Occupational therapy articles in serial publications: an analysis of sources.

This study was designed to locate and document serial literature on occupational therapy published since 1900. Emphasis is placed on finding articles on occupational therapy or by occupational therapists from sources other than those normally associated with the professional journals. Multiple sources were used including print indexes, online databases, occupational therapy bibliographies, and tables of contents or yearly indexes. Almost 7,000 articles were identified, not including those published in foreign journals. Occupational therapy publications have increased steadily since 1900, with the most rapid increase during the 1970s and 1980s when five new occupational therapy journals were initiated. Suggestions for formulating search strategies are included.

Prior history of atopy or autoimmunity increases risk for alopecia areata

Background. The association between a prior history of atopy or other autoimmune diseases and risk of alopecia areata is not well established. ^ Objective. Purpose of this study was to use the National Alopecia Areata Registry database to further investigate the association between history of atopy or other autoimmune diseases and risk of alopecia areata. ^ Methods. A total of 2,613 self-registered sporadic cases (n = 2,055) and controls (n = 558) were included in the present analysis. ^ Results. Possessing a history of any atopy (OR = 2.00; 95% CI 1.50-2.54) or autoimmune disease (OR = 1.73; 95% CI 1.10-2.72) was associated with an increased risk of alopecia areata. There was no trend for possessing a history of more than one atopy or autoimmune disease and increasing risk of alopecia areata. ^ Limitations. Recall, reporting, and recruiting bias are potential sources of limitations in this analysis. ^ Conclusion. This analysis revealed that a prior history of atopy and autoimmune disease was associated with an increased risk of alopecia areata and that the results were consistent for both the severe subtype of alopecia areata (i.e., alopecia totalis and alopecia universalis) and the localized subtype (i.e., alopecia areata persistent).^

Concordance between medical records and personal interview in ascertaining breast cancer and diabetes status: Analysis of the south Texas women's health project

Accurate ascertainment of risk factors and disease status is vital in public health research for proper classification of research subjects. The two most common ways of obtaining this data is by self-report and review of medical records (MRs). South Texas Women’s Health Project was a case-control study looking at interrelationships between hormones, diet, and body size and breast cancer among Hispanic women 30-79 years of age. History of breast cancer, diabetes mellitus (DM) and use of DM medications was ascertained from a personal interview. At the time of interview, the subject identified her major health care providers and signed the medical records release form, which was sent to the designated providers. The MRs were reviewed to confirm information obtained from the interview.^ Aim of this study was to determine the sensitivity and specificity between MRs and personal interview in diagnosis of breast cancer, DM and DM treatment. We also wanted to assess how successful our low-cost approach was in obtaining pertinent MRs and what factors influenced the quality of MR or interview data. Study sample was 721 women with both self-report and MR data available by June 2007. Overall response rate for MR requests was 74.5%. MRs were 80.9% sensitive and 100% specific in confirming breast cancer status. Prevalence of DM was 22.7% from the interviews and 16% from MRs. MRs did not provide definite information about DM status of 53.6% subjects. Sensitivity and specificity of MRs for DM status was 88.9% and 90.4% respectively. Disagreement on DM status from the two sources was seen in 15.9% subjects. This discordance was more common among older subjects, those who were married and were predominantly Spanish speaking. Income and level of education did not have a statistically significantly association with this disagreement.^ Both self-report and MRs underestimate the prevalence of DM. Relying solely on MRs leads to greater misclassification than relying on self-report data. MRs have good to excellent specificity and thus serve as a good tool to confirm information obtained from self-report. Self-report and MRs should be used in a complementary manner for accurate assessment of DM and breast cancer status.^

A History of Organized Medicine in Harris County, Texas

The item was written by the Historical Committee of the Harris County Medical Society and signed on October 28, 1948. A brief history of medicine in Texas is given before the focus shifts to the Harris County and Houston area. Information on the early years is taken from various sources such as Pat Ireland Nixon’s The Medical Story of Early Texas and the writings of George Plunkett (Mrs. S. C.) Red. Significant information comes from the Minutes of the Harris County Medical Society.

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.