Longitudinal follow‐up of adult survivors of Ewing sarcoma: A report from the Childhood Cancer Survivor Study
Bibliographic record
Abstract
BACKGROUND: Ewing sarcoma survivors (ESSs) are at increased risk for treatment-related complications. The incidence of treatment-related morbidity and late mortality with aging is unknown. METHODS: This study reports survival probabilities, estimated with the Kaplan-Meier method, and the cumulative incidence of cause-specific mortality and chronic conditions among ESSs in the Childhood Cancer Survivor Study who were treated between 1970 and 1986. Piecewise exponential models were used to estimate relative rates (RRs) and 95% confidence intervals (CIs) for these outcomes. Chronic conditions were graded with the Common Terminology Criteria for Adverse Events (version 4.03). RESULTS: Among 404 5-year ESSs (median age at last follow-up, 34.8 years; range, 9.1-54.8 years), the 35-year survival rate was 70% (95% CI, 66%-74%). Late recurrence (cumulative incidence at 35 years, 15.1%) was the most common cause of death, and it was followed by treatment-related causes (11.2%). There were 53 patients with subsequent neoplasms (SNs; cumulative incidence at 35 years, 24.0%), and 38 were malignant (14.3% at 35 years). The standardized incidence ratios were 377.1 (95% CI, 172.1-715.9) for osteosarcoma, 28.9 (95% CI, 3.2-104.2) for acute myeloid leukemia, 14.9 (95% CI, 7.9-25.5) for breast cancer, and 13.1 (95% CI, 4.8-28.5) for thyroid cancer. Rates of chronic conditions were highest for musculoskeletal (RR, 18.1; 95% CI, 12.8-25.7) and cardiac complications (RR, 1.8; 95% CI, 1.4-2.3). Thirty-five years after the diagnosis, the cumulative incidences of any chronic conditions and 2 or more chronic conditions were 84.6% (95% CI, 80.4%-88.8%) and 73.8% (95% CI, 67.8%-79.9%), respectively. CONCLUSIONS: With extended follow-up, ESSs' risk for late mortality and SNs does not plateau. Treatment-related chronic conditions develop years after therapy, and this supports the need for lifelong follow-up. Cancer 2017;123:2551-60. © 2017 American Cancer Society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".