Treatment on active surveillance of small renal masses: Progression vs. preference
Bibliographic record
Abstract
INTRODUCTION: Active surveillance (AS) of small renal masses (SRM) is increasingly recognized as a safe option. A recent U.S. study found that half of patients receiving treatment on AS were for preference, but these findings may not be generalizable to other jurisdictions and healthcare models. We aimed to investigate AS failure rates and causes among a contemporary biopsy-evaluated cohort in Canada. METHODS: A retrospective review was performed of SRM patients on AS undergoing treatment at our tertiary care center (1999-2018). All patients had undergone renal biopsy and been diagnosed with renal cell carcinoma (RCC). Demographic and clinical parameters surrounding the decision to treat were extracted from chart review. Indications for treatment were dichotomized into clinical (radiographical) progression or preference. Qualitative assessment of clinic notes confirmed treatment indication. Ethics approval was obtained. RESULTS: A total of 38 SRM-RCC patients who underwent treatment on AS were identified, of which 29 had been on AS ≥1 year. Most (75.9%) were male and the mean age beginning AS was 65.9±9.0 years. Most patients had clear-cell RCC with low-grade disease. Seventeen of 29 (58.6%) patients experienced clinical progression after 3.82 (2.57-7.16) years, whereas preference accounted for 12/29 (41.4%) after 2.22 (1.69-3.53) years (time-to-treatment p=0.032). The longest duration on AS was 14.2 years prior to clinical progression. No patients had metastatic progression before treatment. CONCLUSIONS: Two-fifths of patients received treatment for preference and at a much higher rate vs. clinical progression. These findings suggest a clinical gap where effective patient counselling prior to and during AS may improve adherence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".