A Multicentered, Propensity Matched Analysis Comparing Laparoscopic and Open Surgery for pT3a Renal Cell Carcinoma
Bibliographic record
Abstract
INTRODUCTION: To compare outcomes following laparoscopic renal surgery (LRS) and open renal surgery (ORS) in the treatment of pathologic T3a (pT3a) renal cell carcinoma (RCC) using a propensity matched analysis. MATERIALS AND METHODS: The Canadian Kidney Cancer Information System is a prospectively maintained database for patients diagnosed with RCC from 15 Canadian institutions. Patients treated for nonmetastatic pT3a RCC between 2008 and 2015 were included. Propensity score matching for age, gender, tumor size, grade, histology, and surgical approach was performed to compare laparoscopic radical and partial nephrectomy (LRN or LPN) with open radical or partial nephrectomy (ORN or OPN). The primary endpoint was recurrence-free survival (RFS). RESULTS: Two hundred twenty-six (45%) patients underwent LRS (88% LRN and 12% LPN), and 275 (55%) underwent ORS (75% ORN and 25% OPN). After a median follow-up of 21.1 months, 155 (72 LRS and 83 ORS) patients experienced recurrence. The 3-year RFS was 63% and 50% for the LRS and ORS groups, respectively, p = 0.36. On subgroup analysis, there was no significant difference in RFS among patients who underwent radical nephrectomy (3-year RFS 61% in LRN compared with 46% in ORN group, p = 0.32) or partial nephrectomy (77% in LPN compared with 79% in OPN group, p = 0.82). CONCLUSIONS: This study is the largest matched analysis comparing LRS and ORS for pT3a RCC. In matched patients, LRS showed no difference in oncologic outcomes compared with ORS and should be considered when technically feasible.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".