基于医院的前列腺癌筛查在有下尿路症状的越南男性中的应用：分类回归树模型。
Hospital-based prostate cancer screening in vietnamese men with lower urinary tract symptoms: a classification and regression tree model.
机构信息
Ho Chi Minh City MEDIC Medical Center, Ho Chi Minh City, Vietnam.
Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam.
出版信息
BMC Urol. 2022 Oct 29;22(1):166. doi: 10.1186/s12894-022-01116-2.
BACKGROUND
Prostate cancer (PCa) is a common disease in men over 65 years of age, and should be detected early, while reducing unnecessary biopsies. This study aims to construct a classification and regression tree (CART) model (i.e., risk stratification algorithm) using multivariable approach to select Vietnamese men with lower urinary tract symptoms (LUTS) for PCa biopsy.
METHODS
We conducted a case-control study on 260 men aged ≥ 50 years who visited MEDIC Medical Center, Vietnam in 2017-2018 with self-reported LUTS. The case group included patients with a positive biopsy and the control group included patients with a negative biopsy diagnosis of PCa. Bayesian Model Averaging (BMA) was used for selecting the most parsimonious prediction model. Then the CART with 5-fold cross-validation was constructed for selecting men who can benefit from PCa biopsy in steps by steps and intuitive way.
RESULTS
BMA suggested five potential prediction models, in which the most parsimonious model including PSA, I-PSS, and age. CART advised the following cut-off points in the marked screening sequence: 18 < PSA < 33.5 ng/mL, I-PSS ≥ 19, and age ≥ 71. Patients with PSA ≥ 33.5 ng/mL have a PCa risk was 91.2%; patients with PSA < 18 ng/mL and I-PSS < 19 have a PCa risk was 7.1%. Patient with 18 ≤ PSA < 33.5ng/mL and I-PSS < 19 have a PCa risk is 70% if age ≥ 71; and is 16% if age < 71. In overall, CART reached high predictive value with AUC = 0.915. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CART at the 20% diagnosis probability threshold were 91.5%, 86.2%, 86.9%, 91.2%, and 88.9% respectively; at 80% diagnosis probability threshold were 79.2%, 92.3%, 91.2%, 81.6%, and 85.8% respectively.
CONCLUSION
CART combining PSA, I-PSS, and age has practical use in hospital-based PCa screening in Vietnamese men with lower urinary tract symptoms.
背景
前列腺癌（PCa）是 65 岁以上男性的常见病，应及早发现，同时减少不必要的活检。本研究旨在使用多变量方法构建分类回归树（CART）模型（即风险分层算法），以选择有下尿路症状（LUTS）的越南男性进行 PCa 活检。
方法
我们对 2017-2018 年在越南 MEDIC 医疗中心就诊的 260 名年龄≥50 岁的自报有 LUTS 的男性进行了病例对照研究。病例组包括活检阳性患者，对照组包括活检诊断为 PCa 阴性的患者。采用贝叶斯模型平均（BMA）法选择最简约的预测模型。然后，通过 5 折交叉验证构建 CART，逐步、直观地选择可从 PCa 活检中获益的男性。
结果
BMA 提出了五个潜在的预测模型，其中最简约的模型包括 PSA、I-PSS 和年龄。CART 建议了以下标记筛选序列中的截断点：18<PSA<33.5ng/ml、I-PSS≥19 和年龄≥71。PSA≥33.5ng/ml 的患者 PCa 风险为 91.2%；PSA<18ng/ml 和 I-PSS<19 的患者 PCa 风险为 7.1%。PSA 在 18≤PSA<33.5ng/ml 和 I-PSS<19 的患者，如果年龄≥71，其 PCa 风险为 70%；如果年龄<71，其 PCa 风险为 16%。总体而言，CART 的 AUC 值为 0.915，具有较高的预测价值。CART 在 20%诊断概率阈值下的灵敏度、特异性、阳性预测值、阴性预测值和准确度分别为 91.5%、86.2%、86.9%、91.2%和 88.9%；在 80%诊断概率阈值下分别为 79.2%、92.3%、91.2%、81.6%和 85.8%。
结论
CART 结合 PSA、I-PSS 和年龄，在越南有下尿路症状的男性中具有实用的医院 PCa 筛查价值。
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