Deferred cytoreductive nephrectomy among patients with newly diagnosed metastatic renal cell carcinoma treated initially with sunitinib.
Bibliographic record
Abstract
4578 Background: While the CARMENA trial prompts more caution with upfront cytoreductive nephrectomy (CN) in patients with metastatic renal cell carcinoma (mRCC), 17% of patients in the sunitinib alone arm underwent deferred CN (dCN). Upfront systemic therapy has been proposed as a potential litmus test to identify patients suitable for CN, but data on outcomes are limited. We sought to characterize outcomes of dCN after upfront sunitinib relative to sunitinib alone. Methods: Patients with newly diagnosed mRCC receiving upfront sunitinib were identified from the International mRCC Database Consortium (IMDC) from 2006-2018. All CNs done after initial sunitinib were included, excluding CNs performed after sunitinib failure. The outcomes were overall survival (OS) and time to treatment failure (TTF). Kaplan Meier and multivariable Cox regression analyses were performed; dCN was analyzed as a time-varying covariate to account for immortal time bias. Results: The cohort included 708 patients of whom 53 (7.5%) underwent dCN at a median of 6.5 months (IQR 3.5,10.5) from diagnosis. Patients in the dCN group were more likely to have better Karnofsky performance status (KPS), intermediate IMDC risk, fewer metastatic sites, and response to upfront sunitinib (Table). There were 604 deaths during a median follow-up of 63 months. Median OS and TTF with dCN were 43.5 and 19.8 months vs. 9.4 and 4.3 months without, respectively. Upon multivariable analysis, dCN remained significantly associated with OS (HR 0.45, 95%CI 0.31-0.65; p < 0.001) but not TTF (HR 0.73, 95%CI 0.52-1.01; p = 0.056). Conclusions: Patients who received dCN were carefully selected and achieved long OS. With these benchmark outcomes, optimal selection criteria need to be identified and confirmation of the role of dCN in a clinical trial is warranted. [Table: see text]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".