Abstract B115: A pooled analysis of smoking and alcohol drinking and risk of multiple myeloma in the International Multiple Myeloma Consortium
Bibliographic record
Abstract
Abstract Risk of multiple myeloma (MM), a highly fatal cancer, is increased in older age, men, African Americans, and persons with monoclonal gammopathy of undetermined significance (MGUS). Modifiable risk factors for MM remain obscure. Tobacco and alcohol use findings are inconsistent. To further assess the etiologic role of these lifestyle factors, the International Multiple Myeloma Consortium (IMMC) pooled individual-level questionnaire data from 6 case-control studies with alcohol data (n: cases=1,484, controls=6,542) and 9 case-control studies with smoking data (n: cases=2,662, controls=11,890). A pooled multivariable logistic regression analysis using a random effects model and adjusting for age, race, and study center location showed a decreased MM risk among men who reported ever drinking alcohol regularly compared with non-drinkers [odds ratio (OR) 0.71, 95% confidence interval (CI) 0.57–0.87], while results among women were null (OR 0.98, 0.76–1.26). Frequency, duration, and cumulative lifetime consumption of alcohol use were not linearly associated with MM risk among men or women. Neither a history of cigarette smoking compared to never smokers, nor any quantification of dose or duration of smoking was associated with MM risk in the pooled study population. Our findings are very similar to those reported from a pooled analysis of smoking and alcohol use conducted among case-control studies of non-Hodgkin lymphoma, a collection of lymphoid malignancies that are predominatly B-cell in origin, like MM (1, 2). Prospective studies may provide further insight into the association between alcoholic beverage consumption and MM risk. References: 1. Morton LM, Zheng T, Holford TR, Holly EA, Chiu BC, Costantini AS, Stagnaro E, Willett EV, Dal Maso L, Serraino D, Chang ET, Cozen W, Davis S, Severson RK, Bernstein L, Mayne ST, Dee FR, Cerhan JR, Hartge P; InterLymph Consortium. Alcohol consumption and risk of non-Hodgkin lymphoma: a pooled analysis. Lancet Oncol 2005;6:469–76. 2. Morton LM, Hartge P, Holford TR, Holly EA, Chiu BC, Vineis P, Stagnaro E, Willett EV, Franceschi S, La Vecchia C, Hughes AM, Cozen W, Davis S, Severson RK, Bernstein L, Mayne ST, Dee FR, Cerhan JR, Zheng T. Cigarette smoking and risk of non-Hodgkin lymphoma: a pooled analysis from the International Lymphoma Epidemiology Consortium (interlymph). Cancer Epidemiol Biomarkers Prev 2005;14:925–33. Citation Information: Cancer Prev Res 2011;4(10 Suppl):B115.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 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".