A novel prognostic model for cervical cancer patients with lymph node metastases: based on SEER database and an independent cohort

Author:

Liu Xueting1,Wang Le1,Song Jiayu1,Liu Sijia1,Yan Jiazhuo1,Yang Shanshan1,Zhang Yunyan1ORCID

Affiliation:

1. Harbin Medical University Cancer Hospital

Abstract

Abstract Introduction: Cervical cancer with lymph node metastasis (LNM) has a poor prognosis, but the prognosis of patients varies among individuals to a great extent and depends on diverse factors. This study attempted to develop and externally validate a prognostic model based on risk factors to predict the probability of survival of patients with cervical cancer with LNM. Methods A population-based cohort with 4238 participants diagnosed with cervical cancer with LNM between 2000 and 2016 from the Surveillance, Epidemiology, and End Results database was used to select prognostic variables for inclusion in our model. Model performance was validated internally and externally using the concordance index (C-index), areas under the curve (AUC) of receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA). Kaplan–Meier survival curve was used to validate the risk stratification capability of the established model. Results Prognostic factors included marital status, age, pathological subtype, clinical stage, tumor size, surgical treatment, radiotherapy, and chemotherapy (all P < .05). The C-index (0.736, 0.727, and 0.701 for the training, internal validation, and external validation cohorts) and AUC values of the 3- and 5-year ROC curves (0.781 and 0.777 for the training cohort, 0.78 and 0.759 for the internal validation cohort, and 0.728 and 0.74 for the external validation cohort) demonstrated the satisfactory discrimination and excellent accuracy of the nomogram. Calibration plots showed the favorable agreement between the predicted and observed probabilities, and DCA indicated good clinical benefits. The nomogram-based risk stratification successfully discriminated patients into low-, intermediate-, and high-risk populations. Conclusion An easy-to-use online website of the dynamic nomogram was provided which could help predict overall survival of cervical cancer with LNM.

Publisher

Research Square Platform LLC

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