Keele Cardiovascular Research Group, Centre for Prognosis Research, Keele University, Keele Rd, Stoke-on-Trent ST5 5BG, UK.
Department of Biomedical and Dental Sciences and Morphological and Functional Imaging, University of Messina, Messina 98100, Italy.
Eur Heart J. 2024 Sep 7;45(34):3138-3148. doi: 10.1093/eurheartj/ehae463.
This study assessed the impact of incorporating cancer as a predictor on performance of the PRECISE-DAPT score.
A nationally linked cohort of ST-elevation myocardial infarction patients between 1 January 2005 and 31 March 2019 was derived from the UK Myocardial Ischaemia National Audit Project and the UK Hospital Episode Statistics Admitted Patient Care registries. The primary outcome was major bleeding at 1 year. A new modified score was generated by adding cancer as a binary variable to the PRECISE-DAPT score using a Cox regression model and compared its performance to the original PRECISE-DAPT score.
A total of 216 709 ST-elevation myocardial infarction patients were included, of which 4569 had cancer. The original score showed moderate accuracy (C-statistic .60), and the modified score showed modestly higher discrimination (C-statistics .64; hazard ratio 1.03, 95% confidence interval 1.03-1.04) even in patients without cancer (C-statistics .63; hazard ratio 1.03, 95% confidence interval 1.03-1.04). The net reclassification index was .07. The bleeding rates of the modified score risk categories (high, moderate, low, and very low bleeding risk) were 6.3%, 3.8%, 2.9%, and 2.2%, respectively. According to the original score, 65.5% of cancer patients were classified as high bleeding risk (HBR) and 21.6% were low or very low bleeding risk. According to the modified score, 94.0% of cancer patients were HBR, 6.0% were moderate bleeding risk, and no cancer patient was classified as low or very low bleeding risk.
Adding cancer to the PRECISE-DAPT score identifies the majority of patients with cancer as HBR and can improve its discrimination ability without undermining its performance in patients without cancer.
本研究评估了将癌症作为预测因子纳入 PRECISE-DAPT 评分对其表现的影响。
从英国心肌梗死国家审计项目和英国医院发病统计接受患者护理登记处获得了 2005 年 1 月 1 日至 2019 年 3 月 31 日期间的 ST 段抬高型心肌梗死患者的全国性链接队列。主要结局为 1 年时的大出血。使用 Cox 回归模型将癌症作为二分类变量添加到 PRECISE-DAPT 评分中，生成新的改良评分，并将其与原始 PRECISE-DAPT 评分的性能进行比较。
共纳入 216709 例 ST 段抬高型心肌梗死患者，其中 4569 例患有癌症。原始评分显示出中等准确性（C 统计量.60），改良评分显示出适度较高的区分度（C 统计量.64；危险比 1.03，95%置信区间 1.03-1.04），即使在无癌症患者中也是如此（C 统计量.63；危险比 1.03，95%置信区间 1.03-1.04）。净重新分类指数为.07。改良评分风险类别（高、中、低和极低出血风险）的出血率分别为 6.3%、3.8%、2.9%和 2.2%。根据原始评分，65.5%的癌症患者被归类为高出血风险（HBR），21.6%为低或极低出血风险。根据改良评分，94.0%的癌症患者为 HBR，6.0%为中度出血风险，没有癌症患者被归类为低或极低出血风险。
将癌症纳入 PRECISE-DAPT 评分可确定大多数患有癌症的患者为 HBR，并可在不降低无癌症患者性能的情况下提高其区分能力。
