Safety and Effectiveness of Lenvatinib in Patients with Unresectable Hepatocellular Carcinoma in Real-World Clinical Practice: An Observational Post-Marketing Study in Japan
Bibliographic record
Abstract
BACKGROUND: Lenvatinib was approved for use in unresectable hepatocellular carcinoma (uHCC) in Japan in 2018. Patients with diverse clinical characteristics receive lenvatinib treatment in clinical practice. Thus, it is crucial to evaluate the safety and effectiveness of lenvatinib in real-world clinical settings. OBJECTIVE: This study aimed to evaluate the real-world safety and effectiveness of lenvatinib for uHCC in clinical practice in Japan. PATIENTS AND METHODS: Between July 2018 and January 2019, patients with uHCC who were administered lenvatinib for the first time were enrolled in this prospective, multicenter, observational post-marketing study (NCT03663114). Patients were orally administered lenvatinib and followed up for 12 months. For safety, adverse drug reactions (ADRs) were evaluated. For effectiveness, the objective response rate (ORR) was calculated to evaluate tumor response. Overall survival (OS) was estimated using the Kaplan-Meier method. RESULTS: Data of 703 patients (median age, 73 years; 80.2% males) were analyzed. The median (range) treatment duration was 25.3 (0.3-68.9) weeks. The mean ± standard deviation initial dose was 7.37 ± 1.65 mg in patients with body weight < 60 kg and 10.43 ± 2.49 mg in those with body weight ≥ 60 kg. ADRs (any grade) were reported in 84.9% of the patients, with Grade ≥ 3 ADRs reported in 42.5% of the patients. The most common ADRs (> 10%) were decreased appetite, fatigue, hypertension, proteinuria, palmar-plantar erythrodysesthesia, hypothyroidism, and diarrhea. The median OS of the 703 patients was 498.0 days. In 494 patients assessed using the modified Response Evaluation Criteria in Solid Tumors (mRECIST), the ORR was 39.5% (95% confidence interval: 35.1-43.9%). Patients with better liver or renal function at baseline achieved significantly higher ORR than those with worse liver or renal function. CONCLUSIONS: In patients with uHCC in real-world clinical practice in Japan, treatment with lenvatinib was generally well tolerated, and no new safety concerns were identified. The ORR and median OS were similar to or better than the results of the Japanese subset of the global Phase III REFLECT trial. Our results demonstrated that clinically meaningful treatment responses were achieved with lenvatinib in real-world clinical practice.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".