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Publication History View all

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    ABSTRACT: To develop prognostic models for time to 12-month remission and time to treatment failure after initiating antiepileptic drug monotherapy for generalised and unclassified epilepsy. We analysed data from the Standard and New Antiepileptic Drug (arm B) study, a randomised trial that compared initiating treatment with lamotrigine, topiramate and valproate in patients diagnosed with generalised or unclassified epilepsy. Multivariable regression modelling was used to investigate how clinical factors affect the probability of achieving 12-month remission and treatment failure. Significant factors in the multivariable model for time to 12-month remission were having a relative with epilepsy, neurological insult, total number of tonic-clonic seizures before randomisation, seizure type and treatment. Significant factors in the multivariable model for time to treatment failure were treatment history (antiepileptic drug treatment prior to randomisation), EEG result, seizure type and treatment. The models described within this paper can be used to identify patients most likely to achieve 12-month remission and most likely to have treatment failure, aiding individual patient risk stratification and the design and analysis of future epilepsy trials.
    Journal of neurology, neurosurgery, and psychiatry 11/2013;
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    ABSTRACT: Outcome data from dental caries clinical trials have a naturally hierarchical structure, with surfaces clustered within teeth, clustered within individuals. Data are often aggregated into the DMF index for each individual, losing tooth- and surface-specific information. If these data are to be analysed by tooth or surface, allowing exploration of effects of interventions on different teeth and surfaces, appropriate methods must be used to adjust for the clustered nature of the data. Multilevel modelling allows analysis of clustered data using individual observations without aggregating data, and has been little used in the field of dental caries. A simulation study was conducted to investigate the performance of multilevel modelling methods and standard caries increment analysis. Data sets were simulated from a three-level binomial distribution based on analysis of a caries clinical trial in Scottish adolescents, with varying sample sizes, treatment effects and random tooth level effects based on trials reported in Cochrane reviews of topical fluoride, and analysed to compare the power of multilevel models and traditional analysis. 40,500 data sets were simulated. Analysis showed that estimated power for the traditional caries increment method was similar to that for multilevel modelling, with more variation in smaller data sets. Multilevel modelling may not allow significant reductions in the number of participants required in a caries clinical trial, compared to the use of traditional analyses, but investigators interested in exploring the effect of their intervention in more detail may wish to consider the application of multilevel modelling to their clinical trial data. © 2013 S. Karger AG, Basel.
    Caries Research 11/2013; 48(1):13-18.
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    ABSTRACT: To determine the standard of reporting of harms-related data, in randomised controlled trials (RCTs) according to the Consolidated Standards of Reporting Trials (CONSORT) statement extension for harms. Systematic review. The Cochrane library, Ovid MEDLINE, Scopus and ISI Web of Knowledge were searched for relevant literature. We included publications of studies that used the CONSORT harms extension to assess the reporting of harms in RCTs. We identified 7 studies which included between 10 and 205 RCTs. The clinical areas of the 7 studies were: hypertension (1), urology (1), epilepsy (1), complimentary medicine (2) and two not restricted to a clinical topic. Quality of the 7 studies was assessed by a risk of bias tool and was found to be variable. Adherence to the CONSORT harms criteria reported in the 7 studies was inadequate and variable across the items in the checklist. Adverse events are poorly defined, with 6 studies failing to exceed 50% adherence to the items in the checklist. Readers of RCT publications need to be able to balance the trade-offs between benefits and harms of interventions. This systematic review suggests that this is compromised due to poor reporting of harms which is evident across a range of clinical areas. Improvements in quality could be achieved by wider adoption of the CONSORT harms criteria by journals reporting RCTs.
    BMJ Open 01/2013; 3(9):e003436.
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    ABSTRACT: Many randomised trials in surgery suffer from recruitment rates that lag behind projected targets. We aim to identify perceived barriers to recruitment among these pioneering trials in the field of head and neck cancer surgery. Recruiting centres to all three trials (Selective Elective Neck Dissection (SEND), Positron Emission Tomography (PET)-Neck and Hyperbaric Oxygen in the Prevention of Osteoradionecrosis (HOPON)) were contacted by email by the chief investigators. Responders were asked to complete a web-based survey in order to identify the barriers to recruitment in their centre and grade each by severity. Secondary care: 44 head and neck oncology regional referral centres. Analysis was based on 85 responses evenly distributed between the three trials. The most commonly identified perceived barriers to recruitment (more than 50% of responders identified the item as a barrier in all the three trials) in the order of frequency were: patients consent refusal because of expressed treatment preference, patients consent refusal owing to aversion to randomisation, excess complexity/amount of information provided to patients and lack of time in clinic to accommodate research. The most severely rated of these problems was consent refusal because of the expressed treatment preference and lack of time in the clinic. Our findings confirm others' work in surgery that the most significant barrier to trial recruitment in head and neck cancer surgery is the patient's preference for one arm of the trial. It may be that additional training for those taking consent may be helpful in this regard. It is also important to adequately resource busy surgical clinics to support clinical trial recruitment.
    BMJ Open 01/2013; 3(4).
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    ABSTRACT: Aim: Although several genetic and nongenetic factors are associated with warfarin dose, approximately 40% of variability remains unexplained. An as yet unexplored factor is medication adherence. Here, we investigate the influence of adherence on response to warfarin and on pharmacogenetic analyses of association. Patients & methods: A total of 311 patients starting warfarin were followed-up prospectively, and adherence was measured at 1, 8 and 26 weeks. The association between adherence and warfarin response was tested, and the additional proportion of variability in response explained by adherence was assessed. Results: Significant associations were found between adherence and achievement of stable dose and time taken to achieve it, with nonadherers taking longer. Adjusting for adherence increased the proportion of explained variability in treatment response by up to 8%. Conclusion: Given the significant contribution of adherence to drug response, we recommend that consideration is given to the value of assessing adherence when designing future pharmacogenetic studies of warfarin and other drugs. Original submitted 19 July 2012; Revision submitted 26 November 2012.
    Pharmacogenomics 01/2013; 14(2):151-163.
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    ABSTRACT: Outcome reporting bias (ORB) in randomised trials has been identified as a threat to the validity of systematic reviews. Previous work highlighting this problem is limited to considering a single primary review outcome. The aim of this study was to assess ORB across all efficacy outcomes in the Cochrane systematic reviews of cystic fibrosis. Systematic reviews of interventions for cystic fibrosis published on the Cochrane Library by the Cochrane Cystic Fibrosis and Genetic Disorders Group before 2010 were assessed for discrepancies in outcomes between review protocol and full review. ORB in eligible trials was also assessed for all efficacy review outcomes. Two authors independently classified each outcome using a nine-point classification system developed by the Outcome Reporting Bias In Trials study. These classifications were used to inform the assessment of the risk of bias for selective outcome reporting for each trial. -46 Cochrane cystic fibrosis systematic reviews were included. The median number of primary outcomes, number of trials and participants per trial in the reviews were 3 (IQR 2, 3), 4 (IQR 2, 8) and 21 (IQR 14, 41), respectively. 18 reviews (39%, 18/46) had a discrepancy in outcomes between protocol and full review. 37 reviews were eligible to be included in the ORB assessment. When considering review primary outcomes and all review outcomes, ORB was suspected in at least one trial in 86% and 100%, respectively. Assessment of ORB within a systematic review of a single primary outcome underestimates the risk of ORB in comparison to the assessment of multiple primary and secondary outcomes. ORB in trials is highly prevalent within systematic reviews of cystic fibrosis when assessed across all outcomes. This could be reduced by the development of a core outcome set for trials and systematic reviews in cystic fibrosis.
    BMJ Open 01/2013; 3(6).
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    ABSTRACT: This is an updated version of the original Cochrane review published in The Cochrane Library 2001, Issue 4.Worldwide, particularly in the developing world, phenytoin and phenobarbitone are commonly used antiepileptic drugs, primarily because they are inexpensive. The aim of this review is to summarise data from existing trials comparing phenytoin and phenobarbitone. To review the best evidence comparing phenobarbitone and phenytoin when used as monotherapy in participants with partial onset seizures or generalised tonic-clonic seizures with or without other generalised seizure types. We searched the Cochrane Epilepsy Group trials register (31 May 2012), the Cochrane Central Register of Controlled Trials (CENTRAL Issue 5 of 12, The Cochrane Library 2012) and MEDLINE (1946 to May week 4, 2012). We hand-searched relevant journals, contacted pharmaceutical companies, original trial investigators and experts in the field. Randomised controlled trials in children or adults with partial onset seizures or generalised onset tonic-clonic seizures with a comparison of phenobarbitone monotherapy with phenytoin monotherapy. This was an individual participant data (IPD) review. Outcomes were time to (a) treatment withdrawal (b) 12-month remission (c) six-month remission and (d) first seizure post randomisation. Cox proportional hazards regression models were used to obtain study-specific estimates of hazard ratios (HRs) with 95% confidence intervals (CIs) with the generic inverse variance method used to obtain the overall pooled estimate of HRs and 95% CIs. Data have been obtained for four of eight studies meeting the inclusion criteria, amounting to 599 individuals, or approximately 63% of the potential data.The main overall results (pooled HR, 95% CI) were (a) time to treatment withdrawal 1.62 (1.23 to 2.14); (b) time to 12-month remission 0.90 (0.69 to 1.18) (c) time to six-month remission 0.92 (0.73 to 1.16) and (d) time to first seizure 0.85 (0.68 to 1.05). These results indicate a statistically significant clinical advantage for phenytoin in terms of treatment withdrawal. However, this result may have been confounded by several factors including substantial statistical heterogeneity between studies and lack of blinding in two studies. The results of this review show that phenobarbitone was significantly more likely to be withdrawn than phenytoin. Given that no significant differences for seizure outcomes were found, the higher withdrawal rate with phenobarbitone may be due to adverse effects. Several factors may have confounded the results of this review.
    Cochrane database of systematic reviews (Online) 01/2013; 1:CD002217.
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    ABSTRACT: Background Individual patient data (IPD) meta-analysis is the gold standard. Aggregate data (AD) and IPD can be combined using conventional pairwise meta-analysis when IPD cannot be obtained for all relevant studies. We extend the methodology to combine IPD and AD in a mixed treatment comparison (MTC) meta-analysis. Methods The proposed random-effects MTC models combine IPD and AD for a dichotomous outcome. We study the benefits of acquiring IPD for a subset of trials when assessing the underlying consistency assumption by including treatment-by-covariate interactions in the model. We describe three different model specifications that make increasingly stronger assumptions regarding the interactions. We illustrate the methodology through application to real data sets to compare drugs for treating malaria by using the outcome unadjusted treatment success at day 28. We compare results from AD alone, IPD alone and all data. Results When IPD contributed (i.e. either using IPD alone or combining IPD and AD), the chains converged, and we identified statistically significant regression coefficients for the interactions. Using IPD alone, we were able to compare only three of the six treatments of interest. When models were fitted to AD, the treatment effects and regression coefficients for the interactions were far more imprecise, and the chains did not converge. Conclusions The models combining IPD and AD encapsulated all available evidence. When exploring interactions, it can be beneficial to obtain IPD for a subset of trials and to combine IPD with additional AD. Copyright © 2012 John Wiley & Sons, Ltd.
    Statistics in Medicine 09/2012;
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    ABSTRACT: The selection of appropriate outcomes or domains is crucial when designing clinical trials in order to compare directly the effects of different interventions in ways that minimize bias. If the findings are to influence policy and practice then the chosen outcomes need to be relevant and important to key stakeholders including patients and the public, health care professionals and others making decisions about health care. There is a growing recognition that insufficient attention has been paid to the outcomes measured in clinical trials. These issues could be addressed through the development and use of an agreed standardized collection of outcomes, known as a core outcome set, which should be measured and reported, as a minimum, in all trials for a specific clinical area. Accumulating work in this area has identified the need for general guidance on the development of core outcome sets. Key issues to consider in the development of a core outcome set include its scope, the stakeholder groups to involve, choice of consensus method and the achievement of a consensus.
    Trials 08/2012; 13:132.
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    ABSTRACT: Mixed treatment comparison (MTC) meta-analysis allows several treatments to be compared in a single analysis while utilising direct and indirect evidence. Treatment by covariate interactions can be included in MTC models to explore how the covariate modifies the treatment effects. If interactions exist, the assumptions underlying MTCs may be invalidated. For conventional pair-wise meta-analysis, important benefits regarding the investigation of such interactions, gained from using individual patient data (IPD) rather than aggregate data (AD), have been described. We aim to compare IPD MTC models including patient-level covariates with AD MTC models including study-level covariates. IPD and AD random-effects MTC models for dichotomous outcomes are specified. Three assumptions are made regarding the interactions (i.e. independent, exchangeable and common interactions). The models are applied to a dataset to compare four drugs for treating malaria (i.e. amodiaquine-artesunate, dihydroartemisinin-piperaquine (DHAPQ), artemether-lumefantrine and chlorproguanil-dapsone plus artesunate) using the outcome unadjusted treatment success at day 28. The treatment effects and regression coefficients for interactions from the IPD models were more precise than those from AD models. Using IPD, assuming independent or exchangeable interactions, the regression coefficient for chlorproguanil-dapsone plus artesunate versus DHAPQ was statistically significant and assuming common interactions, the common coefficient was significant; whereas using AD, no coefficients were significant. Using IPD, DHAPQ was the best drug; whereas using AD, the best drug varied. Using AD models, there was no evidence that the consistency assumption was invalid; whereas, the assumption was questionable based on the IPD models. The AD analyses were misleading. Copyright © 2012 John Wiley & Sons, Ltd.
    Statistics in Medicine 07/2012;
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