Incidence of Neuroblastoma After a Screening Program
Bibliographic record
Abstract
PURPOSE: A significant increase in the incidence of neuroblastoma occurred among a 5-year birth cohort (May 1989 to April 1994) during an active urinary screening program for its early detection. We examined the postscreening incidence of neuroblastoma in the subsequent 5-year birth cohort (May 1994 to April 1999), with follow-up to 2002, to determine whether the incidence remained increased. PATIENTS AND METHODS: We reviewed institutional records of patients diagnosed with neuroblastoma during the period from 1994 to 2002 who were born in 1994 to 1999 in the province of Quebec, as well as in the state of Minnesota and the province of Ontario, regions that had served as controls during the screening interval. We calculated and compared incidence rates during the 1994 to 2002 time period. RESULTS: For the 5-year birth cohort as a whole, the rate of newly diagnosed neuroblastoma was higher in Quebec than in the control populations of Minnesota and Ontario (standardized incidence ratio, 1.34; 95% CI, 1.03 to 1.70). However, in years 4 and 5 of the interval, population-based incidence declined to the same levels as those seen in the control areas. CONCLUSION: The institution of a urinary screening program for neuroblastoma led to increased awareness of the diagnosis and an elevated rate of diagnosis even after the completion of the screening evaluation. However, this halo effect was transient, with diagnostic rates subsequently decreasing within the range seen in control populations.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".