Morbidity and health care use among siblings of children with cancer: A population‐based study
Bibliographic record
Abstract
BACKGROUND: Childhood cancer impacts the entire family unit. We sought to investigate its impact on the long-term physical health outcomes of siblings of children with cancer. PROCEDURE: Pediatric cancer patients diagnosed in Ontario, Canada between 1988 and 2016 were linked to biological siblings. Sibling cases were matched to population controls based on sex, age, geographic location, and number of other children in the family. After individual linkage to health services data, we compared several outcomes between sibling cases and controls: (a) physical health conditions (such as diabetes, hypertension, and death); (b) acute health care use (hospitalization, low- and high-acuity emergency department [ED] visits); and (c) preventive health care use (periodic health checkups, influenza vaccinations). Cox proportional hazards, recurrent event, or logistic regression models were used as appropriate. RESULTS: We identified 8529 sibling cases and 30,364 matched controls (median age at index: 6 years, median age at last follow-up 17 years). Compared to controls, siblings were at increased risk of hypertension (hazard ratio [HR] 1.8; 95% confidence interval [CI] 1.1-2.9; p = .01), had higher rates of low- and high-acuity ED visits (rate ratio 1.1; 95% CI 1.1-1.2; p < .001), and increased risk of hospitalization (HR 1.1; 95% CI 1.1-1.2; p < .001). Sibling cases were also more likely to receive preventive health care (p < .05). CONCLUSION: Increased risk of hypertension, high-acuity ED visits, and hospitalizations suggest that siblings may experience poorer health compared to controls. Counseling families about this potential increased risk and long-term follow-up of siblings to monitor their physical health may be justified.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".