Predicting outcomes in locally advanced cervical cancer treated with radiotherapy: a systematic review of nomograms
- 1Center for Gynecologic Cancer, National Cancer Center
- 2Department of Cancer Control and Policy, Graduate School of Cancer Science and Policy, National Cancer Center
Abstract
Objective: To systematically evaluate published nomograms developed for patients with locally advanced cervical cancer (LACC) treated with radiotherapy, focusing on prognostic performance, core predictive variables, and implications for future model development.
Methods: A systematic literature search of PubMed, Embase, Scopus, Web of Science, and the Cochrane Library identified studies published between 2010 and 2025 that developed new nomograms for LACC cohorts treated with radiotherapy or chemoradiotherapy. Data extraction included study population, predicted outcomes (overall survival [OS], progression-free survival [PFS], or disease-free survival [DFS]), model performance (C-index), validation methods, calibration, and predictor variables. Predictor patterns were summarized primarily by frequency of inclusion across nomograms, with β-coefficients used only for exploratory within-model descriptions.
Results: Nine studies met the inclusion criteria; eight developed nomograms for OS and three evaluated disease progression outcomes (PFS or DFS), with two studies evaluating both outcome categories. Reported C-indices ranged from 0.68 to 0.835, indicating moderate to good discrimination. Lymph node status, FIGO stage, and tumor size were among the most frequently incorporated predictors, while histology and SCC-Ag were also recurrently included. Validation in independent cohorts remained limited. Graphical calibration was commonly reported, whereas quantitative calibration measures and decision-curve analyses were inconsistently reported.
Conclusions: Nomograms for LACC treated with radiotherapy generally demonstrate moderate-to-good discriminative performance and frequently incorporate lymph node status, stage, and tumor size. However, methodological heterogeneity, incomplete validation, and evolving treatment paradigms limit their immediate generalizability. Future work should focus on robust external validation, recalibration, and evaluation in contemporary treatment cohorts before clinical implementation.
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BibTeX
@article{bae2026predicting,
title = {{Predicting outcomes in locally advanced cervical cancer treated with radiotherapy: a systematic review of nomograms}},
author = {Jaekyung Bae and Uisuk Kim and Sokbom Kang},
journal = {Frontiers in Oncology},
year = {2026},
month = oct,
doi = {10.3389/fonc.2026.1940047},
url = {https://www.frontiersin.org/articles/10.3389/fonc.2026.1940047/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Predicting outcomes in locally advanced cervical cancer treated with radiotherapy: a systematic review of nomograms
AU - Jaekyung Bae
AU - Uisuk Kim
AU - Sokbom Kang
PY - 2026
DA - 2026/10/22
JO - Frontiers in Oncology
DO - 10.3389/fonc.2026.1940047
UR - https://www.frontiersin.org/articles/10.3389/fonc.2026.1940047/full
AB - Objective: To systematically evaluate published nomograms developed for patients with locally advanced cervical cancer (LACC) treated with radiotherapy, focusing on prognostic performance, core predictive variables, and implications for future model development. Methods: A systematic literature search of PubMed, Embase, Scopus, Web of Science, and the Cochrane Library identified studies published between 2010 and 2025 that developed new nomograms for LACC cohorts treated with radiotherapy or chemoradiotherapy. Data extraction included study population, predicted outcomes (overall survival [OS], progression-free survival [PFS], or disease-free survival [DFS]), model performance (C-index), validation methods, calibration, and predictor variables. Predictor patterns were summarized primarily by frequency of inclusion across nomograms, with β-coefficients used only for exploratory within-model descriptions. Results: Nine studies met the inclusion criteria; eight developed nomograms for OS and three evaluated disease progression outcomes (PFS or DFS), with two studies evaluating both outcome categories. Reported C-indices ranged from 0.68 to 0.835, indicating moderate to good discrimination. Lymph node status, FIGO stage, and tumor size were among the most frequently incorporated predictors, while histology and SCC-Ag were also recurrently included. Validation in independent cohorts remained limited. Graphical calibration was commonly reported, whereas quantitative calibration measures and decision-curve analyses were inconsistently reported. Conclusions: Nomograms for LACC treated with radiotherapy generally demonstrate moderate-to-good discriminative performance and frequently incorporate lymph node status, stage, and tumor size. However, methodological heterogeneity, incomplete validation, and evolving treatment paradigms limit their immediate generalizability. Future work should focus on robust external validation, recalibration, and evaluation in contemporary treatment cohorts before clinical implementation.
SN - 2234-943X
ER -