Pan-Immune-Inflammation Value: A New Prognostic Index in Operative Breast Cancer

BackgroundTo build a predictive scoring model based on simple immune and inflammatory parameters to predict postoperative survival in patients with breast cancer. MethodsWe used a brand-new immuno-inflammatory index-pan-immune-inflammation value (PIV)-to retrospectively evaluate the relationship between PIV and overall survival (OS), and based on the results of Cox regression analysis, we established a simple scoring prediction model based on several independent prognostic parameters. The predictive accuracy of the model was evaluated and independently validated. ResultsA total of 1,312 patients were included for analysis. PIV was calculated as follows: neutrophil count (10(9)/L) x platelet count (10(9)/L) x monocyte count (10(9)/L)/lymphocyte count (10(9)/L). According to the best cutoff value of PIV, we divided the patients into two different subgroups, high PIV (PIV > 310.2) and low PIV (PIV <= 310.2), associated with significantly different survival outcomes (3-year OS, 80.26% vs. 86.29%, respectively; 5-year OS, 62.5% vs. 71.55%, respectively). Six independent prognostic factors were identified and used to build the scoring system, which performed well with a concordance index (C-index) of 0.759 (95% CI: 0.715-0.802); the calibration plot showed good calibration. ConclusionsWe have established and verified a simple scoring system for predicting prognosis, which can predict the survival of patients with operable breast cancer. This system can help clinicians implement targeted and individualized treatment strategies.

Automated summary

A simple scoring system based on immune and inflammatory parameters has been established and validated to predict postoperative survival in patients with operable breast cancer. The system, utilizing the pan-immune-inflammation value (PIV), is able to predict survival outcomes by evaluating several independent prognostic parameters. This scoring model shows promising accuracy and can assist clinicians in implementing tailored treatment strategies for breast cancer patients.