A Nomogram Model for Predicting Recurrence of Stage I–III Endometrial Cancer Based on Inflammation-Immunity-Nutrition Score (IINS) and Traditional Classical Predictors

Abstract

The purpose of this study was to investigate the prognostic value of the inflammation-immunity-nutrition score (IINS) in patients with stage I-III endometrial cancer (EC) and establish a nomogram model to predict the recurrence of EC by combining IINS and traditional classical predictors. Methods: Seven hundred and seventy-five patients with stage I-III EC who underwent initial surgical treatment at the First Affiliated Hospital of Chongqing Medical University were included in this study as the training cohort. In the training cohort, IINS (0-3) was constructed based on preoperative C-reactive protein (CRP), lymphocytes (LYM), and albumin (ALB). Univariate and multivariate Cox regression analysis were used to screen independent predictors associated with recurrence of EC for developing the nomogram model. Internal validation of the model was performed in the training cohort by using the C-index and calibration curve, while external validation of the model was performed in another cohort (validation cohort) of 491 patients from the Second Affiliated Hospital of Chongqing Medical University. Results: IINS was successfully constructed, and survival analysis showed that patients with high IINS had a worse prognosis. Multivariate analysis showed that IINS, age, FIGO stage, pathological type, myometrial invasion, lymphatic vessel space invasion (LVSI), Ki67 expression, estrogen receptor (ER) expression, and P53 expression were significantly associated with shorter recurrencefree survival, and then a nomogram model for predicting the recurrence of EC was successfully established. The internal and external calibration curves of the model showed that the model fit well, and the C-index (0.887 in training cohort and 0.883 in validation cohort) showed that the model proposed in this study had better prediction accuracy than other prediction models. Conclusion: IINS may be a strong predictor of prognosis in patients with EC. The nomogram model incorporated into the IINS can better predict the recurrence of EC than the traditional models.

Predicting the Recurrence of Operable Cervical Cancer Patients Based on Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score and Classical Clinicopathological Parameters

“…5 The postoperative pathological examination results were jointly evaluated by two pathological experts from the pathological experiment center of Chongqing Medical University according to the unified pathological analysis process and truthfully recorded in the electronic medical record system. 6 NLR, PLR, MLR, SIRI, PNI and HALP were calculated as follows: NLR=neutral count/lymphocyte count; PLR, platelet count/lymphocyte count; MLR, monocyte count/lymphocyte count; SIRI=neutrophil count × monocyte count/lymphocyte count; PNI= albumin × total lymphocyte count × 109/L; HALP= hemoglobin × albumin × lymphocyte/platelet. 5,12,15…”

“…21 The training cohort was used to construct the model and verify the model internally, while the validation cohort was used for external verification of the model. 6 The differences between the basic parameters of the two cohorts were compared: the categorical variables were compared by chi-square test; t-test and rank sum test were used to compare continuous variables. P value <0.05 was considered as a statistically significant difference.…”

“…Finally, the nomogram proposed in this study was compared with similar models proposed by other studies through C-index to further prove the superiority of the model proposed in this study. 6…”

“…5 There has been evidence reported that inflammatory response and nutritional status are closely related to tumor progression. 6 On the one hand, cytokines produced by chronic inflammation promote the occurrence and development of tumors through a series of pathophysiological processes. 7,8 On the other hand, malnutrition can lead to impaired immune function, increased inflammatory response and increased treatment side effects in cancer patients.…”

“…5,11,12 However, the above prognostic index only focuses on one of the inflammatory response or nutritional status, and in clinical practice, we may need to comprehensively evaluate the inflammatory response and nutritional status of patients. 6 Hemoglobin, albumin, lymphocyte, and platelet (HALP) index is a new score based on the combination of inflammation and nutritional status. 13,14 It has been found that this index can improve the prediction accuracy of the prognosis of various cancers.…”