Fractures in the prodromal period of Parkinson disease

Safety profile of hypnotics or sedatives on community-dwelling older adults aged 75 or older in Japan: A retrospective propensity-matched cohort study

OBJECTIVE

The purpose of the study is to assess if daily use of hypnotics increases mortality, aspiration pneumonia and hip fracture among relatively healthy individuals aged 75 years or older who lead independent lives in the community.

METHOD AND PATIENTS

Of the adults aged 75 years or older residing in Hokkaido prefecture of Japan (n = 705,538), those who did not meet several exclusion criteria were eligible for generating propensity score-matched cohorts (n = 214,723). Exclusion criteria included co-prescribed medications acting on the central nervous system, diagnoses of malignant neoplasm, dementia, depression, etc. We compared 33,095 participants who were prescribed hypnotics for daily use (hypnotic group) with a propensity score-matched cohort without a prescription (control group). Participants were followed for more than 42 months.

RESULTS

During the 42-month follow-up period, the incidence of the three outcome measures in the hypnotics group was significantly higher than that in the control group (aspiration pneumonia p < 0.001, hip fracture p = 0.007, and all-cause mortality p < 0.001). Sensitivity analyses utilizing inverse probability weighting demonstrated hazard ratios of 1.083 [1.023-1.146] for mortality, 1.117 [1.014-1.230] for aspiration pneumonia, and 1.720 [1.559-1.897] for hip fracture. Meanwhile, the attribute risk differences were 2.7, 1.5, and 1.0 per 1000 patient-years, respectively.

CONCLUSIONS

Although daily use of hypnotics increased the risk of three events, their attribute risk differences were fewer than 3.0 per 1000 patient-years. The results will help provide guidance on whether it is reasonable to prescribe hypnotics to geriatric population aged 75 or older leading independent lives in the community.

CLINICAL TRIAL REGISTRATION

UMIN-CTR UMIN000048398.

A predictive algorithm to identify ever smoking in medical claims-based epidemiologic studies

PURPOSE

To develop and validate an algorithm to estimate probability of ever smoking using administrative claims.

METHODS

Using population-based samples of Medicare-aged individuals (121,278 Behavioral Risk Factor Surveillance System survey respondents and 207,885 Medicare beneficiaries), we developed a logistic regression model to predict probability of ever smoking from demographic and claims data. We applied the model in 1,657,266 additional Medicare beneficiaries and calculated area under the receiver operating characteristic curve (AUC) using presence or absence of a tobacco-specific diagnosis or procedure code as our "gold standard." We used these "gold standard" and lung/laryngeal cancer codes to over-ride predicted probability as 100%. We calculated Spearman's rho between probability from this full algorithm and smoking assessed in prior Parkinson disease studies, by substituting our observed and prior ("true") smoking-Parkinson disease odds ratios into the attenuation equation.

RESULTS

The predictive model contained 23 variables, including basic demographics, high alcohol consumption, asthma, cardiovascular disease and associated risk factors, selected cancers, and indicators of routine medical usage. The AUC was 67.6% (95% confidence interval 67.5%-67.7%) comparing smoking probability to tobacco-specific diagnosis or procedure codes. Spearman's rho for the full algorithm was 0.82.

CONCLUSIONS

Ever smoking might be approximated in administrative data for use as a continuous, probabilistic variable in epidemiologic analyses.

Increased fracture risk in Parkinson's disease - An exploration of mechanisms and consequences for fracture prediction with FRAX

The relative contributions of factors such as muscle strength, falls risk and low bone mineral density (BMD) to increased fracture risk in Parkinson's Disease (PD) were examined in an analysis of 5212 community-dwelling women age 75 years or more recruited to a randomised, double-blind, placebo-controlled study of the oral bisphosphonate, clodronate. Similar number of PD and non-PD subjects received treatment. Each participant had measurements of hip and forearm BMD, muscle strength (hand grip strength and maximum isometric quadriceps strength), ability in the sit-to-stand test, and postural stability. Incident radiographic and/or surgically verified fractures, and deaths, were recorded over an average follow-up of 3.8 years. A diagnosis of PD was made if it was self-reported and appropriate medication was recorded at the study entry. 47 of the women (0.9 %) had a diagnosis of PD at baseline. They were of similar age to those without PD, but reported higher disability scores and lower quality of life. While BMD at the forearm and hip regions was lower in PD, this only reached statistical significance at the femoral neck (0.61 ± 0.12 vs 0.65 ± 0.12 g/cm², p = 0.037). Right hand grip strength was non-significantly lower in PD, but maximum right quadriceps strength was much reduced (96.9 ± 49.3 vs 126.3 ± 59.2 N, p = 0.003). Eleven (23.4 %) of the women with PD sustained 12 fractures, while 609 women (11.8 %) without PD sustained 742 osteoporotic fractures. The risk of osteoporotic fracture associated with PD was 2.24-fold higher in women with PD (Cox-regression HR 2.24, 95 % CI 1.23-4.06) and this remained high when adjusted for death as a competing risk (2.17, 95 % CI 1.17-4.01, p = 0.013). Following adjustment for femoral neck BMD, PD remained a significant predictor of fracture (HR 2.04, 1.12-3.70, p = 0.020). Entering PD as a risk variable using the rheumatoid arthritis input as a surrogate resulted in a reduction in PD as a FRAX-independent risk factor, particularly when BMD was included in FRAX (1.65, 95 % CI), but the relationship between PD and fracture risk appears to remain of clinical significance. The study suggests that PD may be an independent input in future iterations of FRAX, possibly due to non-skeletal components of risk such as reduced lower limb muscle strength. Introducing measures of muscle strength and performance in FRAX could also be considered.

Osteoporosis epidemiology using international cohorts

PURPOSE OF REVIEW

To provide an update on the most important new cohort studies within osteoporosis and their bearing on clinical management and directions for future research.

RECENT FINDINGS

We identified a collection of new observational cohort studies - including new reports from already established large cohorts - and intervention studies providing new insights into osteoporosis pathophysiology, risk finding, intervention, and treatment barriers.

SUMMARY

Recent cohort studies in osteoporosis highlight the importance of timely identification and treatment of people who are at high risk of suffering osteoporotic fractures. Physical performance is a strong indicator of fracture risk and one that is tightly linked to a number of chronic conditions, not least inflammatory conditions like rheumatoid arthritis. Advances in case finding may involve opportunistic screening for low bone mineral density and vertebral fractures of radiology images obtained for other purposes, polygenic risk scores, and routinely collected medication and comorbidity information.

Fracture risk and impact of osteoporosis in patients with Parkinson's disease: a nationwide database study

INTRODUCTION

Patients with Parkinson's disease (PD) showed an increased risk of fractures in previous studies and a high prevalence of osteoporosis is reportedly a potential contributor. We conducted a nationwide database study on the risk of fractures and the impact of osteoporosis on patients with PD compared to controls.

MATERIALS AND METHODS

Using a nationwide database in South Korea, we identified incident patients with PD in 2004-2006 and selected four age- and sex-matched controls. We checked the occurrence rates of overall and hip fractures and plotted Kaplan-Meier curves and a Cox proportional hazards model to determine risk. We also conducted stratified analyses according to the presence or absence of osteoporosis.

RESULTS

We identified 9126 patients with PD and 35,601 controls. Patients with PD had a greater probability of fractures throughout the study period in Kaplan-Meier curves, and an increased risk of overall (aHR 1.35, 95% CI 1.297-1.405) and hip (aHR 1.814, 95% CI 1.66-1.983) fractures in a Cox proportional hazards model. In the stratified analysis, the increased risk of overall fracture (aHR 1.333, 95% CI 1.273-1.396 and aHR 1.412, 95% CI 1.301-1.532, respectively) and hip fracture (aHR 1.773, 95% CI 1.604-1.96 and aHR 2.008, 95% CI 1.657-2.434, respectively) due to PD was similar between patients with and without osteoporosis.

DISCUSSION

Patients with PD, with or without osteoporosis, are more likely to experience fractures, especially hip fractures. There seems to be no interaction between PD and osteoporosis in regard to the occurrence of fractures, and therefore no effect modification by osteoporosis.

A comparison of prediction approaches for identifying prodromal Parkinson disease

Identifying people with Parkinson disease during the prodromal period, including via algorithms in administrative claims data, is an important research and clinical priority. We sought to improve upon an existing penalized logistic regression model, based on diagnosis and procedure codes, by adding prescription medication data or using machine learning. Using Medicare Part D beneficiaries age 66–90 from a population-based case-control study of incident Parkinson disease, we fit a penalized logistic regression both with and without Part D data. We also built a predictive algorithm using a random forest classifier for comparison. In a combined approach, we introduced the probability of Parkinson disease from the random forest, as a predictor in the penalized regression model. We calculated the receiver operator characteristic area under the curve (AUC) for each model. All models performed well, with AUCs ranging from 0.824 (simplest model) to 0.835 (combined approach). We conclude that medication data and random forests improve Parkinson disease prediction, but are not essential.

Bone-Derived Factors as Potential Biomarkers for Parkinson's Disease

Background: Parkinson’s disease (PD) and osteoporosis are both common aging diseases. It is reported that PD has a close relationship with osteoporosis and bone secretory proteins may be involved in disease progression.

Objectives: To detect the bone-derived factors in plasma and cerebrospinal fluid (CSF) of patients with PD and evaluate their correlations with C-reaction protein (CRP) level, motor impairment, and Hoehn-Yahr (HY) stage of the disease.

Methods: We included 250 PD patients and 250 controls. Levels of osteocalcin (OCN), osteopontin (OPN), osteoprotegerin (OPG), Sclerostin (SO), Bone morphogenetic protein 2 (BMP2), and Dickkopf-1 (DKK-1) in plasma and CSF were measured by custom protein antibody arrays. Data were analyzed using Mann–Whitney U-test and Spearman’s receptor activator of NF-κB (RANK) correlation.

Results: Plasma levels of OCN and OPN were correlated with CRP levels and HY stage and motor impairment of PD. Furthermore, the plasma assessment with CSF detection may enhance their potential prediction on PD.

Conclusions: OCN and OPN may serve as potential biomarkers for PD. The inflammation response may be involved in the cross-talk between the two factors and PD.