临床真实世界研究中的实验性研究设计

真实世界研究作为解释性随机对照试验在医疗实践中评价干预措施效果的进一步验证和补充已成为医疗卫生领域关注的焦点。但是也存在错误将真实世界研究等同于观察性研究,认为真实世界研究不能实施人为干预,更不能采取随机化。实际上,真实世界研究的基本设计既可以是观察性的,也可以是实验性的。其中真实世界研究的实验性研究设计主要是指实用性随机对照试验和基于注册登记研究的随机对照试验,也可采用非随机对照、自适应设计等其他研究设计方案。     

模拟目标试验在真实世界中的应用：他汀类药物对糖尿病患者死亡率的影响

模拟目标试验是一种观察性研究方法，该方法在无法进行随机对照试验（RCT）的情况下，可以利用真实世界数据（如观察性数据及历史性数据）按照RCT的设计原则进行研究设计，模拟随机分组形成干预组和对照组，最终得到近似RCT的高可信度结论。本研究以他汀类药物对糖尿病患者心肌梗死预后的影响为例，对模拟目标试验的基本概念和应用流程进行介绍，为其在真实世界中的应用提供参考。     

倾向性评分法简介及其SAS实现

随机对照试验(RCT)被视为评估治疗效果的金标准,其关注效力(efficacy)研究,但是人们的兴趣通常还是集中在评估RCT严格控制的范围之外的真实世界的效果(effectiveness),更加重视外部有效性[1]。因此,越来越多的研究者使用观察数据来评估治疗效果。在RCT中,受试者被随机分配到治疗组和对照组,从而保证了两组基线协变量的分布相同,而观察性研究并非如此,如果某些协变量同时与治疗方案和结果相关,则可能会造成混杂。此时,需要通过统计方法消除混杂的影响,常用的方法有匹配法、多元统计分析法等。近十几年来,倾向性评分(propensity score,PS)法作为一种控制混杂偏倚的方法被研究者们越来越关注,其实现的统计软件有R语言、stata、SPSS等。     

多危险因素干预试验中吸烟干预研究

本对多危险因素干预试验（ＭＦＲＩＴ）中吸烟干预的历史、试验对象的标准、分组原则、死亡资料的查证方法、资料的收集方法、干预措施的实验方法进行了叙述，简要阐述了该大型干预试验研究的重要结论。     

应用Markov模型进行临床决策分析

对一项临床干预措施的全面评价应包括临床效果和卫生经济学两个方面,但由于种种原因,评价所需资料并非都能从科学性及论证力较强的随机临床对照试验或前瞻性研究中得到,特别是一些治疗措施远期效果的评价,往往无法在短期内进行前瞻性研究。而对一些已进行了随机对照临床试验的治疗方法,常常因试验期内进行前瞻性研究。而对一些已进行了随机对照临床试验的治疗方法,常常因试验期有限、并存在依从性及副作用的问题,仍不能确定理     

青少年戒烟信息通信技术干预实施方案可行性分析

目的设计整合个性化手机短信和网络互动交流通信技术的青少年个性化戒烟干预方案,论证其实施的可行性。方法在文献评阅、定性和定量研究的基础上,设计并制定基于信息通信技术的个性化戒烟干预实施方案,以自行阅读戒烟宣传手册为对照,在上海市6所中等职业技术学校募集176名吸烟学生,进行为期3个月的群干预对照试验,调查受试者对于该干预模式感兴趣程度、可接受性和自感有用性。结果 80%以上的干预对象对于本项目实施中的5个主要干预环节感到有兴趣,认为基于通信技术的戒烟干预方法的优点突出体现在方便实用(37.5%)、容易记住(33.3%)和内容更适合自己(26.7%)。与对照组采用的阅读戒烟文字材料比较,新型的干预方法在增强戒烟信心、掌握技巧、减少吸烟量和缓解压力方面尤显优势。结论基于信息通信技术的个性化、交互式戒烟干预模式在青少年吸烟人群中进行现场干预实施的可接受性和满意度较高,具有较强的可行性。     

变化区组随机化及其SAS宏实现北大核心CSCD

目的非固定区组长度可有效降低随机对照临床试验(RCT)中区组随机化分组的可预测性,为此编制全自动SAS宏程序实现变化区组随机化。方法结合变化区组随机化的原理编制SAS宏程序,通过模拟实例演示程序的使用。结果输入设定的宏变量参数,运行SAS宏程序即可生成变化区组随机化的受试者分配方案。此外,该SAS宏能实现多臂不等比RCT的分配问题,提供了受试者随机分配序列重现的功能。结论多区组长度的设置和区组长度的随机选择能够降低分组可预测性,避免随机分组阶段选择偏倚的产生。本文的SAS宏为随机对照临床试验实现变化区组随机化提供了便利。     

流行病学实验研究发展历史

流行病学实验研究作为流行病学的重要研究方法之一,是通过比较给予干预措施后的实验组人群与对照组人群的结局,从而验证研究假设和考核干预措施效果的一种前瞻性研究方法,又称干预研究、实验流行病学研究等。其中包括临床试验、现场试验和社区干预项目等研究类型。这类研究方法在临床治疗和疾病预防措施的科学评价和筛选、医疗卫生政策、健康教育及诊断技术效果评估等方面起着举足轻重的作用,已被视为评价干预措施有效性的标准方法。但流行病学实验研究在方法学发展和科学性不断完善方面经历了漫长的历程。     

浅谈新药临床试验中的知情同意

从一个可能的受试者处获得知情同意书 ,也许是试验中研究者必须面临的最困难的工作之一。尽管如此 ,使每个受试者充分了解试验目的 ,预期他可能的受益和可能承担的风险与不便 ,仍是十分必要的。尽管已有许多有关知情同意的文章发表 ,但对研究者在临床试验中如何获得受试者的知情同意 ,却很少有指导性的文章。本文的目的不是讨论在临床试验中不获得受试者的知情同意是否符合伦理道德 ,而是对受试者明确的同意参加临床试验时 ,研究者如何获得知情同意提供一些实际帮助。一、认真研究实验设计要想获得受试者的知情同意 ,必须认真的研究实验设计…     

观察性研究文献评价标准

临床研究根据有无设计的干预措施,分为观察性研究和试验性研究,试验性研究主要类型包括随机对照研究(RCT)和非随机对照研究,观察性研究中最常用的是病例对照研究和队列研究.在阅读文献或荟萃分析时均须对文献质量进行客观评价,本文对观察性研究文献评价标准进行介绍.     

Should meta-analyses of interventions include observational studies in addition to randomized controlled trials? A critical examination of underlying principles

Some authors argue that systematic reviews and meta-analyses of intervention studies should include only randomized controlled trials because the randomized controlled trial is a more valid study design for causal inference compared with the observational study design. However, a review of the principal elements underlying this claim (randomization removes the chance of confounding, and the double-blind process minimizes biases caused by the placebo effect) suggests that both classes of study designs have strengths and weaknesses, and including information from observational studies may improve the inference based on only randomized controlled trials. Furthermore, a review of empirical studies suggests that meta-analyses based on observational studies generally produce estimates of effect similar to those from meta-analyses based on randomized controlled trials. The authors found that the advantages of including both observational studies and randomized studies in a meta-analysis could outweigh the disadvantages in many situations and that observational studies should not be excluded a priori.     

Adapting the randomized consent (Zelen) design for trials of behavioural interventions for chronic disease: feasibility study

OBJECTIVES: Standard randomized controlled trials of interventions for chronic conditions that involve behavioural change, or that are highly desired by participants, are difficult to undertake because of problems with recruitment and contamination. Alternatives include cluster-randomized trials or pre-randomization designs such as the Zelen design. The aim here was to develop a pre-randomization design that would overcome ethical and methodological problems associated with the conventional Zelen design, and permit the rigorous evaluation of a complex package of care, involving physical therapy and behavioural changes, for patients with painful patello-femoral osteoarthritis of the knee joint. METHODS: Eligible patients were first consented to a one-year observational study of their arthritis. They were subsequently randomized into intervention and control arms. Those in the intervention arm were then asked if they were willing to participate in a further study involving regular sessions with a physiotherapist. Those in the control arm were not told about this, but were followed up as agreed. RESULTS: Eighty-seven patients consented to the observational study, 43 of whom were subsequently randomized to the intervention arm. All 43 consented to the intervention, although five of these did not receive the full package of care. Assessments were carried out at five months and one year on 82 patients, and concealment was satisfactorily maintained in the majority. CONCLUSIONS: We conclude that this study design could potentially offer an acceptable compromise between the need for scientific rigour and the ethical imperative of fully informed consent in trials that involve behavioural change or interventions that patients might want to obtain.     

Nested randomized trials in large cohorts and biobanks: studying the health effects of lifestyle factors

Most diseases are likely to result largely from the interplay of lifestyle and genetic factors. However, both observational studies and randomized trials have faced major limitations in trying to address the impact of lifestyle on health. As large cohorts and biobanks are being developed, we need to find novel, efficient ways to address the effects of lifestyle interventions. We propose that this could be done using multiple lifestyle factorial experimental designs that combine characteristics of randomized trials and epidemiologic studies. Randomized trials of simple lifestyle interventions can be nested within large cohorts linked to reliable registries of outcomes. Participants can choose from a long list of simple lifestyle randomization options and many interventions may be tested concurrently with factorial randomization. Participants can tailor their own personal trial choosing several items among long laundry lists of randomization options. Participants are citizen-scientists rather than passive subjects and this may be attractive in modern societies of health-conscious people. These trials can use the existing machinery of the cohort for data collection and outcome linkage at no or minimal additional cost. We discuss a number of issues on the implementation of multiple lifestyle factorial experimental designs, as compared with the usual observational studies and randomized trials. These include participation, the number of allowed randomizations per participant, compliance/adherence, power, false-negatives, false-positives, composite lifestyle effects, selection of outcomes, follow-up and monitoring, masking and allocation concealment, age of participants, confounding, and cost. The aim should be to combine carefully the strengths of both observational epidemiology and randomized research without compounding their limitations.     

Mendelian randomization: using genes as instruments for making causal inferences in epidemiology

Observational epidemiological studies suffer from many potential biases, from confounding and from reverse causation, and this limits their ability to robustly identify causal associations. Several high-profile situations exist in which randomized controlled trials of precisely the same intervention that has been examined in observational studies have produced markedly different findings. In other observational sciences, the use of instrumental variable (IV) approaches has been one approach to strengthening causal inferences in non-experimental situations. The use of germline genetic variants that proxy for environmentally modifiable exposures as instruments for these exposures is one form of IV analysis that can be implemented within observational epidemiological studies. The method has been referred to as 'Mendelian randomization', and can be considered as analogous to randomized controlled trials. This paper outlines Mendelian randomization, draws parallels with IV methods, provides examples of implementation of the approach and discusses limitations of the approach and some methods for dealing with these.     

The reverse propensity score to detect selection bias and correct for baseline imbalances

The propensity score has been proposed, and for the most part accepted, as a tool to allow for the evaluation of medical interventions in the presence of baseline imbalances arising in the context of observational studies. The lack of an analogous tool to allow for the evaluation of medical interventions in the presence of potentially systematic baseline imbalances in randomized trials has required the use of ad hoc methods. This, in turn, leads to challenges to the conclusions. For example, much of the controversy surrounding recommendations for or against mammography for some age groups stems from the fact that all the randomized trials to study mammography had baseline imbalances, to some extent, in important prognostic covariates. While some of these trials used cluster randomization, baseline imbalances are prevalent also in individually randomized trials. We provide a systematic approach for evaluating medical interventions in the presence of potentially systematic baseline imbalances in individually randomized trials with allocation concealment. Specifically, we define the reverse propensity score as the probability, conditional on all previous allocations and the allocation procedure (restrictions on the randomization), that a given patient will receive a given treatment. We demonstrate how the reverse propensity score allows for both detection of and correction for selection bias, or systematic baseline imbalances.     

Limits to causal inference based on Mendelian randomization: a comparison with randomized controlled trials

"Mendelian randomization" refers to the random assortment of genes transferred from parent to offspring at the time of gamete formation. This process has been compared to a randomized controlled trial of genetic variants. This could greatly aid observational epidemiology by potentially allowing an unbiased estimate of the effects of gene products on disease outcomes. However, studies utilizing Mendelian randomization to estimate effects of gene products on outcomes should be interpreted with caution. In this paper, the authors discuss some of the challenges facing epidemiologists in the analysis and interpretation of Mendelian randomization studies, particularly those that become apparent when the analogy with randomized controlled trials is closely examined. The authors conclude that Mendelian randomization is a powerful addition to etiologic research tools. However, care must be taken, because drawing valid causal inferences from its application depends upon more extensive assumptions than are required in randomized controlled trials.     

Randomized trials versus observational studies in adolescent pregnancy prevention

The objective of this study is to compare the results of randomized trials and observational studies of interventions to prevent adolescent pregnancy. We identified published and unpublished reports through computerized searches of CATLINE, CINAHL, CONFERENCE PAPERS INDEX, DISSERTATION ABSTRACTS ONLINE, EMBASE, ERIC, MEDLINE, NTIS, POPLINE, PsycINFO, and SOCIOLOGICAL ABSTRACTS; manual searches of eight relevant journals; reference lists from primary articles; and contact with content experts. We included randomized trials and observational studies that evaluated the impact of primary prevention interventions including sex education classes, school-based clinics, free-standing clinics, physician/nurse practitioner practice-based service, improved access, and community-based programs on four outcomes: sexual intercourse, birth control use, responsible sexual behavior, or pregnancy in adolescents. One investigator abstracted the data and a second conducted a detailed review of the abstraction. We identified 13 randomized trials and 17 observational studies. We generated estimates of the impact of the interventions separately for males and females for all four outcomes for both observational studies and randomized trials. For six of the eight outcomes the summary odds ratios for the observational studies showed a significant intervention benefit (P<0.05) while the randomized trials did not show a benefit for any outcome in either females or males. The difference between the results of the observational studies and randomized trials was statistically significant in two of the eight outcomes (P<0.05 for initiation of intercourse and pregnancy in females). Observational studies yield systematically greater estimates of treatment effects than randomized trials of adolescent pregnancy prevention interventions. Public policy or individual patient treatment decisions should be based on observational studies only when randomized trials are unavailable and only with careful consideration of possible biases.     

Context by treatment interactions as the primary object of study in cluster randomized controlled trials of population health interventions

Cluster randomized controlled trials are increasingly used in population health intervention research. Through randomization, researchers attempt to isolate the treatment effect and remove all other effects, including any effects of social context. In many cases, the constant effect assumption cannot be satisfied in cluster randomized controlled trials. We argue that when studying population health interventions, the effective mechanism of intervention lies in the interaction between the treatment and social context. Researchers should be cognizant that attempts to remove the effect of social context using CRTC may fail. The interaction between the treatment and social context should be the primary object of study in population health intervention research.     

Support in pregnancy.

Both observational studies and nonrandomized controlled trials have found the presence of support during pregnancy to be associated with superior outcomes in terms of preventing abortion, extending the length of gestation, and reducing interventions in labor. However, randomized controlled trials of supportive interventions in pregnancy have not demonstrated any physical benefits from the interventions. It is also unlikely there are any significant adverse effects. Psychological benefits do appear to result from supportive interventions, including better enjoyment of the pregnancy and better postnatal status.