Prevalence and impact on survival of positive surgical margins in partial nephrectomy for renal cell carcinoma: a population‐based study
Bibliographic record
Abstract
What's known on the subject? and What does the study add? The increased detection of small renal masses ( SRMs ) with diagnostic imaging has highlighted the importance of preserving renal function, with many patients with SRMs being managed with nephron‐sparing procedures. The significance of positive surgical margins ( PSMs ) is debatable and various studies have looked at the risk factors for PSMs and recurrence. It has been suggested that tumour size may be a risk factor and the centrality of the tumour has been found to be an increased risk factor. The indication and location of the tumour has been found to be an independent predictive factor for recurrence. Various studies have assessed the outcome of patients with PSMs with short‐ to intermediate‐term follow‐up. Our study has an intermediate‐term median follow‐up of 7.9 years, and found no significant difference in 5‐year disease‐specific and overall survival rates between patients with PSMs and negative surgical margins. We also found that tumour size was not significant, but pathological stage and fat invasion were found to be significant. These risk factors have not been published in previous studies. Objectives To determine the prevalence of positive surgical margins ( PSMs ) on a population level. To identify the predictors of PSMs and assess their impact on survival. Patients and Methods Using the Ontario Cancer Registry, we reviewed pathology reports on 664 patients after partial nephrectomy for renal cell carcinoma between 1995 and 2004. Demographic information and pathological characteristics were obtained and multivariable logistic regression analysis was performed to determine the predictors of PSMs . Kaplan–Meier analysis was used to examine disease‐specific ( DSS ) and overall survival ( OS ) by margin status. A multivariable Cox proportional hazards model was used to determine the independent association between PSMs and survival. Results The mean patient age was 57.7 years and 61.6% were men. Tumour size was <2.0 cm in 25%, 2.0–3.9 cm in 59%, 4.0–6.9 cm in 13%, and ≥7.0 cm in 3% of patients. Seventy‐one patients (10.7%) had PSMs on final pathology. Only stage ( P = 0.02) and fat invasion ( P = 0.04) were significantly associated with PSMs . At a median follow‐up of 7.9 years, the unadjusted 5‐year DSS and OS rates were 91.8 and 88.3%, respectively. Survival rates did not differ by surgical margin status, with 90.9 and 84.4% 5‐year DSS and OS rates for patients with PSMs compared with 91.9 and 88.6% for those with a negative surgical margin ( P = 0.58, log rank test). Using a Cox proportional hazards model, surgical margin status was not associated with time to all‐cause death ( P = 0.67). Conclusion Our population‐level data suggest that, although PSMs are fairly prevalent, they appear to have little to no impact on 5‐year survival rates.
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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 | 0.000 |
| 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".