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Xie F.,Programs for Assessment of Technology in Health | Xie F.,McMaster University | Lo N.-N.,Singapore General Hospital | Pullenayegum E.M.,McMaster University | And 8 more authors.
Health and Quality of Life Outcomes | Year: 2010

Objectives: To quantify the improvement in health outcomes in patients after total knee replacement (TKR).Methods: This was a two-year non-randomized prospective observational study in knee osteoarthritis (OA) patients undergone TKR. Patients were interviewed one week before, six months after, and two years after surgery using a standardized questionnaire including the SF-36, the Oxford Knee Score (OKS), and the Knee Society Clinical Rating Scale (KSS). A generalized estimating equation (GEE) model was used to estimate the magnitudes of the changes with and without the adjustment of age, ethnicity, BMI, and years with OA.Results: A total of 298 (at baseline), 176 (at six-months), and 111 (at two-years) eligible patients were included in the analyses. All the scores changed significantly over time, with the exception of SF-36 social functioning, vitality, and mental health. With the adjustment of covariates, the magnitude of changes in these scores was similar to those without the adjustment.Conclusions: Both general and knee-specific physical functioning had been significantly improved after TKR, while other health domains have not been substantially improved after the surgery. © 2010 Xie et al; licensee BioMed Central Ltd.


Thabane L.,McMaster University | Thabane L.,Center for Evaluation of Medicine | Thabane L.,Biostatistics Unit | Thabane L.,Hamilton Health Sciences | And 26 more authors.
BMC Medical Research Methodology | Year: 2013

Background: Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations - such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers - on the overall conclusions of a study. The current paper is the second in a series of tutorial-type manuscripts intended to discuss and clarify aspects related to key methodological issues in the design and analysis of clinical trials. Discussion. In this paper we will provide a detailed exploration of the key aspects of sensitivity analyses including: 1) what sensitivity analyses are, why they are needed, and how often they are used in practice; 2) the different types of sensitivity analyses that one can do, with examples from the literature; 3) some frequently asked questions about sensitivity analyses; and 4) some suggestions on how to report the results of sensitivity analyses in clinical trials. Summary. When reporting on a clinical trial, we recommend including planned or posthoc sensitivity analyses, the corresponding rationale and results along with the discussion of the consequences of these analyses on the overall findings of the study. © 2013 Thabane et al.; licensee BioMed Central Ltd.


Mbuagbaw L.,McMaster University | Mbuagbaw L.,Biostatistics Unit | Mbuagbaw L.,Yaounde Central Hospital | Mbuagbaw L.,South African Cochrane Center | And 12 more authors.
Contemporary Clinical Trials | Year: 2014

Background: We sought to determine if the publication of the Consolidated Standards of Reporting Trials (CONSORT). 11CONSORT: Consolidated Standards of Reporting Trials. extension for abstracts in 2008 had led to an improvement in reporting abstracts of randomized controlled trials (RCTs).22RCT: Randomized controlled trial. Methods: We searched PubMed for RCTs published in 2007 and 2012 in top-tier general medicine journals. A random selection of 100 trial abstracts was obtained for each year. Data were extracted in duplicate on the adherence to the CONSORT extension for abstracts. The primary outcome was the mean number of items reported and the secondary outcome was the odds of reporting each item. We also estimated incidence rate ratios (IRRs).33IRRs: Incidence rate ratios. Results: Significantly more checklist items were reported in 2012 than in 2007: adjusted mean difference was 2.91 (95% confidence interval [CI]. 44CI: Confidence interval. 2.35, 3.41; p. <. 0.001). In 2012 there were significant improvements in reporting the study as randomized in the title, describing the trial design, the participants, and objectives and blinding. In the Results section, trial status and numbers analyzed were also reported better. The IRRs were significantly higher for 2012 (IRR 1.32; 95% CI 1.25, 1.39; p. <. 0.001) and in multisite studies compared to single site studies (IRR 1.08; 95% CI 1.03, 1.15; p. = 0.006). Conclusions: There was a significant improvement in the reporting of abstracts of RCTs in 2012 compared to 2007. However, there is still room for improvement as some items remain under-reported. © 2014 Elsevier Inc.


Mbuagbaw L.,McMaster University | Mbuagbaw L.,Father Sean ullivan Research Center | Mbuagbaw L.,Yaounde Central Hospital | Mursleen S.,McMaster University | And 8 more authors.
BMC Health Services Research | Year: 2015

Background: Strong international commitment and the widespread use of antiretroviral therapy have led to higher longevity for people living with human immune deficiency virus (HIV). Text messaging interventions have been shown to improve health outcomes in people living with HIV. The objectives of this overview were to: map the state of the evidence of text messaging interventions, identify knowledge gaps, and develop a framework for the transfer of evidence to other chronic diseases. Methods: We conducted a systematic review of systematic reviews on text messaging interventions to improve health or health related outcomes. We conducted a comprehensive search of PubMed, EMBASE (Exerpta Medica Database), CINAHL (Cumulative Index to Nursing and Allied Health Literature), PsycINFO, Web of Science (WoS) and the Cochrane Library on the 17th April 2014. Screening, data extraction and assessment of methodological quality were done in duplicate. Our findings were used to develop a conceptual framework for transfer. Results: Our search identified 135 potential systematic reviews of which nine were included, reporting on 37 source studies, conducted in 19 different countries. Seven of nine (77.7%) of these reviews were high quality. There was some evidence for text messaging as a tool to improve adherence to antiretroviral therapy. Text messages also improved attendance at appointments and behaviour change outcomes. The findings were inconclusive for self-management of illness, treatment of tuberculosis and communicating results of medical investigations. The geographical distribution of text messaging research was limited to specific regions of the world. Prominent knowledge gaps included the absence of data on long term outcomes, patient satisfaction, and economic evaluations. The included reviews also identified methodological limitations in many of the primary studies. Conclusions: Global evidence supports the use of text messaging as a tool to improve adherence to medication and attendance at scheduled appointments. Given the similarities between HIV and other chronic diseases (long-term medications, life-long care, strong link to behaviour and the need for home-based support) evidence from HIV may be transferred to these diseases using our proposed framework by integration of HIV and chronic disease services or direct transfer © 2015 Mbuagbaw et al.; licensee BioMed Central.


Mbuagbaw L.,Yaounde Central Hospital | Mbuagbaw L.,McMaster University | Ongolo-Zogo P.,Yaounde Central Hospital | Thabane L.,McMaster University | And 3 more authors.
BMJ Open | Year: 2013

Introduction: Mobile phone ownership and use are growing fastest in sub-Saharan Africa, and there is evidence that mobile phone text messages can be used successfully to significantly improve adherence to antiretroviral therapy and reduce treatment interruptions. However, the effects of many mobile health interventions are often reduced by human resource shortages within health facilities. Also, research projects generating evidence for health interventions in developing countries are most often conducted using external funding sources, with limited sustainability and adoption by local governments following completion of the projects. Strong community participation driven by active outreach programmes and mobilisation of community resources are the key to successful adoption and long-term sustainability of effective interventions. Our aim was to develop a framework for community ownership of a text messaging programme to improve adherence to antiretroviral therapy; improve communication between patients and doctors and act as a reminder for appointments. Methods and analysis: We will use the exploratory sequential mixed methods approach. The first qualitative phase will entail focus group discussions with people living with HIV at the Yaoundé Central Hospital in Yaoundé, Cameroon (6-10 participants/group). The second quantitative phase will involve a cross-sectional survey (n=402). In this study, binary logistic regression techniques will be used to determine the factors associated with community readiness and acceptability of ownership. Data from both phases will be merged. Ethics and dissemination: This study has been approved by the Yaoundé Central Hospital Institutional Review Board. The results of this paper will be disseminated as peer-reviewed publications at conferences and as part of a doctoral thesis.


Vanniyasingam T.,McMaster University | Cunningham C.E.,McMaster University | Foster G.,McMaster University | Foster G.,Biostatistics Unit | And 4 more authors.
BMJ Open | Year: 2016

Objectives: Discrete choice experiments (DCEs) are routinely used to elicit patient preferences to improve health outcomes and healthcare services. While many fractional factorial designs can be created, some are more statistically optimal than others. The objective of this simulation study was to investigate how varying the number of (1) attributes, (2) levels within attributes, (3) alternatives and (4) choice tasks per survey will improve or compromise the statistical efficiency of an experimental design. Design and methods: A total of 3204 DCE designs were created to assess how relative design efficiency (d-efficiency) is influenced by varying the number of choice tasks (2-20), alternatives (2-5), attributes (2-20) and attribute levels (2-5) of a design. Choice tasks were created by randomly allocating attribute and attribute level combinations into alternatives. Outcome: Relative d-efficiency was used to measure the optimality of each DCE design. Results: DCE design complexity influenced statistical efficiency. Across all designs, relative d-efficiency decreased as the number of attributes and attribute levels increased. It increased for designs with more alternatives. Lastly, relative d-efficiency converges as the number of choice tasks increases, where convergence may not be at 100% statistical optimality. Conclusions: Achieving 100% d-efficiency is heavily dependent on the number of attributes, attribute levels, choice tasks and alternatives. Further exploration of overlaps and block sizes are needed. This study's results are widely applicable for researchers interested in creating optimal DCE designs to elicit individual preferences on health services, programmes, policies and products. © 2016 Published by the BMJ Publishing Group Limited.


Dennis B.B.,McMaster University | Naji L.,McMaster University | Bawor M.,McMaster University | Bonner A.,McMaster University | And 16 more authors.
Systematic Reviews | Year: 2014

Background: Opioids are psychoactive analgesic drugs prescribed for pain relief and palliative care. Due to their addictive potential, effort and vigilance in controlling prescriptions is needed to avoid misuse and dependence. Despite the effort, the prevalence of opioid use disorder continues to rise. Opioid substitution therapies are commonly used to treat opioid dependence; however, there is minimal consensus as to which therapy is most effective. Available treatments include methadone, heroin, buprenorphine, as well as naltrexone. This systematic review aims to assess and compare the effect of all available opioid substitution therapies on the treatment of opioid dependence. Methods/Design: The authors will search Medline, EMBASE, PubMed, PsycINFO, Web of Science, Cochrane Library, Cochrane Clinical Trials Registry, World Health Organization International Clinical Trials Registry Platform Search Portal, and the National Institutes for Health Clinical Trials Registry. The title, abstract, and full-text screening will be completed in duplicate. When appropriate, multiple treatment comparison Bayesian meta-analytic methods will be performed to deduce summary statistics estimating the effectiveness of all opioid substitution therapies in terms of retention and response to treatment (as measured through continued opioid abuse). Discussion: Using evidence gained from this systematic review, we anticipate disseminating an objective review of the current available literature on the effectiveness of all opioid substitution therapies for the treatment of opioid use disorder. The results of this systematic review are imperative to the further enhancement of clinical practice in addiction medicine. Systematic review registration: PROSPERO CRD42013006507. © 2014 Dennis et al.; licensee BioMed Central Ltd.


Xie F.,Programs for Assessment of Technology in Health | Xie F.,McMaster University | Pullenayegum E.M.,McMaster University | Pullenayegum E.M.,Center for Evaluation of Medicine | And 5 more authors.
Value in Health | Year: 2010

Objective: To map the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) onto the EuroQol 5 Dimension (EQ-5D) utility index in patients with knee osteoarthritis (OA). Methods: A consecutive sample of patients (n = 258) diagnosed with knee OA completed both the WOMAC and the EQ-5D. Regression models with the ordinary least squares (OLS) or the censored least absolute deviations as the estimator were used to establish the mapping function. The WOMAC was represented as explanatory variables in four ways: 1) total score; 2) domain scores (i.e., pain, stiffness, and physical function); 3) domain scores plus pair-wise interaction terms to account for possible nonlinearities; and 4) individual item scores. Goodness-of-fit criteria included the mean absolute error (the primary criterion) and the root mean squared error, and were obtained using an iterative random sampling procedure. Prediction precision was evaluated at individual patient level and at the group level. Results: The model using the OLS estimator and the WOMAC domain scores as explanatory variables had the best fit and was chosen as the preferred mapping model. The prediction error at the individual level exceeded the maximal tolerance value (i.e., the minimally important difference of the EQ-5D) in about 16% of the patients. At the group level, the width of the 95% confidence interval of prediction errors varied from 0.0176 at a sample size of 400 to 0.0359 at a sample size of 100. Conclusions: EQ-5D scores can be predicted using WOMAC domain scores with an acceptable precision at both individual and group levels in patients with mild to moderate knee OA. © 2010, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).


Dennis B.B.,McMaster University | Constantine Samaan M.,McMaster University | Bawor M.,McMaster University | Paul J.,McMaster University | And 11 more authors.
Neuropsychiatric Disease and Treatment | Year: 2014

Background: Chronic pain is the most commonly reported comorbidity among patients with opioid addiction receiving methadone maintenance treatment (MMT), with an estimated prevalence ranging between 30% and 55%. Evidence suggests that patients with comorbid pain are at high risk for poor treatment response, including continued illicit substance use. Due to the important relationship between the presence of pain and illicit substance abuse within the MMT setting, it is imperative that we target our efforts toward understanding the characteristics of this patient population Methods: The primary objective of this study was to explore the clinical and inflammatory profile of MMT patients reporting comorbid pain. This multicenter study enrolled patients (n=235) on MMT for the treatment of opioid dependence. Clinical history and blood and urine data were collected. Blood samples were obtained for estimating the serum levels of inflammatory markers (tumor necrosis factor [TNF]-α, interleukin-1 receptor antagonist [IL-1ra], IL-6, IL-8, IL-10, interferon [IFN]-γ and chemokine (C-C motif) ligand 2 [CCL2]). The study objectives were addressed using a descriptive statistical summary and a multivariable logistic regression model constructed in STATA version 12 Results: Among the participants eligible for inclusion (n=235), serum IFN-γ level and substance abuse behavior proved to be important delineating characteristics for the detection of comorbid pain. Analysis of inflammatory profile showed IFN-γ to be significantly elevated among patients reporting comorbid pain (odds ratio [OR]: 2.02; 95% confidence interval [CI]: 1.17, 3.50; P=0.01). Patients reporting comorbid pain were also found to have an increase in positive opioid urine screens (OR: 1.02; 95% CI: 1.00, 1.03; P=0.01), indicating an increase in illicit opioid consumption Conclusion: MMT patients with comorbid pain were shown to have elevated IFN-γ and higher rates of continued opioid abuse. The ability to objectively distinguish between patients with comorbid pain may help to both improve the prediction of poor responders to MMT as well as identify treatment approaches such as anti-inflammatory medications as safe alternatives for MMT patients with comorbid pain. © 2014 Dennis et al.


Chu R.,McMaster University | Chu R.,Biostatistics Unit | Thabane L.,McMaster University | Thabane L.,Biostatistics Unit | And 9 more authors.
BMC Medical Research Methodology | Year: 2011

Background: Multicentre randomized controlled trials (RCTs) routinely use randomization and analysis stratified by centre to control for differences between centres and to improve precision. No consensus has been reached on how to best analyze correlated continuous outcomes in such settings. Our objective was to investigate the properties of commonly used statistical models at various levels of clustering in the context of multicentre RCTs. Methods. Assuming no treatment by centre interaction, we compared six methods (ignoring centre effects, including centres as fixed effects, including centres as random effects, generalized estimating equation (GEE), and fixed- and random-effects centre-level analysis) to analyze continuous outcomes in multicentre RCTs using simulations over a wide spectrum of intraclass correlation (ICC) values, and varying numbers of centres and centre size. The performance of models was evaluated in terms of bias, precision, mean squared error of the point estimator of treatment effect, empirical coverage of the 95% confidence interval, and statistical power of the procedure. Results: While all methods yielded unbiased estimates of treatment effect, ignoring centres led to inflation of standard error and loss of statistical power when within centre correlation was present. Mixed-effects model was most efficient and attained nominal coverage of 95% and 90% power in almost all scenarios. Fixed-effects model was less precise when the number of centres was large and treatment allocation was subject to chance imbalance within centre. GEE approach underestimated standard error of the treatment effect when the number of centres was small. The two centre-level models led to more variable point estimates and relatively low interval coverage or statistical power depending on whether or not heterogeneity of treatment contrasts was considered in the analysis. Conclusions: All six models produced unbiased estimates of treatment effect in the context of multicentre trials. Adjusting for centre as a random intercept led to the most efficient treatment effect estimation across all simulations under the normality assumption, when there was no treatment by centre interaction. © 2011 Chu et al; licensee BioMed Central Ltd.

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