Real-world dosing and drug costs with everolimus or axitinib as second targeted therapies for advanced renal cell carcinoma: a retrospective chart review in the US
Bibliographic record
Abstract
OBJECTIVE: To describe dosing patterns and to compare the drug costs per month spent in progression-free survival (PFS) among patients with advanced renal cell carcinoma (aRCC) treated with everolimus or axitinib following a first tyrosine kinase inhibitor (TKI). METHODS: A medical record retrospective review was conducted among medical oncologists and hematologists/oncologists in the US. Patient eligibility criteria included: (1) age ≥18 years; (2) discontinuation of first TKI (sunitinib, sorafenib, or pazopanib) for medical reasons; (3) initiation of axitinib or everolimus as a second targeted therapy during February 2012-January 2013. Real-world dosing patterns were summarized. Dose-specific drug costs (as of October 2014) were based on wholesale acquisition costs from RED BOOK Online. PFS was compared between everolimus and axitinib using a multivariable Cox proportion hazards model. Everolimus and axitinib drug costs per month of PFS were compared using multivariable gamma regression models. RESULTS: A total of 325 patients received everolimus and 127 patients received axitinib as second targeted therapy. Higher proportions of patients treated with axitinib vs everolimus started on a higher than label-recommended starting dose (14% vs 2%) or experienced dose escalation (11% vs 1%) on second targeted therapy. The PFS did not differ significantly between patients receiving everolimus or axitinib (adjusted hazard ratio (HR) = 1.16; 95% confidence interval [CI] = 0.73-1.82). After baseline characteristics adjustment, axitinib was associated with 17% ($1830) higher drug costs per month of PFS compared to everolimus ($12,467 vs $10,637; p < 0.001). LIMITATIONS: Retrospective observational study design and only drug acquisition costs considered in drug costs estimates. CONCLUSIONS: Patients with aRCC receiving axitinib as second targeted therapy were more likely to initiate at a higher than label-recommended dose and were more likely to dose escalate than patients receiving everolimus. With similar observed durations of PFS, drug costs were significantly higher-by 17% per month of PFS-with axitinib than with everolimus.
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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 | 0.002 | 0.000 |
| 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".