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.     

Challenges with Forecasting Budget Impact: A Case Study of Six ICER Reports

Background

Payers frequently rely on budget impact model (BIM) results to help determine drug coverage policy and its effect on their bottom line. It is unclear whether BIMs typically overestimate or underestimate real-world budget impact.

尿液10项肾损伤标志物检测试剂的性能评价

摘要:目的对尿液 10项肾损伤标志物检测试剂进行性能评价,并评估其临床适用性。方法对北京利德曼公司尿液a1 微球蛋白(u-a|MG)、总蛋白(u-TP)、免疫球蛋白G(u-IgG) 、微量清蛋白(u-Alb)、中性粒细胞明胶酶相关脂质运载蛋白(u-NGAL)、半胱氨酸蛋白酶抑制剂C(u-CysC).视黄醇结合蛋白(u-RBP)、β2微球蛋白(u-β2MG)、N-乙酰-β-D-氨基葡萄糖苷酶(u-NAG).、转铁蛋白(u-Trf)检测试剂盒进行性能评价。正确度和精密度验证参考美国临床和实验室标准协会(CLSI)EP15-A3,验证物质采用ERM-DA470k、ERM-DA471、B2M-NIBSC等参考物质及纯度物质;线性验证参考CLSI EP06;抗干扰能力参考CISI EP07;不同检测系统间比对参考CISI EP09。结果正确度方面,10 项标志物检测试剂测定标准物质在低值、中值、高值的偏倚分别为-2.69% ~4.67%、-3.60% ~3.33% .-2.38% ~3.02%;不精密度方面,重复性以不精密度表示,在低值和高值处分别为1.90%~5.43%、0.63% ~2.42%,室内不精密度为2.27%~5.63%、1.09%~3.41%,均满足临床要求;10项尿液标志物线性范围在0.06~4.40 mg/L至21.83~2 146.77 mg/L之间。抗干扰方面,u-1 MG、u-Alb、u-β2MG、u-Trf 、u-CysC、u-NAG分别在血红蛋白终浓度≤8 g/L、≤8 g/L、≤4 g/L、≤4 g/L、≤2g/L、≤1 g/L时,未受到明显干扰(百分偏差≤+ 10%) ,而u-TP、u-IgG、 u-RBP、u-NGAL在血红蛋白终浓度≥0.125 g/L时即受干扰。不同检测系统间偏差超出临床允许范围。结论尿液 10项肾损伤标志物的正确度、精密度、线性范围和抗血红蛋白干扰能力满足临床需要,不同检测系统间标志物测量结果可比性欠佳。     

Statistical analysis of gait patterns of persons with cerebral palsy

Patients at Boston's Children's Hospital diagnosed as having cerebral palsy were filmed walking. These films were digitized and translated into measurements associated with leg motion. In this paper we use the gait measurements of 128 such patients to illustrate that the kth nearest neighbour clustering procedure results in a gait typology for patients with cerebral palsy. The procedure identifies four subpopulations from the sample data; the membership of a patient within this typology is mostly determined by the patient's motor control. The developed typology differs from the present diagnostic system which classifies a cerebral palsy patient as either quadriplegic, diaplegic or hemiplegic.     

Developing Organ Offer and Acceptance Measures: When 'Good' Organs Are Turned Down

Turndowns of offers of deceased donor kidneys for transplantation can contribute to inefficiencies in the organ distribution system and inequality in access to donated organs. Match run data were obtained for 4967 'good' kidneys placed and transplanted in 2005 after fewer than 50 offers. These kidneys were not recovered from donation after cardiac death or expanded criteria donors, or from donors with a history of substance abuse. On average, these good kidneys were not accepted until after seven offers to candidates and after offers to 2.4 programs. Models for the likelihood of acceptance found several donor and candidate characteristics to be significantly related to acceptance rates (p < 0.05). After accounting for these variables, there remained 2- to 3-fold differences among transplant programs in acceptance rates. These models could be used to identify kidney transplant centers with exceptional acceptance practices. Several strategies might be employed to increase acceptance rates for good organs.