Clinical Prediction Models of Severe Cancer-Related Fatigue in Cervical Cancer Patients and Effectiveness of Mindfulness-Based Stress Reduction: A Randomized Controlled Trial

Abstract

Objective To build a clinical prediction models (CPMs) for severe CRF of cervical cancer (CC) patients, and conduct online 8-week mindfulness-based stress reduction (MBSR). Design Single-centre, cross-sectional, randomized controlled trial. Setting Gynecological clinic of a tertiary hospital in Shenyang. Population 284 patients, and 100 patients with severe CRF included in randomized controlled trial. Methods Patients were divided into construction group and validation group to verify the accuracy of CPMs. All patients participated in online 8-week MBSR and were followed up for 3 and 6 months. Main outcome measures The primary outcome were the accuracy of the CPMs and effectiveness of MBSR on CRF at 6 month. Secondary outcomes included the influencing factors of CRF, effectiveness of MBSR on sense of coherence, coping style, and perceived social support. Results In the CPMs: the C-Index was 0.921; the sensitivity was 0.821; the specificity was 0.900; the accuracy was 0.857; the AUC was 0.916; the area under the ROC curve was greater than 0.8; the calibration curve fitted well (P<0.05); and the net benefit of applying the model to most thresholds was good in DCA. At 6 months, CRF was from 37.70 to 31.25; SOC was from 55.07 to 64.17; ways to face was from 19.20 to 20.95; and ways to yield was from 12.10 to 8.90 in MBSR group (P<0.01). Conclusion The CPMs could be used as a prediction and evaluation tool for severe CRF, and the online 8-week MBSR can effectively improve the CRF of CC patients.