Time dependent predictors of cardiac inflammatory adverse events in cancer patients receiving immune checkpoint inhibitors
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View abstract on PubMed
Summary
This summary is machine-generated.Predicting cardio-inflammatory immune-related adverse events (irAEs) from immune checkpoint inhibitor (ICI) therapy is crucial. Distinct risk factors identify patients at risk for early or late-onset irAEs, improving monitoring.
Area Of Science
- Cardio-oncology
- Immunology
- Pharmacovigilance
Background
- Cardio-inflammatory immune-related adverse events (irAEs) associated with immune checkpoint inhibitor (ICI) therapy can worsen patient outcomes.
- Understanding predictive factors for these irAEs, using a time-dependent approach, is vital for identifying at-risk individuals.
Purpose Of The Study
- To identify patient data elements that predict early and late-onset cardio-inflammatory irAEs.
- Employ various predictive modeling strategies to analyze risk factors for distinct irAE onset times.
Main Methods
- Utilized TriNetX platform data from January 1, 2010, to May 1, 2022, for patients on ICI therapy.
- Collected data on irAE occurrence, survival, demographics, ICI types, comorbidities, and medication history.
- Applied predictive and statistical modeling to pinpoint unique risk factors for early and late irAEs.
Main Results
- Analyzed 66,068 patients; 0.30% experienced early and 0.26% experienced late cardio-inflammatory irAEs.
- Early irAE predictors: anti-PD-1 therapy, combination ICI therapy, and peripheral vascular disease history.
- Late irAE predictors: myocarditis/pericarditis history, cerebrovascular disease, and NSAID use history.
Conclusions
- Cardio-inflammatory irAEs can be categorized as early or late based on ICI therapy initiation time.
- Recognizing distinct risk factors for early and late events can enhance patient monitoring and risk stratification.
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