ArticleExploration of targeted anti-tumor therapy2026
Survival prediction in triple-negative breast cancer: a Cox model with fairness assessment using ISO/IEC TR 24027:2021 in a MENA cohort.
Article in Exploration of targeted anti-tumor therapy, 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: Triple-negative breast cancer (TNBC) is an aggressive subtype with limited therapeutic options and poor survival outcomes. Prognostic models developed in Western cohorts rarely assess algorithmic fairness. This study aimed to develop and internally validate a clinically interpretable Cox survival model for TNBC using baseline diagnostic variables and to evaluate its fairness according to ISO/IEC TR 24027:2021 guidelines in a Middle East and North Africa (MENA) cohort. Methods: A total of 138 TNBC patients were included after merging two institutional datasets and removing variables with > 25% missingness. Baseline features comprised age, tumor size, lymph node involvement, tumor grade, Ki-67, type of surgery, metastasis at diagnosis, chemotherapy, and radiotherapy. A Cox proportional hazards (CoxPH) model with six clinically established predictors was fitted to reduce overfitting. Model performance was assessed through five-fold stratified cross-validation using Harrell's concordance index (C-index), receiver operating characteristic area under the curve (AUROC), and calibration curves. Fairness was evaluated using demographic parity, equality of opportunity, predictive equality, and equalized odds metrics following ISO/IEC TR 24027:2021. Results: During follow-up, 34 patients (24.6%) died. Metastasis at diagnosis, high tumor grade, and radical mastectomy were significantly associated with mortality. The CoxPH model achieved a C-index of 0.80 [SE = 0.04; 95% confidence interval (CI): 0.72-0.87] and an AUROC of 0.81 (95% CI: 0.72-0.90). Calibration plots showed strong agreement between predicted and observed survival probabilities, with a modest overall bias of -8.8%. Fairness assessment revealed small but notable disparities in false-positive rates across age groups and surgical categories, while lymph node status and other variables showed no significant bias. Conclusions: This study presents a robust and fairness-aware survival prediction model for TNBC using routinely available clinical features. The model demonstrates strong discrimination, good calibration, and quantifiable fairness across patient subgroups, offering a clinically interpretable and ethically aligned tool to support TNBC risk stratification and decision-making in the MENA region.
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.