Outcomes of systemic targeted therapy in recurrent renal cell carcinoma treated with adjuvant sunitinib
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy and tolerability of rechallenge with sunitinib and other targeted therapies (TTs) in patitents with relapsed recurrent renal cell carcinoma (RCC) in the advanced setting. METHODS: In this multi-institutional retrospective study, patients with relapsed RCC were rechallenged with sunitinib or other systemic TTs as a first-line therapeutic approach after failed adjuvant sunitinib treatment. Patient characteristics, treatments and clinical outcomes were recorded. The primary endpoint was progression-free survival (PFS). Secondary endpoints were objective response rate (ORR) and overall survival (OS). RESULTS: A total of 34 patients with relapses were recorded, and 25 of these (73.5%) were men. Twenty-five patients were treated with systemic TT: 65% of patients received TT against the vascular endothelial growth factor pathway (including sunitinib), 21.7% received mammalian target of rapamycin inhibitors and 13% received immunotherapy. The median (interquartile range) time to relapse was 20.3 (5.2-20.4) months from diagnosis, and 7.5 months (1.0-8.5) from the end of adjuvant suntinib treatment. At a median follow-up of 23.5 months, 24 of the 25 patients had progressed on first-line systemic therapy. The median PFS was 12.0 months (95% confidence interval [CI] 5.78-18.2). There were no statistical differences in PFS between different treatments or sunitinib rechallenge. PFS was not statistically different in patients relapsing on or after adjuvant suntinib treatment (≤ 6 or >6 months after adjuvant suntinib ending). The ORR was 20.5%. The median OS was 29.1 months (95% CI 16.4-41.8). CONCLUSIONS: Rechallenge with sunitinib or other systemic therapies is still a feasible therapeutic option that provides patients with advanced or metastastic RCC with additional clinical benefits with regard to PFS and OS after failed response to adjuvant sunitinib.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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; 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".