{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Gholi Zadeh Kharrat F"],"funding":["NIAMS NIH HHS"],"pubmed_abstract":["<h4>Objective</h4>This study identifies distinct biobehavioral phenotypes among patients with chronic low back pain (cLBP) using Latent Profile Analysis (LPA).<h4>Methods</h4>These phenotypes were derived from baseline data from two cohorts within the NIH HEAL BACPAC consortium: BACKHOME, a large nationwide e-cohort (N = 3,025) utilized for model training, and COMEBACK as external test set, a deep phenotyping cohort (N = 450) utilized for generalization. The analysis incorporated variables including pain characteristics, psychosocial factors, lifestyle habits, and social determinants of health. Model fit was optimized via 10-fold cross-validation with 100 bootstraps and evaluated using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Entropy(uncertainty).<h4>Re"],"journal":["Pain medicine (Malden, Mass.)"],"pagination":["pnaf095"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12419233"],"repository":["biostudies-literature"],"pubmed_title":["Biobehavioral Phenotypes of Chronic Low Back Pain: Psychosocial Subgroup Identification Using Latent Profile Analysis."],"pmcid":["PMC12419233"],"funding_grant_id":["U19 AR076737"],"pubmed_authors":["REACH Investigators","Bishara A","Shah S","Fishman SM","Ewing SK","Mummaneni P","Barylak J","Matthew R","Guo XS","Torrisi S","Amar Kumar P","Berven S","Demarchis E","Mendoza E","Lynch J","Hue T","Castellanos J","Wu PH","Ornowski J","Butte A","Wu LA","Zheng P","Black DM","Keller A","Krug R","Vashisht R","Demir-Deviren S","Rupanagunta A","Scheffler A","Lin F","Bailey J","O'Neill C","Ferguson AR","Peterson T","Cummings J","Guerra SG","Fields A","Hunt CA","Del Rosario K","Han M","Takegami N","Gholi Zadeh Kharrat F","Lotz J","Navy C","Khattab K","Torres-Espin A","Strigo I","Zhou J","Huie JR","Zeidan F","Link T","Wallace MS","Mehling W","Akkaya Z","Kurillo G","Peterson TA","Lyu T","Vu AJ","Veres J","Umrao S","Bonnheim N"],"additional_accession":[]},"is_claimable":false,"name":"Biobehavioral Phenotypes of Chronic Low Back Pain: Psychosocial Subgroup Identification Using Latent Profile Analysis.","description":"<h4>Objective</h4>This study identifies distinct biobehavioral phenotypes among patients with chronic low back pain (cLBP) using Latent Profile Analysis (LPA).<h4>Methods</h4>These phenotypes were derived from baseline data from two cohorts within the NIH HEAL BACPAC consortium: BACKHOME, a large nationwide e-cohort (N = 3,025) utilized for model training, and COMEBACK as external test set, a deep phenotyping cohort (N = 450) utilized for generalization. The analysis incorporated variables including pain characteristics, psychosocial factors, lifestyle habits, and social determinants of health. Model fit was optimized via 10-fold cross-validation with 100 bootstraps and evaluated using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Entropy(uncertainty).<h4>Re","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jul","modification":"2026-06-02T17:40:59.439Z","creation":"2026-04-18T03:11:29.998Z"},"accession":"S-EPMC12419233","cross_references":{"pubmed":["40711854"],"doi":["10.1093/pm/pnaf095"]}}