Adjuvant therapy with tyrosine kinase inhibitors for localized and locally advanced renal cell carcinoma: an updated systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: Tyrosine kinase inhibitors (TKIs) have been widely used in the management of patients with metastatic renal cell carcinoma (RCC). However, the use of systemic therapies in the adjuvant setting of localized and locally advanced RCC has shown conflicting results across the literature. Therefore, we aimed to conduct an updated systematic review and meta-analysis comparing the efficacy and safety of TKIs in the adjuvant setting for patients with localized and locally advanced RCC. MATERIALS AND METHODS: The MEDLINE and EMBASE databases were searched in December 2020 to identify phase III randomized controlled trials of patients receiving adjuvant therapies with TKI for RCC. Disease-free survival (DFS) and overall survival (OS) were the primary endpoints. The secondary endpoints included treatment-related adverse events (TRAEs) of high and any grade. RESULTS: Five trials (S-TRAC, ASSURE, PROTECT, ATLAS, and SORCE) were included in our meta-analysis comprising 6,531 patients. The forest plot revealed that TKI therapy was associated with a significantly longer DFS compared to placebo (pooled HR: 0.88, 95% CI: 0.81-0.96, P= 0.004). The Cochrane's Q test (P = 0.51) and I2 test (I2 = 0%) revealed no significant heterogeneity. Adjuvant TKI was not associated with improved OS compared to placebo (pooled HR: 0.93, 95% CI: 0.83-1.04, P= 0.23). The Cochrane's Q test (P = 0.74) and I2 test (I2 = 0%) revealed no significant heterogeneity. The forest plot revealed that TKI therapy, compared to placebo, was associated with higher rates of high grade TRAEs (OR: 5.20, 95% CI: 4.10-6.59, P< 0.00001) as well as any grade TRAEs (OR: 3.85, 95% CI: 1.22-12.17, P= 0.02). The Cochrane's Q tests (P < 0.0001 and P < 0.00001, respectively) and I2 tests (I2 = 79% and I2 = 90%, respectively) revealed significant heterogeneity. CONCLUSIONS: The findings of our analyses suggest an improved DFS in patients with localized and locally advanced RCC receiving adjuvant TKI as compared to placebo; however, this did not translate into any significant OS benefit. Additionally, TKI therapy led to significant toxicity. Adjuvant TKI does not seem to offer a satisfactory risk and/orbenefit balance for all patients. Select patients with very poor prognosis may be considered in a shared decision-making process with the patient. With the successful arrival of immune-based therapies in RCC, these may allow a more favorable risk/benefit profile.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".