Relative lymphocyte percentage as a predictive biomarker for immune checkpoint inhibitor in metastatic melanoma: A real-world analysis.

F Furkan Bahar (Dana-Farber Cancer Institute, Boston, MA) Y Yu Chang (State Key Laboratory of Structural Chemistry, Fujian Provincial Key Laboratory of Materials and Techniques toward Hydrogen Energy, Fujian Institute of Research on the Structure of Matter) C Cho Han Chiang (Harvard Medical School, Cambridge, Massachusetts, United States) B Betul Ibis (Mount Auburn Hospital, Harvard Medical School, Cambridge, MA) X Xiaocao Xu (UMass Chan Medical School, Worcester, MA) S Shuwen Lin (Montefiore Einstein Comprehensive Cancer Center/Albert Einstein College of Medicine, Bronx, NY) K Karam Khaddour (Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA)

Abstract

e21549 Background: Response variability to immune checkpoint inhibitors (ICIs) necessitates the identification of predictive biomarkers. Relative lymphocyte percentage (RLP), an easily measurable marker, has shown prognostic potential in small studies. This study validates RLP predictive value using a large real-world database, assessing the impact of high vs. low RLP on survival in ICI-treated patients. Methods: We conducted a retrospective cohort study using the TriNetX Analytics Network, a HIPAA-compliant database of de-identified electronic health records. Adult patients (≥18 years) with metastatic melanoma who received ICIs between 2015–2023 were included. RLP (lymphocytes per 100 leukocytes) was measured within one month before or after ICI initiation, with patients stratified into high (> 20.5) and low (< 20.5) RLP cohorts, with 20.5 chosen as it represents the mean RLP of the entire cohort. Exclusion criteria included prior leukemia/lymphoma and leukocyte counts > 20,000/μL. The primary outcome was overall survival (OS). Propensity score matching (1:1) controlled for age, sex, comorbidities, tumor burden, absolute leukocyte count (ALC), and absolute lymphocyte count (ALN). Survival was analyzed using Kaplan-Meier curves and Cox proportional hazards models. Results: After matching, 3,976 patients per cohort were analyzed. The high RLP group (mean age 63.6 ± 14.1, 36% female) had significantly improved survival, with two-year OS of 74.3% vs. 69.3% in the low RLP group (HR 0.81, 95% CI: 0.74–0.88, p < 0.001), indicating a 19.3% reduction in mortality risk. In a secondary analysis, 1,533 patients per cohort were stratified using more extreme RLP thresholds (> 30.5 and < 10.5, ±1 SD from the mean). The high RLP group (mean age 62.0 ± 14.1, 40% female) demonstrated two-year OS of 77.8% vs. 61.1% in the low RLP group (HR 0.50, 95% CI: 0.44–0.57, p < 0.001), reflecting a 50.1% reduction in mortality risk (Table). Conclusions: Higher RLP was significantly associated with improved OS in metastatic melanoma patients receiving ICIs, with a stronger association observed at higher thresholds. Given its accessibility, RLP may serve as a valuable biomarker for stratifying patients and guiding treatment decisions. Further prospective studies are warranted to confirm these findings and explore underlying mechanisms. Summary of the primary and secondary analysis. Analysis Cohort Number of Patients 2-Year Survival Probability (%) Hazard Ratio (95% CI) p-value Primary Analysis High RLP (>20.5) 3,976 74.30% 0.81 (0.74–0.88) <0.001 Low RLP (<20.5) 3,976 69.30% Secondary Analysis High RLP (>30.5) 1,533 77.80% 0.50 (0.44–0.57) <0.001 Low RLP (<10.5) 1,533 61.10%

Article Details

Volume / Issue Vol. 43, Issue 16_suppl
Published June 01, 2025
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (7)

F

Furkan Bahar

Dana-Farber Cancer Institute, Boston, MA

Y

Yu Chang

State Key Laboratory of Structural Chemistry, Fujian Provincial Key Laboratory of Materials and Techniques toward Hydrogen Energy, Fujian Institute of Research on the Structure of Matter

C

Cho Han Chiang

Harvard Medical School, Cambridge, Massachusetts, United States

B

Betul Ibis

Mount Auburn Hospital, Harvard Medical School, Cambridge, MA

X

Xiaocao Xu

UMass Chan Medical School, Worcester, MA

S

Shuwen Lin

Montefiore Einstein Comprehensive Cancer Center/Albert Einstein College of Medicine, Bronx, NY

K

Karam Khaddour

Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA