ArticleGland surgery2026
Development and validation of a prognostic nomogram based on the clinical indicators for breast cancer.
Article in Gland surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Breast cancer (BC) is one of the most prevalent malignancies among women worldwide, with heterogeneous outcomes necessitating individualized prognostic assessment. Existing models often rely on specialized biomarkers, limiting their accessibility in routine practice. This study aimed to develop and internally validate a prognostic nomogram based on readily available clinical indicators to predict overall survival (OS) in BC patients. Methods: In this retrospective study, 217 BC patients diagnosed between 2012 and 2015 at The First Affiliated Hospital of Soochow University and The 904th Hospital of the Joint Logistics Support Force of the People's Liberation Army were enrolled. The cohort was randomly split into training and internal validation sets. Prognostic factors were selected using least absolute shrinkage and selection operator (LASSO) regression, followed by univariate and multivariate Cox regression analyses. A nomogram was constructed based on significant predictors from the training set. Its discriminative ability and calibration were evaluated using Harrell's concordance index (C-index), calibration curves, and time-dependent area under the curve (AUC). Results: Six clinical indicators-hypertension, American Joint Committee on Cancer (AJCC) stage, metastasis, Ki-67 status, endocrine therapy, and red blood cell (RBC) count-were identified as independent prognostic factors and incorporated into the nomogram. The model demonstrated excellent discrimination, with a C-index of 0.898. In the training cohort, the AUCs for predicting 1-, 3-, and 5-year OS were 0.93, 0.89, and 0.93, respectively; corresponding values in the validation cohort were 0.98, 0.86, and 0.85. Calibration curves indicated good agreement between predicted and observed survival probabilities. Conclusions: We developed and validated a novel nomogram based on clinical indicators for predicting OS for BC, which showed good application prospect. This model has the potential to help in clinical decision-making and evaluating patient outcomes.
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.