Incidence and Risk of Congestive Heart Failure in Patients With Renal and Nonrenal Cell Carcinoma Treated With Sunitinib
Bibliographic record
Abstract
PURPOSE: Sunitinib is a multitargeted receptor tyrosine kinase inhibitor approved for treatment of renal cell carcinoma (RCC) and GI stromal tumor. Congestive heart failure (CHF) is an important adverse effect that has been reported with sunitinib, but overall incidence and relative risk (RR) remain undefined. We performed an up-to-date meta-analysis to determine the risk of developing CHF in patients with both RCC and non-RCC tumors treated with sunitinib. METHODS: Medline databases were searched for articles published between January 1966 and February 2011. Eligible studies were limited to phase II and III trials of sunitinib with adequate safety reporting in patients with cancer of any tumor type. Summary incidence, RR, and 95% CIs were calculated using random- or fixed-effects models based on the heterogeneity of included studies. RESULTS: A total of 6,935 patients were included. Overall incidence for all- and high-grade CHF in sunitinib-treated patients was 4.1% (95% CI, 1.5% to 10.6%) and 1.5% (95% CI, 0.8% to 3.0%), respectively. RR of all- and high-grade CHF in sunitinib-treated patients compared with placebo-treated patients was 1.81 (95% CI, 1.30 to 2.50; P < .001) and 3.30 (95% CI, 1.29 to 8.45; P = .01), respectively. On subgroup analysis, there was no difference observed in CHF incidence for patients with RCC versus non-RCC or in trials with or without cardiac monitoring. No evidence of publication bias was observed. CONCLUSION: Sunitinib use is associated with increased risk of CHF in patients with cancer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".