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OT1-02-02: HALT MBC: HER2 Suppression with the Addition of Lapatinib to Trastuzumab in HER2−Positive Metastatic Breast Cancer (LPT112515).

2011· article· en· W2051827896 on OpenAlexaboutno aff
Nong Lin, Michael A. Danso, A David, Joseph J. Muscato, Christopher Ellis, Michelle DeSilvio, Amanda Garofalo, Yasir M. Nagarwala, EP Winer

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsnot available
Fundersnot available
KeywordsLapatinibTrastuzumabMedicineMetastatic breast cancerInternal medicineOncologyBreast cancerDiscontinuationPaclitaxelCancerChemotherapy

Abstract

fetched live from OpenAlex

Abstract Background Lapatinib in combination with trastuzumab enhanced anti-tumor activity in HER2−positive breast cancer (BC) preclinical models. In patients (pts) with trastuzumab-treated, HER2−positive metastatic (M) BC, treatment with the combination was associated with longer progression-free (PFS) and overall survival (OS) compared with lapatinib alone. In pts with stage II/III BC, preoperative treatment with the combination plus paclitaxel resulted in significantly higher pathological complete response rates compared with paclitaxel combined with either agent alone. This evidence supports the concept of dual HER2 blockade as a treatment strategy for HER2−positive BC. This present study is designed to evaluate whether the addition of lapatinib improves PFS among women with HER2−positive MBC receiving trastuzumab as maintenance therapy. Trial Design In this open-label, Phase III study, pts are stratified by line of treatment (first/second) and hormone receptor status (positive/negative) then randomized 1:1 to receive maintenance treatment with either lapatinib (1000mg once daily, continuously) in combination with trastuzumab (6mg/kg once every 3 weeks [Q3W]) or trastuzumab (6mg/kg Q3W) alone. Pts will receive study treatment until disease progression, death, discontinuation due to adverse events or other reasons. Eligibility Criteria Pts with HER2−positive MBC who have completed 12–24 weeks of first- or second-line treatment with trastuzumab plus chemotherapy and have objective response or stable disease. Pts with stable brain metastasis are eligible if entering the study on second-line treatment. Specific Aims The primary objective is to compare PFS of lapatinib in combination with trastuzumab to trastuzumab as continued HER2 suppression therapy. Secondary objectives are to evaluate OS, clinical benefit rate, safety and tolerability. Statistical Methods Efficacy endpoints will be analyzed in the intent to treat population. A total of 193 PFS events from 280 randomized pts will be required to detect a 50% increase in median PFS in pts who receive lapatinib plus trastuzumab compared with trastuzumab (median PFS time is 27 versus 18 weeks, respectively); hazard ratio of 0.67 with an 80% power and a 1-sided type I error of 0.025. Present and Target Accrual Sixteen of the target 280 pts have been randomized. The trial is currently open for accrual in the United States and Canada. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr OT1-02-02.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.138
GPT teacher head0.451
Teacher spread0.313 · 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 designRandomized 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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