A Statistical Approach Regarding the Diagnosis of Osteoporosis and Osteopenia From DXA: Are We Underdiagnosing Osteoporosis?

Osteoporosis and osteopenia are diagnosed most commonly by evaluating the lowest T-score of BMD measurements, typically taken at three sites: the L1-L4 lumbar spine, femoral neck, and total hip. This study aimed to evaluate the effect of using all three BMD measurements and multivariate statistical theory to evaluate how the diagnoses of osteoporosis and osteopenia change in simulation studies and in real data. First, it was found that the T-scores from these three BMD measurements rarely give concordant diagnoses using the same World Health Organization (WHO) and International Society for Clinical Densitometry (ISCD) guidelines, so that the diagnosis strongly depends on the BMD sites measured. Next, strong correlations were found between the BMD measurements at different sites within the same person, which resulted in increased congruence/concordance between the diagnoses obtained from the BMD T-scores. Multivariate statistical theory was used to show that the joint distribution of the BMD T-scores at different sites follows a multivariate t distribution and found that the marginal distribution of any BMD T-score follows a univariate t distribution. Confidence ellipsoids were derived that are equivalent to the univariate WHO/ISCD thresholds for osteoporosis (T-score ≤-2.5) and osteopenia (-2.5 < T-score <-1). The study found that more patients are diagnosed with osteoporosis using the multivariate version of the WHO/ISCD guidelines rather than the current WHO/ISCD guidelines in both real data and simulation studies. Diagnoses of osteoporosis using the statistics derived method were also associated with higher FRAX (fracture risk assessment tool) probabilities of major osteoporotic (p = 0.001) and hip fractures (p = 2.2 × 10-6). In conclusion, this study shows that considering all three BMD T-scores is potentially more informative than using the single lowest BMD T-score.