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Record W4323294773 · doi:10.2217/fon-2022-1059

TRUST-II: a global phase II study of taletrectinib in <i>ROS1</i> -positive non-small-cell lung cancer and other solid tumors

2023· article· en· W4323294773 on OpenAlexaff
Misako Nagasaka, Yuichiro Ohe, Caicun Zhou, Chang‐Min Choi, Nong Yang, Geoffrey Liu, Enriqueta Felip, M. Pérol, Benjamin Besse, Jorgé Nieva, Luis E. Raez, Nathan A. Pennell, Anastasios Dimou, Filippo de Marinis, Fortunato Ciardiello, Takashi Seto, Zheyi Hu, Max Yu-Chen Pan, Weiqing Wang, Shuanglian Li, Sai‐Hong Ignatius Ou

Bibliographic record

VenueFuture Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsCrizotinibROS1MedicineLung cancerInternal medicineOncologyCancerBrain metastasisClinical trialInterim analysisClinical endpointAdverse effectAdenocarcinomaMetastasis

Abstract

fetched live from OpenAlex

Crizotinib and entrectinib have been approved to treat ROS1 fusion-positive (ROS1+) non-small-cell lung cancer. However, unmet needs remain, including treatment of patients with resistance mutations, efficacy in brain metastasis and avoidance of neurological side effects. Taletrectinib was designed to: improve efficacy; overcome resistance to first-generation ROS1 inhibitors; and address brain metastasis while conferring fewer neurological adverse events. All of these features are demonstrated and supported by the interim data from the regional phase II TRUST-I clinical study. Here we describe the rationale and design of TRUST-II, a global phase II study of taletrectinib in patients with locally advanced/metastatic ROS1+ non-small-cell lung cancer and other ROS1+ solid tumors. The primary end point is confirmed objective response rate. Secondary end points include duration of response, progression-free survival, overall survival and safety. This trial is enrolling patients in North America, Europe and Asia.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.386
Teacher spread0.373 · 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

Citations31
Published2023
Admission routes1
Has abstractyes

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