Treating osteoporosis in Canada: what clinical efficacy data should be considered by policy decision makers?

Using a Markov state-transition model, we estimated fractures averted with risedronate using two different types of clinical efficacy data. Summary data, as opposed to individual patient data (IPD), underestimated the number of fractures averted when applied in a specified high risk population. The choice of clinical efficacy data is an important consideration in health economic models evaluating osteoporosis therapies. This paper contrasts fracture reduction estimates for risedronate utilizing efficacy data from two approaches to meta-analysis: summary data versus individual patient data. We also examined differences in fracture reduction explained by varied cohort selection, especially the inclusion of low- versus high-risk populations. Using a Markov state-transition model, we compared fractures averted over 3 years in a hypothetical cohort by inputting fracture risk reduction estimates (risedronate versus placebo) from two data sources (summary data versus IPD). The cohort consisted of 100,000 Canadian women, age a parts per thousand yen65 years with osteoporosis (WHO criteria T-score a parts per thousand currency signaEuro parts per thousand-2.5) and prevalent morphometric vertebral fracture. Non-vertebral fractures averted with risedronate were: 3,571 and 6,584 per 100,000 women for summary data and IPD, respectively. For vertebral fractures, the numbers were 8,552 and 10,127. When IPD versus summary data was used, an additional 3,013 more non-vertebral fractures and 1,575 vertebral fractures were averted. Relative risk estimates from IPD analyses were the best choice for modelling fracture outcomes when applied in a specified high-risk population. In addition to superior statistical methodology, they utilized RCT cohorts that are more representative of higher risk patients requiring treatment (osteoporotic women a parts per thousand yen65 years with a prevalent vertebral fracture).