Analysis of ordered composite endpoints

Composite endpoints are frequently used in clinical trials, but simple approaches, such as the time to first event, do not reflect any ordering among the endpoints. However, some endpoints, such as mortality, are worse than others. A variety of procedures have been proposed to reflect the severity of the individual endpoints such as pairwise ranking approaches, the win ratio, and the desirability of outcome ranking. When patients have different lengths of follow-up, however, ranking can be difficult and proposed methods do not naturally lead to regression approaches and require specialized software. This paper defines an ordering score O to operationalize the patient ranking implied by hierarchical endpoints. We show how differential right censoring of follow-up corresponds to multiple interval censoring of the ordering score allowing standard software for survival models to be used to calculate the nonparametric maximum likelihood estimators (NPMLEs) of different measures. Additionally, if one assumes that the ordering score is transformable to an exponential random variable, a semiparametric regression is obtained, which is equivalent to the proportional hazards model subject to multiple interval censoring. Standard software can be used for estimation. We show that the NPMLE can be poorly behaved compared to the simple estimators in staggered entry trials. We also show that the semiparametric estimator can be more efficient than simple estimators and explore how standard Cox regression maneuvers can be used to assess model fit, allow for flexible generalizations, and assess interactions of covariates with treatment. We analyze a trial of short versus long-term antiplatelet therapy using our methods.     

Validation of PATHFx 2.0: An open-source tool for estimating survival in patients undergoing pathologic fracture fixation

Treatment decisions in patients with metastatic bone disease rely on accurate survival estimation. We developed the original PATHFx models using expensive, proprietary software and now seek to provide a more cost-effective solution. Using open-source machine learning software to create PATHFx version 2.0, we asked whether PATHFx 2.0 could be created using open-source methods and externally validated in two unique patient populations. The training set of a well-characterized, database records of 189 patients and the bnlearn package within R Version 3.5.1 (R Foundation for Statistical Computing), was used to establish a series of Bayesian belief network models designed to predict survival at 1, 3, 6, 12, 18, and 24 months. Each was externally validated in both a Scandinavian (n = 815 patients) and a Japanese (n = 261 patients) data set. Brier scores and receiver operating characteristic curves to assessed discriminatory ability. Decision curve analysis (DCA) evaluated whether models should be used clinically. DCA showed that the model should be used clinically at all time points in the Scandinavian data set. For the 1-month time point, DCA of the Japanese data set suggested to expect better outcomes assuming all patients will survive greater than 1 month. Brier scores for each curve demonstrate that the models are accurate at each time point. Statement of Clinical Significance: we successfully transitioned to PATHFx 2.0 using open-source software and externally validated it in two unique patient populations, which can be used as a cost-effective option to guide surgical decisions in patients with metastatic bone disease.     

Seeking the optimal schedule for chickenpox vaccination in Canada: Using an agent-based model to explore the impact of dose timing,coverage and waning of immunity on disease outcomes

Many countries continue to consider implementing a universal chickenpox vaccine program; however, there is no consensus on the most appropriate and effective timing between vaccine doses. The chickenpox vaccine schedule debate is highlighted in Canada, where there are currently eight different vaccine schedules across the country. The objective of this study was to test the overall effectiveness of chickenpox vaccination, as well as the specific impact of two different vaccine schedules, on chickenpox disease outcomes in Alberta over 75 years. Using an agent-based model of chickenpox disease, we tested the impact of three vaccination scenarios including: baseline (no vaccination), a long dosing interval-Schedule LDI (1^st dose – 12 months; 2^nd dose –  4-6 years) and a short dosing interval-Schedule SDI (1^st dose – 12 months; 2^nd dose – 18 months) on chickenpox and shingles disease outcomes. Chickenpox vaccination led to a substantial decrease in chickenpox incidence over 75 years post-vaccine implementation. Compared to Schedule LDI, Schedule SDI resulted in a significantly lower chickenpox incidence, a higher age of chickenpox infection, a lower chickenpox breakthrough rate and a higher shingles incidence rate. Our model findings suggest that the chickenpox vaccine is effective over a long period of time and the dose timing of the vaccine may impact disease outcomes and vaccine effectiveness. However, the effectiveness of the vaccine dose timing is only one consideration for policy-makers who are implementing a chickenpox vaccine program, with others including risk of adverse events, the impact of the schedule on other antigens in a combination vaccine, parental acceptance and the cost associated with different schedules.     

Bayesian leveraging of historical control data for a clinical trial with time-to-event endpoint

The recent 21st Century Cures Act propagates innovations to accelerate the discovery, development, and delivery of 21st century cures. It includes the broader application of Bayesian statistics and the use of evidence from clinical expertise. An example of the latter is the use of trial-external (or historical) data, which promises more efficient or ethical trial designs. We propose a Bayesian meta-analytic approach to leverage historical data for time-to-event endpoints, which are common in oncology and cardiovascular diseases. The approach is based on a robust hierarchical model for piecewise exponential data. It allows for various degrees of between trial-heterogeneity and for leveraging individual as well as aggregate data. An ovarian carcinoma trial and a non-small cell cancer trial illustrate methodological and practical aspects of leveraging historical data for the analysis and design of time-to-event trials.     

A conceptual model and detailed framework for stress-related,strain-related,and overuse athletic injury

A multitude of athletic injuries occur when the various tissues that make up the human body experience stresses and strains that exceed their material strength. The precise amount of stress and strain that any given tissue can withstand is determined by the mechanical properties and resultant strength of that particular tissue. These mechanical properties are directly determined by an individual’s physiology and acute regulation of these properties. A number of theoretical frameworks for athletic injury occurrence have been proposed, however, a detailed conceptual framework for injury aetiology that considers the interplay between the physiological and mechanical factors and outlines the causal pathways to tissue damage and injury is needed. This will guide injury research towards a more thorough investigation of causal mechanisms and understanding of risk factors. Further, it is important to take into account the considerable differences in loading patterns which can result in varying injury outcomes such as acute stress-related, strain-related, or overuse injury. Within this article a simplified conceptual model of athletic injury is proposed along with a detailed, evidence-informed, conceptual framework for athletic injury aetiology that focuses on stress-related, strain-related, and overuse injury.     

The activity prediction of indole inhibitors against HCV NS5B polymerase

Non‐structural viral protein 5B (NS5B) is a viral protein in hepatitis C virus. Although various inhibitors against NS5B have been found, the activity prediction of similar untested inhibitors is still highly desirable. In this respect, the Tchebichef moments (TMs) calculated from the images of molecular structures were regarded as the independent variables while the inhibitory activity (pIC₅₀) was the dependent variable, and the predictive model was established by means of stepwise regression. The R‐squared of leave‐one‐out cross‐validation (Q²) for the training set and the R‐squared of prediction () for external independent test set were 0.919 and 0.927, respectively. The obtained model was also evaluated strictly. Compared with the multivariate curve resolution with alternating least squares (MCR‐ALS) and the QSAR approaches derived from the literature, the proposed method is more accurate and reliable. This study not only provides an effective approach to predict the biological activity of RNA replication's inhibitors, but also extends the QSAR modeling technique.     

一种氯化铁诱导血栓生成的小鼠大脑中动脉远端缺血模型

目的 建立稳定的小鼠大脑中动脉远端氯化铁血栓模型，评价其造成的脑损伤及神经功能损伤程 度。 方法 C57BL6/J雄性小鼠随机分为脑缺血组和假手术组。脑缺血组用10%氯化铁（ferric chloride， FeCl3）溶液诱导右侧大脑中动脉远端形成血栓。在术前、术后10 mi n、术后1 d和7 d观测术侧脑血流 和手术动脉血流量的变化。术后1 d观察脑组织梗死率。术后1 d、3 d、5 d、7 d用3种神经学评分[改良 加西亚评分（modified Garcia score，mGS）、改良神经损伤严重程度评分（modified neurological severity scores，mNSS）和15分神经学评估表（15-point neurological evaluation scale，NES）]和胶黏纸测试评价小 鼠神经功能。术后7 d免疫荧光染色标记神经细胞核观察脑组织损伤，标记CD16/32、CD206和Iba1观 察胶质细胞表达。 结果 与假手术组相比，脑缺血组术后10 mi n、1 d、7 d脑表面血流和手术动脉血流下降，术后1 d脑 皮层梗死明显，术后7 d仍有明显脑组织损伤；脑缺血组术后1 d、3 d、5 d和7 d时3种神经学评分及胶 黏纸测试均提示小鼠神经功能不同程度损伤。术后7 d脑缺血组梗死周围皮层M1和M2型胶质细胞表 达增加。 结论 FeCl3溶液可诱导形成稳定的小鼠脑缺血模型，该模型可造成手术侧大脑中动脉远端及脑表 面血流量降低，皮层脑梗死，小鼠神经功能受损，梗死周围胶质细胞表达上调。本研究建立了稳定 氯化铁诱导血栓形成的小鼠脑缺血模型，为脑血栓形成和抗栓药物治疗提供了一种可靠的研究工 具。     

C57BL/6小鼠放射性心肺功能不全动物模型建立

目的 建立C57BL/6小鼠放射性心肺功能不全动物模型。方法 24只雄性C57BL/6小鼠随机分为对照组、照射组。照射组接受胸部局部单次20 Gy电子线照射,照后饲养6个月。超声心动检查心功能,血气分析检测血氧分压(PaO₂),Tunel染色法检测细胞凋亡,Masson染色法检测心肺纤维化。结果 照射组LVEF (68.60±10.92)%与对照组(81.75±8.79)%降低(P<0.01);照射组心脏凋亡指数(23.90±6.60)%比对照组(3.25±3.38)%增高(P<0.01);照射组心脏CVF (15.42±5.72)%比对照组(1.45±0.64)%增高(P<0.01)。照射组PaO₂(86.10±7.60) mmHg比对照组PaO₂(107.16±9.01) mmHg下降(P<0.01);照射组肺脏凋亡指数(27.90±8.94)%比对照组(2.50±3.55)%增高(P<0.01);照射组肺脏CVF (17.76±5.77)%比对照组(2.50±3.55)%增高(P<0.01)。结论 辐射使心肺凋亡纤维化重塑,进而导致心肺功能的下降,成功构建C57BL/6小鼠放射性心肺功能不全动物模型。     

我国老年长期护理服务质量及其影响因素分析——基于上海市的实证研究

利用上海市调研数据,以60岁及以上老人为研究对象,基于SERVQUAL模型和有序多分类逻辑回归方法分析我国老年长期护理服务质量及其影响因素。研究发现:老人对长期护理服务质量评价不高,且常用临床护理服务质量略低于基本生活照料服务质量。供给方因素中护理机构基础设施、管理水平、护理人员专业水平对长期护理服务质量的提升具有正向激励作用。需求方因素中老人养老金水平对长期护理服务质量的提高具有显著正向激励,而老人的失能程度对服务质量具有显著负向影响,且与男性老人相比,女性老人对长期护理服务质量评价显著更高。研究结果为精确地评估我国老年长期护理服务质量提供了科学依据,对提升失能老人的生活质量,促进我国长期护理服务产业的发展具有重要的政策启示。