Bibliographic record
Abstract
BACKGROUND: Organ transplantation is one of the best modalities for treating fatal organ failure. Despite the success of this procedure, an increasing incidence of cancer in this population has drawn the attention of public health officials in recent years. OBJECTIVES: The overall objective of this study is to conduct a detailed examination of adverse health outcomes among Canadian organ transplant recipients, with an emphasis on cancer incidence and mortality. METHODS: This project employed a retrospective cohort follow-up study design, whereby Canadian Organ Replacement Registry records were linked to the Canadian Mortality Database and the Canadian Cancer Registry Database. The study population consisted of more than 16,000 solid organ transplant recipients registered between January 1, 1981 and December 31, 1998. This study was designed to assess the risks of developing cancer, overall and site-specific, in transplant recipients in comparison to the general Canadian population using Standardized Incidence Ratios (SIR), Standardized Mortality Ratios (SMR), and Proportionate Mortality Ratios (PMR). In addition, Cox and logistic models were used to assess the effects of various risk factors on cancer incidence and mortality in transplant sub-populations, while cumulative incidence was used to study the patient survival pattern. Lastly, Population Attributable Risk (PAR) was used to quantify the impact of organ transplantation on cancer incidence and mortality. RESULTS: Among major causes of death, the highest PMRs are due to genitourinary diseases, followed by endocrine, nutritional and metabolic diseases, and infectious diseases. SIRs indicate that cancer incidence and mortality were relatively lower than that observed for other major causes of death, and slightly higher than that observed in the general Canadian population. Lastly, logistic regression results indicate that age, year of surgery, and smoking status were significant risk factors in mortality due to all causes, while the Cox regression model shows that age, sex and year of surgery were significant risk factors for cancer incidence. Overall, the PAR in this cohort was very minimal, indicating that the risk in mortality and cancer incidence due to organ transplantation is negligible. CONCLUSION: Life threatening diseases such as those of the genitourinary system, as well as endocrine, nutritional and metabolic diseases and infectious diseases are leading causes of death. Future research should be directed at ways of reducing incidence and subsequent mortality due to these causes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".