Screening for Prostate, Breast and Colorectal Cancer in Renal Transplant Recipients
Bibliographic record
Abstract
American Society of Transplantation guidelines recommend screening renal transplant recipients for breast, colorectal and prostate cancer. However there is a lack of evidence to support this practice. Computer simulation modeling was used to estimate the years of life lost as a result of these cancers in 50-year-old renal transplant recipients and subjects in the general population. Renal transplant recipients lost fewer years of life to cancer than people in the general population largely because of reduced life expectancy. In nondiabetic transplant recipients, loss of life as a result of these cancers was comparable with that in the general population only under assumptions of increased cancer incidence and cancer-specific mortality risks. Even with two-fold higher cancer incidence and disease-specific mortality risks, diabetic transplant recipients lost considerably fewer life years to cancer than those in the general population. Recommended cancer screening for the general population may not yield the expected benefits in the average renal transplant recipient but the benefits will be considerably higher than for patients on dialysis. Transplanted patients at above-average cancer risk in good health may achieve the benefits of screening that are seen in the general population.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".