{"doi":"10.1002/acr.24962","title":"Patient Acceptable Symptom State Versus Latent Class Analysis Outcome Classification: A Comparative Longitudinal Study of Knee Arthroplasty","abstract":"OBJECTIVE: To determine whether Patient Acceptable Symptom State (PASS), a single-item deterministic binary measure of pain and function outcome satisfaction, leads to better differentiation of outcome classification versus latent class analysis probability-based outcome subgroups 1 year after knee arthroplasty (KA). METHODS: We used data from Knee Arthroplasty Skills Training for Pain (KASTPain), a 1-year no-effect multicenter randomized clinical trial of participants with KA, along with prior work that developed and externally validated good and poor outcome trajectories. Confirmatory latent class analyses were conducted on 2 exemplar outcome measures (Euroquol visual analog scale single-item self-rated health and 4-item pain ratings) and compared with PASS scores. Separation of trajectories were used to compare good and poor latent class self-rated health/4-item pain trajectories and PASS score trajectories. RESULTS: Prevalence rates for poor outcomes were 10% for self-rated health and 20% for 4-item pain and PASS. Probabilistic latent class-derived classifications of self-rated health and 4-item pain outcomes outperformed PASS in separating growth trajectories. The effect size point estimates for 12-month 4-item pain scale score separation was approximately 3 times larger for latent class analyses as compared with PASS. CONCLUSIONS: When used for outcome classification, observed PASS scores consistently underperform relative to probabilistic latent class-derived subgroups of pain and self-rated health outcome. PASS is a weak substitute for probabilistic classification of other patient-reported outcome measures of KA outcome. Clinicians and researchers should rely on latent class analyses over PASS to differentiate between outcome subgroups after KA.","journal":"Arthritis Care & Research","year":2022,"id":267117,"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":null,"corpus_rank":null,"citation_count":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.6034,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":387712,"name":"Levent Dumenci","orcid":"0000-0003-0702-9511","position":1,"is_corresponding":false},{"id":387717,"name":"Daniel L. Riddle","orcid":"0000-0002-3611-2739","position":0,"is_corresponding":true}],"reference_count":36,"raw_metadata":null,"created_at":"2026-07-19T00:27:02.050512Z","pmid":"35638702","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":[]}