Late Mortality Among 5-Year Survivors of Childhood Cancer: A Summary From the Childhood Cancer Survivor Study
Bibliographic record
Abstract
The Childhood Cancer Survivor Study (CCSS) has assembled the largest cohort to date for assessment of late mortality. Vital status and cause of death of all patients eligible for participation in CCSS was determined using the National Death Index and death certificates to characterize the mortality experience of 20,483 survivors, representing 337,334 person-years of observation. A total of 2,821 deaths have occurred as of December 31, 2002. The overall cumulative mortality is 18.1% (95% CI, 17.3 to 18.9) at 30 years from diagnosis. With time, while all-cause mortality rates have been stable, the pattern of late death is changing. Mortality attributable to recurrence or progression of primary disease is decreasing, with increases in rates of mortality attributable to subsequent neoplasms (standardized mortality ratios [SMR], 15.2; 95% CI, 13.9 to 16.6), cardiac death (SMR, 7.0; 95% CI, 5.9 to 8.2), and pulmonary death (SMR, 8.8; 95% CI, 6.8 to 11.2) largely due to treatment-related causes. In addition, the CCSS has identified specific treatment-related risk factors for late mortality. Radiotherapy (relative risk [RR], 2.9; 95% CI, 2.1 to 4.2), alkylating agents (RR, 2.2; 95% CI, 1.6 to 3.0), and epipodophyllotoxins (RR, 2.3; 95% CI, 1.2 to 4.5) increase the risk of death due to subsequent malignancy. Cardiac radiation exposure (RR, 3.3; 95% CI, 2.0 to 5.5) and high dose of anthracycline exposure (RR, 3.1; 95% CI, 1.6 to 5.8) are associated with late cardiac death. By continued longitudinal follow-up of the cohort and expansion of the cohort to include patients diagnosed between 1987 and 1999, the CCSS will remain a primary resource for assessment of late mortality of survivors of childhood cancers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".