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Bleeding risk prediction after acute myocardial infarction-integrating cancer data: the updated PRECISE-DAPT cancer
Mohamed Dafaalla1, Francesco Costa2, Evangelos Kontopantelis3
1Keele Cardiovascular Research Group, Centre for Prognosis Research, Keele University, Keele Rd, Stoke-on-Trent ST5 5BG, UK.
Insights
Adding cancer to the PRECISE-DAPT score improves its accuracy in predicting major bleeding risk for ST-elevation myocardial infarction patients. The modified score better identifies cancer patients as high bleeding risk without compromising performance in those without cancer.
Area of Science:
- Cardiology
- Oncology
- Clinical Risk Prediction
Background:
- The PRECISE-DAPT score is used to predict bleeding risk in patients with ST-elevation myocardial infarction (STEMI).
- Cancer is a significant comorbidity that may influence bleeding risk in STEMI patients.
Purpose of the Study:
- To evaluate the impact of incorporating a cancer diagnosis as a predictor on the performance of the PRECISE-DAPT score.
- To assess if adding cancer improves the accuracy of bleeding risk stratification in STEMI patients.
Main Methods:
- A national cohort of STEMI patients (n=216,709) from UK registries (2005-2019) was analyzed.
- A modified PRECISE-DAPT score was created by adding cancer as a binary variable.
- The modified score's performance was compared to the original score using Cox regression and C-statistics.
Main Results:
- The modified score demonstrated modestly higher discrimination (C-statistic 0.64) compared to the original score (C-statistic 0.60).
- In cancer patients, the modified score reclassified 94.0% as high bleeding risk (HBR), versus 65.5% with the original score.
- The modified score maintained performance in patients without cancer (C-statistic 0.63).
Conclusions:
- Incorporating cancer into the PRECISE-DAPT score significantly improves bleeding risk prediction, particularly for cancer patients.
- The modified score effectively identifies the majority of cancer patients as HBR, enhancing clinical decision-making.
- The enhanced score maintains its predictive ability in non-cancer STEMI patients.
Background And Aims:
This study assessed the impact of incorporating cancer as a predictor on performance of the PRECISE-DAPT score.
Methods:
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.
Results:
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.
Conclusions:
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.
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