A Review on Joint Models in Biometrical Research

In some fields of biometrical research joint modelling of longitudinal measures and event time data has become very popular. This article reviews the work in that area of recent fruitful research by classifying approaches on joint models in three categories: approaches with focus on serial trends, approaches with focus on event time data and approaches with equal focus on both outcomes. Typically longitudinal measures and event time data are modelled jointly by introducing shared random effects or by considering conditional distributions together with marginal distributions. We present the approaches in an uniform nomenclature, comment on sub-models applied to longitudinal measures and event time data outcomes individually and exemplify applications in biometrical research

Association between walking speed and age in healthy, free-living individuals using mobile accelerometry--a cross-sectional study.

Walking speed is a fundamental parameter of human motion and is increasingly considered as an important indicator of individuals' health status.To evaluate the relationship of gait parameters, and demographic and physical characteristics in healthy men and women.Recruitment of a subsample (n = 358) of male and female blood donors taking part in the Cambridge CardioResource study. Collection of demographic data, measurement of physical characteristics (height, weight and blood pressure) and assessment of 7-day, free-living activity parameters using accelerometry and a novel algorithm to measure walking speed. Participants were a median (interquartile range[IQR]) age of 49 (16) years; 45% women; and had a median (IQR) BMI of 26 (5.4).Walking speed.In this study, the hypothesis that walking speed declines with age was generated using an initial 'open' dataset. This was subsequently validated in a separate 'closed' dataset that showed a decrease of walking speed of -0.0037 m/s per year. This is equivalent to a difference of 1.2 minutes, when walking a distance of 1 km aged 20 compared to 60 years. Associations between walking speed and other participant characteristics (i.e. gender, BMI and blood pressure) were non-significant. BMI was negatively correlated with the number of walking and running steps and longest non-stop distance.This is the first study using accelerometry which shows an association between walking speed and age in free-living, healthy individuals. Absolute values of gait speed are comparable to published normal ranges in clinical settings. This study highlights the potential use of mobile accelerometry to assess gait parameters which may be indicative of future health outcomes in healthy individuals

Validating Predictors of Disease Progression in a Large Cohort of Primary-Progressive Multiple Sclerosis Based on a Systematic Literature Review

<div><p>Background</p><p>New agents with neuroprotective or neuroregenerative potential might be explored in primary-progressive Multiple Sclerosis (PPMS) - the MS disease course with leading neurodegenerative pathology. Identification of patients with a high short-term risk for progression may minimize study duration and sample size. Cohort studies reported several variables as predictors of EDSS disability progression but findings were partially contradictory.</p><p>Objective</p><p>To analyse the impact of published predictors on EDSS disease progression in a large cohort of PPMS patients.</p><p>Methods</p><p>A systematic literature research was performed to identify predictors for disease progression in PPMS. Individual case data from the Sylvia Lawry Centre (SLC) and the Hamburg MS patient database (HAPIMS) was pooled for a retrospective validation of these predictors on the annualized EDSS change.</p><p>Results</p><p>The systematic literature analysis revealed heterogeneous data from 3 prospective and 5 retrospective natural history cohort studies. Age at onset, gender, type of first symptoms and early EDSS changes were available for validation. Our pooled cohort of 597 PPMS patients (54% female) had a mean follow-up of 4.4 years and mean change of EDSS of 0.35 per year based on 2503 EDSS assessments. There was no significant association between the investigated variables and the EDSS-change.</p><p>Conclusion</p><p>None of the analysed variables were predictive for the disease progression measured by the annualized EDSS change. Whether PPMS is still unpredictable or our results may be due to limitations of cohort assessments or selection of predictors cannot be answered. Large systematic prospective studies with new endpoints are needed.</p></div

Descriptive statistics.

<p>Descriptive statistics for the pooled dataset and separately for the datasets from Hamburg (HH) respectively from the Sylvia Lawry Centre (SLC).</p

Association between Early and Late EDSS-Progression.

<p>Delta-EDSS in the first two years after baseline and delta-EDSS from year three on, delta-EDSS = annualized difference between first and last EDSS assessment, Spearman's rank correlation  =  −0.0445, p = 0.6536.</p

Median delta-EDSS in Women and Men.

<p>Boxplot with median, quartiles, 95% interval whiskers and outliers, delta-EDSS = annualized difference between first and last EDSS assessment, Wilcoxon rank-sum test: p = 0.1996. Two outliers with an annualized delta-EDSS >10 were excluded.</p

Association between Age at Onset and annualized EDSS progression.

<p>delta-EDSS = annualized difference between first and last EDSS assessment, Spearman's rank correlation r = −0.0359, p = 0.4508. One outlier with an annualized delta-EDSS >10 was excluded.</p

Median delta-EDSS and Type of First Symptoms.

<p>Groups split by absence or presence of motor symptoms at disease onset. Boxplot with median, quartiles and 95% interval whiskers, delta-EDSS = annualized difference between first and last EDSS assessment, Wilcoxon rank-sum test: p = 0.2418.</p

Participant characteristics (median [IQR]).

<p>Participant characteristics (median [IQR]).</p

Boxplot showing relationship between walking speed and age.

<p>Boxplot showing relationship between walking speed and age.</p