ArticleBreast cancer research and treatment2025
Predicting the likelihood of carrying BRCA1 or BRCA2 pathogenic variants in high-risk Pakistani breast cancer patients.
Article in Breast cancer research and treatment, 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
8 authors.
Funding
Abstract
purposePathogenic variants (PVs) in BRCA1/2 increase the lifetime risk of breast cancer (BC). Predictive algorithms for BRCA1/2 PVs, primarily developed for Caucasian BC patients, often underestimate carrier probability in Asian populations. The recently developed Asian Risk Calculator (ARiCa) aims to predict BRCA1/2 PV likelihood in Malaysian/Singaporean BC patients. This study investigates the ARiCa's performance in Pakistani female BC patients.
methodsA cohort of 627 high-risk Pakistani female BC patients was evaluated. Using ARiCa, the likelihood of being a BRCA1/2 carrier was estimated based on factors such as age at diagnosis, ethnicity, bilateral BC status, tumor histopathological features, and family history of BC or ovarian cancer. The tool's discriminative ability was evaluated using the area under the curve (AUC).
resultsOf the participants, 133 (21.2%) were BRCA1 carriers, 25 (4.0%) were BRCA2 carriers, and 469 (74.8%) were non-carriers. The mean age at BC diagnosis was 34.3 years (range 19-73). Overall, ARiCa showed well calibration for predicting BRCA1/2 (HL 12.11, P = 0.147), BRCA1 (HL 14.17, P = 0.078), and BRCA2 carriers (HL 9.01, P = 0.342). The tool showed acceptable discrimination for BRCA1/2 (AUC 0.77, 95% CI 0.72-0.81) and BRCA1 carriers (AUC 0.80, 95% CI 0.75-0.84), but lower discrimination for BRCA2 carriers (AUC 0.51, 95% CI 0.39-0.64). At a 21% threshold, ARiCa would recommend BRCA1/2 screening for 43% of patients, with sensitivity and specificity at 73% and 68%, respectively.
conclusionThe ARiCa tool demonstrates strong predictive performance for BRCA1/2 carriers, specifically for BRCA1 carriers in Pakistani BC patients, suggesting its potential clinical utility.
Indexed as
Identifiers
40392478What 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.