Individualization of osteoporosis risk

Abstract

Anti-fracture therapy is often pursued in individuals with osteoporosis or low bone mineral density with or without a prior fracture [1–3], because they are at high risk of subsequent fracture [4, 5]. In recent years, there has been a proliferation of clinical prediction rules, including clinical risk indices and scores, for identifying individuals with osteoporosis. The main problem with these clinical prediction rules is that they categorize individuals into low-risk versus high-risk groups based on some arbitrary threshold. As a result, when this risk stratification-based approach is applied to an individual, its prognostic performance is often poor. Among the clinical indices for predicting osteoporosis, the Osteoporosis Self-Assessment Tool (OST) [6] is perhaps the simplest score and has perhaps been the most widely studied. However, the clinical usefulness of this score in different populations has not been systematically studied. In this issue, Rud and colleagues [7] systematically summarize some key prognostic properties of the OST score across different Asian and Caucasian populations. They especially focus on the prognostic value of OST in ruling out osteoporosis (i.e., LR−). Their meta-analysis showed that the overall LR− was 0.19 (95% confidence interval: 0.17 and 0.21) with considerable heterogeneity between populations. Although Rud and colleagues do not report other prognostic measures of the OST score in their paper, it is possible to estimate the LR+, sensitivity, specificity, and summary receiver operating characteristic curve (sROC) from the data (Table 1). These results suggest that in both Asian and Caucasian populations, the OST score has good sensitivity, but poor specificity, and moderate discriminatory value (i.e., with sROC being between 0.74 and 0.79). The odds for OST positivity among women with osteoporosis is 11 times (in Asians) and 7.8 times (in Caucasians) higher than the odds for positivity among women without osteoporosis. This diagnostic odds ratio is much lower than the criterion required for an “adequate test”. However, these results are broadly consistent with prognostic values of the simple calculated osteoporosis risk estimation (SCORE), osteoporosis risk assessment instrument (ORAI) and National Osteoporosis Foundation guidelines, which were also found to have poor specificity and high sensitivity [8]. When the prevalence of osteoporosis is 17% (which is observed in Caucasian populations [7]) and given the observed LR− and LR+ in Table 1, it can be estimated that if an individual is classified as “low risk” by OST, the probability that the individual has no osteoporosis is 0.96; and if the individual is classified as “high risk”, the probability that the individual has osteoporosis is only ~0.25. In other words, the OST score is useful in ruling out the possibility of osteoporosis, but it performs badly in ruling in the possibility of osteoporosis. The best positive and negative predictive values are achieved when the sensitivity is around 70% and specificity is approximately 80% (Fig. 1). However, in all studies reviewed, the OST score has a sensitivity of >90% and specificity of <57%. Several factors contribute to the relatively poor performance of OST. First, the prevalence of osteoporosis in the populations under review, and the relationships between age, weight and BMD is not constant across the population. For example, the prevalence of osteoporosis varied between 7 to 21%, with and the LR− being between 0.02 and 0.49 among the Asian populations under review. Indeed, a Osteoporos Int (2007) 18:1153–1156 DOI 10.1007/s00198-007-0415-z