Risk of COVID-19 Infections and of Severe Complications Among Survivors of Childhood, Adolescent, and Young Adult Cancer: A Population-Based Study in Ontario, Canada
Bibliographic record
Abstract
PURPOSE Survivors of childhood, adolescent, and young adult cancer are at risk of late effects, including pulmonary and infectious complications. Whether survivors are at increased risk of COVID-19 infection and severe complications is unknown. METHODS Population-based registries in Ontario, Canada, identified all 5-year survivors of childhood cancer diagnosed age 0-17 years between 1985 and 2014, and of six common adolescent and young adult cancers diagnosed age 15-21 years between 1992 and 2012. Each survivor alive on January 1, 2020, was randomly matched by birth year, sex, and residence to 10 cancer-free population controls. Individuals were linked to population-based laboratory and health care databases to identify COVID-19 tests, vaccinations, infections, and severe outcomes (emergency department [ED] visits, hospitalizations, intensive care unit admissions, and death within 60 days). Demographic, disease, and treatment-related variables were examined as possible predictors of outcomes. RESULTS Twelve thousand four hundred ten survivors were matched to 124,100 controls. Survivors were not at increased risk of receiving a positive COVID-19 test (386 [3.1%] v 3,946 [3.2%]; P = .68) and were more likely to be fully vaccinated (hazard ratio, 1.23; 95 CI, 1.20 to 1.37). No increase in risk among survivors was seen in emergency department visits (adjusted odds ratio, 1.2; 95 CI, 0.9 to 1.6; P = .19) or hospitalization (adjusted odds ratio, 1.8; 95 CI, 1.0 to 3.5; P = .07). No survivor experienced intensive care unit admission or died after COVID-19 infection. Pulmonary radiation or chemotherapies associated with pulmonary toxicity were not associated with increased risk. CONCLUSION Cancer survivors were not at increased risk of COVID-19 infections or severe sequelae. These results can inform risk-counseling of survivors and their caregivers. Further study is warranted to determine risk in older survivors, specific subsets of survivors, and that associated with novel COVID-19 variants.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".