As all patients with TB do not present with this peculiar clinical feature, a genetic susceptibility
is suspected.
OBJECTIVE: To determine the major histocompatibility complex (MHC) class I and II alleles in Mexican mestizo patients with Poncet’s disease.
DESIGN: In this case-control study of 16 Mexican mestizo patients diagnosed with Poncet’s disease and 99 ethnically matched healthy controls, high resolution human leukocyte antigen (HLA) typing was performed for HLA-A, B, DR and DQ by polymerase chain reaction. HLA-DRB1 and HLA-DQB1 subtypes were performed by sequence-specific oligonucleotide probe hybridization.
RESULTS: A significantly increased frequency of HLA-B27 (corrected P = 0.01) and DQB1*0301 (corrected P = 0.0009) alleles and decreased frequency of HLA-DQB1* 0302 (corrected AZD1480 P = 0.00001) were identified in patients compared to healthy controls.
CONCLUSION: These data suggest that genes located within the MHC may play a role in the susceptibility to Poncet’s disease in patients diagnosed with TB.”
“Implicit in the growing interest in patient-centered outcomes research is a growing need for better evidence regarding
how responses to a given intervention or treatment may vary across patients, referred to as heterogeneity of treatment effect (HTE). A variety of methods are available for exploring HTE, each associated with unique strengths and limitations. This paper reviews a selected set of methodological approaches to understanding HTE,
focusing largely but not Selleckchem Pexidartinib exclusively on their uses with randomized trial data. It is oriented for the “”intermediate”" outcomes researcher, who may already be familiar with some methods, but would value a systematic overview of both more and less familiar methods with attention to when and why they may be used. Drawing from the biomedical, statistical, epidemiological and econometrics literature, we describe the steps involved in choosing an HTE approach, focusing on whether the intent of the analysis is for exploratory, initial testing, or confirmatory testing purposes. We also map HTE methodological approaches to data considerations as well as the strengths and limitations of each approach. Methods reviewed include formal subgroup analysis, meta-analysis and meta-regression, Selleck BAY 73-4506 various types of predictive risk modeling including classification and regression tree analysis, series of n-of-1 trials, latent growth and growth mixture models, quantile regression, and selected non-parametric methods. In addition to an overview of each HTE method, examples and references are provided for further reading.
By guiding the selection of the methods and analysis, this review is meant to better enable outcomes researchers to understand and explore aspects of HTE in the context of patient-centered outcomes research.