Long-term follow-up and exploratory analysis of lenvatinib in patients with metastatic or recurrent thymic carcinoma: Results from the multicenter, phase 2 REMORA trial
Bibliographic record
Abstract
OBJECTIVES: The main objective of this report was to detail the long-term follow-up data from the REMORA study, which investigated the safety and efficacy of lenvatinib in patients with thymic carcinoma. In addition, an exploratory analysis of the association between relative dose intensity (RDI) and the efficacy of lenvatinib is presented. MATERIALS AND METHODS: The single-arm, open-label, phase 2 REMORA study was conducted at eight Japanese institutions. Forty-two patients received oral lenvatinib 24 mg once daily in 4-week cycles until the occurrence of intolerable adverse events or disease progression. The REMORA long-term follow-up data were evaluated, including overall survival (OS). RDI was calculated by dividing the actual dose administered to the patient by the standard recommended dose. This trial is registered on JMACCT (JMA-IIA00285) and on UMIN-CTR (UMIN000026777). RESULTS: The updated median OS was 28.3 months (95 % confidence interval [CI]: 17.1-34.0 months), and the OS rate at 36 months was 35.7 % (95 % CI: 21.7 %-49.9 %). When grouped by RDI of lenvatinib, the median OS was 38.5 months (95 % CI: 31.2-not estimable) in patients with ≥ 75 % RDI and 17.3 months (95 % CI: 13.4-26.2 months) in patients with < 75 % RDI (hazard ratio 0.46 [95 % CI: 0.22-0.98]; P = 0.0406) at 8 weeks. Patients who maintained their lenvatinib dose over 8 weeks had a higher objective response rate than patients whose doses were reduced (75.0 % vs 29.4 %; P = 0.0379). No new safety concerns or treatment-related deaths were reported, and lenvatinib had a tolerable safety profile. CONCLUSION: This follow-up report updated OS in patients with metastatic or recurrent thymic carcinoma. A higher RDI of lenvatinib at 8 weeks could be associated with improved outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".