Research Question: Prospective longitudinal case-cohort study in adults aged 50 or over designed to assess the absolute risk of atypical femoral fracture (AFF) and provide important data on impact of bisphosphonate use and other risk factures for AFF.
Background: Studies to date have generated inconsistent estimates of the incidence of AFF and the magnitude of the association with bisphosphonate use, perhaps a result of differing study designs, comparators and definitions of AFF. Because there are few adequately powered large prospective studies, critical areas of uncertainty include the relationships with bisphosphonate exposure, particularly the duration of treatment, and importantly, the resolution of risk after discontinuation. Uncertainty also exists regarding additional risk factors, such as the effects of age and gender, severity of osteoporosis, concurrent medical conditions (such as rheumatoid arthritis), and other medication use (such as corticosteroids and proton pump inhibitors). Given the relative infrequency of AFF, randomized designs are not feasible and very large population-based cohorts with complete drug exposure and objective fracture ascertainment are needed.
Kaiser Southern California (KPSC) is very large, about 4.7 million members, providing high power for an analysis. KPSC has an ethnically diverse population and can explore the interesting suggestion of a strong relationship of race. Moreover, unlike almost all previous studies of AFF, there will be detailed information that will include BMD measurements and drug exposure information on most women who have been treated, which will allow for control of confounding by indication. Additional advantages of the Kaiser data not available in previous studies include access to digital radiographs for reported fractures, comprehensive information about previous fractures and other comorbidities, and availability of pre-treatment bone density measurements.
Sampling strategy: In addition to the AFF cases, it would be necessary to obtain a stratified random sample of subjects from Kaiser Southern California (KPSC) 50 years and older at the start of the study. The cohort will include a good number of bisphosphonate users and should provide good covariate overlap between bisphosphonate users and non-users. In addition, random sampling of typical hip fractures (THF) and typical femur fractures (TFF) for analyses comparing bisphosphonate effects across fracture types will be completed.
The comparison group for the specified fracture outcomes is the unique subcohort consisting of the randomly selected individuals from the cohort minus those in the cohort with the outcome of interest. Thus, the comparison group (subcohort) for the AFF case-cohort analyses are all members of the randomly selected cohort, minus any individual with verified AFF.
Advantages: For this proposed study, it would be appropriate to conduct a case-cohort study, as the aim is to achieve the same goal as in cohort studies, but more efficiently, using a sample of the denominators of the exposed and unexposed cohorts (and to ensure inclusion of all AFF cases). The case-cohort design is chosen rather than the stratified cohort design to ensure inclusion of the percentage (%) of AFFs expected to occur among those with no history of bisphosphonate use.
In the case-cohort design, one would include the same cases and classify them as exposed or unexposed (one would start by choosing the cases which is by design a case-control study). Instead of getting exposure information from all individuals constituting the denominators of exposed and unexposed cohorts, you only use a sample of them. The purpose of this sample is to estimate the relative size of exposed and unexposed components of the source population (the proportion of exposed in the source population at the beginning of the cohort).
Disadvantages: Case-crossover designs would control confounding by fixed factors such as pre-treatment bone mineral density (BMD), but are not suitable for exposures with potential carryover effects. Active comparator designs would be problematic and potentially subject to uncontrolled confounding; also, this design does not ensure inclusion of all AFF cases. Propensity score matching could be utilized, which effectively controls confounding if there are no unmeasured confounders, but this would not ensure inclusion of all AFF cases.