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Abstract P5-20-12: Adjuvant DCH vs TCH for low-risk (node negative); and FECDH vs TCH for high-risk (node positive) HER2+ breast cancer – A retrospective provincial analysis

2018· article· en· W2793372579 on OpenAlexaffabout
ZW Veitch, OF Khan, D G Tilley, Xanthoula Kostaras, PA Tang, Karen King, Sasha Lupichuk

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsUniversity of AlbertaAlberta Health Services
Fundersnot available
KeywordsMedicineBreast cancerTrastuzumabInternal medicineOncologyCohortRegimenGynecologyCancerProportional hazards model

Abstract

fetched live from OpenAlex

Abstract Background: Chemotherapy plus trastuzumab for early HER2+ breast cancer (BC) is associated with improved survival. Optimal regimens for low-risk (node negative) and high-risk (node positive) HER2+ breast cancers are unknown and choice of regimen varies in real-world clinical practice. Objective: (1) For low-risk breast cancer, to compare DCH (4 cycles) and TCH (6 cycles) in terms of disease free (DFS) and overall survival (OS). (2) For high-risk breast cancer, to compare FECDH (6 cycles) and TCH (6 cycles) in terms of DFS and OS. Methods: All women diagnosed from 2007-2014 with stage I-III, hormone receptor (HR) +/-, HER2+ BC receiving adjuvant chemotherapy plus trastuzumab (n=986) in Alberta, Canada were included. Patients with low-risk (node negative) disease were stratified into DCH (n=104) or TCH (n=360) cohorts for DFS/OS comparison (Kaplan-Meier). Patients with high-risk (node positive) disease were stratified into FECDH (n=145) or TCH (n=314) cohorts. Subgroup analysis of the high-risk cohorts by HR+/HER2+ and HR-/HER2+ for FECDH vs TCH were performed. Chi-square was used to evaluate for difference between cohort variables. Low- Risk Cohort DCH TCH n (104)%n (360)%Age (mean)55.3 53.0 Hormone Status ER+ or PR+8682.727676.7ER and PR-1817.38423.3Grade 121.951.423230.88523.637067.327075.0Surgery lumpectomy525010830.5mastectomy525024669.5 High-Risk Cohort FECDH TCH n (145)%n (314)%Age (mean)50.2 53.6 Hormone Status ER+ or PR+11579.323875.8ER and PR-3020.77624.2Grade 10051.6229206119.631168014678.8Surgery lumpectomy3927.19831.2mastectomy10572.921668.8Node Status N18357.219461.8N24128.37323.2N32114.54715 Results: Median follow-up was 58.1 months in the low-risk cohort and 63.1 months in the high-risk cohort. In the low-risk group, patients receiving TCH had more mastectomy (69.5%) than lumpectomy (30.5%; p<0.001) compared to those receiving DCH (50%; 50%). No significant difference was seen in DFS (p=0.153) or OS (p=0.409) for patients in the DCH (92.3%; 95.2%) vs TCH (95.2%; 96.9%) cohorts. In the high-risk group, no significant difference was seen in DFS (p=0.226) or OS (p=0.164) for FECDH (92.4; 95.2%) or TCH (88.5%; 91.4%) respectively. In subgroup analysis of high-risk HR+/HER2+ BC, patients receiving FECDH demonstrated superior OS (98.3%; p=0.014) and a trend towards superior DFS (94.8%; p=0.069) relative to TCH patients (OS = 91.6%; DFS= 88.7%). Conversely, analysis of high-risk HR-/HER2+ BC, patients demonstrated higher DFS and OS for TCH (88.2%; 90.8%) relative to FECDH (83.3%; 83.3%); although this was non-significant (p=0.516; p=0.298) and likely underpowered. Nodal status was balanced between all groups (p=0.602). Conclusion: In low-risk HER2+ BC, 4 cycles of DCH chemotherapy has high survival with similar outcomes to 6 cycles of TCH. In high-risk HER2+ BC, FECDH has comparable outcomes to TCH consistent with BCIRG-006. This study suggests that women with HR+/HER2+ breast cancer have improved OS with anthracycline containing regimens, such as FECDH. Although non-significant, patients with HR-/HER2+ BC may have some improvement in DFS and OS with TCH, a carboplatin containing regimen. Citation Format: Veitch ZW, Khan OF, Tilley D, Kostaras X, Tang PA, King K, Lupichuk S. Adjuvant DCH vs TCH for low-risk (node negative); and FECDH vs TCH for high-risk (node positive) HER2+ breast cancer – A retrospective provincial analysis [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-20-12.

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)0.001
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 score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.015
GPT teacher head0.339
Teacher spread0.324 · 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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