The contribution of observational studies to the knowledge of drug effectiveness in heart failure

AIMS: Randomized controlled trials (RCTs) are the golden standard for the assessment of drug efficacy. Little is known about the add-on value of observational studies in heart failure (HF). We aimed to assess the contribution of observational studies to actual knowledge regarding the effectiveness of angiotensin-converting enzyme inhibitors (ACEI), and beta-blockers (BB) in HF. METHODS: Observational studies that assessed the effectiveness of ACEI and BB in HF were identified by searching Medline, Embase, Cochrane Database (1990-2005) and the bibliographies of published articles. Cohort, case-control and time-series analysis studies were considered for inclusion. Studies with <100 patients and those who did not perform a multivariate analysis were excluded. RESULTS: A total of 23 cohort studies met the inclusion criteria. Studies of ACEI and BB showed a decrease in mortality with drug use in elderly patients with a broad range of ejection fraction (EF), and in those with depressed EF. Additionally, they showed a decrease in mortality in patients with renal insufficiency. The effect of ACEI and BB in HF with preserved EF was not clear, although last evidence suggests a potential benefit. Low-dose ACEI and BB may have beneficial effects. Target doses of ACEI seemed superior to low doses, but there was no clear dose-response relationship. CONCLUSIONS: Observational studies in HF validate the effectiveness of ACEI and BB in populations underrepresented or excluded from RCTs. Observational studies of drug effectiveness provide relevant additional information for clinical practice.     

Approaches to combat with confounding by indication in observational studies of intended drug effects

There has been a resurgence of controversy about the usefulness of observational data to study the efficacy of drugs. Nearly every week a researcher makes some criticism of clinical trials or justifies observational research into intended effects, with other researchers offering a contradictory viewpoint. Literature reviews are not useful in this regard because the contradictory studies will not usually be carried out. Some methods are discussed which may have potential utility in the study of intended effects. There may be a marginal role for statistical techniques such as propensity scores and confounder scores. More promising techniques may include ecological analyses, restriction of subjects and blinded prospective review. Because it is currently unknown when the observational study of drug efficacy is possible, we should arguably always carry out a study of the determinants of prescribing first, and possibly consider using the various techniques that are outlined in this article.     

An analysis of the exclusion criteria used in observational pharmacoepidemiological studies

PURPOSE: The application of exclusion criteria in pharmacoepidemiological studies could have a major impact on the findings but there appears to have been no previous research to examine the types of exclusion criteria applied. METHODS: We searched the literature and identified 10 senior pharmacoepidemiologists who had published five or more relevant papers between 1999 and 2004. All their published drug safety studies during this period were reviewed. A classification system was developed to categorise the exclusion criteria, with 5 categories and 11 sub-categories. The categories were: (1) data quality and validation, (2) disease-related, (3) exposure-related, (4) patient characteristics and (5) miscellaneous reasons. Within each sub-category, only the first exclusion criterion identified for that study was counted. RESULTS: We identified 200 studies, from which a total of 752 exclusion criteria sub-categories had been applied (mean 3.8 per study; between-author range of means 2.8-5.1). At the category level, exclusion criteria relating to data quality and validation were the most commonly applied (87% of publications), followed by patient characteristics (75%), disease-related (69%), exposure-related (38%) and miscellaneous (3%). The main categories for which research practice appeared to differ were those relating to diseases and exposures. The application of sub-category 'risk factors and alternative causes' varied between authors from 0% to 81% of studies, and for the sub-category 'medication of interest' it varied from 5% to 93%. CONCLUSIONS: There are important differences between investigators in the application of exclusion criteria in pharmacoepidemiological studies. It is likely that a substantial part of the observed variation reflects different research practices of investigators.     

An algorithm for the design of epidemiologic studies applied to drug surveillance

Spontaneous reporting of adverse drug reactions (ADRs), although commonly used, is of limited efficacy for the establishment of causation, and must be complemented by more rigorous epidemiologic studies. This article presents a decision algorithm that could be used as a tool in the selection of the most appropriate study design to investigate the causal relationship between a given ADR and a drug. It is based on the incidence of the ADR, on the objective of the study – determination of all the adverse effects of a given drug, or all the drugs increasing the risk of occurrence of a given adverse event – and on the funds available to the researcher.     

The relationship between time since registration and measured incidence rates in the General Practice Research Database

BACKGROUND: The General Practice Research Database (GPRD) is widely used to study incidence rates. This study examines whether incidence rates are overestimated during the first year after registration, how long one needs to wait to obtain accurate incidence rates, and whether the time period of overestimation differs among disease types. METHODS: We measured incidence rates of nine acute, eight chronic, and eight neoplastic outcomes in 3-month intervals through month 36 after enrollment in GPRD. The incidence rates in months 13-36 were used to estimate baseline incidence rates for each diagnosis. RESULTS: For patients registering with practices that were already UTS, incidence rates were highest in the first 3 months after registration. In eight of nine acute diagnoses, the incidence rate was within 20% of baseline by months 4-6; and in seven of eight cancers, the incidence rate was within 20% of baseline by months 7-9. For chronic conditions, the incidence rate in months 10-12 differed from baseline by more than 20% for five of the eight outcomes, respectively. For patients registering prior to UTS, incidence rates during the first quarter were within 20% of baseline for all acute and cancer diagnoses and six of eight chronic diagnoses. CONCLUSIONS: Reported incidence rates are highest in the first 3 months after registration with an UTS practice and decline to baseline over the first year, more quickly for acute conditions than chronic conditions. For patients who registered prior to UTS, incidence rates are near the baseline level at the start of follow-up.     

Structural accelerated failure time models for survival analysis in studies with time-varying treatments

BACKGROUND: In the absence of unmeasured confounding factors and model misspecification, standard methods for estimating the causal effect of time-varying treatments on survival are biased when (i) there exists a time-dependent risk factor for survival that also predicts subsequent treatment and (ii) past treatment history predicts subsequent risk factor level. In contrast, structural models provide consistent estimates of causal effects when unmeasured confounding and model misspecification are absent. The parameters of nested structural models are estimated by g-estimation and those of marginal structural models by inverse probability weighting. METHODS: We describe a nested structural accelerated failure time model and use it to estimate the total causal effect of highly active antiretroviral therapy (HAART) on the time to AIDS or death among human immunodeficiency virus (HIV)-infected participants of the Multicenter AIDS Cohort and Women's Interagency HIV Studies. The Appendix describes g-estimation and methods to deal with censoring. RESULTS: Comparing the regime 'always treated' to 'never treated,' the AIDS-free survival time ratio was 2.5 (95% confidence interval [CI]: 1.7, 3.3). CONCLUSIONS: Our finding of a strongly beneficial effect is consistent with results from randomized trials and from a previous analysis of the same data using a marginal structural Cox model. In contrast, a previous analysis using a standard (non-structural) model did not find an effect of treatment on survival.     

Company observational post-marketing studies: drug risk assessment and drug research in special populations – a study-based analysis

Objectives: Company observational post-marketing studies (COPS) claim to provide essential data about drug risks and effectiveness in special populations not admitted to pre-approval clinical trials. Since COPS are often mainly regarded as a marketing activity, this study-based analysis tries to evaluate the scientific contributions of COPS. Material and methods: Thirty-five COPS were identified by hand-searching through medical journals, writing to pharmaceutical manufacturers and using MEDLINE. Fourteen COPS evaluated cardiovascular drugs, 9 evaluated NSAIDs and 12 evaluated various other indications. Results: Thirty-five COPS listed effectiveness, 31 listed safety and 8 listed patient compliance as principal objectives. Not a single COPS included a control group. Seventeen of 21 evaluable COPS mentioned extensive exclusion criteria similar to those in clinical trials. Median observation time was 8 weeks, too short for chronic diseases and for adverse drug reactions with longer latency periods. One new adverse event was regarded. Global assessments of the outcomes by physicians dominated and were not based on objective clinical findings. None of the studies specified any details concerning the standardisation of observations or quality-control procedures. Discussion and conclusion: The current COPS scheme does not contribute significantly to our knowledge of drug safety and the effects in special populations. Despite serious criticism over the past 20 years, the poor quality of COPS – compared with dramatic improvements of pre-approval trials – implies a need for detailed guidelines for non-experimental phase IV research, similar to the Good Clinical Practice-Guideline of the European Community. Received: 13 June 1997 / Accepted in revised form: 4 August 1997     

Confounding in longitudinal studies in addiction treatment research

Background: The effectiveness of treatment for people with substance use disorders is usually examined using longitudinal cohorts. In these studies, treatment is often considered as a time-varying exposure. The aim of this commentary is to examine confounding in this context, when the confounding variable is time-invariant and when it is time-varying.

Method: Types of confounding are described with examples and illustrated using path diagrams. Simulations are used to demonstrate the direction of confounding bias and the extent that it is accounted for using standard regression adjustment techniques.

Results: When the confounding variable is time invariant or time varying and not influenced by prior treatment, then standard adjustment techniques are adequate to control for confounding bias, provided that in the latter scenario the time-varying form of the variable is used. When the confounder is time varying and affected by prior treatment status (i.e. it is a mediator of treatment), then standard methods of adjustment result in inconsistency.

Conclusions: In longitudinal cohorts where treatment exposure is time varying, confounding is an issue which should be considered, even if treatment exposure is initially randomized. In these studies, standard methods of adjustment may result be inadequate, even when all confounders have been identified. This occurs when the confounder is also a mediator of treatment. This is a likely scenario in many studies in addiction.     

The economic burden of preventable adverse drug reactions: a systematic review of observational studies

Introduction: Adverse drug reactions (ADRs) are an important cause of morbidity and mortality worldwide. They are associated with healthcare costs due to hospital admissions or prolonged length of stay, as well as additional interventions. The aim of this study was to conduct a systematic review of observational studies to evaluate the economic impact of preventable ADRs.

Areas covered: Published observational research investigating the cost of preventable ADRs in Western countries (limited to the USA and European countries).

Expert opinion: Several reviews have been carried out in the field of the ADR epidemiology but fewer reviews have investigated the economic impact of ADRs, and at the time of writing, none has focused on preventable ADRs. The reason why future research should focus on the costs of preventable ADRs is that both the costs and the negative clinical outcomes are preventable, and as such, are a key point of public health policy action. Nevertheless, the present review highlights an important and sobering limitation of published research on the cost of preventable ADRs, of which the major limitation is the heterogeneity in methods and in reporting which limit what can be known through the summarizing work of a systematic review.     

试论在我国开展药物流行病学研究的必要性

本文从药物的重要性、有效性及开展药物不良反应监察工作等方面，论述了在我国开展药物流行病学研究的重要性和必要性。