ArticleScientific reports2025
Development and validation of a postoperative prognostic model for hormone receptor positive early stage breast cancer recurrence.
Article in Scientific reports, 2025. 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
13 authors.
Funding
Abstract
Predicting recurrence among early-stage hormone receptor-positive human epidermal growth factor receptor-negative breast cancer (HR+/HER2- BC) is crucial for guiding adjuvant therapy. However, studies are limited for patients with low recurrence risk. HR+/HER2- early-stage (T1-2N0-1) invasive BC patients who received definitive surgery and followed by endocrine therapy from four independent medical centers were included in this retrospective study. Patients from center 1 were used as derivation cohort, while those from other centers were combined as an external test cohort. A deep learning prognostic model, HERPAI, was developed based on Transformer to predict risk of invasive disease-free survival (iDFS) utilizing clinical and pathological predictors. The model performance was evaluated using C-index for the overall population and subgroups. Threshold for selecting 5-year recurrence risk > 10% was determined. Hazard ratio (HR) was estimated between risk groups for iDFS. A total of 6340 patients were included, of whom 5424 were assigned to the derivation cohort (training and validation [N = 4882] and internal test cohort [N = 542]), while 916 patients were utilized as external cohort. HERPAI yielded a C-index of 0.73 (95% CI 0.65-0.81), 0.73 (95% CI 0.62-0.85), and 0.68 (95% CI 0.60-0.77), in the validation, internal, and external test cohort, respectively. Consistent performances were observed for pre-specified subgroups. High-risk patients were associated with an increased risk of recurrence for validation (HR, 2.56 [95% CI 1.25-5.22], P = 0.01), internal test (HR, 2.52 [95% CI 0.97-6.57], P = 0.06) and external test (HR, 1.94 [95% CI 1.00-3.74], P = 0.049) cohort, respectively. HERPAI was a promising tool for selecting vulnerable early-stage HR+/HER2- BC patients who were at high-risk of recurrence. It could facilitate the prioritization of patients who may benefit more from escalating adjuvant treatment.
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.