Risk prediction model for disease-free survival in women with early-stage cervical cancers following postoperative (chemo)radiotherapy

Prediction Models for Prognosis of Cervical Cancer: Systematic Review and Critical Appraisal

Objective: This work aims to systematically identify, describe, and appraise all prognostic models for cervical cancer and provide a reference for clinical practice and future research. Methods: We systematically searched PubMed, EMBASE, and Cochrane library databases up to December 2020 and included studies developing, validating, or updating a prognostic model for cervical cancer. Two reviewers extracted information based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modeling Studies checklist and assessed the risk of bias using the Prediction model Risk Of Bias ASsessment Tool. Results: Fifty-six eligible articles were identified, describing the development of 77 prognostic models and 27 external validation efforts. The 77 prognostic models focused on three types of cervical cancer patients at different stages, i.e., patients with early-stage cervical cancer (n = 29; 38%), patients with locally advanced cervical cancer (n = 27; 35%), and all-stage cervical cancer patients (n = 21; 27%). Among the 77 models, the most frequently used predictors were lymph node status (n = 57; 74%), the International Federation of Gynecology and Obstetrics stage (n = 42; 55%), histological types (n = 38; 49%), and tumor size (n = 37; 48%). The number of models that applied internal validation, presented a full equation, and assessed model calibration was 52 (68%), 16 (21%), and 45 (58%), respectively. Twenty-four models were externally validated, among which three were validated twice. None of the models were assessed with an overall low risk of bias. The Prediction Model of Failure in Locally Advanced Cervical Cancer model was externally validated twice, with acceptable performance, and seemed to be the most reliable. Conclusions: Methodological details including internal validation, sample size, and handling of missing data need to be emphasized on, and external validation is needed to facilitate the application and generalization of models for cervical cancer.

Postoperative nomogram for the prediction of disease-free survival in lymph node-negative stage I-IIA cervical cancer patients treated with radical hysterectomy

The purpose of this study was to develop and validate a nomogram for individual prediction of recurrence and disease-free survival (DFS) among lymph node (LN)-negative early-stage (I-IIA) cervical cancer (CC) patients treated with Type B or Type C2 hysterectomy. Data were collected from patients diagnosed with CC between 1995 and 2017 at the Gynecological Oncology Department, Tepecik Training and Research Hospital. A total of 194 cases with stage IA2-IIA CC were evaluated retrospectively. Patients with stage IA2-IIA CC who underwent radical (Type C2) or modified radical (Type B) hysterectomy and pelvic ± paraaortic LN dissection with LN negativity were included in the study. The relationships between prognostic factors such as stage, tumour size, parametrial involvement, vaginal cuff margin, endomyometrial infiltration, and lymphovascular space invasion status and DFS were compared using a univariable Cox regression model. When the nomogram was prepared, the scores of the risk factors were collected, and we observed that scores were at least 0 to a maximum of 414 points. The concordance-index for the nomogram was 0.895 (95% confidence interval, 0.79-0.99). The nomogram based on the indicated prognostic factors yielded excellent results in predicting recurrence in early-stage CC patients without LN metastasis who underwent radical hysterectomy.Impact statementWhat is already known on this subject? Pathology of radical hysterectomy specimens in patients with early-stage cervical cancer provides information that has predictive prognostic potential. In addition to FIGO stage, other important prognostic factors are lymph node status, tumour size, parametrial involvement, vaginal cuff margin status, endomyometrial infiltration, histological type, patient age, lymphovascular space invasion, histological grade, and depth of cervical stromal invasion.What do the results of this study add? In this study, patients with early-stage cervical cancer who underwent radical and modified radical hysterectomy without retroperitoneal lymph node involvement were evaluated, and recurrence development and factors affecting disease-free survival were investigated. A nomogram consisting of factors influencing disease-free survival was constructed. The total score was determined according to the status of all risk factors. This allowed clear definition of the risk for each patient. A nomogram predicting recurrence in patients with stages IA2-IIA cervical cancer with radical hysterectomy without lymph node involvement has not previously been published.What are the implications of these findings for clinical practice and/or further research? Our study investigated early-stage cervical cancer (CC) patients without lymph node (LN) metastasis. Cox regression analysis was performed with six prognostic factors: FIGO stage, tumour size, parametrial margin infiltration, vaginal cuff margin involvement, endomyometrial infiltration, and LVSI positivity. The nomogram was constructed based on the results of Cox regression. The C-index for the nomogram was 0.895 (95% CI, 0.79-0.99). These results can be considered excellent. The higher concordance index in our study indicates that these six factors may be more valuable in predicting recurrence development in CC patients.