Natural History of Renal Masses Followed Expectantly
Bibliographic record
Abstract
PURPOSE: An increasing number of incidental renal masses have been detected with increasing use of ultrasonography, computerized tomography and magnetic resonance imaging. We investigated the natural history of incidentally detected renal masses. MATERIALS AND METHODS: A total of 24 patients were included in this retrospective analysis. Average patient age was 68.3 years (range 29 to 83). The 16 males and 8 females were followed with abdominal imaging for a mean and median followup of 31.6 and 24 months, respectively (range 8 to 86). Patients elected to be observed because of age, poor medical condition or the presence of a mass in a solitary kidney. The majority of patients (22 of 24) were asymptomatic at diagnosis. Two patients were followed with bilateral renal masses, and 2 with T3b tumors. Of the 20 patients with incidental solitary renal masses, 6 were at the upper pole, 9 were mid polar and 5 lower pole. Mean maximum diameter of lesions was 3.3 cm (median 2.7, range 0.9 to 10). Growth rate was calculated based on diameter and tumor volume. RESULTS: Of the 24 patients only 5 demonstrated tumor growth during the surveillance period. No metastasis developed in any patients. Mean tumor growth rate observed in the 5 patients was 0.49 cm per year or 7.3 cc per year. Of the 24 patients 4 underwent surgery after surveillance because of apparent tumor growth or per patient request. Pathology revealed renal cell carcinoma in all 4. CONCLUSIONS: Tumor growth of renal masses is often limited. Most of our patients did not demonstrate significant growth when followed expectantly. Without tumor growth the risk of metastasis seems limited.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".