Heteroscedastic regression analysis of factors affecting BMD monitoring

Identifying factors affecting BMD precision and interindividual heterogeneity in BMD change can help optimize BMD monitoring. BMD change for the lumbar spine and total hip for short-term reproducibility (n = 328) and long-term clinical monitoring (n = 2720) populations were analyzed with heteroscedastic regression using linear prediction for mean (monitoring population only) and log-linear prediction for SD (both populations). For clinical monitoring, male sex, baseline body mass index (BMI), and systemic corticosteroid use were associated with greater SD of BMD change. Weight gain was negatively associated with SD for the hip, whereas height change was positively associated with SD for the spine. Each additional year of monitoring increased the SD by 6.5-9.2%. Osteoporosis treatment affected mean change but did not increase dispersion. For short-term reproducibility, performing scans on a different day increased the SD of measurement error by 38-44%. Baseline BMD, difference in bone area, and a repeat scan performed by different technologists were associated with higher measurement error only for the hip. For both samples, heteroscedastic regression outperformed models that assumed homogeneous variance. Heteroscedastic regression techniques are powerful yet underused tools in analyzing longitudinal BMD data and can be used to generate individualized predictions of BMD change and measurement error.