Prognostic value of the lactate dehydrogenase-to-albumin ratio (LAR) combined with clinicopathological indicators for predicting outcomes in locally advanced cervical cancer undergoing concurrent chemoradiotherapy: a retrospective cohort study and nomogram development.

This two-center retrospective study aimed to evaluate the prognostic value of the lactate dehydrogenase-to-albumin ratio (LAR) combined with clinicopathological variables for predicting short-term therapeutic response and overall survival (OS) in patients with locally advanced cervical cancer (LACC) undergoing concurrent chemoradiotherapy (CCRT), and to develop and validate dual nomogram models. A total of 622 patients treated with standard CCRT between January 2018 and June 2022 were enrolled. Patients from the Third Affiliated Hospital of Guangzhou Medical University were randomly divided into a training cohort (n = 373) and an internal validation cohort (n = 124) at a ratio of 0.75:0.25, while an external validation cohort (n = 125) was obtained from Jinshazhou Hospital of Guangzhou University of Chinese Medicine during the same period. Optimal cutoff values for squamous cell carcinoma antigen (SCCA), albumin (ALB), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), albumin-to-fibrinogen ratio (AFR), and LAR were determined using the surv_cutpoint function in the training cohort and uniformly applied to the validation cohorts. Logistic regression was used to identify predictors of treatment response, and Cox proportional hazards regression was applied to construct nomograms predicting 1-, 2-, and 3-year OS. Model performance was assessed using receiver operating characteristic (ROC) curves, concordance index (C-index), Hosmer-Lemeshow test, calibration curves, and decision curve analysis (DCA), with internal validation performed by bootstrap resampling. Baseline clinicopathological characteristics were well balanced across the three cohorts (all P > 0.05), and the overall complete response rate was 81.99% (510/622). Multivariate logistic regression identified tumor stage, histological differentiation, depth of stromal invasion, NLR, and PLR as independent predictors of therapeutic response (all P < 0.05). Multivariate Cox regression analysis demonstrated that age ≥ 60 years, FIGO stage III-IV, poor differentiation, deep stromal invasion (≥ 1/2), SCCA ≥ 13.2 ng/mL, LAR ≥ 4.015, and negative HPV status were independent predictors of poor OS (all P < 0.05). The OS nomogram achieved C-index values of 0.792, 0.928, and 0.918 in the training, internal validation, and external validation cohorts, respectively, showing good calibration and consistent net clinical benefit across a wide range of threshold probabilities. Stratified survival analysis revealed a significantly lower 3-year OS rate in patients with high LAR compared with those with low LAR (P < 0.001). Furthermore, the area under the curve (AUC) of the nomogram-derived risk score was significantly higher than that of FIGO staging and LAR alone in the training cohort (0.853 vs. 0.708 and 0.706, respectively; all P < 0.001). These findings indicate that LAR combined with clinicopathological characteristics is a reliable predictor of both short-term treatment response and long-term survival in LACC patients receiving CCRT, and that the proposed nomograms provide a low-cost, non-invasive, and clinically useful tool for risk stratification, individualized treatment, and follow-up management.