Renal nephrometry score and predictors of pathologic upstaging in patients undergoing partial and radical nephrectomies.
Bibliographic record
Abstract
412 Background: To examine the predictive capability of pre-operative anatomic imagining characterization of the R.E.N.A.L. Nephrometry Score (RNS) in assessing pathologic upstaging of clinical T1 (cT1) lesions to pathologic T3 (pT3) in partial and radical nephrectomy specimens. Methods: We conducted a retrospective review of all patients undergoing radical and partial nephrectomies between January 1, 2011 and May 31, 2014 for cT1 renal masses. All pre-operative imaging scans were reviewed and the R.E.N.AL. Nephrometry score (radius for tumor size as maximal diameter, exophytic/endophytic tumor properties, nearness of deepest portion of tumor to collecting system or sinus, anterior/posterior descriptor and location relative to polar line) was applied to each scan. Chi-square, Fisher exact test, and Student t test were utilized to examine associations. Results: Of the 229 patients who underwent partial or radical nephrectomy for cT1, 124 (54%) underwent partial nephrectomy. On pathologic evaluation 195 (85%) patients had malignancy. Of all tumors 26 (13%) were pathologically upstaged to pT3 with the majority attributable to renal sinus/fat (35%) or perinephric fat (31%) involvement. High RNS (>10) was significant in predicting pathologic T3 upstaging (p=0.039) but did not predict high grade (Furhman grade 3-4) disease (p=0.803). While a high nephrometry score trended toward predicting malignancy vs benign disease (p=0.086), a higher mean nephrometry score (7.81 vs. 6.84) significantly predicted malignancy (p=0.015). When controlled for cT1a lesions, tumor location relative to polar lines (L=3 vs. L1+2) was predictive of pT3 upstaging (24 vs. 6%, p=0.03). Age >65 was significantly associated with upstaging (26 vs. 7%, p=0.0001). Conclusions: Surveillance of small renal masses is common but high RNS and age >65 significantly predicted pathologic upstaging. Mean nephrometry score was also useful in predicting malignancy. Nephrometry score may aid in deciding on early surgical intervention.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".