Demographic Variations in Immune Checkpoint Inhibitor Adverse Events: A Real-World Study
Bibliographic record
Abstract
Background: Immune checkpoint inhibitors (ICIs) have caused a paradigm shift in cancer therapy, but the resultant immune activation also precipitates autoimmune toxicities termed immune-related adverse events (irAEs). However, system-specific analyses of irAEs remain limited, particularly their variation with body mass index (BMI), race, sex, age, and type of ICI. Methods: A retrospective analysis was conducted on 244 patients who developed irAEs after receiving ICI. Among the study population, 58% were female; the racial and ethnic distribution was 84% White, 13% Hispanic, 2% African American, and 1% Asian; and the age breakdown was 23% under 65 years, 38% between 65 and 79 years, and 39% over 80 years. Univariate analysis was performed employing the Chi-square test. Multivariable logistic regression and cluster analyses revealed distinct irAE predictors. Results: Univariate analysis (Chi-square) showed significant associations between BMI and pneumonitis (P = 0.02) and between race and hepatitis (P = 0.04), but these did not persist in multivariate regression. No significant correlations were found between thyroiditis or colitis and sex, race, BMI, age, or immunotherapy type. Increasing age was protective against neutropenia, with significantly lower risk in patients aged 65 - 79 (odds ratio (OR) 0.38, P = 0.007) and ≥ 80 years (OR 0.18, P < 0.001); African Americans were at higher risk (OR 10.29, P = 0.02), and male sex was protective (OR 0.51, P = 0.03). Anemia was less frequent in those ≥ 80 years (OR 0.48, P = 0.03) and Hispanics (OR 0.4, P = 0.03). Thrombocytopenia risk was reduced in patients aged 65 - 79 (OR 0.41, P = 0.03) and ≥ 80 (OR 0.36, P < 0.001). Cluster analysis showed higher irAE rates in patients treated with nivolumab (alone or with ipilimumab) compared to pembrolizumab. Conclusion: Advanced age showed a protective effect on cytopenias. Hispanics had reduced anemia and dermatitis risk; African Americans and females had higher neutropenia, and obesity was linked to dermatitis. These findings may aid clinicians in personalizing ICI counseling and recognizing at-risk groups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".