A Nomogram Model Involving Immunohistochemical Markers for Predicting the Recurrence of Stage I-II Endometrial Cancer

Abstract

Background: The purpose of this study was to establish a nomogram combining classical parameters and immunohistochemical markers to predict the recurrence of patients with stage I-II endometrial cancer (EC).

Methods: 419 patients with stage I-II endometrial cancer who received primary surgical treatment at the First Affiliated Hospital of Chongqing Medical University were involved in this study as a training cohort. Univariate and multivariate Cox regression analysis of screening prognostic factors were performed in the training cohort to develop a nomogram model, which was further validated in 248 patients (validation cohort) from the Second Affiliated Hospital of Chongqing Medical University. The calibration curve was used for internal and external verification of the model, and the C-index was used for comparison among different models.

Results: There were 51 recurrent cases in the training cohort while 31 cases in the validation cohort. Univariate analysis showed that age, histological type, histological grade, myometrial invasion, cervical stromal invasion, postoperative adjuvant treatment, and four immunohistochemical makers (Ki67, estrogen receptor, progesterone receptor, P53) were the related factors for recurrence of EC. Multivariate analysis demonstrated that histological type (P = 0.029), myometrial invasion (P = 0.003), cervical stromal invasion (P = 0.001), Ki67 (P < 0.001), ER (P = 0.009) and P53 expression (P = 0.041) were statistically correlated with recurrence of EC. Recurrence-free survival was better predicted by the proposed nomogram with a C-index of 0.832 (95% CI, 0.752-0.912) in the training cohort, and the validation set confirmed the finding with a C-index of 0.861 (95% CI, 0.755-0.967).

Conclusion: The nomogram model combining classical parameters and immunohistochemical markers can better predict the recurrence in patients with FIGO stage I-II EC.

Keywords: classical parameters; endometrial cancer; immunohistochemical markers; nomogram model; recurrence.

Figure 1

Flow chart for patient inclusion. Description: (A) Flow chart for inclusion of patients in the training cohort. (B) Flow chart for inclusion of patients in the validation cohort.

Figure 2

Nomogram model for estimating the rate of recurrence free survival (3 or 5 years) for women with I–II FIGO stage endometrial cancer Description: To estimate the recurrence risk, calculate points for each variable by drawing a straight line from patient’s variable value from the 2nd to 6th line to the 1st line labelled ‘Points’. Sum all points and draw a straight line from the 7th line to the 9th line-10th line to get the 3-, and 5-year recurrence-free survival rate.

Figure 3

The calibration curve for internal and external validation of the nomogram model. Description: (A) The calibration curve for internal validation of the nomogram model for predicting the RFS in EC; (B) The calibration curve for external validation of the nomogram model for predicting the RFS in EC (notes: The blue dotted line: Reference line; The red solid line: The prediction curve given by the model).

Figure 4

The ROC curve of the optimal threshold value of the 3-year recurrence-free survival rate predicted by the model. Description: Black dot: the area under the curve at this point is the largest, which indicates the optimal threshold value of the 3-year recurrence-free survival rate predicted by the model is 0.82 (area under the curve = 0.848; sensitivity, 76.5%; specificity, 86.7%); (Dotted line: reference line; Solid line: the ROC curve of the model).

Figure 5

Kaplan-Meier Survival Curve of low-RFS group and high-RFS group. Description: (A) Recurrence-free survival curve of low-RFS group and high-RFS group. (B) Overall survival curve of low-RFS group and high-RFS group (The dotted line: low-RFS group; The solid line: high-RFS group).