Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).     

Impact of stereotactic body radiation therapy on geriatric assessment and management for older patients with head and neck cancer using G8

PurposeManagement of head and neck cancers (HNC) in older adults is a common but challenging clinical scenario. We assess the impact of Stereotactic Body Radiation Therapy (SBRT) on survival utilizing the Geriatric-8 (G8) questionnaire.Materials and methods171 HNC patients, deemed medically unfit for definitive treatment, were treated with SBRT ± systemic therapy. G8 questionnaires were collected at baseline, at 4–6 weeks, and at 2–3 months post-treatment. Patients were stratified according to their baseline G8 score: <11 as ‘vulnerable’, 11–14 as ‘intermediate’, and >14 as ‘fit’. Overall survival (OS) was assessed through univariate Kaplan Meier analysis. Repeated measures ANOVA was used to determine if baseline characteristics affected G8 score changes.ResultsMedian follow-up was seventeen months. 60% of patients presented with recurrent HNC, 30% with untreated HNC primaries, and 10% with metastatic non-HNC primaries. Median age was 75 years. Median Charlson Comorbidity Index score was 2. 51% of patients were ‘vulnerable’, 37% were ‘intermediate’, and 12% were ‘fit' at baseline, with median survival of 13.2, 24.3, and 41.0 months, respectively (p = .004). Patients who saw a decrease in their follow-up G8 score (n = 69) had significantly lower survival than patients who had stable or increased follow-up G8 scores (n = 102), with median survival of 8.6 vs 36.0 months (p < .001).ConclusionThe G8 questionnaire may be a useful tool in upfront treatment decision-making to predict prognosis and prevent older patients from receiving inappropriate anti-cancer treatment. Decline in follow-up G8 scores may also predict worse survival and aid in goals of care following treatment.