Oncological outcomes of partial nephrectomy for tumours larger than 4 cm: A systematic review
Bibliographic record
Abstract
INTRODUCTION: Many medical associations recommend nephron-sparing surgery (NSS) for tumours larger than 4 cm amenable to partial nephrectomy (PN). These recommendations are, however, mostly based on isolated reports. We systematically review the oncological outcomes of partial nephrectomy procedures performed for tumours larger than 4-cm. METHODS: A PubMed search was carried out using keywords "partial nephrectomy" and "nephron sparing" for records dating back to 1995. In total, 2136 abstracts were analyzed; from these, 174 studies were scrutinized. We identified 32 manuscripts reporting size-specific cancer-specific survival rates for masses greater than 4 cm. From each of these studies, we recorded the number of PN, tumour diameter, follow-up duration, 5- and 10-year recurrence, overall and cancer-specific survival rates (OS, CSS). We also calculated weighted OS and CSS rates. RESULTS: This systematic review includes 2445 patients with renal tumours larger than 4 cm who underwent PN: 1858 patients with tumours between 4 to 7 cm, 410 patients with tumours larger than 7 cm and 177 patients with tumours greater than 4 cm (exact size unknown). Our analysis revealed weighted 5-year CSS rates of 95.4%, 86.2% and 93.9% for tumours 4 to 7 cm, >7 cm, and all tumours >4 cm, respectively. The respective 5-year OS rates were 84.7%, 76.4%, and 84.7%. CONCLUSIONS: We found excellent 5-year CSS and OS rates for patients with tumours 4 to 7 cm treated with PN. These outcomes compare favourably to those reported in historical radical nephrectomy (RN) series for similarly sized tumours. Thus, PN is an acceptable and often preferred treatment for renal masses >4 cm which are amenable to nephron-sparing procedures.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".