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Patterns of early and late recurrence across breast cancer subtypes in the CCTGMA.32 trial.

2025· article· en· W4410808887 on OpenAlexafffund
Ana Elisa Lohmann, Bingshu E. Chen, Wendy R. Parulekar, Katarzyna J. Jerzak, Pamela J. Goodwin

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalSunnybrook Health Science CentreWestern University
FundersCanadian Cancer Society Research InstituteApotex
KeywordsMedicineBreast cancerCancerOncologyCancer recurrenceInternal medicine

Abstract

fetched live from OpenAlex

534 Background: An ongoing constant risk of recurrence out to 20 years is well established in hormone receptor positive breast cancer (BC) less so in other BC subtypes. This study aims to describe patters of early (≤ 5 years of BC diagnosis) and late recurrence (> 5 years of BC diagnosis) across immunohistochemically defined BC subtypes - luminal (ER/PgR+HER2-), triple negative (TN: ER/PgR/HER2-) and HER2+ (any ER/PgR) in CCTGMA.32 (NCT01101438) which investigated metformin vs placebo in patients enrolled 2010-2013. Methods: 3649 patients with high-risk non-metastatic BC were enrolled and followed for first locoregional and distant recurrence, new primary cancers and death. Annual rates of these events were calculated in each BC subtype and averaged for early (years 0-5) and late (after 5 years) post randomization. Results: In luminal (n = 2104), TN (n = 925), HER2+ (n = 620) BC the median follow-ups were 96.2 (range 0.2 to 120.7), 94.5 (0.03 to 120.5), 95.2 months (0.03 to 119.8), respectively. Patterns of events varied across subtypes and early vs late. In luminal BC, the early vs late annual invasive cancer event rates (ICERs) was 3.04 vs. 2.31 % (late rate 0.76 of early rate). The annual early vs late rates of distant recurrence (DR) were 2.33 vs 1.72% (late rate 0.74 of early rate). Bone was the most common site of DR both early and late. In the TN BC, the early vs late annual ICERs were 4.6 and 1.21% (late rate 0.35 of early rate). Annual early vs late DR rates were 3.09 vs. 0.20 % (late rate 0.28 of early rate). Visceral metastases (lung, liver, CNS) were most common early. In HER2+, early vs late annual ICERs were 2.93 vs 1.47% (late rate 0.50 of early rate). Annual early vs late DR rates were 2.25 vs 0.71% (late rate 0.32 of early rate). Bone and visceral metastases were common early. CNS was rare after 5 years in all BC subtypes. Second primary cancers (new BC and non-primary BC) were frequent across BC subtypes, with no fall-off over time; they were responsible for the majority of late events in TN and HER2+ BC. Conclusions: In luminal BC, risk of late ICER remains high (annual rate about three-quarters of early rate), while risk of late events was lower in TN and HER2+BC (late rates one quarter to one-third of early rates). Risk of second primary cancers did not decrease over time, and second primaries were the most frequent late events in TN and HER2+BC. Clinical trial information: NCT01101438 . Luminal TN HER2+ Annual event rate (%) Annual event rate (%) Annual event rate (%) Year 0-5 Year 5+ Year 0-5 Year 5+ Year 0-5 Year 5+ Any Invasive Cancer Event 3.04 2.31 4.60 1.21 2.93 1.47 Locoregional Event 0.50 0.29 1.15 0.26 0.64 0.15 Distant Recurrence* 2.08 1.29 3.09 0.20 2.03 0.57 Sites of First Metastasis: Bone 1.40 0.88 1.13 0.10 0.65 0.42 Lung 0.59 0.56 1.73 0.20 0.83 0.07 Liver 0.71 0.56 0.73 0.00 0.50 0.21 CNS 0.18 0.06 0.65 0.00 0.61 0.00 Second Primary Cancer** 0.66 0.92 0.96 0.90 0.60 0.74 *Including distant recurrence after a local regional events. **Non-breast cancer and new breast cancer events.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.462
Teacher spread0.402 · 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
Published2025
Admission routes2
Has abstractyes

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