ArticleActa oncologica (Stockholm, Sweden)2025
Predicting neoadjuvant chemotherapy treatment response in hormone- receptor-positive/HER2-negative breast cancer - results from the Swedish SCAN-B population-based cohort.
Article in Acta oncologica (Stockholm, Sweden), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Simultaneous Preoperative Prediction of Locally Advanced Breast Cancer, DCIS Component, and Multifocality Using Structured Mammographic Features and Gradient-Boosting Machine Learning.Diagnostics (Basel, Switzerland) · 2026Article
- Letter to the Editor "Adjuvant ovarian function suppression and aromatase inhibitors in premenopausal patients with hormone receptor-positive, HER2-positive breast cancer".Breast (Edinburgh, Scotland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeHormone-receptor-positive/HER2-negative (HR+/HER2-) early-stage breast cancers (EBCs) display heterogenous responses to neoadjuvant chemotherapy (NACT) warranting biomarkers to tailor optimal treatment for individual patients. PATIENTS/MATERIAL AND
methodsWomen with HR+/HER2- EBC (N = 178) included in the Swedish Sweden Cancerome Analysis Network-Breast (SCAN-B) population-based cohort (2010-2019) treated with NACT were included. We analyzed rates of pathologic complete response (pCR), objective response (OR), breast conserving surgery (BCS), and recurrence-free interval (RFI) in subgroups defined by baseline clinicopathological and molecular characteristics.
resultsThe pCR rate was low (6%); nonetheless, after a median follow-up of 5.41 years, all patients who achieved pCR remained recurrence-free despite uniform baseline predicted high PAM50 risk of recurrence (ROR). Younger age (≤ 40 years), cT1, ER% positivity (≤ 66%), and negative PR (≤ 10%) were conventional clinicopathological factors positively associated with increased pCR. Molecular predictors of pCR included negative HR status by gene-expression signatures and non-luminal PAM50 subtypes. Tumor shrinkage ≥ 30%, i.e., OR and BCS, was achieved in 59% and 34%, respectively. No factor was significantly associated with ORR, whereas non-lobular histology and cT1 were positively associated with BCS. In addition, only 1/49 patients who underwent BCS experienced a recurrence during follow-up. Low/intermediate ER% positivity, PR negativity, and non-luminal PAM50 subtype were baseline factors univariately prognostic for inferior long-term outcome in case of residual disease.
interpretationBaseline characteristics indicative of reduced hormonal signaling and non-luminal tumor biology assessed more precisely using mRNA profiling can guide optimal tailoring of NACT for patients with high-risk HR+/HER2-tumors. Baseline molecular biology did not predict surgical outcomes following NACT.
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.