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Record W7116844250 · doi:10.1177/17588359251385410

TROPION-Lung15: a randomized phase III study of osimertinib combined with datopotamab deruxtecan (Dato-DXd) or Dato-DXd alone versus platinum-doublet chemotherapy in patients with <i>EGFR</i> -mutated advanced non-small cell lung cancer and whose disease has progressed on prior osimertinib

2025· article· en· W7116844250 on OpenAlexaff
Daniel Shao‐Weng Tan, Ernest Nadal, Parneet K. Cheema, Y. Wu, Myung-Ju Ahn, Junko Tanizaki, Ellie Grainger, Emily Nizialek, Alessandra Forcina, Toon van der Gronde, H. Yu

Bibliographic record

VenueTherapeutic Advances in Medical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsWilliam Osler Health System
FundersDaiichi Sankyo EuropeNational Cancer InstituteEli Lilly JapanPfizer JapanEMD SeronoDaiichi-SankyoEli Lilly and CompanyOno PharmaceuticalSanofiApollomicsYuhanTaiho PharmaceuticalBoehringer Ingelheim JapanBeiGeneChugai PharmaceuticalNihon Medi-PhysicsAstellas PharmaAstraZenecaNovocureGenomic HealthGlaxoSmithKlineAmgenPfizerLes Laboratories Pierre FabreBristol-Myers Squibb
KeywordsOsimertinibLung cancerChemotherapyDiseaseRandomized controlled trialPhases of clinical researchClinical trialLung disease

Abstract

fetched live from OpenAlex

Background: Osimertinib is the preferred treatment for patients with EGFR -mutated advanced non-small cell lung cancer (NSCLC) in several settings; however, disease progression is common, and treatment options after progression are limited. Datopotamab deruxtecan (Dato-DXd), an antibody-drug conjugate comprising a humanized anti-trophoblast cell-surface antigen 2 (TROP 2) monoclonal antibody conjugated to a potent topoisomerase I inhibitor via a plasma-stable linker, has demonstrated efficacy in advanced NSCLC, including previously treated EGFR -mutated advanced NSCLC. Combining osimertinib and Dato-DXd may overcome heterogeneous osimertinib resistance mechanisms and limit tumor progression. Objectives: TROPION-Lung15 is an ongoing, phase III, open-label, sponsor-blind, multicenter, randomized trial evaluating Dato-DXd ± osimertinib versus chemotherapy in patients with EGFR -mutated advanced NSCLC and disease progression on prior osimertinib. Methods and design: Approximately 630 patients with histologically/cytologically confirmed non-squamous NSCLC, documented epidermal growth factor receptor tyrosine kinase inhibitor-sensitive mutations, and radiologic progression on prior osimertinib monotherapy will be enrolled. Patients will be randomized 1:1:1 to Dato-DXd (6 mg/kg intravenously every 3 weeks), osimertinib (80 mg orally once daily) plus Dato-DXd, or platinum-doublet chemotherapy, stratified by the history/presence of brain metastases (yes vs no), prior osimertinib therapy (adjuvant vs post-chemoradiotherapy/first-line vs second-line), and race. Treatment will continue until radiological progression (per Response Evaluation Criteria in Solid Tumors version 1.1), unacceptable toxicity, or another discontinuation criterion is met. The dual primary endpoints are progression-free survival (PFS) by blinded independent central review (BICR) for osimertinib + Dato-DXd and PFS by BICR for Dato-DXd alone versus chemotherapy. Secondary endpoints include overall survival, central nervous system PFS by BICR, and safety/tolerability. Ethics: The study is approved by independent ethics committees/institutional review boards at each center. Patients will provide written informed consent. Discussion: TROPION-Lung15 will assess Dato-DXd ± osimertinib in patients with EGFR -mutated advanced NSCLC and disease progression on prior osimertinib. Data from this study could lead to a new treatment option in this setting. Trial registration: ClinicalTrials.gov identifier: NCT06417814 (date of registration: May 13, 2024).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.013
GPT teacher head0.369
Teacher spread0.356 · 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 designRandomized 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

Citations2
Published2025
Admission routes1
Has abstractyes

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