Citations

Abstract Motivation: Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. Results: We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. Conclusion: We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. Availability and implementation: The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. Contact: reesese@vcu.edu or eckel@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.

ABSTRACT To assess recent trends in fracture incidence from all causes at all skeletal sites, we used the comprehensive (inpatient and outpatient) data resources of the Rochester Epidemiology Project to estimate rates for Olmsted County, MN, USA, residents in 2009 to 2011 compared with similar data from 1989 to 1991. During the 3-year study period, 2009 to 2011, 3549 residents ≥50 years of age experienced 5244 separate fractures. The age- and sex-adjusted (to the 2010 US white population) incidence of any fracture was 2704 per 100,000 person-years (95% confidence interval [CI] 2614 to 2793) and that for all fractures was 4017 per 100,000 (95% CI 3908 to 4127). Fracture incidence increased with age in both sexes, but age-adjusted rates were 49% greater among the women. Overall, comparably adjusted fracture incidence rates increased by 11% (from 3627 to 4017 per 100,000 person-years; p = 0.008) between 1989 to 1991 and 2009 to 2011. This was mainly attributable to a substantial increase in vertebral fractures (+47% for both sexes combined), which was partially offset by a decline in hip fractures (−25%) among the women. There was also a 26% reduction in distal forearm fractures among the women; an increase in distal forearm fractures among men aged 50 years and over was not statistically significant. The dramatic increase in vertebral fractures, seen in both sexes and especially after age 75 years, was attributable in part to incidentally diagnosed vertebral fractures. However, the fall in hip fracture incidence, observed in most age groups, continues the steady decline observed among women in this community since 1950. More generally, these data indicate that the dramatic increases in the incidence of fractures at many skeletal sites that were observed decades ago have now stabilized. © 2014 American Society for Bone and Mineral Research.

Current methods used to assess calibration are limited, particularly in the assessment of prognostic models. Methods for testing and visualizing calibration (e.g. the Hosmer–Lemeshow test and calibration slope) have been well thought out in the binary regression setting. However, extension of these methods to Cox models is less well known and could be improved. We describe a model-based framework for the assessment of calibration in the binary setting that provides natural extensions to the survival data setting. We show that Poisson regression models can be used to easily assess calibration in prognostic models. In addition, we show that a calibration test suggested for use in survival data has poor performance. Finally, we apply these methods to the problem of external validation of a risk score developed for the general population when assessed in a special patient population (i.e. patients with particular comorbidities, such as rheumatoid arthritis).

ABSTRACT Distal forearm fractures are among the most common fractures during childhood, but it remains unclear whether they predict an increased fracture risk later in life. We studied a population-based cohort of 1776 children ≤18 years of age, from Olmsted County, MN, USA, who had a distal forearm fracture in 1935–1992. Incident fractures occurring at age ≥35 years were identified through review of complete medical records using the linkage system of the Rochester Epidemiology Project. Observed nonpathologic fractures resulting from no more than moderate trauma (fragility fractures) were compared with expected numbers estimated from fracture site–specific incidence rates, based on age, sex, and calendar year, for Olmsted County (standardized incidence ratios [SIR]). In 1086 boys (mean ± SD age; 11 ± 4 years) and 690 girls (10 ± 4 years) followed for 27,292 person-years after the age of 35 years, subsequent fragility fractures were observed in 144 (13%) men and 74 (11%) women. There was an increased risk for future fragility fractures in boys who had a distal forearm fracture (SIR, 1.9; 95% CI, 1.6–2.3) but not girls (SIR, 1.0; 95% CI, 0.8–1.2). Fragility fractures at both major osteoporotic (hip, spine, wrist, and shoulder) sites (SIR, 2.6; 95% CI, 2.1–3.3) and remaining sites (SIR, 1.7; 95% CI, 1.3–2.0) were increased in men, irrespective of age at distal forearm fracture as boys. A distal forearm fracture in boys, but not girls, is associated with an increased risk for fragility fractures as older adults. It is necessary to determine whether the increased fractures observed in men is due to persistent deficits of bone strength, continued high fracture risk activity, or both. Until then, men should be asked about a childhood distal forearm fracture and, if so, warrant further screening and counseling on measures to optimize bone health and prevent fractures.

Abstract Hip fracture risk rises exponentially with age, but there is little knowledge about how fracture-related alterations in hip structure differ from those of aging. We employed computed tomography (CT) imaging to visualize the three-dimensional (3D) spatial distribution of bone mineral density (BMD) in the hip in relation to age and incident hip fracture. We used intersubject image registration to integrate 3D hip CT images into a statistical atlas comprising women aged 21 to 97 years (n = 349) and a group of women with (n = 74) and without (n = 148) incident hip fracture 4 to 7 years after their imaging session. Voxel-based morphometry was used to generate Student's t test statistical maps from the atlas, which indicated regions that were significantly associated with age or with incident hip fracture. Scaling factors derived from intersubject image registration were employed as measures of bone size. BMD comparisons of young, middle-aged, and older American women showed preservation of load-bearing cortical and trabecular structures with aging, whereas extensive bone loss was observed in other trabecular and cortical regions. In contrast, comparisons of older Icelandic fracture women with age-matched controls showed that hip fracture was associated with a global cortical bone deficit, including both the superior cortical margin and the load-bearing inferior cortex. Bone size comparisons showed larger dimensions in older compared to younger American women and in older Icelandic fracture women compared to controls. The results indicate that older Icelandic women who sustain incident hip fracture have a structural phenotype that cannot be described as an accelerated pattern of normal age-related loss. The fracture-related cortical deficit noted in this study may provide a biomarker of increased hip fracture risk that may be translatable to dual-energy X-ray absorptiometry (DXA) and other clinical images. © 2013 American Society for Bone and Mineral Research.

To determine if the revised US FRAX can identify those at high risk for fractures at any skeletal site, we studied 250 women and 249 men ≥ 40 years old from an age-stratified random sample of Rochester, MN residents. At baseline, femoral neck (FN) bone density was assessed, as were the clinical risk factors included in FRAX, along with additional fracture risk factors such as bone turnover markers and fall history. Fracture ascertainment through periodic interviews and comprehensive medical record review was performed over 10 years of followup. In both women and men, a higher FRAX probability at baseline was associated with greater subsequent likelihood of a major osteoporotic fracture. However, a relative 10% increase in the FRAX 10-year fracture probability was also associated with a 1.4-fold increase (95% confidence interval (CI) 1.1–1.7) in other fractures in women and a 1.7-fold increase (95% CI 0.8–3.1) in men. Furthermore, FRAX predicted asymptomatic vertebral fractures and fractures generally in both sexes. The addition of risk factors not currently included in FRAX did not appear to improve the accuracy of fracture risk prediction. FRAX may provide a conservative estimate of risk for major osteoporotic fractures, but it also predicts fractures generally.

Background: It is unclear if all patients with relapsing–remitting multiple sclerosis (RRMS) ultimately develop progressive MS. Onset of progressive disease course seems to be age- rather than disease duration-dependent. Some forms of progressive MS (e.g. primary progressive MS (PPMS)) are uncommon in population-based studies. Ascertainment of patients with PPMS from clinic-based populations can facilitate a powerful comparison of age at progression onset between secondary progressive MS (SPMS) and PPMS but may introduce unclear biases. Objective: Our aim is to confirm that onset of progressive disease course is more relevant to the patient’s age than the presence or duration of a pre-progression relapsing disease course in MS. Methods: We studied a population-based MS cohort ( n =210, RRMS n =109, progressive MS n =101) and a clinic-based progressive MS cohort ( n =754). Progressive course was classified as primary (PPMS; n =322), single attack (SAPMS; n =112) and secondary progressive (SPMS; n =421). We studied demographics (chi 2 or t -test), age-of-progression-onset ( t -test) and time to Expanded Disability Status Scale of 6 (EDSS6) (Kaplan–Meier analyses). Results: Sex ratio ( p =0.58), age at progression onset ( p =0.37) and time to EDSS6 ( p =0.16) did not differ between the cohorts. Progression had developed before age 75 in 99% of patients with known progressive disease course; 38% with RRMS did not develop progression by age 75. Age at progression onset did not differ between SPMS (44.9±9.6), SAPMS (45.5±9.6) and PPMS (45.7±10.8). In either cohort, only 2% of patients had reached EDSS6 before onset of progression. Conclusions: Patients with RRMS do not inevitably develop a progressive disease course. Onset of progression is more dependent on age than the presence or duration of a pre-progression symptomatic disease course. Moderate disability is sustained predominantly after the onset of a progressive disease course in MS.