Development and Validation of a New Clinical Diagnostic Screening Model for Osteoporosis in Postmenopausal Women.

Background: Age and weight are not only strong predictive parameters for osteoporosis diagnosis but can also be easily acquired from patients. This study aimed to develop and validate a new diagnostic screening model for postmenopausal osteoporosis that uses only 2 parameters, viz., age and weight. The discriminative ability of the model was analyzed and compared with that of the osteoporosis self-assessment tool for Asians (OSTA) index.

Methods: The age-weight diagnostic screening model was developed using a retrospective chart review of postmenopausal women aged ≥50 years who underwent dual energy X-ray absorptiometry at a tertiary hospital from November 2017 to April 2022. Logistic regression analysis was used to derive a diagnostic screening model for osteoporosis.

Results: A total of 533 postmenopausal women were included in the study. According to the highest Youden index value, a probability cut-off value of 0.298 was used in the diagnosis screening model at any site, which yielded a sensitivity of 84.3% and a specificity of 53.8%. For increased sensitivity as a screening tool, a cut-off value of 0.254 was proposed to obtain a sensitivity of 90.2% and a specificity of 42.2%. The area under receiver operating characteristic curves from all screening models were significantly higher than those from the OSTA index model (p<0.05).

Conclusions: This study showed the feasibility of a postmenopausal osteoporosis diagnostic screening model that uses 2 strong predictors for osteoporosis diagnosis: age and weight. This age-weight diagnostic model is a simple, effective option in postmenopausal osteoporosis screening.