A geospatial assessment of industrial releases and pediatric neuroblastic tumours at diagnosis: A retrospective case series
Bibliographic record
Abstract
Environmental risk factors associated with malignancy of pediatric neuroblastic tumours are not well-known and few studies have examined the relationship between industrial emissions and neuroblastic tumour diagnosis. A retrospective case series of 310 patients was evaluated at a tertiary hospital in Toronto, Canada between January 2008, and December 2018. Data from the National Pollutant Release Inventory (NPRI) were used to estimate exposure for a dozen chemicals with known or suspected carcinogenicity or embryotoxicity. Comparative analysis and predictive logistic regression models for malignant versus benign neuroblastic tumours included variables for residential proximity, number, and type of industries, mean total emissions within 2 km, and inverse distance weighted (IDW) quantity of chemical-specific industrial emissions estimated within 10 and 50 km of cases. No significant difference was seen between malignant and benign cases with respect to the mean nearest residential distance to industry, the number or type of industry, or the mean total quantity of industrial emissions within a 2 km radius of residential location of cases. However, there were statistically significant differences in the interpolated IDW emissions of dioxins and furans released between 1993 and 2019 within 10 km. Concentrations were significantly higher in malignant neuroblastic tumours at 1.65 grams (g) toxic equivalent (TEQ) (SD 2.01 g TEQ) compared to benign neuroblastic tumours at 1.13 g TEQ (SD 0.84 g TEQ) (p = 0.05). Within 50 km 3 years prior to diagnosis, malignant cases were exposed to higher levels of aluminum, benzene, and nitrogen dioxide (p = 0.02, p = 0.04, and p = 0.02 respectively). Regression analysis of the IDW emissions within a 50 km radius revealed higher odds of exposure to benzene for malignant neuroblastic tumours (OR = 1.03, CI: 1.01–1.05, p = 0.01). These preliminary findings suggest a potential role of industrial emissions in the development of malignant pediatric neuroblastic tumours and underscore the need for further research to investigate these associations.
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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) | 0.000 | 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".