Cancer Screening in Solid Organ Transplant Recipients: A Focus on Screening Liver, Lung, and Kidney Recipients for Cancers Related to the Transplanted Organ
Bibliographic record
Abstract
Over the last few decades, the life expectancy of solid organ transplant recipients (SOTRs) has improved significantly. With SOTRs living longer, more recipients are dying from cancer. There is a reported 2- to 3-fold increased risk of cancer-specific mortality in SOTRs compared with the general population. Cancer in an SOTR can be de novo, recurrent, or donor-derived. Cancer screening in this population is crucial, as early detection and treatment may improve outcomes. In the absence of randomized controlled trials dedicated to SOTRs, clinicians rely on clinical practice guidelines from regional and national transplant societies; however, these may vary considerably across jurisdictions and transplanted organ. At present, no widely accepted consensus exists for cancer screening protocols in SOTRs, particularly with regard to screening for malignancy related to transplanted organ. Some SOTRs may be at higher risk of malignancies within the allograft. This is particularly the case in lung and liver recipients, though less common in kidney recipients who are at increased risk of developing renal cell cancer in their native kidneys. This increased risk has not been uniformly incorporated into screening recommendations for SOTRs. In this review, we summarize the cancer screening recommendations for SOTRs from various transplant organizations based on transplanted organ. This review also discusses the complexity and controversies surrounding screening of cancer in the allograft and future avenues to improve cancer detection in this context. More studies specific to SOTRs are required to form generalizable and evidence-based cancer screening guidelines, particularly with respect to cancer screening in the allograft.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".