Efficacy Assessment and Prognostic Value of Inflammatory Markers in Patients with Stage IV Acral and Cutaneous Melanoma Receiving PD-1 Inhibitors.

Background: Malignant melanoma (MM) is a highly aggressive cancer. Different subtypes have different sensitivities to immunotherapy and lack peripheral blood markers. Few studies have examined the role of inflammatory markers in predicting the overall survival (OS) in stage IV acral melanoma (AM) and cutaneous melanoma (CM) patients receiving immunotherapy.

Purpose: This study aimed to investigate the value of inflammatory markers in efficacy and prognosis for stage IV melanoma patients who underwent immunotherapy.

Patients and methods: This multicenter study reviewed the clinicopathological characteristics and inflammatory markers of 94 stage IV AM and CM patients receiving PD-1 inhibitors therapy. Pearson's chi-squared test or Fisher's exact test was used to compare baseline characteristics. The optimal cut-off values for these markers were stratified using time-dependent receiver operating characteristic curves (t-ROC). Kaplan-Meier (KM) curves and Log rank test were used to explore the relationship between inflammatory markers and survival outcomes. Cox regression analysis was performed to screen for independent prognostic factors and a nomogram was constructed. The model ability was tested by the C-index, t-ROC, calibration curves, and decision curve analysis curves.

Results: High NLR level was significantly correlated with lymph node metastasis and 3 or above metastatic sites (P=0.009, P=0.012). High PNI level favored a better ECOG PS (P=0.023). According to the KM curves, patients with baseline NLR>2.37, PNI<=42.65, and RLR>11.08 had worse OS (P<0.001, P<0.001, P<0.001). Cox regression analysis based on P<0.05 showed that M1c/M1d (P<0.001), NLR (P=0.003), and PNI (P<0.001) were significantly correlated with OS, and were visualized in a nomogram. C-index, t-ROC, area under the curve (AUC), and calibration curves revealed promising discrimination and accuracy of the nomogram. Decision curve analysis curves showed good clinical utility.

Conclusion: We established a prognostic predictive model based on distant metastatic sites, NLR, and PNI, and verified its superior performance and potential for clinical application.