Prognostic Potential of Baseline Eosinophils at the Initiation of Immune Checkpoint Inhibitor Treatment of Metastatic Melanoma: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Cutaneous melanoma (CM) remains a rapidly rising malignancy, with metastatic disease still carrying a limited 5‐year survival. Immune checkpoint inhibitors (ICIs) have changed the treatment landscape, yet only a fraction of patients achieves durable benefit. Easily obtainable blood‐based biomarkers are, therefore, needed to guide patient selection and prognostication. Eosinophilic granulocytes have emerged as potential modulators of antitumor immunity. In this systematic review and meta‐analysis, we adhered to PRISMA guidelines and searched PubMed, Cochrane Library, and Scopus for studies published from 2011 onward that evaluated baseline peripheral eosinophil counts (absolute or percentage) as predictors of overall survival (OS) in advanced (stage III/IV) melanoma patients treated with ICI. Six cohort studies totaling 4.243 patients met inclusion criteria, each reporting hazard ratios (HRs) and 95% confidence intervals (CIs) in multivariable analyses for high versus low baseline eosinophil groups. Study quality was high (Newcastle–Ottawa Scale ≥ 7 stars), though selection biases were noted across all cohorts. A random‐effects meta‐analysis (DerSimonian–Laird method) initially yielded a pooled HR of 0.69 (95% CI: 0.36–1.30) for high versus low eosinophil counts, but heterogeneity was substantial ( I 2 = 77.8%, p < 0.001). Through Baujat and leave‐one‐out diagnostics, one study was identified as an influential outlier; its exclusion reduced heterogeneity down to 33.3% ( p = 0.20). Reanalysis of the remaining five studies ( n = 4.158) demonstrated a significant survival advantage for patients with elevated baseline eosinophils (HR: 0.51 and 95% CI: 0.39–0.66; p < 0.001). Funnel plot symmetry and a nonsignificant Egger’s test ( p = 0.27) indicated no evidence of publication bias. These findings support baseline peripheral eosinophil count as a cost‐effective, readily available biomarker associated with improved OS under ICI therapy in advanced melanoma. However, prospective studies with standardized eosinophil thresholds, comprehensive covariate adjustment, and integrated mechanistic analyses are warranted to validate and operationalize this marker for patient stratification in clinical practice.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.037 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".