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    Dynamic Alteration of HALP Score as a Predictor in Patients with Receiving Immunotherapy for Advanced Non-Small Cell Lung Cancer
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025) Koçanoğlu, Abdulkadir; Karakaya, Serdar; Zeynelgil, Esra; Düzköprü, Yakup; Doğan, Özlem
    Background and Objectives: This study aimed to investigate the prognostic value of the hemoglobin–albumin–lymphocyte–platelet (HALP) score—a marker reflecting both inflammatory and nutritional status—in patients with metastatic non-small cell lung cancer (NSCLC) undergoing immunotherapy. We also sought to determine whether dynamic changes in the HALP score during treatment could predict therapeutic success and help distinguish between pseudoprogression and hyperprogression. Materials and Methods: A retrospective analysis was conducted on 160 patients diagnosed with metastatic NSCLC and treated with immunotherapy at the Ankara Atatürk Sanatorium Training and Research Hospital. Chemotherapy regimens, metastatic sites, baseline and third-month hemograms and biochemistry parameters, and survival data were recorded. Survival outcomes were analyzed using the Kaplan–Meier method with the log-rank test and the Cox proportional hazards regression model using IBM SPSS Statistics. Results: The median overall survival (OS) for the entire cohort was 15 months (95% CI: 11.88–18.12). HALP1 score (p = 0.048), HALP2 score (p = 0.026), and hyperprogression (p < 0.001) were statistically significant predictors of OS. Regarding progression-free survival (PFS), the HALP2 score (p = 0.031), line of immunotherapy (p = 0.046), and hyperprogression (p < 0.001) were found to be significant. When comparing patients with increasing versus decreasing HALP scores, those with increasing HALP scores demonstrated significantly better outcomes for both OS (p = 0.034) and PFS (p = 0.007). Conclusions: In patients with metastatic NSCLC undergoing immunotherapy, the HALP score and its dynamic alterations during treatment appear to be non-invasive, easily calculable biomarkers that may predict both OS and PFS.