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A phase II study of rucaparib in patients with high genomic LOH and/or BRCA 1/2 mutated stage IV non-small cell lung cancer (Lung-MAP Sub-Study, S1900A).

2021· article· en· W3171070684 on OpenAlexaff
Jonathan W. Riess, Mary W. Redman, Paul Wheatley‐Price, Bryan A. Faller, Liza C. Villaruz, Larry Corum, Aruna Gowda, Gordan Srkalović, Raymond U. Osarogiagbon, Megan Baumgart, Lu Qian, Katherine Minichiello, David R. Gandara, Roy S. Herbst, Karen Kelly

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Institutes of Health
KeywordsMedicineInternal medicineOncologyCohortLung cancerCancerInterim analysisStage (stratigraphy)PARP inhibitorClinical trialGeneticsPoly ADP ribose polymerase

Abstract

fetched live from OpenAlex

9024 Background: While prior studies have shown robust efficacy leading to FDA approval of PARP inhibitors (PARPi) in BRCA-associated cancers, data in NSCLC are much less clear. S1900A, a LUNG-MAP substudy, evaluated the PARPi rucaparib in advanced stage NSCLC harboring BRCA1/2 mutations or genomic loss of heterozygosity (LOH) as a phenotypic marker of homologous recombination deficiency (HRD). Methods: Eligible patients (pts) were required to have a deleterious mutation in BRCA1/BRCA2 and/or high (≥21%) genomic LOH. Key eligibility criteria: advanced NSCLC patients (pts) with progression on or after platinum based chemotherapy and/or PD-(L)1 antibody and progressed on most recent line of systemic therapy, a Zubrod performance status of 0-1, adequate organ function, no ≥ grade 3 hypercholesterolemia, no previous PARPi exposure and no systemic therapy within 21 days of registration. Pts stratified by histology into two cohorts (squamous [sq] and non-squamous/mixed histology [nsq]). With 40 eligible pts per cohort, the design had 91% power to rule out an ORR of 15% if the true ORR was at least 35% at the 1-sided 5% level. A planned interim analysis on the first 20 pts evaluable for response per cohort required ≥ 3 responses to proceed to full enrollment. Results: 64 pts enrolled (27 sq cohort; 37 nsq cohort) of whom 59 are eligible. Median age 65.7 yrs; M/F 33/26 (56/44%); 98% of the pts received at least 1 prior line of treatment for stage IV disease. Biomarker selection included 36 pts (61%) LOH only, 4 pts (7%) BRCA1 only, 11 pts (19%) BRCA2 only, 4 pts (7%) BRCA1 + LOH high and 4 pts (7%) BRCA2 + LOH high. Both cohorts were closed for futility with insufficient responses in the interim analysis populations. In the full study, 4 responses (3 nsq/1 sq) were reported. ORR was 7% (95% CI: 0-13) (9% nsq/4% sq) and DCR was 62% (95% CI: 50-75) (62% nsq/64% sq); 3 of the 4 responders harbored BRCA1/2 mutations and 1 of 4 high LOH; ORR in BRCA1/2+ pts 3/23 (13%). Median PFS was 3.2 months (95% CI: 1.6-4.6) in nsq cohort and 2.9 months (95% CI 1.6-6.2) in sq cohort. Median OS was 7.8 months in nsq cohort and 7.9 months in sq cohort. The most frequent grade ≥3 adverse events were anemia (22%), lymphopenia (8%), fatigue (8%) and transaminitis (5%). Conclusions: S1900A failed to show the requisite level of efficacy for rucaparib in advanced NSCLC pts with high genomic LOH and/or a BRCA1/2 mutation. There were no new safety signals and hematologic toxicities were the most frequent adverse events. Genomic LOH as a phenotypic marker of HRD does not predict sufficient activity of rucaparib in NSCLC. These results stand in contrast to the high level of efficacy of PARPi in patients with BRCA-associated or high LOH cancers of other tumor types. Underlying biologic differences in the genomic characteristics of these cancers vs. NSCLC may be responsible. Studies examining this premise are ongoing. (NCT03845296). Clinical trial information: NCT03845296.

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)0.001
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.059
GPT teacher head0.439
Teacher spread0.380 · 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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Citations10
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of Clinical OncologySame topicPARP inhibition in cancer therapyFrench-language works237,207