Bayesian consensus clustering for multivariate longitudinal data

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.     

Prolyl and lysyl hydroxylases in collagen synthesis

Collagens are the most abundant proteins in the extracellular matrix. They provide a framework to build organs and tissues and give structural support to make them resistant to mechanical load and forces. Several intra‐ and extracellular modifications are needed to make functional collagen molecules, intracellular post‐translational modifications of proline and lysine residues having key roles in this. In this article, we provide a review on the enzymes responsible for the proline and lysine modifications, that is collagen prolyl 4‐hydroxylases, 3‐hydroxylases and lysyl hydroxylases, and discuss their biological functions and involvement in diseases.     

我国家庭医生签约服务政策执行的制约因素与优化路径：基于史密斯政策执行过程模型

深化家庭医生签约服务是深化医药卫生体制改革、强化基层医疗卫生服务、实现"健康中国"战略目标的重要选择，也是当前更好维护人民群众健康的重要途径。为有效推进签约服务工作，国家陆续推出各项政策，全国各地也在积极进行实践探索，成效明显。但是，签约服务仍面临诸多问题，其中"执行难"是签约服务深度推进的一大困境。通过史密斯政策执行过程模型，结合签约服务政策执行过程，发现签约服务仍存在法治性不足、政策执行人员水平不高、激励不足、政策环境影响等诸多制约因素。因此，需要从法律和制度方面进行顶层设计、提升执行人员素质和职业认同、建立医患互信、优化政策执行环境等角度进行政策创新，探索家庭医生签约服务可持续发展的路径。     

Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

1. Download : Download high-res image (173KB)
2. Download : Download full-size image

     

A Coupled FEM-BEM Approach for the Solution of the Free-Boundary Axi-Symmetric Plasma Equilibrium Problem

In this paper we present a coupled Finite Element Method – Boundary Element Method (FEM-BEM) approach for the solution of the free-boundary axi-symmetric plasma equilibrium problem. The proposed method, obtained from an improvement of the Hagenow-Lackner coupling method, allows to efficiently model the equilibrium problem in unbounded domains by discretizing only the plasma region; the external conductors can be modelled either as 2D or 3D models, according to the problem of interest. The paper explores different iterative methods for the solution of the nonlinear Grad-Shafranov equation, such as Picard, Newton-Raphson and Newton-Krylov, in order to provide a robust and reliable tool, able to handle large-scale problems (e.g. high resolution equilibria). This method has been implemented in the FRIDA code (FRee-boundary Integro-Differential Axisimmetric – https://github. om/matteobonotto/ FRIDA), together with a suitable Adaptive Integration Technique (AIT) for the computation of the source term. FRIDA has been successfully tested and validated against experimental data from RFX-mod device, and numerical equilibria of an ITER-like device.     

Predicting Survival for Chimeric Antigen Receptor T-Cell Therapy: A Validation of Survival Models Using Follow-Up Data From ZUMA-1

ObjectivesSurvival extrapolation for chimeric antigen receptor T-cell therapies is challenging, owing to their unique mechanistic properties that translate to complex hazard functions. Axicabtagene ciloleucel is indicated for the treatment of relapse or refractory diffuse large B-cell lymphoma after 2 or more lines of therapy based on the ZUMA-1 trial. Four data snapshots are available, with minimum follow-up of 12, 24, 36, and 48 months. This analysis explores how survival extrapolations for axicabtagene ciloleucel using ZUMA-1 data can be validated and compared.MethodsThree different parametric modeling approaches were applied: standard parametric, spline-based, and cure-based models. Models were compared using a range of metrics, across the 4 data snapshot, including visual fit, plausibility of long-term estimates, statistical goodness of fit, inspection of hazard plots, point-estimate accuracy, and conditional survival estimates.ResultsStandard and spline-based parametric extrapolations were generally incapable of fitting the ZUMA-1 data well. Cure-based models provided the best fit based on the earliest data snapshot, with extrapolations remaining consistent as data matured. At 48 months, the maximum survival overestimate was 8.3% (Gompertz mixture-cure model) versus the maximum underestimate of 33.5% (Weibull standard parametric model).ConclusionsWhere a plateau in the survival curve is clinically plausible, cure-based models may be helpful in making accurate predictions based on immature data. The ability to reliably extrapolate from maturing data may reduce delays in patient access to potentially lifesaving treatments. Additional research is required to understand how models compare in broader contexts, including different treatments and therapeutic areas.     

2013-2017年我国四种恶性肿瘤住院费用水平及结构变动度分析

背景　恶性肿瘤给家庭、社会带来了沉重的医疗、经济负担，极易导致部分家庭“因病致贫”或放弃治疗，目前相关研究多集中于单一病种、分散地域的研究，仍缺乏对于全国范围与多病种恶性肿瘤住院费用变化及结构构成的考量。目的　分析2013-2017年我国4种恶性肿瘤住院费用水平以及影响住院费用的主要项目和结构变动情况，为控制医疗费用上涨、深化新医改提供参考依据。方法　本研究数据来源于《2014中国卫生和计划生育统计年鉴》《2015中国卫生和计划生育统计年鉴》《2016中国卫生和计划生育统计年鉴》《2017中国卫生和计划生育统计年鉴》以及《2018中国卫生健康统计年鉴》，样本跨度为2013-2017年。统计“30种疾病人均住院费用”中的胃恶性肿瘤、肺恶性肿瘤、食管恶性肿瘤以及膀胱恶性肿瘤的数据，4种恶性肿瘤的人均住院费用包括药费、检查费、治疗费、手术费和手术材料费。2019年4-8月，采用结构变动度法分析我国2013-2017年4种恶性肿瘤的住院费用的结构变动情况〔结构变动值（VSV）、结构变动度（DSV）、结构变动贡献率〕。结果　2013-2017年，4种恶性肿瘤的人均住院费用逐年上升，其中胃恶性肿瘤的人均住院费用始终最高，且肺恶性肿瘤的人均住院费用上升幅度最大。2013-2017年，在4种恶性肿瘤住院各项费用的占比中，药费占比最高且总体逐年下降。从4种恶性肿瘤住院各项费用的实际变化来看，药费在2013-2014年有所上升，2014-2017年逐年下降；检查费在2013-2014年下降，2014-2017年缓慢上升；手术费与手术材料费在2013-2017年逐年上升。2013-2017年，在4种恶性肿瘤住院各项费用中均是药费的VSV最大；4种恶性肿瘤药费、检查费的VSV均呈负向变化，手术费和手术材料费的VSV均呈正向变化，治疗费的VSV增减均不明显。2013-2017年，4种恶性肿瘤住院费用的DSV从大到小依次为肺恶性肿瘤、胃恶性肿瘤、食管恶性肿瘤、膀胱恶性肿瘤。2013-2017年，4种恶性肿瘤住院各项费用中均是药费的结构变动贡献率最大，治疗费的结构变动贡献率最小；除药费外，胃恶性肿瘤、肺恶性肿瘤住院各项费用中均是手术材料费和手术费的结构变动贡献率次之，食管恶性肿瘤住院各项费用中手术费、检查费的结构变动贡献率次之，膀胱恶性肿瘤住院各项费用中检查费、手术材料费的结构变动贡献率次之。结论　2013-2017年我国4种恶性肿瘤手术费的结构变动贡献率虽然较为理想，但药费、治疗费仍是住院费用结构的重点调整对象；同时为有效降低恶性肿瘤的人均住院费用，应当加强控制手术材料费与检查费；而胃恶性肿瘤与肺恶性肿瘤患者的疾病经济负担严重，若要缓解应加强疾病的早期预防与住院费用管控。