An analysis of clinical characteristics in genetically linked migraine-affected pedigrees

Migraine is a common complex disorder characterized by severe recurrent headache and usually accompanied by nausea and vomiting. Previous studies in our laboratory have utilized three large multigenerational Australian pedigrees affected with migraine to indicate that the disease is genetically heterogeneous, with linkage results implicating genomic susceptibility regions on both chromosomes 19p and Xq. The present study explores the possibility of a correlation between genetic and clinical heterogeneity in these affected pedigrees. Specifically, the clinical characteristics of migraine including subtype, age of onset, frequency, duration, and disease symptoms were compared between the migraine pedigrees, and gender differences were also assessed. Our exploratory analyses revealed no significant differences in any of the clinical characteristics tested between the chromosome 19-linked family and the two X-linked families. Also, we did not detect any differences in male vs. female clinical features for these pedigrees. In conclusion, migraine is considered to be a clinically and genetically heterogeneous disorder; however, our study provided no conclusive evidence that variation in genomic susceptibility region is related to heterogeneity at the clinical level in these migraine-affected pedigrees.

A systematic review and meta-analysis of clinical trials on physical interventions for lateral epicondylalgia

A systematic review of the literature on the effectiveness of physical interventions for lateral epicondylalgia ( tennis elbow) was carried out. Seventy six randomised controlled trials were identified, 28 of which satisfied the minimum criteria for meta-analysis. The evidence suggests that extracorporeal shock wave therapy is not beneficial in the treatment of tennis elbow. There is a lack of evidence for the long term benefit of physical interventions in general. However, further research with long term follow up into manipulation and exercise as treatments is indicated.

Lymphoproliferative disease of the ocular adnexa: A clinical and pathologic study with statistical analysis of 69 patients

Purpose: To evaluate the clinical features, treatment, and outcomes of a cohort of patients with ocular adnexal lymphoproliferative disease classified according to the World Health Organization modification of the Revised European-American Classification of Lymphoid neoplasms and to perform a robust statistical analysis of these data. Methods: Sixty-nine cases of ocular adnexal lymphoproliferative disease, seen in a tertiary referral center from 1992 to 2003, were included in the study. Lesions were classified by using the World Health Organization modification of the Revised European-American Classification of Lymphoid neoplasms classification. Outcome variables included disease-specific Survival, relapse-free survival, local control, and distant control. Results: Stage IV disease at presentation, aggressive lymphoma histology, the presence of prior or concurrent systemic lymphoma at presentation, and bilateral adnexal disease were significant predictors for reduced disease-specific survival, local control, and distant control. Multivariate analysis found that aggressive histology and bilateral adnexal disease had significantly reduced disease-specific Survival. Conclusions: The typical presentation of adnexal lymphoproliferative disease is with a painless mass, swelling, or proptosis; however, pain and inflammation occurred in 20% and 30% of patients, respectively. Stage at presentation, tumor histology, primary or secondary status, and whether the process was unilateral or bilateral were significant variables for disease outcome. In this study, distant spread of lymphoma was lower in patients who received greater than 20 Gy of orbital radiotherapy.

Confirmatory factor analysis and psychometric properties of the Anxiety Sensitivity Index-Revised in clinical and normative populations

The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.

On the simultaneous use of clinical and microarray expression data in the cluster analysis of tissue samples

This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).