Characteristics Associated With 5-Year Fracture Risk Versus 5-Year Mortality Risk Among Late-Life Men

Balancing fracture risk versus risk of mortality before fracture among women aged 80 years or older

BACKGROUND

Most fractures occur in women aged ≥80 years but competing mortality unrelated to fracture may limit the benefit of osteoporosis drug therapy for some women in late life. Our primary aim was to develop separate prediction models for non-spine fracture (NSF) and mortality before fracture to identify subsets of women with varying fracture versus mortality risks.

METHODS

Separate prediction models were developed for NSF and mortality before NSF for 4895 women aged ≥80 years enrolled in the Study of Osteoporotic Fractures (SOF) or the Health Aging and Body Composition (HABC) study. Proportional hazards models modified to account for competing mortality were used to identify candidate risk factors for each outcome. Predictors associated with NSF or mortality (p < 0.2) were included in separate competing risk models to estimate the cumulative incidence of NSF and mortality before NSF during 5 years of follow-up. This process was repeated to develop separate prediction models for hip fracture and mortality before hip fracture.

RESULTS

Significant predictors of NSF (race, total hip BMD, grip strength, prior fracture, falls, and use of selective serotonin reuptake inhibitors, benzodiazepines, or oral/transdermal estrogen) differed from predictors of mortality before NSF (age, walking speed, multimorbidity, weight change, shrinking, smoking, self-rated health, dementia, and use of warfarin). Within nine subsets of women defined by tertiles of risk, 5-year outcomes varied from 28% NSF and 8% mortality in the high-risk NSF/low-risk mortality subset, to 9% NSF and 22% mortality in the low-risk NSF/high-risk mortality subset. Similar results were seen for predictors of hip fracture and mortality before hip fracture.

CONCLUSION

Considerable variation in 5-year competing mortality risk is present among women in late life with similar 5-year NSF risk. Both fracture risk and life expectancy should inform shared clinical decision-making regarding initiation or continuation of osteoporosis drug therapy for women aged ≥80 years.

A meta-analysis of previous falls and subsequent fracture risk in cohort studies

The relationship between self-reported falls and fracture risk was estimated in an international meta-analysis of individual-level data from 46 prospective cohorts. Previous falls were associated with an increased fracture risk in women and men and should be considered as an additional risk factor in the FRAX® algorithm.

INTRODUCTION

Previous falls are a well-documented risk factor for subsequent fracture but have not yet been incorporated into the FRAX algorithm. The aim of this study was to evaluate, in an international meta-analysis, the association between previous falls and subsequent fracture risk and its relation to sex, age, duration of follow-up, and bone mineral density (BMD).

METHODS

The resource comprised 906,359 women and men (66.9% female) from 46 prospective cohorts. Previous falls were uniformly defined as any fall occurring during the previous year in 43 cohorts; the remaining three cohorts had a different question construct. The association between previous falls and fracture risk (any clinical fracture, osteoporotic fracture, major osteoporotic fracture, and hip fracture) was examined using an extension of the Poisson regression model in each cohort and each sex, followed by random-effects meta-analyses of the weighted beta coefficients.

RESULTS

Falls in the past year were reported in 21.4% of individuals. During a follow-up of 9,102,207 person-years, 87,352 fractures occurred of which 19,509 were hip fractures. A previous fall was associated with a significantly increased risk of any clinical fracture both in women (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.33-1.51) and men (HR 1.53, 95% CI 1.41-1.67). The HRs were of similar magnitude for osteoporotic, major osteoporotic fracture, and hip fracture. Sex significantly modified the association between previous fall and fracture risk, with predictive values being higher in men than in women (e.g., for major osteoporotic fracture, HR 1.53 (95% CI 1.27-1.84) in men vs. HR 1.32 (95% CI 1.20-1.45) in women, P for interaction = 0.013). The HRs associated with previous falls decreased with age in women and with duration of follow-up in men and women for most fracture outcomes. There was no evidence of an interaction between falls and BMD for fracture risk. Subsequent risk for a major osteoporotic fracture increased with each additional previous fall in women and men.

CONCLUSIONS

A previous self-reported fall confers an increased risk of fracture that is largely independent of BMD. Previous falls should be considered as an additional risk factor in future iterations of FRAX to improve fracture risk prediction.

Advantages and Disadvantages of Random Forest Models for Prediction of Hip Fracture Risk Versus Mortality Risk in the Oldest Old

Targeted fracture prevention strategies among late-life adults should balance fracture risk versus competing mortality risk. Models have previously been constructed using Fine-Gray subdistribution methods. We used a machine learning method adapted for competing risk survival time to evaluate candidate risk factors and create models for hip fractures and competing mortality among men and women aged 80 years and older using data from three prospective cohorts (Study of Osteoporotic Fractures [SOF], Osteoporotic Fracture in Men study [MrOS], Health Aging and Body Composition study [HABC]). Random forest competing risk models were used to estimate absolute 5-year risk of hip fracture and absolute 5-year risk of competing mortality (excluding post-hip fracture deaths). Models were constructed for both outcomes simultaneously; minimal depth was used to rank and select variables for smaller models. Outcome specific models were constructed; variable importance was used to rank and select variables for inclusion in smaller random forest models. Random forest models were compared to simple Fine-Gray models with six variables selected a priori. Top variables for competing risk random forests were frailty and related components in men while top variables were age, bone mineral density (BMD) (total hip, femoral neck), and frailty components in women. In both men and women, outcome specific rankings strongly favored BMD variables for hip fracture prediction while frailty and components were strongly associated with competing mortality. Model discrimination for random forest models varied from 0.65 for mortality in women to 0.81 for hip fracture in men and depended on model choice and variables included. Random models performed slightly better than simple Fine-Gray model for prediction of competing mortality, but similarly for prediction of hip fractures. Random forests can be used to estimate risk of hip fracture and competing mortality among the oldest old. Modest gains in performance for mortality without hip fracture compared to Fine-Gray models must be weighed against increased complexity. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.