Cytoreductive nephrectomy and exposure to sunitinib – a <i>post hoc</i> analysis of the Immediate Surgery or Surgery After Sunitinib Malate in Treating Patients With Metastatic Kidney Cancer (SURTIME) trial
Bibliographic record
Abstract
OBJECTIVE: To analyse if exposure to sunitinib in the Immediate Surgery or Surgery After Sunitinib Malate in Treating Patients With Metastatic Kidney Cancer (SURTIME) trial, which investigated opposite sequences of cytoreductive nephrectomy (CN) and systemic therapy, is associated with the overall survival (OS) benefit observed in the deferred CN arm. PATIENTS AND METHODS: A post hoc analysis of SURTIME trial data. Variables analysed included number of patients receiving sunitinib, time from randomisation to start sunitinib, overall response rate by Response Evaluation Criteria In Solid Tumors (RECIST) version 1.1, and duration of drug exposure and dose in the intention-to-treat population of the immediate and deferred arm. Descriptive methods and 95% confidence-intervals (CI) were used. RESULTS: In the deferred arm, 97.7% (95% CI 89.3-99.6%; n = 48) received sunitinib vs 80% (95% CI 66.9-88.7%, n = 40) in the immediate arm. Following immediate CN, 19.6% progressed 4 weeks after CN and the median time to start sunitinib was 39.5 vs 4.5 days in the deferred arm. At week 16, 46.0% had progressed at metastatic sites in the immediate CN arm vs 32.7% in the deferred arm. Sunitinib dose reductions, escalations and interruptions were not statistically significantly different between arms. Among patients who received sunitinib in the immediate or deferred arm the median total sunitinib treatment duration was 172.5 vs 248 days. Reduction of target lesions was more profound in the deferred arm. CONCLUSIONS: In comparison to the deferred CN approach, immediate CN impairs administration, onset, and duration of sunitinib. Starting with systemic therapy leads to early and more profound disease control and identification of progression prior to planned CN, which may have contributed to the observed OS benefit.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".