{"doi":"10.1002/acr.25654","title":"Development and External Validation of a Multivariable Predictive Model for Progression to Difficult‐to‐Treat Rheumatoid Arthritis in Biologic‐Experienced Patients","abstract":"OBJECTIVE: Approximately 20% of patients with rheumatoid arthritis (RA) cycle through multiple therapies without achieving treatment goals and are classified as having \"difficult-to-treat\" RA (D2T-RA); however, no risk prediction tools exist to identify which patients are at highest risk. Our aim was to develop and validate a predictive model for progression to D2T-RA among patients with RA. METHODS: We used data from two large independent observational cohorts of patients with RA to develop and externally validate a multivariable prediction model to identify participants at risk of D2T-RA, defined using EULAR 2021 criteria. We developed a multivariable predictive model for D2T-RA using random survival forests in participants treated with their first biologic and/or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) (derivation cohort). We validated the model in a cohort of participants initiating or switching b/tsDMARD therapies. RESULTS: A total of 700 participants were in the derivation cohort (84% female, mean age 55 years, median follow-up 40 months, 113 [16%] with D2T-RA), and 2,070 participants were included in the validation cohort (79% female, mean age 56 years, median follow-up 8 months, 571 [28%] with D2T-RA). We observed C-index values of 0.643 (95% confidence interval [CI] 0.585-0.698; derivation cohort) and 0.620 (95% CI 0.596-0.643; validation cohort). Calibration measures suggested overall moderate predictive ability. Worsened functional status, pain, fatigue, and global disease activity were consistently top predictors across both cohorts. CONCLUSION: Our model demonstrated moderate discrimination and calibration, highlighting the challenge in accurately predicting D2T-RA outcomes. These findings underscore the need for further research to improve predictive performance, potentially through the incorporation of additional biomarkers.","journal":"Arthritis Care & Research","year":2025,"id":526931,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9505,"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":27560,"name":"Nancy A. Shadick","orcid":"0000-0003-3953-845X","position":1,"is_corresponding":false},{"id":27561,"name":"Michael E. Weinblatt","orcid":"0000-0001-5215-5512","position":2,"is_corresponding":false},{"id":710462,"name":"George Reed","orcid":"0000-0002-2463-4847","position":3,"is_corresponding":false},{"id":1088544,"name":"Heather J. Litman","orcid":"0000-0003-3511-4078","position":4,"is_corresponding":false},{"id":27557,"name":"Joel M. Kremer","orcid":"0000-0001-6674-9901","position":5,"is_corresponding":false},{"id":27548,"name":"Dimitrios A. Pappas","orcid":"0000-0001-8338-027X","position":6,"is_corresponding":false},{"id":391215,"name":"Daniel H. Solomon","orcid":"0000-0001-8202-5428","position":7,"is_corresponding":false},{"id":1213180,"name":"Misti L. Paudel","orcid":"0000-0002-8361-0650","position":0,"is_corresponding":true}],"reference_count":29,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:50:34.851930Z","pmid":"40977501","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":[]}