A validated clinical calculator of a brain metastasis risk (BrMR) prediction model in stage I-III breast cancer patients

Clicks: 10
ID: 331867
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #312 of 380 articles by views in JNCI Journal of the National Cancer Institute

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 380 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Abstract Background Brain metastasis (BM) significantly affects survival and quality of life in patients with breast cancer. A validated tool to predict BM risk at diagnosis of early breast cancer (eBC) could enable targeted surveillance and improve patient selection for clinical trials. Methods Patients with stage I-III eBC diagnosed from January 1, 1997, to May 6, 2020, at The University of Texas MD Anderson Cancer Center were reviewed as a training cohort. After data curation and multiple imputation of missing values, a linear predictive model (Brain Metastasis Risk [BrMR]) was developed and implemented as an online calculator. The model was applied to an independent validation cohort of stage I-III patients referred to Institut Jules Bordet, Belgium, from 2001 to 2021. Results BM occurred in 2408 of 40 282 training-cohort patients and 35 of 1644 validation-cohort patients. BrMR showed strong discrimination (C-index = 0.79, training; 0.76, validation), with areas under the receiver operating characteristic curve of 0.81, 0.79, 0.76, and 0.75 at 4, 6, 8, and 10 years, respectively. Inflammatory breast cancer, HER2 positivity, higher Ki-67, lymphovascular invasion, adjuvant chemotherapy, grade III, and higher T/N-status were associated with increased BM risk; ER/PR positivity, older age, endocrine therapy, lobular histology, grade II, and lower T-status were associated with decreased risk. Conclusions BrMR accurately predicts BM risk in eBC and may support risk stratification and trial enrichment. Prospective validation is needed before clinical use as a surveillance tool.
Reference Key
openalex_W7221064866 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Akshara Singareeka Raghavendra, Nuria Kotecki, Kristofer Jennings, Ottavia Amato, Ahmad Hussein Awada, Nuhad K. Ibrahim
Journal JNCI Journal of the National Cancer Institute
Year 2026
DOI
10.1093/jnci/djag377
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.