Long-term outcomes by race/ethnicity in the Childhood Cancer Survivor Study (CCSS) cohort.
Bibliographic record
Abstract
10070 Background: Racial/ethnic differences in risk for long-term adverse outcomes in childhood cancer survivors are not well established. Methods: Hispanic (H: 750, 5.4%) and African American (AA: 694, 5%) survivors were compared to non-Hispanic whites (NHW: 12,397, 89.6%) for late mortality, subsequent malignant neoplasms (SMN), and CTCAE-graded chronic health conditions. Poisson regression models adjusted for demographic/clinical factors were used to calculate relative rate (RR) and 95% confidence intervals (CI). Results: AA and H survivors were younger at diagnosis, and had lower SES. Mortality: No racial/ethnic difference was observed (Table). SMN: Risk did not differ by race/ethnicity (cumulative incidence 30y from diagnosis: NHW: 9.0%, AA: 6.6%, H: 7.0%, p=0.3). However, risk for non-melanoma skin cancer (NMSC) was very low among irradiated AA and H survivors (Table). Chronic Health Conditions (grades 3-5): Compared to NHW, AA were more likely to report cardiac conditions and H endocrine conditions (Table). These differences were attenuated after adjusting for cardiovascular risk factors (CVRF: dyslipidemia, hypertension, smoking). Conclusions: By and large, when adjusted for SES and treatment, morbidity/mortality did not differ by race/ethnicity. However, specific morbidities (H: endocrine, AA: cardiac) were more prevalent, and were partially explained by CVRFs. Risk of NMSC was negligible among irradiated AA and H, relative to irradiated NHW. These findings inform targeted intervention opportunities. NHW AA H Late Mortality RR (95% CI)* All-cause Ref 1.0 (0.8 – 1.4) 0.9 (0.7 – 1.2) P = 0.9 P = 0.5 SN 1.3 (0.7–2.2) 0.9 (0.5-1.6) P = 0.4 P = 0.7 Cardiac 1.6 (0.5–4.6) 1.5 (0.7–3.5) P = 0.4 P = 0.3 SMNs RR (95% CI)* 1.3 (0.8-2.0) 1.2 (0.8-1.7) P = 0.2 P = 0.4 NMSC (irradiated cohort) 0.0 (0.0-0.2) 0.3 (0.1-0.8) P < 0.001 P = 0.01 Chronic Health Conditions (grade 3-5) RR (95% CI)* Any 1.1 (0.9-1.4) 1.2 (1.0-1.5) P = 0.5 P = 0.06 Cardiac 1.6 (1.0-2.4) 1.2 (0.8-1.7) P = 0.03 P = 0.5 CardiacΩ 1.4 (0.9-2.1) 1.1 (0.7-1.7) P = 0.1 P = 0.7 Endocrine 1.0 (0.6-1.5) 1.7 (1.2-2.3) P = 0.8 P = 0.001 EndocrineΩ 0.9 (0.6-1.4) 1.4 (1.0-1.9) P = 0.7 P = 0.08 *From Poisson models adjusted for treatment, SES. Ω Further adjusted for CVRF.
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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 | 0.002 |
| 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) | 0.002 | 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".