Nomograms combining clinical factors and apparent diffusion coefficient to predict downstaging and progression-free survival after concurrent chemoradiotherapy in patients with cervical cancer

Background: Concurrent chemoradiotherapy (CCRT) is used as the primary treatment modality for currently limited cervical cancer and lacks non-invasive quantitative parameters to assess clinical outcomes of treatment for cervical cancer treatment. Purpose: To develop nomograms based on clinical prognostic factors and apparent diffusion coefficient (ADC) in predicting downstaging and progression-free survival (PFS) after CCRT for cervical cancer. Material and Methods: X-tile was used to calculate the optimal threshold for Delta ADC(mean)(%) for prognostic stratification. Kaplan-Meier curves were used to calculate the difference in PFS between high- and low-risk groups. Univariate and multivariate Cox proportional risk regression models were used to identify clinical and radiological risk factors for prognosis and construct a prognostic nomogram model. Results: Delta ADC(mean)(%) was significantly correlated with tumor downstaging; the area under the receiver operating characteristic curve (AUC) was 0.868. X-tile showed that the optimal threshold for Delta ADC(mean)(%) to diagnose prognosis was 40.8. Kaplan-Meier curves showed that the low-risk population in the training group had significantly longer PFS within 3 years (P < 0.001). Multivariate Cox regression showed that Delta ADC (%) is independent risk factor for PFS. The C-index of Delta ADC(%) predicting 3-year PFS in the training set is 0.761 and the C-index of the nomogram model is 0.862. Conclusion: Delta ADC(mean)(%) is a non-invasive biomarker for predicting tumor downstaging in cervical cancer after CCRT. The nomograms based on Delta ADC(mean)(%) predict PFS of patients with cervical cancer with moderate accuracy.