Abstract 3446: Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of glioma: Results from the Glioma International Case Control Study
Bibliographic record
Abstract
Abstract Background: Numerous epidemiologic studies have examined the association between aspirin (ASA), non-steroid anti-inflammatory drugs (NSAIDs) and the development of glioma, but the results have been inconsistent. The goal of this study was to evaluate the relationship between the intake of these drugs and glioma risk in a large, international case-control study. Methods: Between 2010 and 2015, the Glioma International Case-Control Study (GICC) recruited newly diagnosed glioma cases and matched controls in 14 different sites across five countries. Each subject was interviewed using a standardized questionnaire to obtain NSAIDs and ASA use. We examined the associations between ever use (at least > 6 months), duration of drug use and glioma histology. Ever use data on 4533 glioma cases and 4171 controls was combined using maximum likelihood estimation/restricted maximum likelihood meta-analysis methods. Furthermore, based on a priori hypotheses, we performed subgroup analyses based on gender and glioma histological grades. Results: Use of ASA for > 6 months was associated with a 33% lower glioma risk compared to those who never took it (adjusted Meta-OR 0.67, 95% CI 0.54-0.83). Duration of intake showed a significant trend test (p < 0.0001), with ORs became lower for increasing number of years of ASA use. In subgroup analyses, intake of ASA was significantly associated with glioma risk in both men and women (adjusted Meta-OR = 0.65, 95% CI 0.51-0.84 for men; adjusted Meta-OR = 0.74, 95% CI 0.58-0.93 for women). ASA intake was protective for grade IV glioma (glioblastoma) and grade II/III glioma (adjusted meta-OR 0.63, 95% CI 0.5-0.8 for glioblastoma; adjusted meta-OR 0.67, 95% CI 0.50 - 0.89 for grade II/III glioma). For NSAIDs intake, ever use > 6 months was not associated with glioma risk (adjusted meta-OR 0.87, 95% CI 0.71-1.07). However, NSAIDs use was protective for women (adjusted meta-OR 0.72, 95% CI 0.55-0.93) in subgroup analyses but not for men (adjusted meta-OR 1.03; 95% CI 0.86-1.23). The interaction between gender, NSAIDs and glioma risk was significant (p-value 0.0076).. Sensitivity analyses excluding those who took ASA or NSAIDs within the past 12 months for headache, and the removal of proxy respondents did not change our results. Conclusion: ASA was associated with a significant protective effect for glioma, but NSAIDs were only associated with reduced glioma risk in women. Given the possibility of recall bias in case-control studies of brain tumors, we may verify dosage and duration of drug intake in those countries with electronic pharmacy records within the GICC. Citation Format: Rose K. Lai, Renke Zhou, E. Susan Amirian, Christoffer Johansen, Michael E. Scheurer, Georgina N. Armstrong, Ching C. Lau, Elizabeth B. Claus, Jill S. Barnholtz-Sloan, Dora Il’yasova, Joellen Schildkraut, Francis Ali-Osman, Siegal Sadetzki, Richard Houlston, Robert B. Jenkins, Daniel Lachance, Sara H. Olson, Jonine L. Bernstein, Ryan T. Merrell, Margaret R. Wrensch, Faith G. Davis, Sanjay Shete, Christopher I. Amos, Beatrice S. Melin, Melissa Bondy. Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of glioma: Results from the Glioma International Case Control Study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3446.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.006 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".