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1.
In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data. 相似文献
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Danielle E Whittier Elizabeth J Samelson Marian T Hannan Lauren A Burt David A Hanley Emmanuel Biver Pawel Szulc Elisabeth Sornay-Rendu Blandine Merle Roland Chapurlat Eric Lespessailles Andy Kin On Wong David Goltzman Sundeep Khosla Serge Ferrari Mary L Bouxsein Douglas P Kiel Steven K Boyd 《Journal of bone and mineral research》2022,37(3):428-439
Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR). 相似文献
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Xin Yi Wong Andrew Qi Jun Lim Qianyu Shen John Whay Kuang Chia Min Hoe Chew Wah Siew Tan 《Current medical research and opinion》2020,36(10):1677-1686
Abstract
Objective
Ras wild-type metastatic colorectal cancers (mCRC) may be treated with anti-vascular endothelial growth factor (VEGF) or anti-epidermal growth factor receptor (EGFR) agents. We aim to estimate patients’ preferences for mCRC treatment and relative importance of cost, efficacy improvement, avoidance of side effects and therapy convenience, and relative uptake between profiles that resemble Bevacizumab (anti-VEGF) and Cetuximab (anti-EGFR), two commonly prescribed mCRC targeted therapies. 相似文献8.
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PNPLA3 gene polymorphism and response to lifestyle modification in patients with nonalcoholic fatty liver disease
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