Cardiovascular immunotoxicities associated with immune checkpoint inhibitors: a safety meta-analysis
Abstract
AIMS
The risk and incidence of cardiovascular (CV) immune-related adverse events (irAEs) associated with immune checkpoint inhibitors (ICIs) in cancer patients remain unknown.
METHODS AND RESULTS
We systematically reviewed all randomized clinical trials (RCTs) including at least one ICI-containing arm and available CV adverse event (CVAE) data in cancer patients in the ClinicalTrials.gov registry, Medline, and the Cochrane CENTRAL Register of Controlled Trials, up to 31 August 2020 (CRD42020165672). The primary outcome was the summary risk of 16 different CVAEs associated with ICI exposure vs. controls (placebo and non-placebo) in RCTs. CVAEs with an increased risk associated with ICI exposure were considered as CV irAEs. Summary incidences of CV irAEs identified in our primary outcome analyses were computed using all RCTs including at least one ICI-containing arm. We used a random-effects meta-analysis to obtain Peto odds ratios (ORs) with 95% confidence intervals (CIs) and logit transformation and inverse variance weighting to compute summary incidences. Sixty-three unique RCTs with at least one ICI-containing arm (32 518 patients) were retrieved, among which 48 (29 592 patients) had a control arm. Among the 16 CVAEs studied, ICI use was associated with an increased risk of 6 CV irAEs including myocarditis, pericardial diseases, heart failure, dyslipidemia, myocardial infarction, and cerebral arterial ischaemia with higher risks for myocarditis (Peto OR: 4.42, 95% CI:…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 1,000 participants or records.
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.