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Abstract PO2-08-07: Evaluating chemotherapy receipt and candidacy for PARP inhibitors in germline BRCA1/2 carriers with early and locally advanced breast cancer

2024· article· en· W4396588053 on OpenAlexaff
Stephanie M. Wong, Carla Apostolova, Amina Ferroum, Basmah Alhassan, Ipshita Prakash, Mark Basik, Karyne Martel, Sarkis Meterissian, David Fleiszer, Nora Wong, Talía Malagón, William D. Foulkes, Jean-François Boileau

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsCandidacyGermlineOncologyMedicineReceiptBreast cancerInternal medicineChemotherapyCancerBiologyGeneticsPolitical science

Abstract

fetched live from OpenAlex

Abstract Introduction: While enhanced breast screening of germline BRCA1/2 carriers results in earlier stage at diagnosis, the impact of tumour biology and BRCA mutation on chemotherapy receipt in early stage disease remains understudied. Methods: We retrospectively reviewed treatment administered following a first diagnosis of BRCA1/2-associated breast cancer between 2003-2023 at our institution. Chemotherapy receipt (neoadjuvant or adjuvant) was evaluated according to tumor size, biologic subtype, and BRCA mutation. Current guidelines for PARP inhibitor use were applied to estimate the proportion of affected BRCA1/2 carriers that would be deemed eligible for targeted therapy in the future. Results: Overall, 251 affected BRCA1/2 carriers were included; 137 (54.6%) BRCA1 (median age 40 years, range 19-72) and 114 (45.4%) BRCA2 (median age 43, range, 24-80 years). Chemotherapy was administered in 70.1% of index breast cancer cases and was significantly associated with clinical tumor size (36.7% T1a-T1b, 90.9% T1c, 95.2% T2, 95.3% T3-T4, p< 0.001), nodal status (71.8% cN0 vs. 100% cN1-2, p=0.004), and biologic subtype (90.0% TNBC vs. 75.0% ER+HER2-, p=0.02). BRCA1-associated breast cancers were less likely to present with DCIS or T1 tumours (%Tis/T1; 46.7% BRCA1 vs. 70.8% BRCA2, p< 0.001) and more likely to present with triple negative disease (71.4% BRCA1 vs. 24.6% BRCA2, p< 0.001). BRCA1 carriers were more likely to require chemotherapy for index breast cancer (81.8% BRCA1 vs. 56.1% BRCA2, p< 0.001). In subgroup analysis of early stage, T1N0 disease, chemotherapy was administered in 79.0% BRCA1 and 52.2% BRCA2 patients (p=0.03). If recent guidelines incorporating biologic subtype, nodal involvement, and response to neoadjuvant chemotherapy were retrospectively applied to the cohort, 33.6% would be deemed eligible for PARP inhibitors in the adjuvant setting, including 40.9% BRCA1 and 17.5% BRCA2 affected carriers (p < 0.001). Conclusion: Chemotherapy receipt is high in BRCA-associated breast cancers including in early stage, node-negative disease. Overall, one third of affected carriers are expected to be eligible for PARP inhibitors in the adjuvant setting. Future studies exploring how this information may impact decisions around risk-reducing mastectomy are warranted. Citation Format: Stephanie Wong, Carla Apostolova, Amina Ferroum, Basmah Alhassan, Ipshita Prakash, Mark Basik, Karyne Martel, Sarkis Meterissian, David Fleiszer, Nora Wong, Talia Malagon, William Foulkes, Jean-Francois Boileau. Evaluating chemotherapy receipt and candidacy for PARP inhibitors in germline BRCA1/2 carriers with early and locally advanced breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-08-07.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.403
Teacher spread0.373 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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