Diagnostic sensitivity of immune-inflammatory cell proportion in early diagnosis of endometrial cancer

Abstract

Background

Previous studies have shown that inflammation is closely linked to the occurrence and progression of cancer. While the role of immune-inflammatory cell proportions in cancer prognosis has been demonstrated, further research is required to fully understand their predictive value. This study aims to investigate the potential of immune-inflammatory cell proportions, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), red blood cell distribution width-to-platelet ratio (RPR), and monocyte-to-lymphocyte ratio (MLR), in predicting endometrial cancer (EC).

Methods

In this study, 18 patients with EC were included to create receiver operating characteristic (ROC) curves for NLR, MLR, PLR, and RPR, and the area under the curve (AUC) was calculated. Binary LOGISTIC regression analysis was then used to develop composite indicators. Subsequently, ROC curves were generated for the combined indicators, and the corresponding AUCs were calculated to evaluate the diagnostic efficacy of NLR, MLR, PLR, and RPR individually and in combination. The model was validated in an additional cohort.

Result

In the single-indicator ROC analysis, the baseline AUC for NLR was 0.724, with a significance level of p ​< ​0.05, indicating good predictive power. For the two-indicator combined ROC analysis, the combined AUC of NLR with each of the three other indicators was greater than 0.724 with a significance level of p ​< ​0.05. In the three-indicator combined ROC analysis, the baseline AUC of the combined indicators (including NLR) was greater than 0.766, and a p value of 0.001. Moreover, the baseline AUC of the validation set was 0.726.

Conclusion

Our findings suggest that the immune-inflammatory cell ratios, especially NLR, have a good predictive value for EC. Furthermore, the combined predictive value of the immune-inflammatory cell ratio is more effective than using individual applications.