Abstract: Objective To predict the clinical value of nomograms based on the change rate in the dynamic apparent diffusion coefficient (ADC) for progression-free survival (PFS) after concurrent chemoradiotherapy (CCRT) for cervical cancer. 
Methods A total of 75 patients with cervical cancer who underwent CCRT at the First Affiliated Hospital of Xi′an Jiaotong University were retrospectively enrolled as the training group, while 36 patients from the Second Affiliated Hospital of Xi′an Jiaotong University were included as the external validation group. The mean change rate of ADC (△ADCmean ［%］) before and after treatment was calculated for each patient. Receiver operating characteristic (ROC) curves were plotted to assess the accuracy of △ADCmean (%) in predicting International Federation of Gynecology and Obstetrics(FIGO) downstaging. The optimal threshold of △ADCmean (%) for prognostic stratification was determined using X-tile, and the difference in 3-year PFS between high hrisk and low risk groups was evaluated using survival curves. Multivariate Cox proportional hazards regression analysis was performed in the training group to identify independent risk factors associated with PFS, and a prognostic nomogram model was constructed. The consistent threshold was applied to the validation group for prediction. The Concordance Index (C-index) was calculated, and time-dependent ROC curve analysis of relevant indicators was used to evaluate the discriminative ability of the model in both the training and validation groups. Decision curve analysis (DCA) was conducted to assess the clinical applicability of the △ADCmean (%) prediction model and the nomogram model, quantifying the net benefit within the threshold range. 
Results According to FIGO staging, patients with tumor downstaging after CCRT had significantly longer PFS compared with those without downstaging (P=0.002). The optimal threshold of △ADCmean (%) for prognostic stratification was 40.8 determined by X-tile. Survival curves demonstrated that the low risk group had significantly longer 3-year PFS than the high risk group at this threshold (P=0.002), with similar results observed in the validation group (P=0.013). Multivariate Cox regression analysis identified △ADCmean (%), pathological grade, para-aortic lymph node metastasis, and pelvic lymph node metastasis as independent risk factors affecting PFS. The C-indices for predicting 3-year PFS using △ADCmean (%) in the training and validation groups were 0.75 and 0.691, respectively, while the C-indices for the combined nomogram model were 0.861 and 0.727, respectively. DCA showed that the nomogram model provided higher net benefit for predicting 3-year PFS compared with the △ADCmean (%) model alone, with threshold ranges of 0.11-0.59 in the training group and 0.08-0.65 in the validation group. 
Conclusion Among cervical cancer patients, those with tumor downstaging after CCRT treatment have significantly longer PFS than those without downstaging. △ADCmean (%) has obvious advantages in predicting presence or absence of tumor downstaging in cervical cancer patients. The nomogram model based on clinical information and △ADCmean (%) has high clinical value in predicting the downstaging and PFS of cervical cancer patients after CCRT, and can provide a strong reference for the prognosis evaluation and individualized treatment planning of cervical cancer patients. 

Key words: uterine cervical neoplasms, chemoradiotherapy, nomograms