Prognostic nomogram for early-onset locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: a SEER analysis.

Authors

Yi-Kai Kao, Pin-Chun Chen, Po-Wen Yang, Chia-Hung Chen, Chih-I Chen

Published in

Updates in surgery. Oct 16, 2026. Epub Oct 16, 2026.

Abstract

Early-onset locally advanced rectal cancer presents unique challenges in treatment and prognosis. This study aimed to develop and validate a prognostic nomogram for patients aged 18-50 years with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy, addressing the lack of tailored prognostic tools for this growing patient population.
Using the Surveillance, Epidemiology, and End Results (SEER) database, we analyzed 2,853 patients who received neoadjuvant chemoradiotherapy between 2010 and 2020. Patients were divided into training (n = 1,990) and validation (n = 863) cohorts. Cox proportional hazard regression models identified prognostic factors for overall survival (OS) and cancer-specific survival (CSS). Nomograms were constructed and validated using Harrell's C-index and receiver operating characteristic (ROC) curve analysis.
Independent predictors of poor OS and CSS included male sex, unmarried status (particularly divorced/separated/widowed), non-Hispanic black and American Indian/Alaskan native races, advanced T stage, increased positive regional nodes, and positive carcinoembryonic antigen (CEA). The nomogram demonstrated good discriminative ability in the validation cohort, with area under the curve (AUC) values of 0.767 and 0.742 for 3-year OS and CSS, respectively, and 0.705 and 0.697 for 5-year OS and CSS, respectively.
The developed nomogram and identified prognostic factors provide valuable tools for individualized risk stratification and treatment optimization in young patients with locally advanced rectal cancer. These findings can aid in clinical decision-making and patient counseling. However, further external validation and prospective evaluations are necessary to confirm the clinical utility of this prognostic model in diverse healthcare settings.

PMID:
42888297
Bibliographic data and abstract were imported from PubMed on 17 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.