Opioid activities of human β-casomorphins

Summary Opioid activities of human -casomorphin-4,-5,-7 and -8 and, for comparison, of the corresponding bovine -casomorphins were studied in the guinea-pig ileum preparation. Binding parameters, i.e. K _d -values and binding site concentrations, for the interaction of human and bovine -casomorphins with opioid receptors in rat brain homogenates were determined in inhibition experiments, using [³H]-(d-Ala², MePhe⁴, Gly-ol⁵)enkephalin, [³H]-(d-Ala², d-Leu⁵)enkephalin and [³H]ethylketazocin as -, - and -opioid receptor ligands. Analysis of binding data was performed using a non-linear curve fitting program. All -casomorphins examined displayed opioid activity. The affinity was highest for -receptors, less so for -receptors and lowest for -receptors. It is suggested that human -casomorphins might play a role as food hormones.     

Longitudinal studies of drug abuse in a fifteen-year-old population. 5. Prognostic factors

In an attempt to identify prognostic factors, non-drug users and abusers in the Gothenburg year cohort of 1953 were compared with reference to background data. Individuals with chronic abuse differed most from the "normal" group. Prognostic factors for drug abuse were: member of a multiproblem family, child psychiatric care, contact with the Social Welfare Administration at an early age, truancy, placement in special class, premature drop-out from school, admitted high-frequency drug use in a school questionnaire, for boys early registration for crimes and for girls nervous complaints. The results indicate the necessity of earlier and more effective prevention.     

科技期刊关联数据开放共享及出版政策研究

【目的】 搭建一个适合我国科技期刊关联数据出版的框架,为科技期刊制订关联数据开放共享及出版政策提供参考。【方法】 通过文献分析和网络调研方法,对国内外出版机构及科技期刊在关联数据出版方面的政策进行跟踪调研,并基于数据FAIR原则,分别从数据的可发现、可获取、可互操作和可重用4个维度进行具体分析,明确科技期刊关联数据出版的要素。【结果】 结合我国科技期刊发展现状及规划,通过共享分级并将数据出版要素纳入其中,提出符合国际数据共享政策、面向我国科技期刊的关联数据出版通用数据政策框架。【结论】 所提出的期刊关联数据共享分级策略,可为不同期刊数据政策的制订提供参考。     

学术期刊关联数据出版与共享中的信息安全管理

【目的】 对我国学术期刊关联数据出版与共享中的信息安全管理的概念、政策及其存在的问题进行梳理,有助于科学数据出版与共享工作的推进。【方法】 基于我国科学数据出版与共享的演化过程,以及地理资源期刊在科学数据共享方面的现状与发展情况,对期刊论文关联数据出版和安全管理情况进行分析,对平台间合作的模式进行探讨。【结果】 为实现科学数据的价值最大化,中国自上而下建立起了科学数据共享系统,包括网络基础设施、数据库、数据中心、数据服务平台等,制定了一系列数据获取和管理规范,并制定了保障科学数据信息安全的相关法律。【结论】 科学数据出版与共享应建立在安全的基础上。经过初期的大规模建设后,数据出版与共享及其安全管理应走向“提质增效”阶段,要注重高新技术的注入和专业人才的培养。在管理措施上要以保证数据安全为基础,以数据质量为核心,从而提升信息安全管理水平,提高数据再应用效率。     

Reported Challenges in Health Technology Assessment of Complex Health Technologies

ObjectivesWith complex health technologies entering the market, methods for health technology assessment (HTA) may require changes. This study aimed to identify challenges in HTA of complex health technologies.MethodsA survey was sent to European HTA organizations participating in European Network for HTA (EUnetHTA). The survey contained open questions and used predefined potentially complex health technologies and 7 case studies to identify types of complex health technologies and challenges faced during HTA. The survey was validated, tested for reliability by an expert panel, and pilot tested before dissemination.ResultsA total of 22 HTA organizations completed the survey (67%). Advanced therapeutic medicinal products (ATMPs) and histology-independent therapies were considered most challenging based on the predefined complex health technologies and case studies. For the case studies, more than half of the reported challenges were “methodological,” equal in relative effectiveness assessments as in cost-effectiveness assessments. Through the open questions, we found that most of these challenges actually rooted in data unavailability. Data were reported as “absent,” “insufficient,” “immature,” or “low quality” by 18 of 20 organizations (90%), in particular data on quality of life. Policy and organizational challenges and challenges because of societal or political pressure were reported by 8 (40%) and 4 organizations (20%), respectively. Modeling issues were reported least often (n = 2, 4%).ConclusionsMost challenges in HTA of complex health technologies root in data insufficiencies rather than in the complexity of health technologies itself. As the number of complex technologies grows, the urgency for new methods and policies to guide HTA decision making increases.     

A Framework for Using Real-World Data and Health Outcomes Modeling to Evaluate Machine Learning–Based Risk Prediction Models

ObjectivesWe propose a framework of health outcomes modeling with dynamic decision making and real-world data (RWD) to evaluate the potential utility of novel risk prediction models in clinical practice. Lung transplant (LTx) referral decisions in cystic fibrosis offer a complex case study.MethodsWe used longitudinal RWD for a cohort of adults (n = 4247) from the Cystic Fibrosis Foundation Patient Registry to compare outcomes of an LTx referral policy based on machine learning (ML) mortality risk predictions to referral based on (1) forced expiratory volume in 1 second (FEV₁) alone and (2) heterogenous usual care (UC). We then developed a patient-level simulation model to project number of patients referred for LTx and 5-year survival, accounting for transplant availability, organ allocation policy, and heterogenous treatment effects.ResultsOnly 12% of patients (95% confidence interval 11%-13%) were referred for LTx over 5 years under UC, compared with 19% (18%-20%) under FEV₁ and 20% (19%-22%) under ML. Of 309 patients who died before LTx referral under UC, 31% (27%-36%) would have been referred under FEV₁ and 40% (35%-45%) would have been referred under ML. Given a fixed supply of organs, differences in referral time did not lead to significant differences in transplants, pretransplant or post-transplant deaths, or overall survival in 5 years.ConclusionsHealth outcomes modeling with RWD may help to identify novel ML risk prediction models with high potential real-world clinical utility and rule out further investment in models that are unlikely to offer meaningful real-world benefits.     

Validating Restricted Mean Survival Time Estimates From Reconstructed Kaplan-Meier Data Against Original Trial Individual Patient Data From Trials Conducted by the Canadian Cancer Trials Group

ObjectivesThe development of novel cancer therapies, including immuno-oncology agents, has increased interest in reconstructed individual patient data (IPD) based restricted mean survival time (RMST) analyses. Additionally, reconstructed IPD–based RMST is recommended in cost-effectiveness analyses when original trial IPD are not available. Nevertheless, recently concerns regarding potential bias of reconstructed-IPD RMST have been presented, because reconstructed-IPD RMSTs have not been validated and previous validation endpoints may not capture the entire Kaplan-Meier (KM) curve, especially the “tail.” Our study aims to validate the recommended method of IPD reconstruction by comparing reconstructed IPD– and original trial IPD–based RMST.MethodsCanadian Cancer Trials Group trials from 1990 to 2017 were included. Overall survival and progression-free survival IPD were reconstructed based on published KM curves using the Guyot method. Analysts were blinded to original trial IPD. RMST was calculated at 1 year and over the entire KM curve. Reconstructed-IPD and original trial–IPD (gold-standard) RMSTs were compared for accuracy and predictive error via mean deviation, mean absolute error (MAE), mean percentage bias, and Bland-Altman plots and across KM curve quality (vector traced or bitmapped).ResultsWe identified 39 trials. The mean deviation, MAE, and mean percentage bias of RMST between the reconstructed IPD and original trial IPD were small. In particular, the mean deviation was ?0.01 months and ?0.04 months, MAE was 0.19 months and 0.24 months, and mean percentage bias was 0.82% and 0.84% in overall survival KM curves in control and experimental arms, respectively. Accuracy was generally not associated with KM curve quality.ConclusionsRMST derived from reconstructed IPD displayed excellent accuracy and predictive error compared with the gold standard. Reconstructed IPD could be used to calculate RMST in lieu of original trial IPD, to facilitate decision making for clinicians, researchers, and policy makers.     

Using aggregated mobile phone location data to compare the realised foodscapes of different socio-economic groups.

The foodscape (the built food environment) is considered one of the driving factors of the higher burden of obesity and chronic disease observed in low socio-economic status (SES) groups. Traditional data collection methods struggle to accurately capture actual access and exposure to the foodscape (realised foodscape). We assess the use of anonymised mobile phone location data (location data) in foodscape studies by applying them to a case study in Perth, Western Australia to test the hypothesis that lower SES groups have poorer realised foodscapes than high SES groups. Kernel density estimation was used to calculate realised foodscapes of different SES groups and home foodscape typologies, which were compared to home foodscapes of the different groups. The location data enabled us to measure realised foodscapes of multiple groups over an extended period and at the city scale. Low SES groups had poor availability of food outlets, including unhealthy outlets, in their home and realised foodscapes and may be more susceptible to a poor home foodscape because of low mobility.     

中医药随机对照试验中采用真实世界数据作为对照组的研究设计及挑战

在设计随机对照试验（RCT）时,如果对照组存在患者招募和入组困难的情况,就会影响试验整体实施。近年来,真实世界数据（RWD）作为除RCT之外的数据来源,在医疗领域中发挥着越来越重要的作用。中医药RCT中可以尝试采用将RWD作为对照组的研究设计,不仅可以有效解决中医药RCT西医对照组患者入组困难的问题,同时能提供有力证据来评价中医药的疗效。倾向评分法目前已广泛应用于真实世界研究中混杂因素的处理,该文对RCT采用RWD作为对照组的这类设计中,基于倾向评分法常见的4种研究设计形式以实例分别进行了介绍,包括不对称随机分配、基于倾向评分分层法的两阶段设计、倾向评分联合复合似然法及倾向评分多种方法的联合。同时,这种设计类型也存在着方法学的挑战,包括RWD数据源必须是高质量且关键信息需要规范收集、RCT和RWD患者基线特征应该具有可比性、协变量选择时需要把所有已知与干预措施和结局相关的协变量都纳入进行分析等。在中医药领域采用这种设计时,还存在着有些RWD中医证型信息缺失、中医结局指标缺失等问题,在使用RWD时,需要根据数据实际情况决定如何分析。该文对以RWD作为RCT对照组的设计类型及面临的方法学挑战进行了介绍,期望能为研究者今后使用这类设计提供方法学借鉴。