<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Cerhan JR</submitter><funding>Intramural NIH HHS</funding><funding>NCATS NIH HHS</funding><funding>NCRR NIH HHS</funding><funding>NIDA NIH HHS</funding><funding>NIAID NIH HHS</funding><funding>NIEHS NIH HHS</funding><funding>NIDCD NIH HHS</funding><funding>NHLBI NIH HHS</funding><funding>NCI NIH HHS</funding><funding>CIHR</funding><pagination>15-25</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC4155465</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>2014(48)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>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.&lt;h4>Methods&lt;/h4>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.&lt;h4>Results&lt;/h4>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 = </pubmed_abstract><journal>Journal of the National Cancer Institute. Monographs</journal><pubmed_title>Medical history, lifestyle, family history, and occupational risk factors for diffuse large B-cell lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project.</pubmed_title><pmcid>PMC4155465</pmcid><funding_grant_id>U01 CA118444</funding_grant_id><funding_grant_id>R01 CA104682</funding_grant_id><funding_grant_id>R01CA104682</funding_grant_id><funding_grant_id>R01 CA122663</funding_grant_id><funding_grant_id>K23 CA102216</funding_grant_id><funding_grant_id>R01 CA062006</funding_grant_id><funding_grant_id>R01CA154643-01A1</funding_grant_id><funding_grant_id>N01 PC067010</funding_grant_id><funding_grant_id>CA143947</funding_grant_id><funding_grant_id>R01 CA50850</funding_grant_id><funding_grant_id>N01-PC-65064</funding_grant_id><funding_grant_id>N01-CP-ES-11027</funding_grant_id><funding_grant_id>N01-PC-67009</funding_grant_id><funding_grant_id>R01CA122663</funding_grant_id><funding_grant_id>R03 CA150037</funding_grant_id><funding_grant_id>R01 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CA165923</funding_grant_id><funding_grant_id>R03 CA132153</funding_grant_id><funding_grant_id>R01 CA154643</funding_grant_id><funding_grant_id>R01 DA014690</funding_grant_id><funding_grant_id>CA51086</funding_grant_id><funding_grant_id>T32 HL007152</funding_grant_id><funding_grant_id>R01 CA092153</funding_grant_id><funding_grant_id>R01 CA051086</funding_grant_id><funding_grant_id>CA92153</funding_grant_id><funding_grant_id>R01 AI050850</funding_grant_id><funding_grant_id>N01-CP-95618</funding_grant_id><funding_grant_id>CA62006</funding_grant_id><funding_grant_id>R01 CA14690</funding_grant_id><funding_grant_id>UL 1 RR024160</funding_grant_id><funding_grant_id>CA150037</funding_grant_id><funding_grant_id>R01 CA92153-S1</funding_grant_id><funding_grant_id>R01CA100555</funding_grant_id><funding_grant_id>R01CA087014</funding_grant_id><funding_grant_id>R01CA45614</funding_grant_id><funding_grant_id>R03 CA125831</funding_grant_id><funding_grant_id>CA165923</funding_grant_id><funding_grant_id>R03CA132153</funding_grant_id><pubmed_authors>Sampson JN</pubmed_authors><pubmed_authors>Skibola CF</pubmed_authors><pubmed_authors>Morton LM</pubmed_authors><pubmed_authors>Cerhan JR</pubmed_authors><pubmed_authors>Dal Maso L</pubmed_authors><pubmed_authors>Flowers CR</pubmed_authors><pubmed_authors>Miligi L</pubmed_authors><pubmed_authors>Clavel J</pubmed_authors><pubmed_authors>Monnereau A</pubmed_authors><pubmed_authors>Blair A</pubmed_authors><pubmed_authors>Kane EV</pubmed_authors><pubmed_authors>Rothman N</pubmed_authors><pubmed_authors>Paltiel O</pubmed_authors><pubmed_authors>Foran JM</pubmed_authors><pubmed_authors>Kricker A</pubmed_authors><pubmed_authors>Wang SS</pubmed_authors><pubmed_authors>Nieters A</pubmed_authors><pubmed_authors>Bernstein L</pubmed_authors><pubmed_authors>Slager SL</pubmed_authors></additional><is_claimable>false</is_claimable><name>Medical history, lifestyle, family history, and occupational risk factors for diffuse large B-cell lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project.</name><description>&lt;h4>Background&lt;/h4>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.&lt;h4>Methods&lt;/h4>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.&lt;h4>Results&lt;/h4>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 = </description><dates><release>2014-01-01T00:00:00Z</release><publication>2014 Aug</publication><modification>2026-05-07T07:11:37.807Z</modification><creation>2026-04-07T22:45:08.842Z</creation></dates><accession>S-EPMC4155465</accession><cross_references><pubmed>25174023</pubmed><doi>10.1093/jncimonographs/lgu010</doi></cross_references></HashMap>