Management of Active Surveillance-Eligible Prostate Cancer during Pretransplantation Workup of Patients with Kidney Failure: A Simulation Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The general rule that every active malignancy is an absolute contraindication for kidney transplantation is challenged by kidney failure patients diagnosed with active surveillance-eligible prostate cancer during pretransplantation workup. Interdisciplinary treatment teams therefore often face the challenge of balancing the benefits of early kidney transplantation and the risk of metastatic progression. Hence, we compared the quality-adjusted life expectancy of different management strategies in kidney failure patients diagnosed with active surveillance-eligible prostate cancer during pretransplantation workup. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A discrete event simulation model was developed on the basis of a systematic literature search, clinical guidelines, and expert opinion. After model validation and calibration, we simulated four management strategies in a hypothetical cohort of 100,000 patients: Definitive treatment (surgery or radiation therapy) and listing after a waiting period of 2 years, definitive treatment and immediate listing, active surveillance and listing after a waiting period of 2 years, and active surveillance and immediate listing. Individual patient results (quality-adjusted life years; QALYs) were aggregated into strategy-specific means (± SEs). RESULTS: Active surveillance and immediate listing yielded the highest amount of quality-adjusted life expectancy (6.97 ± 0.01 QALYs) followed by definitive treatment and immediate listing (6.75 ± 0.01 QALYs). These two strategies involving immediate listing not only outperformed those incorporating a waiting period of 2 years (definitive treatment: 6.32 ± 0.01 QALYs; active surveillance: 6.59 ± 0.01 QALYs) but also yielded a higher proportion of successfully performed transplantations (72% and 74% versus 56% and 59%), with less time on hemodialysis on average (4.02 and 3.81 years versus 4.80 and 4.65 years). CONCLUSIONS: Among kidney failure patients diagnosed with active surveillance-eligible prostate cancer during pretransplantation workup, the active surveillance and immediate listing strategy outperformed the alternative management strategies from a quality of life expectancy perspective, followed by definitive treatment and immediate listing.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".