Hospitalization Rates Among Survivors of Young Adult Malignancies
Bibliographic record
Abstract
PURPOSE: There are limited data on health care use among survivors of young adult cancers. We aimed to describe patterns of hospitalization among a cohort of long-term survivors compared with noncancer controls. METHODS: Persons diagnosed between the ages of 20 and 44 years with malignancies in Ontario, Canada, from 1992 to 1999, who lived at least 5 years recurrence free, were identified using the Ontario Cancer Registry and matched to noncancer controls. Hospitalizations were determined using hospital discharges, and rates were compared between survivors and controls. The absolute excess rate of hospitalizations was determined for each type of malignancy in survivors per 100 person-years of follow-up. RESULTS: The cohort included 20,275 survivors and 101,344 noncancer controls. During the study period, 6,948 (34.3%) survivors were admitted to the hospital and the adjusted relative rate (ARR) of hospitalizations in survivors compared with controls was 1.51 (95% CI, 1.48 to 1.54). The rate of hospitalization was highest for survivors of upper GI, leukemia, and urologic malignancies. The hospitalization rate (per person) for survivors significantly decreased from 0.22 in the first time period examined (5 to 8 years after diagnosis) to 0.15 in the last time period examined (18 to 20 years after diagnosis, P < .0001). However, at all time periods, survivors were more likely to be hospitalized than controls (ARR at 5 to 8 years, 1.67 [95% CI, 1.57 to 1.81]; ARR at 18 to 20 years, 1.22 [95% CI, 1.08 to 1.37]). CONCLUSION: Survivors of young adult cancers have an increased rate of hospitalization compared with controls. The rate of hospitalization for 20-year survivors did not return to baseline, indicating a substantial and persistent burden of late effects among this generally young population.
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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 | 0.000 |
| 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 | 0.000 | 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".