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A phase II single-arm, open-label trial of T-DM1 (ado-trastuzumab emtansine) and neratinib for HER2-positive breast cancer with molecular residual disease (KAN-HER2 MRD).

2023· article· en· W4379328597 on OpenAlexafffund
Mitchell J. Elliott, Jesús Fuentes‐Antrás, Philippe Echelard, Nicholas Meti, Alisa Nguyen, Carolina Sanabria Salas, Christopher Gareth Smith, Moira Rushton, Lillian L. Siu, Hal K. Berman, Philippe L. Bédard, David W. Cescon

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsMcGill UniversityUniversity of TorontoToronto General HospitalUniversity Health NetworkOttawa HospitalPrincess Margaret Cancer CentreSt Mary's Hospital Centre
FundersPrincess Margaret Cancer Foundation
KeywordsNeratinibMedicineOncologyInternal medicineTrastuzumab emtansineLapatinibTrastuzumabBreast cancerClinical endpointMinimal residual diseaseAdjuvantAdjuvant therapyCancerClinical trialLeukemia

Abstract

fetched live from OpenAlex

TPS620 Background: HER2-positive breast cancer is a biologically and clinically aggressive subtype that has historically been associated with poor outcomes, but for which there are now multiple effective targeted therapies. Patients who have residual disease following standard neoadjuvant therapy have an elevated risk of metastatic recurrence. In addition, the detection of circulating tumor DNA (ctDNA) in the adjuvant period is strongly associated with relapse and can further stratify patients with residual disease. The ctDNA-based detection of molecular residual disease (MRD) is an emerging strategy to identify patients for treatment intensification, and may enable the development of novel curative treatment strategies for “recurrence interception”. Preclinical and clinical evidence support the investigation of neratinib, an irreversible inhibitor of the HER2 tyrosine kinase, in combination with standard T-DM1 in the adjuvant setting for patients with HER2-positive breast cancer and evidence of MRD. Methods: KAN-HER2 MRD is a multicentre, investigator-initiated, open label, single arm phase II trial to evaluate the addition of neratinib to standard T-DM1 in patients with detected MRD. Participants with HER2-positive breast cancer and residual disease following neoadjuvant therapy are pre-screened (Part A) for MRD using a tumor-informed assay (NeoGenomics RaDaR). Those with ctDNA detected following 2-6 cycles of adjuvant T-DM1 will proceed to the interventional phase (Part B) where neratinib is added to standard T-DM1 at the previously-determined recommended phase 2 combination dose of 160 mg/day, in continuous cycles. The primary endpoint is the rate of ctDNA clearance at 12 weeks after treatment initiation (ctDNAwk12); the study is designed with a 2-stage approach and has sufficient power to detect a clearance rate of 40%. Secondary endpoints include MRD rates and their clinical correlates, invasive disease free survival (iDFS), and safety. Bio-specimens including diagnostic biopsies, residual disease, and peripheral blood are being collected from all participants for additional correlative studies. Enrolment in Part A was initiated at the first trial site (Princess Margaret Cancer Centre) in December 2022. KAN-HER2 represents the first reported MRD-directed interception trial for HER2-positive breast cancer. Clinical trial information: NCT05388149 .

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)0.002
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0080.002

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 head0.084
GPT teacher head0.450
Teacher spread0.365 · 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 designNon-randomized trial
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

Citations1
Published2023
Admission routes2
Has abstractyes

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