Comparison of partial vs radical nephrectomy with regard to other‐cause mortality in T1 renal cell carcinoma among patients aged ≥75 years with multiple comorbidities
Bibliographic record
Abstract
What's known on the subject? and What does the study add? Surgical intervention is the established standard of care option in patients diagnosed with localized RCC . The study found that better and rigorous selection of surgical candidates should be implemented in the context of localized RCC as some patients may not benefit from surgery. Objective To quantify the effect of partial nephrectomy ( PN ) vs radical nephrectomy ( RN ) on other‐cause mortality ( OCM ) in elderly patients with localized renal cell carcinoma ( RCC ) and/or multiple comorbidities. Methods Using the Surveillance, Epidemiology, and End Results Medicare‐linked database, patients with T 1 RCC , aged ≥75 years, or who had ≥2 comorbidities, were identified (1988–2005). To adjust for inherent differences between treatment types, propensity‐based matched analyses were performed. Competing‐risks regression analyses for prediction of OCM were assessed according to treatment type. The effect of PN and RN on OCM was examined in three sub‐groups: patients aged ≥75 years; patients with ≥2 comorbidities; and patients aged ≥75 years with ≥2 comorbidities. Results After propensity‐based matched analyses and adjustment for all covariates, PN was found to exert a protective effect relative to RN with respect to OCM in all patients (hazard ratio [ HR ]: 0.84, P = 0.048). In subanalyses, no difference was recorded between PN and RN in patients who were aged ≥75 years ( HR : 0.83, P = 0.2), with ≥2 baseline comorbidities at diagnosis ( HR : 0.83, P = 0.1), or in patients who were aged ≥75 years and who had ≥2 baseline comorbidities ( HR : 0.77, P = 0.2). Conclusions Some elderly patients and/or those with multiple comorbidities at diagnosis may not benefit from PN with respect to OCM . After rigorous patient selection, alternative treatment options could be considered.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".