{"doi":"10.1016/j.ostima.2025.100380","title":"Association of baseline MRI-defined structural features with knee symptom trajectories over nine years: Data from the osteoarthritis initiative (OAI)","abstract":"The development of knee symptoms in OA over time can present with multiple phenotypes. This study aims to identify MRI-defined predictors of trajectories of knee symptoms. All knees in the Osteoarthritis Initiative (OAI) with at least one baseline score of 0 from one of four knee symptom measurements were included. These measurements included pain severity, knee pain frequency, and the Western Ontario and McMaster Universities Osteoarthritis Index knee pain and knee function scores. The latent class mixed model (LCMM) was employed to categorize knees into different trajectories and to assess their association with various MRI-defined structural features while controlling for important covariates. A total of 1221 knees were grouped into two classes: 596 with a minimal knee symptom trajectory and 625 with a rapidly progressive trajectory. The class-membership model revealed that the following variables were associated with being in the rapidly progressive phenotype: bone marrow lesions (BMLs) score (Odds Ratio (OR) of 1.12 [95% Confidence Interval (CI): 1.03, 1.22]) for each unit increase in BML total size scores; females, widespread pain, CES-D, overweight, and obesity. The age group 65 to 79 vs. that of 45 to 55 and highest year of education completed were less likely to be associated with the rapidly progressive knee pain group. Other covariates were not significant. Two distinct phenotypes/trajectories were consistently identified across all four knee symptom measurements in a multi-trajectory model. Modifiable factors such BMLs, BMI, widespread pain and depression may serve as indicators of higher risk of rapid knee symptom progression.","journal":"Osteoarthritis Imaging","year":2025,"id":580229,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":0.0,"corpus_rank":10304,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.5597,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":988492,"name":"Xiaoxiao Sun","orcid":"0000-0002-0823-8713","position":1,"is_corresponding":false},{"id":1038122,"name":"Yong Ge","orcid":"0000-0002-9630-795X","position":2,"is_corresponding":false},{"id":1491034,"name":"Thang Ngoc Duong","orcid":"0009-0002-4831-6461","position":3,"is_corresponding":false},{"id":325671,"name":"C. Kent Kwoh","orcid":"0000-0001-5937-550X","position":4,"is_corresponding":false},{"id":1038121,"name":"Shen Liu","orcid":"0000-0002-7997-3061","position":0,"is_corresponding":true}],"reference_count":27,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:58:38.868285Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}