{"doi":"10.1111/ene.70262","title":"Validation of the “Patient‐Acceptable Symptom State” Question as Outcome Measure in <scp>AChR</scp> Myasthenia Gravis: A Multicentre, Prospective Study","abstract":"INTRODUCTION: Patient Acceptable Symptom State (PASS) is emerging as a valuable subjective measure of the overall myasthenia gravis (MG)-related burden. This study aimed at identifying PASS-positive thresholds for the most used clinical scales, investigating whether PASS and MGFA post-intervention status capture different aspects of the disease outcome, and identifying clinical variables associated with PASS=YES response. METHODS: Adult AChR-MG patients were prospectively enrolled at two Italian Centres (Rome: index cohort; Florence: validation cohort). PASS thresholds for MG-ADL, QMG, and MG-QOL15r were defined in the index cohort by ROC analysis and validated in the validation cohort; predictors of favorable PASS were identified by multivariable analysis. RESULTS: This study included 173 patients (44% females, median age at onset: 53 years). PASS=YES patients had significantly lower median MG-ADL, QMG, and MG-QOL15r scores, with the following thresholds for PASS=YES: MG ADL ≤ 2, QMG ≤ 8 and MG-QOL15r ≤ 6. The MG-ADL (OR = 0.46, 95% CI = 0.36-0.60, p < 0.001), QMG (OR = 0.72, 95% CI = 0.64-0.81, p < 0.001) and MG-QOL15r (OR = 0.76, 95% CI = 0.70-0.84, p < 0.001), were independently associated with a favorable PASS. The degree of ocular involvement in each scale was the strongest negative determinant of PASS=YES. CONCLUSIONS: This study validates the PASS question and highlights the relevance of ocular complaints in patients' perception of MG burden.","journal":"European Journal of Neurology","year":2025,"id":526085,"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":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.961,"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":1401590,"name":"Massimiliano Ugo Verza","orcid":null,"position":1,"is_corresponding":false},{"id":1401151,"name":"Sara Cornacchini","orcid":"0000-0003-2918-4627","position":2,"is_corresponding":false},{"id":1401152,"name":"Francesca Beretta","orcid":"0000-0003-0887-1495","position":3,"is_corresponding":false},{"id":625343,"name":"Bo Sun","orcid":"0000-0002-5507-6657","position":4,"is_corresponding":false},{"id":1401153,"name":"A Lotti","orcid":"0000-0001-8121-2627","position":5,"is_corresponding":false},{"id":1230294,"name":"Silvia Falso","orcid":"0000-0002-6264-5299","position":6,"is_corresponding":false},{"id":644450,"name":"Alessandro Barilaro","orcid":"0000-0001-7418-7152","position":7,"is_corresponding":false},{"id":644433,"name":"Luca Massacesi","orcid":"0000-0001-5083-372X","position":8,"is_corresponding":false},{"id":1128717,"name":"Amelia Evoli","orcid":"0000-0002-4644-2299","position":9,"is_corresponding":false},{"id":864427,"name":"Valentina Damato","orcid":"0000-0003-1740-4522","position":10,"is_corresponding":false},{"id":864423,"name":"Gregorio Spagni","orcid":"0000-0003-0656-9671","position":0,"is_corresponding":true}],"reference_count":15,"raw_metadata":null,"created_at":"2026-07-19T02:50:25.860105Z","pmid":"40556475","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":[]}