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Predicting the risk of bleeding during dual antiplatelet therapy after acute coronary syndromes
Joakim Alfredsson1,2, Benjamin Neely1, Megan L Neely1
1Duke Clinical Research Institute, Durham, USA.
Insights
Predicting bleeding risk in acute coronary syndrome (ACS) patients on dual antiplatelet therapy (DAPT) is now possible. New models identify key baseline factors to guide DAPT duration and optimize patient care.
Area of Science:
- Cardiology
- Clinical Trials
- Predictive Modeling
Background:
- Dual antiplatelet therapy (DAPT) is standard for acute coronary syndrome (ACS) patients.
- Current guidelines recommend 12 months of DAPT, with shorter durations for high bleeding risk.
- No tools exist to predict individual bleeding risk during DAPT post-ACS.
Purpose of the Study:
- Develop a longitudinal bleeding risk prediction model for DAPT in ACS patients.
- Identify key baseline predictors of bleeding events.
- Inform risk-benefit decisions regarding DAPT duration.
Main Methods:
- Analysis of 9240 ACS patients from the TRILOGY ACS trial.
- Patients managed without revascularization and treated with DAPT.
- Development and validation of bleeding risk prediction models (GUSTO and TIMI).
Main Results:
- Identified 10 significant predictors for GUSTO severe/life-threatening/moderate bleeding.
- Identified 5 significant predictors for TIMI major/minor bleeding.
- Models demonstrated good predictive accuracy (GUSTO C-index=0.78, TIMI C-index=0.67), with good internal and external validation.
Conclusions:
- Longitudinal bleeding risk during DAPT in ACS patients is reliably predictable.
- Baseline characteristics effectively predict bleeding events.
- TRILOGY ACS bleeding models aid DAPT duration decisions post-ACS.
Objectives:
Dual antiplatelet therapy (DAPT) with aspirin + a P2Y12 inhibitor is recommended for at least 12 months for patients with acute coronary syndrome (ACS), with shorter durations considered for patients with increased bleeding risk. However, there are no decision support tools available to predict an individual patient's bleeding risk during DAPT treatment in the post-ACS setting.
Methods:
To develop a longitudinal bleeding risk prediction model, we analy sed 9240 patients with unstable angina/non-ST segment elevation myocardial infarction (NSTEMI) from the Targeted Platelet Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes (TRILOGY ACS) trial, who were managed without revasculari sation and treated with DAPT for a median of 14.8 months.
Results:
We identified 10 significant baseline predictors of non-coronary artery bypass grafting (CABG)-related Global Use of Strategies to Open Occluded Arteries (GUSTO) severe/life-threatening/moderate bleeding: age, sex, weight, NSTEMI (vs unstable angina), angiography performed before randomi sation, prior peptic ulcer disease, creatinine, systolic blood pressure, haemoglobin and treatment with beta-blocker. The five significant baseline predictors of Thrombolysis In Myocardial Infarction (TIMI) major or minor bleeding included age, sex, angiography performed before randomi sation, creatinine and haemoglobin. The models showed good predictive accuracy with Therneau's C-indices: 0.78 (SE = 0.024) for the GUSTO model and 0.67 (SE = 0.023) for the TIMI model. Internal validation with bootstrapping gave similar C-indices of 0.77 and 0.65, respectively. External validation demonstrated an attenuated C-index for the GUSTO model (0.69) but not the TIMI model (0.68).
Conclusions:
Longitudinal bleeding risks during treatment with DAPT in patients with ACS can be reliably predicted using selected baseline characteristics. The TRILOGY ACS bleeding models can inform risk -benefit considerations regarding the duration of DAPT following ACS.
Trial Registration:
ClinicalTrials.gov identifier: https://clinicaltrials.gov/ct2/show/NCT00699998.