Temporal trends in chronic disease among survivors of childhood cancer diagnosed across three decades: A report from the Childhood Cancer Survivor Study (CCSS).
Bibliographic record
Abstract
LBA10500 Background: Modifications in childhood cancer treatments in recent decades have contributed to reductions in late mortality among 5-year survivors. We used the recently expanded CCSS cohort to investigate whether these changes have also reduced the incidence of chronic disease. Methods: We evaluated the incidence of severe, disabling/life-threatening, or fatal chronic health conditions (Common Terminology Criteria for Adverse Events, CTCAE grades 3-5) among 5-year survivors diagnosed prior to age 21 years from 1970 through 1999. We calculated the 15-year cumulative incidence of chronic health conditions by decade of cancer diagnosis and compared risk across decades using Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CI). Results: Among 23,601 survivors, median age 28 years (range 5-63), 21 years from diagnosis (5-43), the 15-year cumulative incidence of grade 3-5 conditions decreased from 12.7% in survivors diagnosed in the 1970s to 10.1% and 8.8% in those diagnosed in the 1980s and 1990s (per 10 years, HR 0.84 [95% CI = 0.80-0.89]). The association with diagnosis decade was attenuated (HR 0.92 [0.85-1.00]) when detailed treatment data were included in the model, indicating that treatment reductions mediated risk. Adjusted for sex and attained age, significant reduction in risk over time was found among survivors of Wilms tumor (HR 0.57 [0.46-0.70]), Hodgkin lymphoma (HR 0.75 [0.65-0.85]), astrocytoma (HR 0.77 [0.64-0.92]), non-Hodgkin lymphoma (HR 0.79 [0.63-0.99]), and acute lymphoblastic leukemia (HR 0.86 [0.76-0.98]). Decreases were largely driven by a reduced incidence of endocrine conditions (1970s: 4.0% v. 1990s:1.6%; HR 0.66 [0.59-0.73]) and subsequent malignant neoplasms (1970s: 2.4% v. 1990s: 1.6%; HR 0.85 [0.76-0.96]). Significant reductions were also found for gastrointestinal (HR 0.80 [0.66-0.97]) and neurological conditions (HR 0.77 [0.65-0.91]), but not cardiac or pulmonary conditions. Conclusions: Changes in childhood cancer treatment protocols have not only extended lifespan for many survivors, but have also reduced the incidence of serious chronic morbidity in this 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".