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Record W4389430282 · doi:10.1016/j.cllc.2023.12.001

Brief Report: Updated Efficacy and Safety Data From an Integrated Analysis of Entrectinib in Locally Advanced/Metastatic ROS1 Fusion-Positive Non–Small-Cell Lung Cancer

2023· article· en· W4389430282 on OpenAlexaff
Yun Fan, Alexander Drilon, Chao‐Hua Chiu, Herbert H. Loong, Salvatore Siena, Maciej Krzakowski, Rafał Dziadziuszko, Harald Zeuner, Cloris Xue, Matthew Krebs

Bibliographic record

VenueClinical Lung Cancer · 2023
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsRoche (Canada)
FundersManchester Biomedical Research CentreNational Institutes of HealthNational Cancer InstituteNational Institute for Health and Care ResearchF. Hoffmann-La Roche
KeywordsMedicineROS1Internal medicineLung cancerOncologyAdverse effectPopulationCancerClinical trialGastroenterologyAdenocarcinoma

Abstract

fetched live from OpenAlex

•Genetic alterations in ROS1 can lead to the expression of oncogenic fusion proteins in multiple tumor types, including in 1% to 2% of non–small-cell lung cancer (NSCLC) cases. Approximately 40% of patients with ROS1 fusion-positive NSCLC have baseline central nervous system (CNS) metastases, indicating the need for a treatment with CNS activity. Entrectinib, a potent ROS1 tyrosine kinase inhibitor with activity in the CNS, has previously demonstrated overall and intracranial efficacy, and a manageable safety profile, in patients with ROS1 fusion-positive NSCLC.•In this updated analysis with 4 additional patients and longer follow-up, the objective response rate (ORR) in the efficacy-evaluable population (N = 172) was 67%; median duration of response (DoR) was 20.4 months, and median progression-free survival was 16.8 months. In 51 patients with baseline CNS metastases, intracranial ORR was 49% and median intracranial DoR was 12.9 months. In a subgroup analysis in patients who had not received any prior systemic therapy in the metastatic setting, ORR was similar to that in the efficacy-evaluable population, but median DoR was numerically longer at 35.6 months. Most treatment-related adverse events were grade 1 to 2 and nonserious.•These data reinforce previous findings on the use of entrectinib for the treatment of patients with ROS1 fusion-positive NSCLC, and support current guidelines that recommend entrectinib as a first-line treatment option for these patients, including those with baseline CNS metastases. •Genetic alterations in ROS1 can lead to the expression of oncogenic fusion proteins in multiple tumor types, including in 1% to 2% of non–small-cell lung cancer (NSCLC) cases. Approximately 40% of patients with ROS1 fusion-positive NSCLC have baseline central nervous system (CNS) metastases, indicating the need for a treatment with CNS activity. Entrectinib, a potent ROS1 tyrosine kinase inhibitor with activity in the CNS, has previously demonstrated overall and intracranial efficacy, and a manageable safety profile, in patients with ROS1 fusion-positive NSCLC.•In this updated analysis with 4 additional patients and longer follow-up, the objective response rate (ORR) in the efficacy-evaluable population (N = 172) was 67%; median duration of response (DoR) was 20.4 months, and median progression-free survival was 16.8 months. In 51 patients with baseline CNS metastases, intracranial ORR was 49% and median intracranial DoR was 12.9 months. In a subgroup analysis in patients who had not received any prior systemic therapy in the metastatic setting, ORR was similar to that in the efficacy-evaluable population, but median DoR was numerically longer at 35.6 months. Most treatment-related adverse events were grade 1 to 2 and nonserious.•These data reinforce previous findings on the use of entrectinib for the treatment of patients with ROS1 fusion-positive NSCLC, and support current guidelines that recommend entrectinib as a first-line treatment option for these patients, including those with baseline CNS metastases.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.441
Teacher spread0.404 · 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 teacher head, not a consensus.

Study designObservational
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

Citations5
Published2023
Admission routes1
Has abstractyes

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