Predictive value of the systemic immune-inflammation index combined with the prognostic nutritional index for postoperative recurrence in early-stage cervical cancer: evidence from a multicenter cohort study

Background Growing evidence suggests that immune-inflammatory status and nutritional condition influence cancer prognosis. In this study, a composite score combining the systemic immune ~ inflammation index (SII) and the prognostic nutritional index (PNI) was investigated for its ability to stratify the risk of postoperative recurrence in patients with early-stage cervical cancer (ESCC). Methods This multicenter, retrospective study enrolled 403 individuals diagnosed with early-stage cervical squamous cell carcinoma and treated with surgery performed with curative intent. Optimal SII and PNI cut-points were selected based on receiver operating characteristic (ROC) curve analysis and validated using internal bootstrapping (1,000 resamples). Disease-free survival was summarized with Kaplan ~ Meier analysis, whereas prognostic associations were quantified using a multivariable Cox proportional hazards model. Results ROC-based analyses yielded cutoff values of 580.99 for SII and 49.81 for PNI, which were subsequently used for patient stratification. The combined SII - PNI score showed improved predictive performance compared to individual indices, with an area under the curve (AUC) of 0.743. Survival curves demonstrated a graded increase in postoperative recurrence with rising SII - PNI scores, and intergroup differences reached statistical significance (log-rank P < 0.001). After adjustment for relevant covariates, the combined SII - PNI score remained independently associated with recurrence risk following surgery. Conclusion Elevated SII - PNI scores were independently associated with an increased probability of postoperative recurrence among patients with early-stage cervical cancer. Although the discriminatory ability is moderate, this combined index holds promise as a cost-effective, complementary tool for refining risk stratification in this population.