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A genome-wide genomic score added to standard recommended stratification tools does not improve the identification of patients with very low bone mineral density.

Authors :
Therkildsen J
Rohde PD
Nissen L
Thygesen J
Hauge EM
Langdahl BL
Boettcher M
Nyegaard M
Winther S
Source :
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA [Osteoporos Int] 2023 Nov; Vol. 34 (11), pp. 1893-1906. Date of Electronic Publication: 2023 Jul 26.
Publication Year :
2023

Abstract

The role of integrating genomic scores (GSs) needs to be assessed. Adding a GS to recommended stratification tools does not improve the prediction of very low bone mineral density. However, we noticed that the GS performed equally or above individual risk factors in discrimination.<br />Purpose: We aimed to investigate whether adding a genomic score (GS) to recommended stratification tools improves the discrimination of participants with very low bone mineral density (BMD).<br />Methods: BMD was measured in three thoracic vertebrae using CT. All participants provided information on standard osteoporosis risk factors. GSs and FRAX scores were calculated. Participants were grouped according to mean BMD into very low (<80 mg/cm <superscript>3</superscript> ), low (80-120 mg/cm <superscript>3</superscript> ), and normal (>120 mg/cm <superscript>3</superscript> ) and according to the Bone Health and Osteoporosis Foundation recommendations for BMD testing into an "indication for BMD testing" and "no indication for BMD testing" group. Different models were assessed using the area under the receiver operating characteristics curves (AUC) and reclassification analyses.<br />Results: In the total cohort (n=1421), the AUC for the GS was 0.57 (95% CI 0.52-0.61) corresponding to AUCs for osteoporosis risk factors. In participants without indication for BMD testing, the AUC was 0.60 (95% CI 0.52-0.69) above or equal to AUCs for osteoporosis risk factors. Adding the GS to a clinical risk factor (CRF) model resulted in AUCs not statistically significant from the CRF model. Using probability cutoff values of 6, 12, and 24%, we found no improved reclassification or risk discrimination using the CRF-GS model compared to the CRF model.<br />Conclusion: Our results suggest adding a GS to a CRF model does not improve prediction. However, we noticed that the GS performed equally or above individual risk factors in discrimination. Clinical risk factors combined showed superior discrimination to individual risk factors and the GS, underlining the value of combined CRFs in routine clinics as a stratification tool.<br /> (© 2023. The Author(s).)

Details

Language :
English
ISSN :
1433-2965
Volume :
34
Issue :
11
Database :
MEDLINE
Journal :
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Publication Type :
Academic Journal
Accession number :
37495683
Full Text :
https://doi.org/10.1007/s00198-023-06857-w