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BMC Medical Research Methodology

Doneal Thomas, Robert Platt, Andrea Benedetti
BACKGROUND: Individual patient data meta-analyses (IPD-MA) are often performed using a one-stage approach-- a form of generalized linear mixed model (GLMM) for binary outcomes. We compare (i) one-stage to two-stage approaches (ii) the performance of two estimation procedures (Penalized Quasi-likelihood-PQL and Adaptive Gaussian Hermite Quadrature-AGHQ) for GLMMs with binary outcomes within the one-stage approach and (iii) using stratified study-effect or random study-effects. METHODS: We compare the different approaches via a simulation study, in terms of bias, mean-squared error (MSE), coverage and numerical convergence, of the pooled treatment effect (β 1) and between-study heterogeneity of the treatment effect (τ 1(2) )...
February 16, 2017: BMC Medical Research Methodology
Charles Fontaine, Jean-Pierre Daurès, Paul Landais
BACKGROUND: Information and theory beyond copula concepts are essential to understand the dependence relationship between several marginal covariates distributions. In a therapeutic trial data scheme, most of the time, censoring occurs. That could lead to a biased interpretation of the dependence relationship between marginal distributions. Furthermore, it could result in a biased inference of the joint probability distribution function. A particular case is the cost-effectiveness analysis (CEA), which has shown its utility in many medico-economic studies and where censoring often occurs...
February 15, 2017: BMC Medical Research Methodology
Belinda von Niederhäusern, Annette Orleth, Sabine Schädelin, Nawal Rawi, Martin Velkopolszky, Claudia Becherer, Pascal Benkert, Priya Satalkar, Matthias Briel, Christiane Pauli-Magnus
BACKGROUND: In spite of efforts to employ risk-based strategies to increase monitoring efficiency in the academic setting, empirical evidence on their effectiveness remains sparse. This mixed-methods study aimed to evaluate the risk-based on-site monitoring approach currently followed at our academic institution. METHODS: We selected all studies monitored by the Clinical Trial Unit (CTU) according to Risk ADApted MONitoring (ADAMON) at the University Hospital Basel, Switzerland, between 01...
February 14, 2017: BMC Medical Research Methodology
Nathalie Gault, Johann Castañeda-Sanabria, Yann De Rycke, Sylvie Guillo, Stéphanie Foulon, Florence Tubach
BACKGROUND: Observational studies are widely used in pharmacoepidemiology. Several designs can be used, in particular self-controlled designs (case-crossover and self-controlled case series). These designs offer the advantage of controlling for time-invariant confounders, which may not be collected in electronic healthcare databases. They are particularly useful in pharmacoepidemiology involving healthcare database. To be valid, they require the presence of some characteristics (key validity assumptions), and in such situations, these designs should be preferred...
February 8, 2017: BMC Medical Research Methodology
Katie Harron, Gareth Hagger-Johnson, Ruth Gilbert, Harvey Goldstein
BACKGROUND: Linkage of administrative data sources often relies on probabilistic methods using a set of common identifiers (e.g. sex, date of birth, postcode). Variation in data quality on an individual or organisational level (e.g. by hospital) can result in clustering of identifier errors, violating the assumption of independence between identifiers required for traditional probabilistic match weight estimation. This potentially introduces selection bias to the resulting linked dataset...
February 7, 2017: BMC Medical Research Methodology
Louise E Craig, Leonid Churilov, Liudmyla Olenko, Dominique A Cadilhac, Rohan Grimley, Simeon Dale, Cintia Martinez-Garduno, Elizabeth McInnes, Julie Considine, Jeremy M Grimshaw, Sandy Middleton
BACKGROUND: Multiple barriers may inhibit the adoption of clinical interventions and impede successful implementation. Use of standardised methods to prioritise barriers to target when selecting implementation interventions is an understudied area of implementation research. The aim of this study was to describe a method to identify and prioritise barriers to the implementation of clinical practice elements which were used to inform the development of the T(3) trial implementation intervention (Triage, Treatment [thrombolysis administration; monitoring and management of temperature, blood glucose levels, and swallowing difficulties] and Transfer of stroke patients from Emergency Departments [ED])...
February 7, 2017: BMC Medical Research Methodology
Guogen Shan, Hua Zhang, Tao Jiang
BACKGROUND: Recently, several adaptive one-arm two-stage designs have been developed by fully using the information from previous stages to reduce the expected sample size in clinical trials with binary endpoints as primary outcome. It is important to compute exact confidence limits for these studies. METHODS: In this article, we propose three new one-sided limits by ordering the sample space based on p-value, average response rate at each stage, and asymptotic lower limit, as compared to another three existing sample size ordering approaches based on average response rate...
February 6, 2017: BMC Medical Research Methodology
M Smuk, J R Carpenter, T P Morris
BACKGROUND: Within epidemiological and clinical research, missing data are a common issue and often over looked in publications. When the issue of missing observations is addressed it is usually assumed that the missing data are 'missing at random' (MAR). This assumption should be checked for plausibility, however it is untestable, thus inferences should be assessed for robustness to departures from missing at random. METHODS: We highlight the method of pattern mixture sensitivity analysis after multiple imputation using colorectal cancer data as an example...
February 6, 2017: BMC Medical Research Methodology
Jie Pu, Di Fang, Jeffrey R Wilson
BACKGROUND: The analysis of correlated binary data is commonly addressed through the use of conditional models with random effects included in the systematic component as opposed to generalized estimating equations (GEE) models that addressed the random component. Since the joint distribution of the observations is usually unknown, the conditional distribution is a natural approach. Our objective was to compare the fit of different binary models for correlated data in Tabaco use. We advocate that the joint modeling of the mean and dispersion may be at times just as adequate...
February 3, 2017: BMC Medical Research Methodology
Xuan Chen, Fabrice Bailleux, Kamal Desai, Li Qin, Andrew J Dunning
No abstract text is available yet for this article.
February 2, 2017: BMC Medical Research Methodology
Manas K Akmatov, Leonhard Jentsch, Peggy Riese, Marcus May, Malik W Ahmed, Damaris Werner, Anja Rösel, Jana Prokein, Inga Bernemann, Norman Klopp, Blair Prochnow, Thomas Illig, Christoph Schindler, Carlos A Guzman, Frank Pessler
BACKGROUND: Participation in epidemiological studies has strongly declined in recent years. We examined the reasons for (non)participation in population-based health studies among participants and nonparticipants of a prospective study on influenza vaccination among the elderly. METHODS: Males and females between 65 and 80 years of age (N = 5582) were randomly selected from the residents' registration office in Hannover, Germany, and were invited to participate in a study featuring vaccination with a seasonal adjuvanted influenza vaccine (Fluad™, Novartis) including five follow-up visits (day 0, 1/3, 7, 21, 70 with respect to vaccination)...
February 2, 2017: BMC Medical Research Methodology
Jane Candlish, Alexander Pate, Matthew Sperrin, Tjeerd van Staa
BACKGROUND: The cohort multiple randomised controlled trial (cmRCT) design provides an opportunity to incorporate the benefits of randomisation within clinical practice; thus reducing costs, integrating electronic healthcare records, and improving external validity. This study aims to address a key concern of the cmRCT design: refusal to treatment is only present in the intervention arm, and this may lead to bias and reduce statistical power. METHODS: We used simulation studies to assess the effect of this refusal, both random and related to event risk, on bias of the effect estimator and statistical power...
January 31, 2017: BMC Medical Research Methodology
Nida H Corry, Christianna S Williams, Mike Battaglia, Hope Seib McMaster, Valerie A Stander
BACKGROUND: In conducting population-based surveys, it is important to thoroughly examine and adjust for potential non-response bias to improve the representativeness of the sample prior to conducting analyses of the data and reporting findings. This paper examines factors contributing to second stage survey non-response during the baseline data collection for the Millennium Cohort Family Study, a large longitudinal study of US service members and their spouses from all branches of the military...
January 28, 2017: BMC Medical Research Methodology
Casper Tax, Marlie E Steenbergen, Petra L M Zusterzeel, Ruud L M Bekkers, Maroeska M Rovers
BACKGROUND: Data on health-related quality of life (HRQoL) is paramount for shared and evidence based decision-making. Since an overview of cervical cancer HRQoL tools and their validity appears to be lacking, we performed a systematic review on usage of disease specific HRQoL instruments in cervical cancer patients and their psychometric properties to identify the most suitable cervical cancer specific HRQoL tool. METHODS: We searched Pubmed, EMBASE and PsycINFO from inception up to 18 October 2016 for studies on quality of life in cervical cancer patients...
January 26, 2017: BMC Medical Research Methodology
Gabriele Helga Franke, Susanne Jaeger, Heide Glaesmer, Claus Barkmann, Katja Petrowski, Elmar Braehler
BACKGROUND: The BSI-18 contains the three six-item scales somatization, depression, and anxiety as well as the Global Severity Index (GSI), including all 18 items. The BSI-18 is the latest and shortest of the multidimensional versions of the Symptom-Checklist 90-R, but its psychometric properties have not been sufficiently clarified yet. METHODS: Based on a representative sample of N = 2516 participants (aged 14-94 years), detailed psychometric analyses were carried out...
January 26, 2017: BMC Medical Research Methodology
Lindsay Stark, Beth L Rubenstein, Kimchoeun Pak, Rosemary Taing, Gary Yu, Sok Kosal, Leslie Roberts
BACKGROUND: The Government of Cambodia has committed to supporting family care for vulnerable children, including homeless populations. Collecting baseline data on the numbers and characteristics of homeless adolescents was prioritized to illuminate the scope of the issue, mobilize resources and direct the response. METHODS: Administrative zones across seven cities were purposively selected to cover the main urban areas known to have homeless populations in Cambodia...
January 26, 2017: BMC Medical Research Methodology
Jing Zhai, Chiu-Hsieh Hsu, Z John Daye
BACKGROUND: Many questions in statistical genomics can be formulated in terms of variable selection of candidate biological factors for modeling a trait or quantity of interest. Often, in these applications, additional covariates describing clinical, demographical or experimental effects must be included a priori as mandatory covariates while allowing the selection of a large number of candidate or optional variables. As genomic studies routinely require mandatory covariates, it is of interest to propose principled methods of variable selection that can incorporate mandatory covariates...
January 25, 2017: BMC Medical Research Methodology
Maxine Johnson, Rachel O'Hara, Enid Hirst, Andrew Weyman, Janette Turner, Suzanne Mason, Tom Quinn, Jane Shewan, A Niroshan Siriwardena
BACKGROUND: Paramedics make important and increasingly complex decisions at scene about patient care. Patient safety implications of influences on decision making in the pre-hospital setting were previously under-researched. Cutting edge perspectives advocate exploring the whole system rather than individual influences on patient safety. Ethnography (the study of people and cultures) has been acknowledged as a suitable method for identifying health care issues as they occur within the natural context...
January 24, 2017: BMC Medical Research Methodology
Malamine Gassama, Jacques Bénichou, Laureen Dartois, Anne C M Thiébaut
BACKGROUND: The attributable risk (AR) measures the proportion of disease cases that can be attributed to an exposure in the population. Several definitions and estimation methods have been proposed for survival data. METHODS: Using simulations, we compared four methods for estimating AR defined in terms of survival functions: two nonparametric methods based on Kaplan-Meier's estimator, one semiparametric based on Cox's model, and one parametric based on the piecewise constant hazards model, as well as one simpler method based on estimated exposure prevalence at baseline and Cox's model hazard ratio...
January 23, 2017: BMC Medical Research Methodology
Xue Feng Hu, Kue Young, Hing Man Chan
BACKGROUND: Disease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and expensive; the latter is not available in most developing countries. Alternatively, mathematical models could be used to estimate disease incidence from prevalence. METHODS: We proposed and validated a method to estimate the age-standardized incidence of cardiovascular disease (CVD), with prevalence data from successive surveys and mortality data from empirical studies...
January 23, 2017: BMC Medical Research Methodology
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