A clinical tool to identify older women with back pain at high risk of osteoporotic vertebral fractures (Vfrac): a population-based cohort study with exploratory economic evaluation
Tarnjit K. Khera, Linda Hunt, Sarah Davis, Rachael Gooberman‐Hill, Howard Thom, Yixin Xu, Zoé Paskins, T. J. Peters, Jonathan H. Tobias, Emma Clark
Abstract
BACKGROUND: osteoporotic vertebral fractures (OVFs) identify people at high risk of future fractures, but despite this, less than a third come to clinical attention. The objective of this study was to develop a clinical tool to aid health care professionals decide which older women with back pain should have a spinal radiograph. METHODS: a population-based cohort of 1,635 women aged 65+ years with self-reported back pain in the previous 4 months were recruited from primary care. Exposure data were collected through self-completion questionnaires and physical examination, including descriptions of back pain and traditional risk factors for osteoporosis. Outcome was the presence/absence of OVFs on spinal radiographs. Logistic regression models identified independent predictors of OVFs, with the area under the (receiver operating) curve calculated for the final model, and a cut-point was identified. RESULTS: mean age was 73.9 years and 209 (12.8%) had OVFs. The final Vfrac model comprised 15 predictors of OVF, with an AUC of 0.802 (95% CI: 0.764-0.840). Sensitivity was 72.4% and specificity was 72.9%. Vfrac identified 93% of those with more than one OVF and two-thirds of those with one OVF. Performance was enhanced by inclusion of self-reported back pain descriptors, removal of which reduced AUC to 0.742 (95% CI: 0.696-0.788) and sensitivity to 66.5%. Health economic modelling to support a future trial was favourable. CONCLUSIONS: the Vfrac clinical tool appears to be valid and is improved by the addition of self-reported back pain symptoms. The tool now requires testing to establish real-world clinical and cost-effectiveness.