Taletrectinib in <i>ROS1</i> + Non–Small Cell Lung Cancer: TRUST
Bibliographic record
Abstract
PURPOSE: + non-small cell lung cancer. METHODS: TRUST-I and TRUST-II were phase II, single-arm, open-label, nonrandomized, multicenter trials. Efficacy outcomes were pooled from TRUST-I and TRUST-II pivotal cohorts. The safety population comprised all patients treated with once-daily oral taletrectinib 600 mg pooled across the taletrectinib clinical program. The primary end point was independent review committee-assessed confirmed objective response rate (cORR). Secondary outcomes included intracranial (IC)-ORR, progression-free survival (PFS), duration of response (DOR), and safety. RESULTS: As of June 7, 2024, the efficacy-evaluable population included 273 patients in TRUST-I and TRUST-II. Among TKI-naïve patients (n = 160), the cORR was 88.8% and the IC-cORR was 76.5%; in TKI-pretreated patients (n = 113), the cORR was 55.8% and the IC-cORR was 65.6%. In TKI-naïve patients, the median DOR and median PFS were 44.2 and 45.6 months, respectively. In TKI-pretreated patients, the median DOR and median PFS were 16.6 and 9.7 months. The cORR in patients with G2032R mutation was 61.5% (8 of 13). Among 352 patients treated with taletrectinib 600 mg once daily, the most frequent treatment-emergent adverse events (TEAEs) were GI events (88%) and elevated AST (72%) and ALT (68%); most were grade 1. Neurologic TEAEs were infrequent (dizziness, 21%; dysgeusia, 15%) and mostly grade 1. TEAEs leading to discontinuations (6.5%) were low. CONCLUSION: Taletrectinib showed a high response rate with durable responses, robust IC activity, prolonged PFS, favorable safety, and low rates of neurologic adverse events in TKI-naïve and pretreated patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".