{"doi":"10.1101/2019.12.30.19016154","title":"Evaluating the performance of the WHO international reference standard for osteoporosis diagnosis in postmenopausal women of varied polygenic score and race","abstract":"Abstract Background Whether the bone mineral density (BMD) T-score performs differently in osteoporosis classification in women of different genetic profiling and race background remains unclear. Methods The genomic data in the Women’s Health Initiative study was analyzed (n=2,417). The polygenic score (PGS) was calculated from 63 BMD-associated single nucleotide polymorphisms (SNPs) for each participant. The World Health Organization’s (WHO) definition of osteoporosis (BMD T-score≤-2.5) was used to estimate the cumulative incidence of fracture. Results T-score classification significantly underestimated the risk of major osteoporotic fracture (MOF) in the WHI study. An enormous underestimation was observed in African American women (POR: 0.52, 95% CI: 0.30-0.83) and in women with low PGS (predicted/observed ratio [POR]: 0.43, 95% CI: 0.28-0.64). Compared to Caucasian women, African American, African Indian, and Hispanic women respectively had a 59%, 41%, and 55% lower hazard of MOF after the T-score was adjusted for. The results were similar when used for any fractures. Conclusions Our study suggested the BMD T-score performance varies significantly by race in postmenopausal women.","journal":"medRxiv","year":2020,"id":123361,"datarank":0.2844976072306429,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.07655345306265927,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.07655345306265927,"corpus_percentile":43.45169026069467,"corpus_rank":7311,"citation_count":3,"citer_count":3,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.6713,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":566183,"name":"Xiangxue Xiao","orcid":"0000-0002-9527-2548","position":1,"is_corresponding":false},{"id":566184,"name":"Yingke Xu","orcid":"0000-0003-0686-5104","position":2,"is_corresponding":false},{"id":566182,"name":"Qing Wu","orcid":"0000-0003-4679-8903","position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":null,"created_at":"2026-07-18T23:14:59.547352Z","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":[]}