective was to compare the diagnostic accuracy of our model when used to guide referral for lung transplant with that of the widely used criterion of an FEV1 of less than 30% predicted. Surprisingly, this well-fitting model derived from the largest collection of data available on patients with CF provided no better diagnostic accuracy than the simpler FEV1 criterion. Both had high negative predictive values (98 and 97%, respectively) but only modest positive predictive values (33 and 28%, respectively). Transplant referral decisions based either on a multivariate logistic model or on the criterion of an FEV1 of less than 30% predicted are likely to result in high rates of premature referral. Better clinical predictors of short-term mortality among patients with CIF are needed.