Nomogram prediction for overall survival of patients diagnosed with cervical cancer

Abstract

Background: Nomograms are predictive tools that are widely used for estimating cancer prognosis. The aim of this study was to develop a nomogram for the prediction of overall survival (OS) in patients diagnosed with cervical cancer.

Methods: Cervical cancer databases of two large institutions were analysed. Overall survival was defined as the clinical endpoint and OS probabilities were estimated using the Kaplan-Meier method. Based on the results of survival analyses and previous studies, relevant covariates were identified, a nomogram was constructed and validated using bootstrap cross-validation. Discrimination of the nomogram was quantified with the concordance probability.

Results: In total, 528 consecutive patients with invasive cervical cancer, who had all nomogram variables available, were identified. Mean 5-year OS rates for patients with International Federation of Gynecologists and Obstetricians (FIGO) stage IA, IB, II, III, and IV were 99.0%, 88.6%, 65.8%, 58.7%, and 41.5%, respectively. Seventy-six cancer-related deaths were observed during the follow-up period. FIGO stage, tumour size, age, histologic subtype, lymph node ratio, and parametrial involvement were selected as nomogram covariates. The prognostic performance of the model exceeded that of FIGO stage alone and the model's estimated optimism-corrected concordance probability was 0.723, indicating accurate prediction of OS. We present the prediction model as nomogram and provide a web-based risk calculator (http://www.ccc.ac.at/gcu).

Conclusion: Based on six easily available parameters, a novel statistical model to predict OS of patients diagnosed with cervical cancer was constructed and validated. The model was implemented in a nomogram and provides accurate prediction of individual patients' prognosis useful for patient counselling and deciding on follow-up strategies.

Figure 1

Kaplan–Meier OS curve for patients with invasive cervical cancer (N=528).

Figure 2

Nomogram to predict 3- and 5-year OS using six easily available clinical characteristics. To use the nomogram, locate patient’s variable on the corresponding axis; draw a line to the points axis, sum the points, and draw a line from the total points axis to the 3-year OS probability axis.

Figure 3

Time-dependent discrimination curves. Optimism-corrected area under the ROC (AUROC): median over 1000 bootstrap replicates shown as solid line, dashed lines denote 25th and 75th percentiles.

Figure 4

Cervical cancer OS nomogram calibration plots: (A) 3-year and (B) 5-year nomogram calibration curve. Nomogram-predicted OS rates are plotted on the x-axis, actual OS are plotted on the y-axis. The dashed line represents the ideal fit where the nomogram-predicted probability matches the observed probability from Kaplan–Meier estimates.

Figure 5

Predicted 5-year OS probability by 2009 FIGO stage.