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Abstract P2-08-01: Validation of a 16-gene genomic signature to identify early-stage invasive breast cancer patients who may omit radiotherapy

2022· article· en· W4220847446 on OpenAlexaff
Anthony Fyles, S. Laura Chang, Katrina Rey‐McIntyre, Wei Shi, Felix Feng, Corey Speers, Lori J. Pierce, David R. McCready, Fei‐Fei Liu

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineRadiation therapyBreast cancerBreast-conserving surgeryTamoxifenOncologyInternal medicineStage (stratigraphy)Adjuvant radiotherapyRandomized controlled trialCancerAdjuvantClinical trialMastectomy

Abstract

fetched live from OpenAlex

Abstract Background While whole breast radiotherapy has been standard of care for invasive breast cancer patients treated with breast conserving surgery, not all women may benefit from radiotherapy. Recently, we demonstrated that a 16-gene signature named Profile for the Omission of Local Adjuvant Radiotherapy (POLAR) could identify breast cancer patients with HR+, HER2- tumors treated with breast conserving surgery alone with a 10-year locoregional recurrence risk of less than 10%. Methods In this study, we apply the signature to patients enrolled in the Princess Margaret Trial, a randomized trial where patients age 50 years or older were randomized to radiotherapy and tamoxifen or tamoxifen alone after breast conserving surgery. Tissue from 132 patients with HR+, HER2- tumors were available for gene expression analysis. Results For women treated with tamoxifen alone after breast conserving surgery, POLAR identified low risk women with a 7% risk of locoregional recurrence at 10 years. Comparison to POLAR-low patients treated with adjuvant radiotherapy did not demonstrate a significant benefit from radiotherapy (HR=1.5[0.14-16], p=0.74). POLAR-high patients not treated with radiotherapy had a 22% risk of locoregional recurrence at 10 years. Comparison to POLAR-high patients treated with adjuvant radiotherapy demonstrated a significant benefit from standard radiotherapy (HR=0.25[0.07-0.92], p=0.038). Conclusions These data suggest that the POLAR genomic signature may be used to identify patients with a low risk of locoregional recurrence without significant benefit from adjuvant radiotherapy. Patients with low POLAR scores may potentially be candidates for radiation therapy omission when treated with breast conserving surgery and tamoxifen. Citation Format: Anthony Fyles, S. Laura Chang, Katrina Rey-McIntyre, Wei Shi, Felix Feng, Corey Speers, Lori Pierce, David McCready, Fei-Fei Liu. Validation of a 16-gene genomic signature to identify early-stage invasive breast cancer patients who may omit radiotherapy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-08-01.

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)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.366
Teacher spread0.335 · 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
Published2022
Admission routes1
Has abstractyes

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