Glyphosate use and associations with non-Hodgkin lymphoma major histological sub-types: findings from the North American Pooled Project
Bibliographic record
Abstract
Objectives Some epidemiological studies have suggested positive associations between glyphosate use and non-Hodgkin lymphoma (NHL), but evidence is inconsistent and few studies could evaluate histological sub-types. Here, associations between glyphosate use and NHL incidence overall and by histological sub-type were evaluated in a pooled analysis of case-control studies. Methods The analysis included 1690 NHL cases [647 diffuse large B-cell lymphoma (DLBCL), 468 follicular lymphoma (FL), 171 small lymphocytic lymphoma (SLL), and 404 other sub-types] and 5131 controls. Logistic regression was used to estimate adjusted odds ratios (OR) and 95% confidence intervals (CI) for NHL overall and sub-types with self-reported ever/never, duration, frequency, and lifetime-days of glyphosate use. Results Subjects who ever used glyphosate had an excess of NHL overall (OR 1.43, 95% CI 1.11-1.83). After adjustment for other pesticides, the OR for NHL overall with "ever use" was 1.13 (95% CI 0.84-1.51), with a statistically significant association for handling glyphosate >2 days/year (OR 1.73, 95% CI 1.02-2.94, P-trend=0.2). In pesticide-adjusted sub-type analyses, the ordinal measure of lifetime-days was statistically significant (P=0.03) for SLL, and associations were elevated, but not statistically significant, for ever years or days/year of use. Handling glyphosate >2 days/year had an excess of DLBCL (OR 2.14, 95% CI 1.07-4.28; P-trend=0.2). However, as with the other sub-types, consistent patterns of association across different metrics were not observed. Conclusions There was some limited evidence of an association between glyphosate use and NHL in this pooled analysis. Suggestive associations, especially for SLL, deserve additional attention.
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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) | 0.001 | 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".