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Ceritinib plus nivolumab (NIVO) in patients (pts) with anaplastic lymphoma kinase positive (ALK+) advanced non-small cell lung cancer (NSCLC).

2017· article· en· W2643935873 on OpenAlexaff
Enriqueta Felip, Filippo de Braud, Michela Maur, Herbert H. Loong, Alice T. Shaw, Johan Vansteenkiste, Geoffrey Liu, Martijn P. Lolkema, Jeffrey W. Scott, Richard Yu, Giovanni Selvaggi, Kaushal Mishra, Yi-Yang Yvonne Lau, Daniel Shao-Weng Tan

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineInternal medicineCeritinibAnaplastic lymphoma kinaseMaculopapular rashGastroenterologyRashNivolumabLung cancerOncologyCancerImmunotherapy

Abstract

fetched live from OpenAlex

2502 Background: Induction of PD-L1 expression due to constitutive oncogenic signaling has been reported in NSCLC models harboring EML4–ALK rearrangements. Here we explore whether the combination of ALKi (ceritinib) and PD1-inhibitor (NIVO) will provide sustained clinical benefit to pts with ALK+ NSCLC. Methods: This phase 1 dose escalation study enrolled previously treated (ALK inhibitor [ALKi] or chemotherapy) or tx-naive pts with stage IIIB/IV ALK+ NSCLC; who received NIVO 3 mg/kg IV Q2W + ceritinib with low-fat meal, at 450 mg/day (group 1) or 300 mg/day (group 2) until progression/unacceptable toxicity. Primary objective: MTD/recommended dose for expansion. Dose escalation was guided by Bayesian logistic regression model with overdose control. Results: Median follow-up: group 1 (n = 14) 13 mos (10-15); group 2 (n = 22) 6 mos (2-10). As of 9 Sep 2016, 16/36 (44%) pts discontinued tx: disease progression (11 [31%] pts), AE’s (3 [8%] pts), and death (2 [6%] pts). In group 1, 4 pts experienced DLT: pancreatitis (n = 2), lipase and transaminase increase (n = 1), and autoimmune hepatitis (n = 1). In group 2, 2 pts experienced DLT: G3 ALT increase. Both dose levels met Bayesian criteria for dose expansion. Overall most frequent (≥40%) AEs (n = 36), were diarrhea (64%), ALT increase (56%), AST increase (44%) and vomiting (42%). Most frequent ( > 10%) grade ≥3 AEs were increases in ALT (22%), GGT (17%), amylase (11%), and lipase (11%), and maculopapular rash (11%). Incidence of rash (grouped term) was 61%; similar in both groups. Grade 3 rash was reported in 29% pts in group 1 and 14% pts in group 2. Preliminary ceritinib steady state PK (AUC0-24 and Cmax) suggested that 300 mg/day exposure was ~ 70-75% of 450 mg/day. Confirmed (c)/unconfirmed (u) ORR: ALKi-pretreated pts (group 1 [n = 8], group 2 [n = 12]) was 63% (4 cPR,1 uPR; 95% CI: 25%, 92%), and 33% (4 uPR) 95% CI: 10%, 65%) respectively; ALKi-naïve pts, (group 1 [n = 6], group 2 [n = 10]) was 83% (5 cPR; 95% CI: 36%, 100%), and 70% (1 cCR, 3 cPR 3uPR; 95% CI: 35%, 93%) respectively. Conclusions: Ceritinib + NIVO is an active combination in ALK+ NSCLC. However, the protocol will be amended to address observed toxicities. Data will be updated for presentation. Clinical trial information: NCT02393625.

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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.424
Teacher spread0.397 · 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

Citations37
Published2017
Admission routes1
Has abstractyes

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