ArticleAmerican journal of cancer research2025
Construction and validation of a Cox regression-based nomogram model for predicting recurrence risk in early endometrial cancer.
Article in American journal of cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo develop and validate a Cox regression-based nomogram model for predicting recurrence risk in early-stage endometrial cancer.
methodsWe retrospectively analyzed 1,540 patients with FIGO stage I-II disease treated between January 2013 and December 2021, of whom 247 (16.04%) experienced recurrence and 1,293 did not. Key predictive factors were identified using Lasso-Cox regression, and a nomogram was constructed and evaluated in training (n=924), validation (n=308), and testing (n=308) cohorts.
resultsThe model demonstrated strong discriminative ability, with C-index values of 0.748, 0.684, and 0.677, and AUCs of 0.767, 0.701, and 0.694 across the three cohorts. Compared with the traditional Naples Prognostic Score, the nomogram showed significantly better performance in both the training cohort (AUC 0.767 vs. 0.687, P=0.009) and the validation cohort (AUC 0.701 vs. 0.580, P=0.041). Calibration curves showed good agreement between predicted and observed outcomes, and decision curve analysis confirmed substantial net clinical benefit, with net reclassification improvement supporting superior accuracy.
conclusionsThe developed nomogram provides a reliable and effective tool for individualized recurrence risk assessment in early-stage endometrial cancer, demonstrating significant clinical potential for improved risk prediction and treatment planning.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.