Treatment of advanced thyroid cancer with axitinib: Phase 2 study with pharmacokinetic/pharmacodynamic and quality‐of‐life assessments
Bibliographic record
Abstract
BACKGROUND: In a previous phase 2 trial, axitinib was active and well tolerated in patients with advanced thyroid cancer. In this second phase 2 trial, the efficacy and safety of axitinib were evaluated further in this population, and pharmacokinetic/pharmacodynamic relationships and patient-reported outcomes were assessed. METHODS: Patients (N = 52) with metastatic or unresectable, locally advanced medullary or differentiated thyroid cancer that was refractory or not amenable to iodine-131 received a starting dose of axitinib 5 mg twice daily. The primary endpoint was the objective response rate (ORR). Secondary endpoints included progression-free survival (PFS), overall survival (OS), safety, pharmacokinetic parameters, and patient-reported outcomes assessed with the MD Anderson Symptom Inventory questionnaire. RESULTS: The overall ORR was 35% (18 partial responses), and 18 patients had stable disease for ≥16 weeks. The median PFS was 16.1 months, and the median OS was 27.2 months. All-causality, grade ≥3 adverse events (>5%) were fatigue, dyspnea, diarrhea, decreased weight, pain in extremity, hypertension, decreased appetite, palmar-plantar erythrodysesthesia, hypocalcemia, and myalgia. Patients who had greater axitinib exposure had a longer median PFS. Quality of life was maintained during treatment with axitinib, and no significant deterioration in symptoms or interference in daily life caused by symptoms, assessed on MD Anderson Symptom Inventory subscales, were observed. CONCLUSIONS: Axitinib has activity and a manageable safety profile while maintaining quality of life, and it represents an additional treatment option for patients with advanced thyroid cancer.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".