SCREENING OF INFANTS AND MORTALITY DUE TO NEUROBLASTOMA
Bibliographic record
Abstract
Background Neuroblastoma, the most common extracranial solid tumor that occurs in early childhood, can be identified in the preclinical stages by the detection of catecholamines in the urine. However, it is unknown whether routine screening for neuroblastoma reduces mortality due to this disease. Methods Through their parents, we offered screening for neuroblastoma at three weeks and six months of age to all 476,654 children born in the province of Quebec, Canada, during a five-year period (May 1, 1989, through April 30, 1994). The participation rate was 92 percent. The rate of death due to neuroblastoma was determined and compared with the rates in several unscreened control populations born during the same period. Results Among children younger than eight years of age in the Quebec cohort, there were 22 deaths due to neuroblastoma; the cumulative (±SE) mortality rate due to neuroblastoma was 4.78±1.14 per 100,000 children over a period of nine years. The standardized incidence ratios for death due to neuroblastoma for the Quebec cohort were 1.11 (95 percent confidence interval, 0.64 to 1.92) as compared with a control group in Ontario, Canada; 0.90 (95 percent confidence interval, 0.48 to 1.70) as compared with a control gr oup in Minnesota; 1.40 (95 percent confidence interval, 0.81 to 2.41) as compared with a control group in Florida; and 0.96 (95 percent confidence interval, 0.56 to 1.66) as compared with a control group in the Greater Delaware Valley. The standardized mortality ratio for the Quebec cohort as compared with the rest of Canada was 1.39 (95 percent confidence interval, 0.85 to 2.30); the odds ratio for the comparison with a cohort born in Quebec before the screening program began was 0.98 (95 percent confidence interval, 0.54 to 1.77). Conclusions Screening infants for neuroblastoma does not appear to reduce mortality due to this disease. (N Engl J Med 2002;346:1041-6.) Copyright © 2002 Massachusetts Medical Society.
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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 | 0.000 |
| 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) | 0.001 | 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".