Donepezil for the symptomatic treatment of patients with mild to moderate Alzheimer's disease: a meta-analysis of individual patient data from randomised controlled trials

Background: The objective was to evaluate the efficacy and tolerability of donepezil (5 and 10 mg/day) compared with placebo in alleviating manifestations of mild to moderate Alzheimer's disease (AD). Method: A systematic review of individual patient data from Phase II and III double-blind, randomised, placebo-controlled studies of up to 24 weeks and completed by 20 December 1999. The main outcome measures were the ADAS-cog, the CIBIC-plus, and reports of adverse events. Results: A total of 2376 patients from ten trials were randomised to either donepezil 5 mg/day (n = 821), 10 mg/day (n = 662) or placebo (n = 893). Cognitive performance was better in patients receiving donepezil than in patients receiving placebo. At 12 weeks the differences in ADAS-cog scores were 5 mg/day-placebo: - 2.1 [95% confidence interval (CI), - 2.6 to - 1.6; p < 0.001], 10 mg/day-placebo: - 2.5 ( - 3.1 to - 2.0; p < 0.001). The corresponding results at 24 weeks were - 2.0 ( - 2.7 to - 1.3; p < 0.001) and - 3.1 ( - 3.9 to - 2.4; p < 0.001). The difference between the 5 and 10 mg/day doses was significant at 24 weeks (p = 0.005). The odds ratios (OR) of improvement on the CIBIC-plus at 12 weeks were: 5 mg/day-placebo 1.8 (1.5 to 2.1; p < 0.001), 10 mg/day-placebo 1.9 (1.5 to 2.4; p < 0.001). The corresponding values at 24 weeks were 1.9 (1.5 to 2.4; p = 0.001) and 2.1 (1.6 to 2.8; p < 0.001). Donepezil was well tolerated; adverse events were cholinergic in nature and generally of mild severity and brief in duration. Conclusion: Donepezil (5 and 10 mg/day) provides meaningful benefits in alleviating deficits in cognitive and clinician-rated global function in AD patients relative to placebo. Increased improvements in cognition were indicated for the higher dose. Copyright © 2004 John Wiley & Sons, Ltd.

Meta-analysis of individual patient data from randomised trials: a review of methods used in practice

Background: Meta-analyses based on individual patient data (IPD) are regarded as the gold standard for systematic reviews. However, the methods used for analysing and presenting results from IPD meta-analyses have received little discussion. Methods We review 44 IPD meta-analyses published during the years 1999–2001. We summarize whether they obtained all the data they sought, what types of approaches were used in the analysis, including assumptions of common or random effects, and how they examined the effects of covariates. Results: Twenty-four out of 44 analyses focused on time-to-event outcomes, and most analyses (28) estimated treatment effects within each trial and then combined the results assuming a common treatment effect across trials. Three analyses failed to stratify by trial, analysing the data is if they came from a single mega-trial. Only nine analyses used random effects methods. Covariate-treatment interactions were generally investigated by subgrouping patients. Seven of the meta-analyses included data from less than 80% of the randomized patients sought, but did not address the resulting potential biases. Conclusions: Although IPD meta-analyses have many advantages in assessing the effects of health care, there are several aspects that could be further developed to make fuller use of the potential of these time-consuming projects. In particular, IPD could be used to more fully investigate the influence of covariates on heterogeneity of treatment effects, both within and between trials. The impact of heterogeneity, or use of random effects, are seldom discussed. There is thus considerable scope for enhancing the methods of analysis and presentation of IPD meta-analysis.

A score test for binary data with patient non-compliance

A score test is developed for binary clinical trial data, which incorporates patient non-compliance while respecting randomization. It is assumed in this paper that compliance is all-or-nothing, in the sense that a patient either accepts all of the treatment assigned as specified in the protocol, or none of it. Direct analytic comparisons of the adjusted test statistic for both the score test and the likelihood ratio test are made with the corresponding test statistics that adhere to the intention-to-treat principle. It is shown that no gain in power is possible over the intention-to-treat analysis, by adjusting for patient non-compliance. Sample size formulae are derived and simulation studies are used to demonstrate that the sample size approximation holds. Copyright © 2003 John Wiley & Sons, Ltd.

Effects of divided attention and speeded responding on implicit and explicit retrieval of artificial grammar knowledge

The artificial grammar (AG) learning literature (see, e.g., Mathews et al., 1989; Reber, 1967) has relied heavily on a single measure of implicitly acquired knowledge. Recent work comparing this measure (string classification) with a more indirect measure in which participants make liking ratings of novel stimuli (e.g., Manza & Bornstein, 1995; Newell & Bright, 2001) has shown that string classification (which we argue can be thought of as an explicit, rather than an implicit, measure of memory) gives rise to more explicit knowledge of the grammatical structure in learning strings and is more resilient to changes in surface features and processing between encoding and retrieval. We report data from two experiments that extend these findings. In Experiment 1, we showed that a divided attention manipulation (at retrieval) interfered with explicit retrieval of AG knowledge but did not interfere with implicit retrieval. In Experiment 2, we showed that forcing participants to respond within a very tight deadline resulted in the same asymmetric interference pattern between the tasks. In both experiments, we also showed that the type of information being retrieved influenced whether interference was observed. The results are discussed in terms of the relatively automatic nature of implicit retrieval and also with respect to the differences between analytic and nonanalytic processing (Whittlesea Price, 2001).

Verb retrieval in fluent aphasia: a clinical study

Background: Problems with lexical retrieval are common across all types of aphasia but certain word classes are thought to be more vulnerable in some aphasia types. Traditionally, verb retrieval problems have been considered characteristic of non-fluent aphasias but there is growing evidence that verb retrieval problems are also found in fluent aphasia. As verbs are retrieved from the mental lexicon with syntactic as well as phonological and semantic information, it is speculated that an improvement in verb retrieval should enhance communicative abilities in this population as in others. We report on an investigation into the effectiveness of verb treatment for three individuals with fluent aphasia. Methods & Procedures: Multiple pre-treatment baselines were established over 3 months in order to monitor language change before treatment. The three participants then received twice-weekly verb treatment over approximately 4 months. All pre-treatment assessments were administered immediately after treatment and 3 months post-treatment. Outcome & Results: Scores fluctuated in the pre-treatment period. Following treatment, there was a significant improvement in verb retrieval for two of the three participants on the treated items. The increase in scores for the third participant was statistically nonsignificant but post-treatment scores moved from below the normal range to within the normal range. All participants were significantly quicker in the verb retrieval task following treatment. There was an increase in well-formed sentences in the sentence construction test and in some samples of connected speech. Conclusions: Repeated systematic treatment can produce a significant improvement in verb retrieval of practised items and generalise to unpractised items for some participants. An increase in well-formed sentences is seen for some speakers. The theoretical and clinical implications of the results are discussed.

Dissociating word stem completion and cued recall as a function of divided attention at retrieval

The aim of this study was to investigate the widely held, but largely untested, view that implicit memory (repetition priming) reflects an automatic form of retrieval. Specifically, in Experiment 1 we explored whether a secondary task (syllable monitoring), performed during retrieval, would disrupt performance on explicit (cued recall) and implicit (stem completion) memory tasks equally. Surprisingly, despite substantial memory and secondary costs to cued recall when performed with a syllable-monitoring task, the same manipulation had no effect on stem completion priming or on secondary task performance. In Experiment 2 we demonstrated that even when using a particularly demanding version of the stem completion task that incurred secondary task costs, the corresponding disruption to implicit memory performance was minimal. Collectively, the results are consistent with the view that implicit memory retrieval requires little or no processing capacity and is not seemingly susceptible to the effects of dividing attention at retrieval.

The benefits of providing benefit information in a patient information leaflet

Objective: To examine the effects of providing two different types of written information about medicine benefits in a patient information leaflet (PIL). Setting: Participants were 358 adult volunteers from the general population recruited from a London railway station and central Reading. Method: The study used a controlled empirical methodology in which people were given a hypothetical, but realistic, scenario about visiting their doctor and being prescribed medication. They then read an information leaflet about the medicine that contained neither, one, or both benefit statements, and finally completed a number of Likert rating scales. Outcome measures included perceived satisfaction and helpfulness of the information, effectiveness and appropriateness of the medicine, benefit and risk to health, and intention to comply. Key findings: Both types of benefit information led to significantly higher ratings on all of the measures taken. Conclusions: Provision of a relatively short ‘benefit’ statement can significantly improve people’s judgements and intention to take a medicine. The findings are important and timely as the European Union is currently considering reviewing their regulations to allow for the inclusion of limited non-promotional benefit information in PILs.

Semi-automatic annotation and retrieval of visual content using the topic map technology

There are still major challenges in the area of automatic indexing and retrieval of multimedia content data for very large multimedia content corpora. Current indexing and retrieval applications still use keywords to index multimedia content and those keywords usually do not provide any knowledge about the semantic content of the data. With the increasing amount of multimedia content, it is inefficient to continue with this approach. In this paper, we describe the project DREAM, which addresses such challenges by proposing a new framework for semi-automatic annotation and retrieval of multimedia based on the semantic content. The framework uses the Topic Map Technology, as a tool to model the knowledge automatically extracted from the multimedia content using an Automatic Labelling Engine. We describe how we acquire knowledge from the content and represent this knowledge using the support of NLP to automatically generate Topic Maps. The framework is described in the context of film post-production.

The DREAM Framework: using a network of scalable ontologies for intelligent indexing and retrieval of visual content

There are still major challenges in the area of automatic indexing and retrieval of digital data. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. Research has been ongoing for a few years in the field of ontological engineering with the aim of using ontologies to add knowledge to information. In this paper we describe the architecture of a system designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval.

Health informatics: improving patient-centred healthcare pathway

Nowadays the use of information and communication technology is becoming prevalent in many aspects of healthcare services from patient registration, to consultation, treatment and pathology tests request. Manual interface techniques have dominated data-capture activities in primary care and secondary care settings for decades. Despites the improvements made in IT, usability issues still remain over the use of I/O devices like the computer keyboard, touch-sensitive screens, light pen and barcodes. Furthermore, clinicians have to use several computer applications when providing healthcare services to patients. One of the problems faced by medical professionals is the lack of data integrity between the different software applications which in turn can hinder the provision of healthcare services tailored to the needs of the patients. The use of digital pen and paper technology integrated with legacy medical systems hold the promise of improving healthcare quality. This paper discusses the issue of data integrity in e-health systems and proposes the modelling of "Smart Forms" via semiotics to potentially improve integrity between legacy systems, making the work of medical professionals easier and improve the quality of care in primary care practices and hospitals.

Semantic-driven context-aware visual information indexing and retrieval: applied in the film post-production domain

A large volume of visual content is inaccessible until effective and efficient indexing and retrieval of such data is achieved. In this paper, we introduce the DREAM system, which is a knowledge-assisted semantic-driven context-aware visual information retrieval system applied in the film post production domain. We mainly focus on the automatic labelling and topic map related aspects of the framework. The use of the context- related collateral knowledge, represented by a novel probabilistic based visual keyword co-occurrence matrix, had been proven effective via the experiments conducted during system evaluation. The automatically generated semantic labels were fed into the Topic Map Engine which can automatically construct ontological networks using Topic Maps technology, which dramatically enhances the indexing and retrieval performance of the system towards an even higher semantic level.