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Abstract OT3-04-04: LUCY: A phase IIIb, single-arm, open-label multicenter study of olaparib in patients with HER2-negative metastatic breast cancer and a germline <i>BRCA1/2</i> mutation

2018· article· en· W2790338852 on OpenAlexaff
Karen A. Gelmon, GP Walker, G V Fisher

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsOlaparibMedicineMetastatic breast cancerInternal medicineBRCA mutationOncologyPARP inhibitorHazard ratioBreast cancerTaxaneProgression-free survivalEribulinCancerChemotherapyConfidence interval

Abstract

fetched live from OpenAlex

Abstract Background Olaparib (Lynparza) is a PARP inhibitor with activity in patients with advanced cancers who have a germline BRCA1 and/or BRCA2 (gBRCA) mutation and is licensed for use in gBRCA-mutated recurrent ovarian cancer. The Phase III OlympiAD trial (NCT02000622) in HER2-negative metastatic breast cancer (mBC) patients with a gBRCA mutation showed a significant progression-free survival (PFS) improvement in favor of olaparib compared with physician's choice of chemotherapy treatment (hazard ratio [HR] 0.58; 95% confidence interval [CI] 0.43–0.80; P<0.001; 7.0 vs 4.2 months, respectively) (Robson et al. NEJM 2017). The LUCY trial (EudraCT number: 2017-001054-34) has been initiated to further evaluate the clinical effectiveness of olaparib in a real-world setting, and to help inform and guide clinical practice. Trial design LUCY is an open-label, single-arm, multicenter, international Phase IIIb trial. All patients will be treated with open-label olaparib tablets (300 mg twice daily) until disease progression, unacceptable toxicity, or other discontinuation criteria. Eligibility criteria Eligible patients aged ≥18 years will have a gBRCA mutation and HER2-negative mBC. Patients are required to have received a prior taxane or anthracycline in either the adjuvant or metastatic setting, but should not have received >1 line of chemotherapy in the metastatic setting. Hormone receptor-positive patients are also required to have received and progressed with ≥1 prior endocrine therapy. Patients will be required to have an expected survival of >6 months. Objectives The primary objective is to evaluate the clinical effectiveness of olaparib through investigator-defined assessment of PFS (radiological, symptomatic, or clear progression of non-measurable disease). Secondary objectives will include assessments of overall survival (OS), time to first/second subsequent therapy, time to second progression and time to study treatment discontinuation, as well as assessment of clinical response rate and duration of clinical response. Safety and tolerability will also be described. Statistical methods Approximately 2500 patients will be screened to identify 250 patients with a gBRCA mutation. The primary analysis of PFS will be performed after 160 progression events: assuming a median PFS of 7 months, the predicted 95% CI for the median is 6.0–8.2 months. Analysis of OS and updated PFS will be performed after 160 deaths: assuming a median OS of 19 months, the predicted 95% CI for the median is 16.3–22.2 months. PFS and OS will be summarized using a Kaplan–Meier plot, from which the median and 95% CI data will be calculated. Present accrual Screening is expected to take place across ˜180 sites in 17 countries. Summary LUCY will provide further data on the efficacy of olaparib in the real-world setting of mBC in patients with gBRCA mutation. Citation Format: Gelmon K, Walker GP, Fisher GV. LUCY: A phase IIIb, single-arm, open-label multicenter study of olaparib in patients with HER2-negative metastatic breast cancer and a germline BRCA1/2 mutation [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr OT3-04-04.

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)0.003
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.004
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 head0.131
GPT teacher head0.470
Teacher spread0.339 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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