De novo thyroid cancer following solid organ transplantation—A 25‐year experience at a high‐volume institution with a review of the literature
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: We investigated the rate, stage, and prognosis of thyroid cancer in patients after solid-organ transplantations, and compared this to the general population. METHODS: We performed a retrospective review of patients who developed thyroid cancer after a solid-organ transplantation between January 1988 and December 2013 at a high volume transplant center. Standardized Incidence Ratio's (SIR) were calculated. Additionally, a systematic review of the literature was performed. RESULTS: A total of 10,428 patients underwent solid organ transplantation. Eleven patients (11.4 per 100,000 person-years) developed thyroid cancer: six men and five women with a mean age at diagnosis of thyroid cancer of 58 years. Ten patients underwent surgery and had stage I thyroid cancer. One patient had recurrent disease after a mean follow-up time of 78 months. The SIR varied between 0.75 and 2.3. Seventeen studies were included in the systematic review with a SIR ranging from 2.5 to 35. CONCLUSION: Rate of thyroid cancer is not significantly higher in patients who underwent solid organ transplantation compared to general population. Stage at presentation and prognosis also appear to be similar to that of the general population. Post-transplant screening for thyroid cancer remains debatable; however, when thyroid cancer is discovered, treatment should be similar to that of non-transplant patients. J. Surg. Oncol. 2017;115:105-108. © 2017 Wiley Periodicals, Inc.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".