Development and Performance of an Algorithm to Estimate the Child-Turcotte-Pugh Score From a National Electronic Healthcare Database.
Development and Performance of an Algorithm to Estimate the Child-Turcotte-Pugh Score From a National Electronic Healthcare Database.
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DOI：
10.1016/j.cgh.2015.07.010
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
VOCAL Study Group
中科院分区：
文献类型：
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作者：
Kaplan DE;Dai F;Aytaman A;Baytarian M;Fox R;Hunt K;Knott A;Pedrosa M;Pocha C;Mehta R;Duggal M;Skanderson M;Valderrama A;Taddei TH;VOCAL Study Group
Child-Turcotte-Pugh(CTP)评分是肝硬变患者长期存活的广泛应用和有效的预测指标。CTP评分由5个子评分组成，其中3个基于客观临床化验值，2个主观变量量化腹水和肝性脑病的严重程度。到目前为止，还没有从行政数据库中量化CTP分数的系统得到验证。退伍军人结果和与肝病相关的成本研究是一项多中心合作研究，旨在评估美国退伍军人健康管理局的肝细胞癌的结果和成本。我们开发并验证了一种算法，通过使用退伍军人健康管理公司数据仓库的数据来计算电子CTP(ECTP)分数。设计了多种算法来确定国际疾病分类第9版、通用程序术语、药学和实验室数据中的每个CTP亚分，并在2名患者队列中进行了测试。对于每个队列，6个现场调查人员(波士顿、布朗克斯、布鲁克林、费城、明尼阿波利斯和西黑文退伍军人医学中心)获得病例，以确定腹水和脑病的诊断、实验室数据和临床评估的有效性。最优算法(指定为eCTP)随后被应用于2008年第一季度存活的30840名肝硬变患者，这些患者的5年总体和无移植生存数据可用。ECTP评分和其他疾病严重程度评分(Charlson-Deyo指数、退伍军人老龄化队列研究指数、终末期肝病模型评分和肝硬变合并症)预测生存的能力随后通过Cox比例风险回归进行评估。在肝细胞癌和肝硬变队列中，管理和研究人员验证的实验室数据的Spearman相关性分别为胆红素0.85和0.92，白蛋白0.92和0.87，国际标准化比率0.84和0.86。在肝细胞癌队列中，总的eCTP评分与96%的患者匹配，与图表验证的CTP评分在1分以内(Spearman相关性，0.81)。在肝硬变队列中，98%的患者与其实际CTP评分匹配在1分以内(Spearman，0.85)。当应用于30,840名肝硬变患者的队列时，eCTP的每单位变化与死亡或移植的相对风险增加39%相关。在预测5年无移植生存方面，eCTP的Harrell C统计量(0.678)在数值上高于其他疾病严重程度指数。将其他预测模型添加到eCTP中，其预测性能的差异很小。我们开发并验证了一种算法，可以从大型管理数据库中的数据推断出eCTP分数，该算法与图表审查中的实际CTP分数具有很好的相关性。当应用于管理数据库时，与其他多个已发表的肝病严重程度指数相比，该算法是一个非常有用的生存预测指标。
The Child-Turcotte-Pugh (CTP) score is a widely used and validated predictor of long-term survival in cirrhosis. The CTP score is a composite of 5 subscores, 3 based on objective clinical laboratory values and 2 subjective variables quantifying the severity of ascites and hepatic encephalopathy. To date, no system to quantify CTP score from administrative databases has been validated. The Veterans Outcomes and Costs Associated with Liver Disease study is a multicenter collaborative study to evaluate the outcomes and costs of hepatocellular carcinoma in the U.S. Veterans Health Administration. We developed and validated an algorithm to calculate electronic CTP (eCTP) scores by using data from the Veterans Health Administration Corporate Data Warehouse. Multiple algorithms for determining each CTP subscore from International Classification of Diseases version 9, Common Procedural Terminology, pharmacy, and laboratory data were devised and tested in 2 patient cohorts. For each cohort, 6 site investigators (Boston, Bronx, Brooklyn, Philadelphia, Minneapolis, and West Haven VA Medical Centers) were provided cases from which to determine validity of diagnosis, laboratory data, and clinical assessment of ascites and encephalopathy. The optimal algorithm (designated eCTP) was then applied to 30,840 cirrhotic patients alive in the first quarter of 2008 for whom 5-year overall and transplant-free survival data were available. The ability of the eCTP score and other disease severity scores (Charlson-Deyo index, Veterans Aging Cohort Study index, Model for End-Stage Liver Disease score, and Cirrhosis Comorbidity) to predict survival was then assessed by Cox proportional hazards regression. Spearman correlations for administrative and investigator validated laboratory data in the HCC and cirrhotic cohorts, respectively, were 0.85 and 0.92 for bilirubin, 0.92 and 0.87 for albumin, and 0.84 and 0.86 for international normalized ratio. In the HCC cohort, the overall eCTP score matched 96% of patients to within 1 point of the chart-validated CTP score (Spearman correlation, 0.81). In the cirrhosis cohort, 98% were matched to within 1 point of their actual CTP score (Spearman, 0.85). When applied to a cohort of 30,840 patients with cirrhosis, each unit change in eCTP was associated with 39% increase in the relative risk of death or transplantation. The Harrell C statistic for the eCTP (0.678) was numerically higher than those for other disease severity indices for predicting 5-year transplant-free survival. Adding other predictive models to the eCTP resulted in minimal differences in its predictive performance. We developed and validated an algorithm to extrapolate an eCTP score from data in a large administrative database with excellent correlation to actual CTP score on chart review. When applied to an administrative database, this algorithm is a highly useful predictor of survival when compared with multiple other published liver disease severity indices.