No excess of early onset cancer in family members of Wilms tumor patients
Bibliographic record
Abstract
BACKGROUND: Wilms tumor is one of the few pediatric cancers with well-defined familial and genetic components. The authors assessed the risk of early-onset cancers in first- and second-degree relatives of patients enrolled by the National Wilms Tumor Study Group. METHODS: Using a stratified sampling scheme that targeted 530 families of patients who were believed a priori to have a genetic contribution to their disease, the authors conducted interviews regarding cancer occurrence in 4258 family members from 296 families of patients with Wilms tumor. Reports of malignant neoplasms that occurred before 55 years of age were confirmed by review of medical records wherever possible. A period of risk was defined for each family member based on calendar time and his or her relationship to the proband. RESULTS: Ninety-nine cancers were observed, whereas 126.8 were expected by applying standard cancer rates for age and calendar period to the 120,885 person-years at risk. The standardized incidence ratio (SIR) was O-E = 0.78 with 95% confidence interval (CI) of (0.64, 0.95). In subgroup analyses, the highest relative risks were observed for parents of the index case (O/E = 21/13.0 = 1.6, 95% CI = 1.0, 2.5) and for leukemia (O/E = 9/4.9 = 1.9, 95% CI= 0.85,3.5). CONCLUSIONS: The results of this study may provide reassurance to families of children who have had Wilms tumor. Potential sources of bias included the low (56%) rate of participation of targeted families. In general, the biases might have led to the underreporting of some cancers, especially in more distant relatives. The possibility of a slight excess of cancer in parents of Wilms tumor patients could not be excluded.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".