In systematic reviews, meta‐analyses are routinely applied to summarize the results of the relevant studies for a specific research question. If one can assume that in all studies the same true effect is estimated, the application of a meta‐analysis with common effect (commonly referred to as fixed‐effect meta‐analysis) is adequate. If between‐study heterogeneity is expected to be present, the method of choice is a meta‐analysis with random effects. The widely used DerSimonian and Laird method for meta‐analyses with random effects has been criticized due to its unfavorable statistical properties, especially in the case of very few studies. A working group of the Cochrane Collaboration recommended the use of the Knapp‐Hartung method for meta‐analyses with random effects. However, as heterogeneity cannot be reliably estimated if only very few studies are available, the Knapp‐Hartung method, while correctly accounting for the corresponding uncertainty, has very low power. Our aim is to summarize possible methods to perform meaningful evidence syntheses in the situation with only very few (ie, 2‐4) studies. Some general recommendations are provided on which method should be used when. Our recommendations are based on the existing literature on methods for meta‐analysis with very few studies and consensus of the authors. The recommendations are illustrated by 2 examples coming from dossier assessments of the Institute for Quality and Efficiency in Health Care.

Phantom limb pain (PLP) associated neuroplastic changes are partly mediated by excitatory amino acids at NMDA receptor sites. This study was undertaken to deduce if NMDA-receptor antagonists may be effective in patients with chronic PLP. Therefore a four week double-blinded, randomized placebo-controlled trial was performed to evaluate the efficacy of 30 mg memantine/day, an orally administrable NMDA receptor antagonist.Thirty-six patients, 18 per group, with a history of at least 12 months PLP and an average pain of at least 4 on the 11-point numeric rating scale (NRS) were enrolled. The patients completed a standardized questionnaire before the trial. PLP intensity and the level of eight complaints were assessed during the trial. Number needed to treat (NNT) was calculated based on the average PLP during the 3rd week (steady state). In both groups, PLP declined significantly in comparison with the baseline (verum: 5.1 (+/-2.1) to 3,8 (+/-2,3), placebo from 5.1 (+/-2.0) to 3.2 (+/-1,46) NRS) without a re-rising of the PLP during the washout period. Mean pain relief was 47% in the memantine group (10 patients reported more than 50% relief), 40% in the placebo group (6>50%): NNT were 4.5 (KI: 2.1-10.6). Analysis of covariance demonstrated a significant impact only on the prior PLP intensity, but no treatment effect. Two patients have demonstrated long-term pain relief under memantine until now (16 months). The total number of slight adverse events were comparable in both groups, but the overall number of severe events was higher in the memantine group (P<0.05). This trial failed to demonstrate a significant clinical benefit of the NMDA-receptor antagonist memantine in chronic PLP. The administration of a higher dosage is probably not tolerable.

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The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit‐risk ratio. The statistical analysis of AEs is complicated by the fact that the follow‐up times can vary between the patients included in a clinical trial. This paper takes as its focus the analysis of AE data in the presence of varying follow‐up times within the benefit assessment of therapeutic interventions. Instead of approaching this issue directly and solely from an analysis point of view, we first discuss what should be estimated in the context of safety data, leading to the concept of estimands. Although the current discussion on estimands is mainly related to efficacy evaluation, the concept is applicable to safety endpoints as well. Within the framework of estimands, we present statistical methods for analysing AEs with the focus being on the time to the occurrence of the first AE of a specific type. We give recommendations which estimators should be used for the estimands described. Furthermore, we state practical implications of the analysis of AEs in clinical trials and give an overview of examples across different indications. We also provide a review of current practices of health technology assessment (HTA) agencies with respect to the evaluation of safety data. Finally, we describe problems with meta‐analyses of AE data and sketch possible solutions.

This systematic review determines the benefit of treatment with Ginkgo biloba (Ginkgo) in Alzheimer's disease (AD) concerning patient-relevant outcomes. Bibliographic databases, clinical trial and study result registries were searched for randomized controlled trials (RCTs) in patients with AD (follow-up ≥16 weeks) comparing Ginkgo to placebo or a different treatment option. Manufacturers were asked to provide unpublished data. If feasible, data were pooled by meta-analysis. Six studies were eligible; overall, high heterogeneity was shown for most outcomes, except safety aspects. Among studies administering high-dose Ginkgo (240 mg), all studies favour treatment though effects remain heterogeneous. In this subgroup, a benefit of Ginkgo exists for activities of daily living. Cognition and accompanying psychopathological symptoms show an indication of a benefit. A harm of Ginkgo is not evident. An estimation of the effect size was not possible for any outcome. Further evidence is needed which focuses especially on subgroups of AD patients.