ArticleJournal of radiation research2026
Mid-treatment MRI-based tumor volume reduction rate as a continuous prognostic factor after chemoradiation for cervical cancer: development and two-center internal-external validation.
Article in Journal of radiation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study aimed to quantify the continuous association of the mid-treatment MRI-based tumor volume reduction rate (TVRR) with oncologic outcomes after chemoradiation for cervical cancer and to develop prognostic models assessed by two-center internal-external cross-validation (IECV). A retrospective analysis was performed in patients with FIGO 2009 stage IB-IVA disease treated with definitive chemoradiation at two centers from 2010 to 2021 with both pre- and mid-treatment pelvic MRI during external beam radiotherapy (24-36 Gy). Pre- and mid-treatment volumes (Vpre, Vmid) were derived and TVRR was defined as (Vpre - Vmid)/Vpre × 100%. Cox models were used to evaluate overall survival (OS) and progression-free survival (PFS), and a Fine-Gray model was used for local control (LC), modeling TVRR with a penalized spline and adjusting for key covariates. IECV assessed discrimination and 60-month calibration for OS and PFS. The analysis included 281 patients (median age 59 years; squamous cell carcinoma 85%; FIGO 2009 stage III-IV 60%; node-positive 56%) with 65 deaths, 97 PFS events, and 27 local failures over a median follow-up period of 69.6 months. Higher TVRR was independently associated with better outcomes: per 10-percentage-point (pp) increase, OS hazard ratio (HR) 0.71 (95% CI, 0.64-0.79; P < 0.001), PFS HR 0.74 (0.68-0.81; P < 0.001), and LC subdistribution HR 0.68 (0.58-0.80; P < 0.001). Non-linear components were not significant. Discrimination was moderate-high (C 0.73-0.81 internally; 0.72-0.79 in IECV) with acceptable 60-month calibration. In conclusion, mid-treatment MRI-based TVRR provides a strong, near-linear prognostic signal and enables threshold-free, calibrated risk estimation and supports design of risk-adapted trials.
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