Outcomes of systemic therapy in relapsed renal cell carcinoma (RCC) treated with adjuvant sunitinib (AS).
Bibliographic record
Abstract
701 Background: There are no available data on the usefulness of targeted therapy (TT) as the first-line treatment for patients with RCC recurrence after AS. We aim to explore the outcomes of systemic therapy with recurrent RCC after AS including re-exposure to sunitinib. Methods: A multi-institutional retrospective study was conducted on RCC patients who relapsed after AS. The primary end point was progression-free survival (PFS). Secondary end points were overall response rate (ORR) and overall survival (OS). Results: 34 relapses were recorded, 25 patients (73,5%) were male. 25 patients were treated with systemic therapy at first-line after relapse: 65% of patients received Vascular Endothelial Growth Factor (VEGF)-TT (including 7 patients retreated with sunitinib), 21,7% mTOR inhibitors and 13% immunotherapy. The median time to relapse was 20,3 months (IQR 5,2-20,4) from diagnosis, and 7,5 months (IQR 1,0-8,5) months from AS ending. At a median time of follow-up of 23,5 months, 24/25 patients had progressed on first-line systemic therapy. The median PFS was 12,0 months (IC95% 6,6-17,8 months). There was no statistical difference in PFS among the different treatments or the re-exposed to sunitinib. PFS was not statistically different between those relapsing on or after AS ( < 6 or > 6 months after AS). ORR was 20,3%. Median OS was 28,7 months (IC95% 24,4-33,0). Conclusions: This study suggests that TT may still improve PFS and OS in RCC patients who relapsed after AS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".