MétaCan
Menu
Back to cohort
Record W3158799514 · doi:10.1093/jncimonographs/lgu010

Medical History, Lifestyle, Family History, and Occupational Risk Factors for Diffuse Large B-Cell Lymphoma: The InterLymph Non-Hodgkin Lymphoma Subtypes Project

2014· article· en· W3158799514 on OpenAlexfundno aff
James R. Cerhan, Anne Kricker, Ora Paltiel, Christopher R. Flowers, Sophia Wang, Alain Monnereau, A. Blair, Luigino Dal Maso, Eleanor Kane, Alexandra Nieters, James M. Foran, Lucia Miligi, Jacqueline Clavel, Leslie Bernstein, Nathaniel Rothman, Susan L. Slager, Joshua N. Sampson, Lindsay M. Morton, Christine F. Skibola

Bibliographic record

VenueJNCI Monographs · 2014
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Institute of Allergy and Infectious DiseasesNational Institute on Deafness and Other Communication DisordersNational Institute on Drug AbuseNational Institutes of HealthNational Cancer InstituteNational Heart, Lung, and Blood InstituteNational Institute of Environmental Health SciencesCanadian Institutes of Health Research
KeywordsMedicineOdds ratioInternal medicineBody mass indexFamily historyConfidence intervalLymphomaDiffuse large B-cell lymphomaGastroenterology

Abstract

fetched live from OpenAlex

BACKGROUND: Although risk factors for diffuse large B-cell lymphoma (DLBCL) have been suggested, their independent effects, modification by sex, and association with anatomical sites are largely unknown. METHODS: In a pooled analysis of 4667 cases and 22639 controls from 19 studies, we used stepwise logistic regression to identify the most parsimonious multivariate models for DLBCL overall, by sex, and for selected anatomical sites. RESULTS: DLBCL was associated with B-cell activating autoimmune diseases (odds ratio [OR] = 2.36, 95% confidence interval [CI] = 1.80 to 3.09), hepatitis C virus seropositivity (OR = 2.02, 95% CI = 1.47 to 2.76), family history of non-Hodgkin lymphoma (OR = 1.95, 95% CI = 1.54 to 2.47), higher young adult body mass index (OR = 1.58, 95% CI = 1.12 to 2.23, for 35+ vs 18.5 to 22.4 kg/m(2)), higher recreational sun exposure (OR = 0.78, 95% CI = 0.69 to 0.89), any atopic disorder (OR = 0.82, 95% CI = 0.76 to 0.89), and higher socioeconomic status (OR = 0.86, 95% CI = 0.79 to 0.94). Additional risk factors for women were occupation as field crop/vegetable farm worker (OR = 1.78, 95% CI = 1.22 to 2.60), hairdresser (OR = 1.65, 95% CI = 1.12 to 2.41), and seamstress/embroider (OR = 1.49, 95% CI = 1.13 to 1.97), low adult body mass index (OR = 0.46, 95% CI = 0.29 to 0.74, for <18.5 vs 18.5 to 22.4 kg/m(2)), hormone replacement therapy started age at least 50 years (OR = 0.68, 95% CI = 0.52 to 0.88), and oral contraceptive use before 1970 (OR = 0.78, 95% CI = 0.62 to 1.00); and for men were occupation as material handling equipment operator (OR = 1.58, 95% CI = 1.02 to 2.44), lifetime alcohol consumption (OR = 0.57, 95% CI = 0.44 to 0.75, for >400 kg vs nondrinker), and previous blood transfusion (OR = 0.69, 95% CI = 0.57 to 0.83). Autoimmune disease, atopy, and family history of non-Hodgkin lymphoma showed similar associations across selected anatomical sites, whereas smoking was associated with central nervous system, testicular and cutaneous DLBCLs; inflammatory bowel disease was associated with gastrointestinal DLBCL; and farming and hair dye use were associated with mediastinal DLBCL. CONCLUSION: Our results support a complex and multifactorial etiology for DLBCL with some variation in risk observed by sex and anatomical site.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.019
GPT teacher head0.257
Teacher spread0.238 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations130
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJNCI MonographsSame topicLymphoma Diagnosis and TreatmentFrench-language works237,207