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Abstract P6-01-10: Prognostic significance of breast cancer index (BCI) in node-positive hormone receptor positive early breast cancer: NCIC CTG MA.14

2015· article· en· W1500798294 on OpenAlexaff
Dennis C. Sgroi, Paul E. Goss, Judy-Anne Chapman, Elizabeth Richardson, Shemeica Binns, Yi Zhang, Cathy Schnabel, Mark G. Erlander, K.I. Pritchard, Lei Han, Lois Sheperd, Michael Pollack

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsMcGill UniversityUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBreast cancerOncologyInternal medicineProportional hazards modelTamoxifenCancer

Abstract

fetched live from OpenAlex

Abstract Background: The continuous linear Breast Cancer Index (BCI) risk index combines the ratio of genes HOXB13 to IL17BR (H/I) and the molecular grade index (MGI) (Zhang et al, Clinical Cancer Research, 2013). The BCI signature was developed for node-negative breast cancer patients treated with tamoxifen. We examine here whether linear BCI is prognostic for node-positive hormone-receptor positive tamoxifen-treated patients. Methods: MA.14 randomly assigned 667 hormone positive (HR+), postmenopausal women to 5 years of tamoxifen (TAM) +/- 2 years of octreotide LAR (TAM-OCT). A representative subgroup of 299 patients underwent gene expression profiling by RT-PCR for linear BCI. We performed exploratory analyses restricted to node positive patients. The primary objective was to assess the prognostic effect of BCI on relapse-free survival (RFS). RFS was defined as the time from randomization to the time of recurrence of the primary disease alone, including local and ipsilateral nodal recurrence and metastatic disease, and censoring at longest follow-up or death from another cause. With a median 9.8 years follow-up, the association of BCI with RFS was assessed by multivariate Cox regression including treatment, stratification factors (other than nodal status), and baseline patient and tumor characteristics. Patients were defined to be low risk based on BCI if the adjusted Cox survival was >95%, where adjustment was by trial treatment, stratification factors, and baseline patient and tumor characteristics, including IGF-1, IGFBP-3, and C-peptide. Results: 292 of 299 patient samples passed internal analytical quality control; 116 node positive ER+ve patients had 34 (29.3%) relapses, with adjusted Cox survival at 9.6 years of 87.8%. Fifty-two of the 116 patients (45%) did not receive adjuvant chemotherapy, and experienced 11 (21%) RFS events. In the 116 patients, higher continuous BCI value was associated with shorter RFS (p=0.002): hazard ratio (HR) 1.49 (95% CI 1.16-1.91). Smaller pathologic T had significantly (p=0.03) better RFS HR=0.39, (95%CI 0.17-0.90). With MA.14 patient mean BCI of 5.09532, Cox survival at 4.1 years was 95.2%; 17/34 (50%) who recurred had failed by this time. Discussion: In this subgroup analysis, we found that BCI and tumor size were significant prognostic factors for node-positive hormone-receptor positive patients who were treated with tamoxifen. Citation Format: Dennis Sgroi, Paul Goss, Judy-Anne Chapman, Elizabeth Richardson, Shemeica Binns, Yi Zhang, Cathy Schnabel, Mark Erlander, Kathy Pritchard, Lei Han, Lois Sheperd, Michael Pollack. Prognostic significance of breast cancer index (BCI) in node-positive hormone receptor positive early breast cancer: NCIC CTG MA.14 [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-01-10.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.343
Teacher spread0.309 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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