Cabozantinib after prior checkpoint inhibitor therapy in patients with solid tumors: A systematic literature review
Bibliographic record
Abstract
INTRODUCTION: We conducted a systematic literature review to identify evidence for cabozantinib activity in patients with solid tumors after prior checkpoint inhibitor (CPI) therapy. METHODS: The review was conducted according to PRISMA guidelines and registered with PROSPERO (CRD42021259873). MEDLINE®, Embase, and the Cochrane Library were searched on 19 May 2021 to identify publications reporting the efficacy/effectiveness and safety/tolerability of cabozantinib in patients with solid tumors who had received prior CPI-based therapy. Publications were screened by one reviewer with uncertainties resolved by a second and/or the full author group. Risk of bias was assessed using Gradingof Recommendations Assessment, Development and Evaluation (GRADE) for clinical trials and the Newcastle-Ottawa Scale (NOS) for observational studies. RESULTS: Of 669 publications screened, 21 were eligible: 18 reported data on renal cell carcinoma, and one each for hepatocellular carcinoma, metastatic urothelial carcinoma, and non-small cell lung cancer. Of six trial publications, three reported moderate-quality evidence and three low-quality evidence. Of 15 observational studies, NOS scores ranged from 3 to 6, suggesting a high potential for uncertainty. The studies consistently reported clinical activity for cabozantinib after CPI therapy, across treatment lines and tumor types, with no new safety signals. The findings were limited by the quality and quantity of available data. CONCLUSION: Cabozantinib appears to have anti-tumor activity after prior CPI therapy in patients with solid tumors. Our results are driven largely by studies in renal cell carcinoma. Evidence from ongoing phase 3 trials is required to establish further the role of cabozantinib after CPI therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.001 | 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; both teacher heads agree on what is shown here.
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".