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Record W4400215156 · doi:10.1158/1055-9965.epi-24-0243

Maternal Substance Use and Childhood Cancer—Letter

2024· article· en· W4400215156 on OpenAlexaff
Banmeet Padda, Émilie Brousseau, Nathalie Auger

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2024
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsMcGill UniversityInstitut National de Santé Publique du QuébecUniversité de Montréal
Fundersnot available
KeywordsChildhood cancerSubstance useMedicineCancerPsychiatryPsychologyInternal medicine

Abstract

fetched live from OpenAlex

To the Editor,Wimberly and colleagues (1) examined the impact of maternal substance use on the development of childhood cancer. The authors surveyed the parents of 3,145 children with cancer and found that prenatal exposure to illicit drugs was associated with an increased prevalence of retinoblastoma and intracranial embryonal tumors but was protective against acute lymphocytic leukemia.The study was based on a case series of children with cancer, the most frequent types being acute lymphocytic leukemia (29%) and neuroblastoma (14%). A representative sample of children without cancer was not included. To account for the absence of a comparison group, the authors compared children with a given cancer against children with other cancers. In total, 15 subtypes of cancer were examined, with each subtype contrasted against the remaining 14. Because of the design, patients with a given cancer were moved from the numerator to the denominator in each prevalence ratio, having the effect of inverting the measure of association. The average of the prevalence ratios is expected to be centered around 1.The analysis was heavily weighted by acute lymphocytic leukemia and neuroblastoma, the most frequent cancers. The pattern of substance use for these two cancers determines the direction of association for other cancers. As the prevalence of illicit drug use was lower for these cancers, placing them in the comparison group necessarily leads to prevalence ratios that are above 1 for every other type of cancer, explaining the association of illicit drugs with retinoblastoma and intracranial embryonal tumors in Table 2 (1). The protective associations of illicit drug use with acute lymphocytic leukemia and of tobacco use with certain cancers are similarly artifacts.To adequately assess the relationship between maternal substance use and childhood cancer, an unaffected group of children without cancer is required in the analysis (2). Each type of cancer is compared against this reference, with no danger of inverting the prevalence ratio each time. Suitable designs include case–control studies, in which representative controls are selected from the underlying population that gave rise to the cases (3).Tobacco is a dangerous carcinogen. There is growing evidence that illicit drugs may also be carcinogenic (4, 5). Suggesting that tobacco or illicit drug use in pregnancy protects against childhood cancer is ill-advised in the absence of a solid study design. Researchers should be mindful of the possibility of bias when the findings of a case series suggest protective effects of known carcinogens.No disclosures were reported.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.016
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0160.019
Insufficient payload (model declined to judge)0.0040.003

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.

Opus teacher head0.041
GPT teacher head0.341
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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