Background

This study uses machine learning techniques to identify sociodemographic and clinical predictors of progression through the hepatitis C (HCV) cascade of care for patients in the 1945–1965 birth cohort in the Southern United States.

Methods

We compared sociodemographic and clinical variables between groups of patients for three care outcomes: linkage to care, initiation of antiviral treatment, and virologic cure. A decision tree model and random forest model were built for each outcome.

Results

Patients were primarily male, African American/Black or Caucasian/White, non-Hispanic or Latino, and insured. The average age at first HCV screening was 60 years old, and common medical diagnoses included chronic kidney disease, fibrosis and/or cirrhosis, transplanted liver, diabetes mellitus, and liver cell carcinoma. Variables used in predicting linkage to care included age at first HCV screening, insurance at first HCV screening, race, fibrosis and/or cirrhosis, other liver disease, ascites, and transplanted liver. Variables used in predicting initiation of antiviral treatment included insurance at first HCV screening, gender, other liver cancer, steatosis, and liver cell carcinoma. Variables used in predicting virologic cure included insurance at first HCV screening, transplanted liver, and ethnicity.

Conclusion

These patients have a high hepatic health burden, likely reflecting complications of untreated HCV and highlighting the urgency to cure HCV in this birth cohort. We found differences in HCV care outcomes based on sociodemographic and clinical variables. More work is needed to understand the mechanisms of these differences in care outcomes and to improve HCV care.

中文翻译：

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使用决策树和随机森林，通过级联护理到丙型肝炎患者治愈的发展过程的预测指标

背景

这项研究使用机器学习技术来确定1945年至1965年美国南部出生人群通过丙型肝炎（HCV）护理服务的社会人口统计学和临床​​预测指标。

方法

我们比较了两组患者在三种护理结局方面的社会人口统计学和临床​​变量：与护理的联系，抗病毒治疗的开始以及病毒学的治愈。为每个结果建立决策树模型和随机森林模型。

结果

患者主要是男性，非裔美国人/黑人或白人/白人，非西班牙裔或拉丁裔并已投保。初次HCV筛查的平均年龄为60岁，常见医学诊断包括慢性肾脏疾病，纤维化和/或肝硬化，肝移植，糖尿病和肝细胞癌。用于预测护理联系的变量包括初次HCV筛查的年龄，初次HCV筛查的保险，种族，纤维化和/或肝硬化，其他肝病，腹水和肝移植。预测开始抗病毒治疗的变量包括首次HCV筛查时的保险，性别，其他肝癌，脂肪变性和肝细胞癌。用于预测病毒学治愈的变量包括首次HCV筛查时的保险，肝移植和种族。

结论

这些患者的肝脏健康负担很高，很可能反映了未经治疗的HCV的并发症，并突出了这一出生队列中治愈HCV的紧迫性。我们根据社会人口统计学和临床​​变量发现了HCV护理结局的差异。需要更多的工作来了解这些护理结果差异的机制并改善HCV护理。