Cabozantinib in the Routine Management of Renal Cell Carcinoma: A Systematic Literature Review of Real-World Evidence
Bibliographic record
Abstract
Real-world cabozantinib use has increased since its approval to treat patients with advanced renal cell carcinoma (RCC) in 2016. We reviewed cabozantinib use in real-world clinical practice and compared outcomes with pivotal cabozantinib randomized control trials (RCTs). This PRISMA-standard systematic literature review evaluated real-world effectiveness and tolerability of cabozantinib in patients with RCC (PROSPERO registration: CRD42021245854). Systematic MEDLINE, Embase, and Cochrane database searches were conducted on November 2, 2022. Eligible publications included ≥ 20 patients with RCC receiving cabozantinib. After double-screening for eligibility, standardized data were abstracted, qualitatively summarized, and assessed for risk of bias using the Newcastle-Ottawa Scale. Of 353 screened publications, 41 were included, representing approximately 11,000 real-world patients. Most publications reported cabozantinib monotherapy cohort studies (40/41) of retrospective (39/41) and multicenter (32/41) design; most included patients from North America and/or Europe (30/41). Baseline characteristics were demographically similar between real-world and pivotal RCT populations, but real-world populations showed greater variation in prevalence of prior nephrectomy, multiple-site/brain metastasis, and nonclear-cell RCC histology. Cabozantinib activity was reported across real-world treatment lines and tumor types. Overall survival, progression-free survival, and objective response rate values from pivotal RCTs were within the ranges reported for equivalent outcomes across real-world studies. Common real-world grade ≥ 3 adverse events were consistent with those in pivotal RCTs (fatigue, palmar-plantar erythrodysesthesia syndrome, diarrhea, hypertension), but less frequent. No new tolerability concerns were identified. Real-world RCC survival outcomes for cabozantinib monotherapy were broadly consistent with pivotal RCTs, despite greater heterogeneity in real-world populations.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".