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Utilization of EHRs for clinical trials: a systematic review BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-18 Leila R. Kalankesh, Elham Monaghesh
Clinical trials are of high importance for medical progress. This study conducted a systematic review to identify the applications of EHRs in supporting and enhancing clinical trials. A systematic search of PubMed was conducted on 12/3/2023 to identify relevant studies on the use of EHRs in clinical trials. Studies were included if they (1) were full-text journal articles, (2) were written in English
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Predicting health outcomes with intensive longitudinal data collected by mobile health devices: a functional principal component regression approach BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-17 Qing Yang, Meilin Jiang, Cai Li, Sheng Luo, Matthew J. Crowley, Ryan J. Shaw
Intensive longitudinal data (ILD) collected in near real time by mobile health devices provide a new opportunity for monitoring chronic diseases, early disease risk prediction, and disease prevention in health research. Functional data analysis, specifically functional principal component analysis, has great potential to abstract trends in ILD but has not been used extensively in mobile health research
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An analysis of published study designs in PubMed prisoner health abstracts from 1963 to 2023: a text mining study BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-17 George Karystianis, Wilson Lukmanjaya, Iain Buchan, Paul Simpson, Natasha Ginnivan, Goran Nenadic, Tony Butler
The challenging nature of studies with incarcerated populations and other offender groups can impede the conduct of research, particularly that involving complex study designs such as randomised control trials and clinical interventions. Providing an overview of study designs employed in this area can offer insights into this issue and how research quality may impact on health and justice outcomes
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Survival analysis under imperfect record linkage using historic census data BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-13 Arielle K. Marks-Anglin, Frances K. Barg, Michelle Ross, Douglas J. Wiebe, Wei-Ting Hwang
Advancements in linking publicly available census records with vital and administrative records have enabled novel investigations in epidemiology and social history. However, in the absence of unique identifiers, the linkage of the records may be uncertain or only be successful for a subset of the census cohort, resulting in missing data. For survival analysis, differential ascertainment of event times
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Assessing the properties of patient-specific treatment effect estimates from causal forest algorithms under essential heterogeneity BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-13 John M. Brooks, Cole G. Chapman, Brian K. Chen, Sarah B. Floyd, Neset Hikmet
Treatment variation from observational data has been used to estimate patient-specific treatment effects. Causal Forest Algorithms (CFAs) developed for this task have unknown properties when treatment effect heterogeneity from unmeasured patient factors influences treatment choice – essential heterogeneity. We simulated eleven populations with identical treatment effect distributions based on patient
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The methodological quality of systematic reviews regarding the Core Outcome Set (COS) development BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-11 Hong Cao, Yan Chen, Zhihao Yang, Junjie Lan, Joey Sum-wing Kwong, Rui Zhang, Huaye Zhao, Linfang Hu, Jiaxue Wang, Shuimei Sun, Songsong Tan, Jinyong Cao, Rui He, Wenyi Zheng, Jiaxing Zhang
The Core Outcome Measures in Effectiveness Trials (COMET) working group proposed core outcome sets (COS) to address the heterogeneity in outcome measures in clinical studies. According to the recommendations of COMET, performing systematic reviews (SRs) usually was the first step for COS development. However, the SRs that serve as a basis for COS are not specifically appraised by organizations such
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Distributive randomization: a pragmatic fractional factorial design to screen or evaluate multiple simultaneous interventions in a clinical trial BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-11 Skerdi Haviari, France Mentré
In some medical indications, numerous interventions have a weak presumption of efficacy, but a good track record or presumption of safety. This makes it feasible to evaluate them simultaneously. This study evaluates a pragmatic fractional factorial trial design that randomly allocates a pre-specified number of interventions to each participant, and statistically tests main intervention effects. We
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Text analysis framework for identifying mutations among non-small cell lung cancer patients from laboratory data BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-11 Amman Yusuf, Devon J. Boyne, Dylan E. O’Sullivan, Darren R. Brenner, Winson Y. Cheung, Imran Mirza, Tamer N. Jarada
Laboratory data can provide great value to support research aimed at reducing the incidence, prolonging survival and enhancing outcomes of cancer. Data is characterized by the information it carries and the format it holds. Data captured in Alberta’s biomarker laboratory repository is free text, cluttered and rouge. Such data format limits its utility and prohibits broader adoption and research development
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Design and statistical analysis reporting among interrupted time series studies in drug utilization research: a cross-sectional survey BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-09 Yuanjin Zhang, Yan Ren, Yunxiang Huang, Minghong Yao, Yulong Jia, Yuning Wang, Fan Mei, Kang Zou, Jing Tan, Xin Sun
Interrupted time series (ITS) design is a commonly used method for evaluating large-scale interventions in clinical practice or public health. However, improperly using this method can lead to biased results. To investigate design and statistical analysis characteristics of drug utilization studies using ITS design, and give recommendations for improvements. A literature search was conducted based
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An assessment of the informative value of data sharing statements in clinical trial registries BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-09 Christian Ohmann, Maria Panagiotopoulou, Steve Canham, Gerd Felder, Pablo Emilio Verde
The provision of data sharing statements (DSS) for clinical trials has been made mandatory by different stakeholders. DSS are a device to clarify whether there is intention to share individual participant data (IPD). What is missing is a detailed assessment of whether DSS are providing clear and understandable information about the conditions for data sharing of IPD for secondary use. A random sample
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The minimal important difference of patient-reported outcome measures related to female urinary incontinence: a systematic review BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-08 Jordana Barbosa-Silva, Letícia Bojikian Calixtre, Daniela Von Piekartz, Patricia Driusso, Susan Armijo-Olivo
The minimal important difference is a valuable metric in ascertaining the clinical relevance of a treatment, offering valuable guidance in patient management. There is a lack of available evidence concerning this metric in the context of outcomes related to female urinary incontinence, which might negatively impact clinical decision-making. To summarize the minimal important difference of patient-reported
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Using the Super Learner algorithm to predict risk of major adverse cardiovascular events after percutaneous coronary intervention in patients with myocardial infarction BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-08 Xiang Zhu, Pin Zhang, Han Jiang, Jie Kuang, Lei Wu
The primary treatment for patients with myocardial infarction (MI) is percutaneous coronary intervention (PCI). Despite this, the incidence of major adverse cardiovascular events (MACEs) remains a significant concern. Our study seeks to optimize PCI predictive modeling by employing an ensemble learning approach to identify the most effective combination of predictive variables. We conducted a retrospective
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Clarifying the biological and statistical assumptions of cross-sectional biological age predictors: an elaborate illustration using synthetic and real data BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-08 Marije H. Sluiskes, Jelle J. Goeman, Marian Beekman, P. Eline Slagboom, Hein Putter, Mar Rodríguez-Girondo
There is divergence in the rate at which people age. The concept of biological age is postulated to capture this variability, and hence to better represent an individual’s true global physiological state than chronological age. Biological age predictors are often generated based on cross-sectional data, using biochemical or molecular markers as predictor variables. It is assumed that the difference
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Power calculation for detecting interaction effect in cross-sectional stepped-wedge cluster randomized trials: an important tool for disparity research BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-02 Chen Yang, Asem Berkalieva, Madhu Mazumdar, Deukwoo Kwon
The stepped-wedge cluster randomized trial (SW-CRT) design has become popular in healthcare research. It is an appealing alternative to traditional cluster randomized trials (CRTs) since the burden of logistical issues and ethical problems can be reduced. Several approaches for sample size determination for the overall treatment effect in the SW-CRT have been proposed. However, in certain situations
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Flexible Bayesian semiparametric mixed-effects model for skewed longitudinal data BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-01 Melkamu M. Ferede, Getachew A. Dagne, Samuel M. Mwalili, Workagegnehu H. Bilchut, Habtamu A. Engida, Simon M. Karanja
In clinical trials and epidemiological research, mixed-effects models are commonly used to examine population-level and subject-specific trajectories of biomarkers over time. Despite their increasing popularity and application, the specification of these models necessitates a great deal of care when analysing longitudinal data with non-linear patterns and asymmetry. Parametric (linear) mixed-effect
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REDCapDM: An R package with a set of data management tools for a REDCap project BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-01 João Carmezim, Pau Satorra, Judith Peñafiel, Esther García-Lerma, Natàlia Pallarès, Naiara Santos, Cristian Tebé
Research Electronic Data CAPture (REDCap) is a web application for creating and managing online surveys and databases. Clinical data management is an essential process before performing any statistical analysis to ensure the quality and reliability of study information. Processing REDCap data in R can be complex and often benefits from automation. While there are several R packages available for specific
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A Bayesian Bernoulli-Exponential joint model for binary longitudinal outcomes and informative time with applications to bladder cancer recurrence data BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-03-01 Michael Safo Oduro
A variety of methods exist for the analysis of longitudinal data, many of which are characterized with the assumption of fixed visit time points for study individuals. This, however is not always a tenable assumption. Phenomenon that alter subject visit patterns such as adverse events due to investigative treatment administered, travel or any other emergencies may result in unbalanced data and varying
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Human biomonitoring without in-person interaction: public health engagements during the COVID-19 pandemic and future implications BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-28 Alyssa J. Mattson, Jiali Yu, Elizabeth M. Miller, Michael Schueller, Michael Pentella, Susie Y. Dai
Public health initiatives, including human biomonitoring, have been impacted by unique challenges since the onset of the COVID-19 pandemic, compounding a decades-long trend of declining public participation. To combat low public participation rates, public health professionals often employ extensive engagement approaches including in-person interactions related to enrollment and sampling, success of
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Selecting a randomization method for a multi-center clinical trial with stochastic recruitment considerations BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-28 Oleksandr Sverdlov, Yevgen Ryeznik, Volodymyr Anisimov, Olga M. Kuznetsova, Ruth Knight, Kerstine Carter, Sonja Drescher, Wenle Zhao
The design of a multi-center randomized controlled trial (RCT) involves multiple considerations, such as the choice of the sample size, the number of centers and their geographic location, the strategy for recruitment of study participants, amongst others. There are plenty of methods to sequentially randomize patients in a multi-center RCT, with or without considering stratification factors. The goal
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Revising model for end-stage liver disease from calendar-time cross-sections with correction for selection bias BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-28 H. C. de Ferrante, M. van Rosmalen, B. M. L. Smeulders, S. Vogelaar, F. C. R. Spieksma
Eurotransplant liver transplant candidates are prioritized by Model for End-stage Liver Disease (MELD), a 90-day waitlist survival risk score based on the INR, creatinine and bilirubin. Several studies revised the original MELD score, UNOS-MELD, with transplant candidate data by modelling 90-day waitlist mortality from waitlist registration, censoring patients at delisting or transplantation. This
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GADNN: a revolutionary hybrid deep learning neural network for age and sex determination utilizing cone beam computed tomography images of maxillary and frontal sinuses BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-27 Omid Hamidi, Mahlagha Afrasiabi, Marjan Namaki
The determination of identity factors such as age and sex has gained significance in both criminal and civil cases. Paranasal sinuses like frontal and maxillary sinuses, are resistant to trauma and can aid profiling. We developed a deep learning (DL) model optimized by an evolutionary algorithm (genetic algorithm/GA) to determine sex and age using paranasal sinus parameters based on cone-beam computed
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Change analysis for intermediate disease markers in nutritional epidemiology: a causal inference perspective BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-27 Dan Tang, Yifan Hu, Ning Zhang, Xiong Xiao, Xing Zhao
Several approaches are commonly used to estimate the effect of diet on changes of various intermediate disease markers in prospective studies, including “change-score analysis”, “concurrent change-change analysis” and “lagged change-change analysis”. Although empirical evidence suggests that concurrent change-change analysis is most robust, consistent, and biologically plausible, in-depth dissection
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A parametric additive hazard model for time-to-event analysis BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-24 Dina Voeltz, Annika Hoyer, Amelie Forkel, Anke Schwandt, Oliver Kuß
In recent years, the use of non- and semi-parametric models which estimate hazard ratios for analysing time-to-event outcomes is continuously criticized in terms of interpretation, technical implementation, and flexibility. Hazard ratios in particular are critically discussed for their misleading interpretation as relative risks and their non-collapsibility. Additive hazard models do not have these
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Treatment effect estimation using the propensity score in clinical trials with historical control BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-22 Saki Kanamori, Masahiro Takeuchi
Clinical trials assessing new treatment effects require a control group to compare the pure treatment effects. However, in clinical trials on regenerative medicine, rare diseases, and intractable diseases, it may be ethically difficult to assign participants to the control group. In recent years, the use of historical control data has attracted attention as a method for supplementing the number of
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Barriers and facilitators for recruiting and retaining male participants into longitudinal health research: a systematic review BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-22 Danielle J. Borg, Melina Haritopoulou-Sinanidou, Pam Gabrovska, Hsu-Wen Tseng, David Honeyman, Daniel Schweitzer, Kym M. Rae
Successfully recruiting male participants to complete a healthcare related study is important for healthcare study completion and to advance our clinical knowledgebase. To date, most research studies have examined the barriers and facilitators of female participants in longitudinal healthcare-related studies with limited information available about the needs of males in longitudinal research. This
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A scoping review on the methodological and reporting quality of scoping reviews in China BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-22 Xinyu Xue, Xintong Tang, Shanshan Liu, Ting Yu, Zhonglan Chen, Ningsu Chen, Jiajie Yu
Scoping reviews have emerged as a valuable method for synthesizing emerging evidence, providing a comprehensive contextual overview, and influencing policy and practice developments. The objective of this study is to provide an overview of scoping reviews conducted in Chinese academic institutions over the last decades. We conducted a comprehensive search of nine databases and six grey literature databases
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Smoothed quantile residual life regression analysis with application to the Korea HIV/AIDS cohort study BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-17 Soo Min Kim, Yunsu Choi, Sangwook Kang, Korea HIV/AIDS cohort study
The residual life of a patient with human immunodeficiency virus (HIV) is of major interest to patients and their physicians. While existing analyses of HIV patient survival focus mostly on data collected at baseline, residual life analysis allows for dynamic analysis based on additional data collected over a period of time. As survival times typically exhibit a right-skewed distribution, the median
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How do quantitative studies involving people with dementia report experiences of standardised data collection? A narrative synthesis of NIHR published studies BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-16 Kate Gridley, Kate Baxter, Yvonne Birks
People with dementia are routinely included as research participants in trials and other quantitative studies in which they are invited to respond to standardised measures. This paper reviews the reporting of standardised data collection from people with dementia in reports published in the National Institute for Health and Care Research (NIHR) Journals Library. The aim was to understand how the administration
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Group sequential designs for pragmatic clinical trials with early outcomes: methods and guidance for planning and implementation BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-16 Nick R. Parsons, Joydeep Basu, Nigel Stallard
Group sequential designs are one of the most widely used methodologies for adaptive design in randomized clinical trials. In settings where early outcomes are available, they offer large gains in efficiency compared to a fixed design. However, such designs are underused and used predominantly in therapeutic areas where there is expertise and experience in implementation. One barrier to their greater
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Comparison of the effects of imputation methods for missing data in predictive modelling of cohort study datasets BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-16 JiaHang Li, ShuXia Guo, RuLin Ma, Jia He, XiangHui Zhang, DongSheng Rui, YuSong Ding, Yu Li, LeYao Jian, Jing Cheng, Heng Guo
Missing data is frequently an inevitable issue in cohort studies and it can adversely affect the study's findings. We assess the effectiveness of eight frequently utilized statistical and machine learning (ML) imputation methods for dealing with missing data in predictive modelling of cohort study datasets. This evaluation is based on real data and predictive models for cardiovascular disease (CVD)
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Extraction frequent patterns in trauma dataset based on automatic generation of minimum support and feature weighting BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-16 Zahra Kohzadi, Ali Mohammad Nickfarjam, Leila Shokrizadeh Arani, Zeinab Kohzadi, Mehrdad Mahdian
Data mining has been used to help discover Frequent patterns in health data. it is widely used to diagnose and prevent various diseases and to obtain the causes and factors affecting diseases. Therefore, the aim of the present study is to discover frequent patterns in the data of the Kashan Trauma Registry based on a new method. We utilized real data from the Kashan Trauma Registry. After pre-processing
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Comparing Bayesian hierarchical meta-regression methods and evaluating the influence of priors for evaluations of surrogate endpoints on heterogeneous collections of clinical trials BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-16 Willem Collier, Benjamin Haaland, Lesley A. Inker, Hiddo J.L. Heerspink, Tom Greene
Surrogate endpoints, such as those of interest in chronic kidney disease (CKD), are often evaluated using Bayesian meta-regression. Trials used for the analysis can evaluate a variety of interventions for different sub-classifications of disease, which can introduce two additional goals in the analysis. The first is to infer the quality of the surrogate within specific trial subgroups defined by disease
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Identifying biologically implausible values in big longitudinal data: an example applied to child growth data from the Brazilian food and nutrition surveillance system BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-15 Juliana Freitas de Mello e Silva, Natanael de Jesus Silva, Thaís Rangel Bousquet Carrilho, Elizabete de Jesus Pinto, Aline Santos Rocha, Jéssica Pedroso, Sara Araújo Silva, Ana Maria Spaniol, Rafaella da Costa Santin de Andrade, Gisele Ane Bortolini, Enny Paixão, Gilberto Kac, Rita de Cássia Ribeiro-Silva, Maurício L. Barreto
Several strategies for identifying biologically implausible values in longitudinal anthropometric data have recently been proposed, but the suitability of these strategies for large population datasets needs to be better understood. This study evaluated the impact of removing population outliers and the additional value of identifying and removing longitudinal outliers on the trajectories of length/height
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Modeling heart rate of individual and team manual handling with one hand using generalized additive mixed models BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-15 Mohammad Hamed Hosseini, Rashid Heidarimoghaddam, Mehrdad Anbarian, Saeed Ilbeigi, Leili Tapak
Despite the fact that team manual handling is common in different working environments, the previous studies in this regard, particularly those with a physiological approach are quite limited. The present study is an attempt to model the heart rate (HR) of individual and team manual handling with one hand. Twenty-five young men (aged 21.24±1.42 year) volunteered for this study. The experiments included
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Calibration and XGBoost reweighting to reduce coverage and non-response biases in overlapping panel surveys: application to the Healthcare and Social Survey BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-15 Luis Castro, María del Mar Rueda, Carmen Sánchez-Cantalejo, Ramón Ferri, Andrés Cabrera-León
Surveys have been used worldwide to provide information on the COVID-19 pandemic impact so as to prepare and deliver an effective Public Health response. Overlapping panel surveys allow longitudinal estimates and more accurate cross-sectional estimates to be obtained thanks to the larger sample size. However, the problem of non-response is particularly aggravated in the case of panel surveys due to
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Contextual effects: how to, and how not to, quantify them BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-13 Tobias Saueressig, Hugo Pedder, Patrick J Owen, Daniel L Belavy
The importance of contextual effects and their roles in clinical care controversial. A Cochrane review published in 2010 concluded that placebo interventions lack important clinical effects overall, but that placebo interventions can influence patient-reported outcomes such as pain and nausea. However, systematic reviews published after 2010 estimated greater contextual effects than the Cochrane review
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A data-adaptive method for investigating effect heterogeneity with high-dimensional covariates in Mendelian randomization BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-10 Haodong Tian, Brian D. M. Tom, Stephen Burgess
Mendelian randomization is a popular method for causal inference with observational data that uses genetic variants as instrumental variables. Similarly to a randomized trial, a standard Mendelian randomization analysis estimates the population-averaged effect of an exposure on an outcome. Dividing the population into subgroups can reveal effect heterogeneity to inform who would most benefit from intervention
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An evaluation of the EASY instrument in a cross-sectional study BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-10 Julie Agel, Umesh Ghimire, Nicholas M. Edwards, Bradley Nelson, Todd Rockwood
The purpose of this paper is to evaluate the impact of modifying the published scoring system to address identified potential weaknesses in the published scoring system for the Evaluation of Activity Surveys in Youth (EASY). A secondary purpose was to evaluate the EASY on children in Grades 1–5. The EASY is a self-report physical activity instrument for youth. Original EASY survey results were collected
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Model-based standardization using multiple imputation BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-10 Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
When studying the association between treatment and a clinical outcome, a parametric multivariable model of the conditional outcome expectation is often used to adjust for covariates. The treatment coefficient of the outcome model targets a conditional treatment effect. Model-based standardization is typically applied to average the model predictions over the target covariate distribution, and generate
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Comparison of statistical methods used to meta-analyse results from interrupted time series studies: an empirical study BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-10 Elizabeth Korevaar, Simon L. Turner, Andrew B. Forbes, Amalia Karahalios, Monica Taljaard, Joanne E. McKenzie
The Interrupted Time Series (ITS) is a robust design for evaluating public health and policy interventions or exposures when randomisation may be infeasible. Several statistical methods are available for the analysis and meta-analysis of ITS studies. We sought to empirically compare available methods when applied to real-world ITS data. We sourced ITS data from published meta-analyses to create an
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Estimating cutoff values for diagnostic tests to achieve target specificity using extreme value theory BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-08 Sierra Pugh, Bailey K. Fosdick, Mary Nehring, Emily N. Gallichotte, Sue VandeWoude, Ander Wilson
Rapidly developing tests for emerging diseases is critical for early disease monitoring. In the early stages of an epidemic, when low prevalences are expected, high specificity tests are desired to avoid numerous false positives. Selecting a cutoff to classify positive and negative test results that has the desired operating characteristics, such as specificity, is challenging for new tests because
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Designing tailored maintenance strategies for systematic reviews and clinical practice guidelines using the Portfolio Maintenance by Test-Treatment (POMBYTT) framework BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-02 Michiel S. Oerbekke, Roy G. Elbers, Maarten J. van der Laan, Lotty Hooft
Organizations face diverse contexts and requirements when updating and maintaining their portfolio, or pool, of systematic reviews or clinical practice guidelines they need to manage. We aimed to develop a comprehensive, theoretical framework that might enable the design and tailoring of maintenance strategies for portfolios containing systematic reviews and guidelines. We employed a conceptual approach
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An empirical comparison of statistical methods for multiple cut-off diagnostic test accuracy meta-analysis of the Edinburgh postnatal depression scale (EPDS) depression screening tool using published results vs individual participant data BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-01 Zelalem F. Negeri, Brooke Levis, John P. A. Ioannidis, Brett D. Thombs, Andrea Benedetti
Selective reporting of results from only well-performing cut-offs leads to biased estimates of accuracy in primary studies of questionnaire-based screening tools and in meta-analyses that synthesize results. Individual participant data meta-analysis (IPDMA) of sensitivity and specificity at each cut-off via bivariate random-effects models (BREMs) can overcome this problem. However, IPDMA is laborious
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A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the USA BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-02-01 William A. Walters, Catherine Ley, Trevor Hastie, Ruth E. Ley, Julie Parsonnet
Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis–Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated whether this equation could be used to interpolate missing growth data in children in the first
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Gaussian process emulation to improve efficiency of computationally intensive multidisease models: a practical tutorial with adaptable R code BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-27 Sharon Jepkorir Sawe, Richard Mugo, Marta Wilson-Barthes, Brianna Osetinsky, Stavroula A. Chrysanthopoulou, Faith Yego, Ann Mwangi, Omar Galárraga
The rapidly growing burden of non-communicable diseases (NCDs) among people living with HIV in sub-Saharan Africa (SSA) has expanded the number of multidisease models predicting future care needs and health system priorities. Usefulness of these models depends on their ability to replicate real-life data and be readily understood and applied by public health decision-makers; yet existing simulation
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Bayesian Mendelian randomization with an interval causal null hypothesis: ternary decision rules and loss function calibration BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-27 Linyi Zou, Teresa Fazia, Hui Guo, Carlo Berzuini
We enhance the Bayesian Mendelian Randomization (MR) framework of Berzuini et al. (Biostatistics 21(1):86–101, 2018) by allowing for interval null causal hypotheses, where values of the causal effect parameter that fall within a user-specified interval of “practical equivalence” (ROPE) (Kruschke, Adv Methods Pract Psychol Sci 1(2):270–80, 2018) are regarded as equivalent to “no effect”. We motivate
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Health estimate differences between six independent web surveys: different web surveys, different results? BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-27 Rainer Schnell, Jonas Klingwort
Most general population web surveys are based on online panels maintained by commercial survey agencies. Many of these panels are based on non-probability samples. However, survey agencies differ in their panel selection and management strategies. Little is known if these different strategies cause differences in survey estimates. This paper presents the results of a systematic study designed to analyze
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A time series driven model for early sepsis prediction based on transformer module BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-25 Yan Tang, Yu Zhang, Jiaxi Li
Sepsis remains a critical concern in intensive care units due to its high mortality rate. Early identification and intervention are paramount to improving patient outcomes. In this study, we have proposed predictive models for early sepsis prediction based on time-series data, utilizing both CNN-Transformer and LSTM-Transformer architectures. By collecting time-series data from patients at 4, 8, and
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Comparison of Pocock and Simon’s covariate-adaptive randomization procedures in clinical trials BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-25 Guogen Shan, Yulin Li, Xinlin Lu, Yahui Zhang, Samuel S. Wu
When multiple influential covariates need to be balanced during a clinical trial, stratified blocked randomization and covariate-adaptive randomization procedures are frequently used in trials to prevent bias and enhance the validity of data analysis results. The latter approach is increasingly used in practice for a study with multiple covariates and limited sample sizes. Among a group of these approaches
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Estimation of place-based vulnerability scores for HIV viral non-suppression: an application leveraging data from a cohort of people with histories of using drugs BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-25 Trang Quynh Nguyen, Laken C. Roberts Lavigne, Carly Lupton Brantner, Gregory D. Kirk, Shruti H. Mehta, Sabriya L. Linton
The relationships between place (e.g., neighborhood) and HIV are commonly investigated. As measurements of place are multivariate, most studies apply some dimension reduction, resulting in one variable (or a small number of variables), which is then used to characterize place. Typical dimension reduction methods seek to capture the most variance of the raw items, resulting in a type of summary variable
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Navigating PROSPERO4animals: 10 top tips for efficient pre-registration of your animal systematic review protocol BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-24 Alexandra Bannach-Brown, Torsten Rackoll, Nurcennet Kaynak, Natascha Drude, René Aquarius, Sofija Vojvodić, Mariana Abreu, Julia M. L. Menon, Kimberley E. Wever
Systematic reviews are an essential tool in identifying knowledge gaps and synthesizing evidence from in vivo animal research to improve human health. The review process follows an explicit and systematic methodology to minimize bias, but is not immune to biases or methodological flaws. Pre-registering a systematic review protocol has several benefits, including avoiding unplanned duplication of reviews
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Exploring trial publication and research waste in COVID-19 randomised trials of hydroxychloroquine, corticosteroids, and vitamin D: a meta-epidemiological cohort study BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-23 Lisa Fincham, Ameer Hohlfeld, Mike Clarke, Tamara Kredo, Michael McCaul
The global research response to the COVID-19 pandemic was impressive, but also led to an infodemic and considerable research waste. Registered, but unpublished trials added to this noise. We aimed to determine the proportion of registered randomised trials of common COVID-19 treatments that were published and to describe the characteristics of these trials to examine the association between trial characteristics
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Understanding facilitators of research participation among adults with self-reported chronic pain – a survey examining hypothetical research participation BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-22 Charles Start, Meagan McBride, Guohao Zhu, Sana Shaikh, Jennifer Pierce
An inability to successfully recruit participants into clinical research has consequences that negatively affect the conduct and reliability of research studies. Understanding facilitators of research participation, namely motives for participation and preferred research outcomes, may improve recruitment and retention of clinical trials related to chronic pain. The present study explored research participation
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A cautionary tale: an evaluation of the performance of treatment switching adjustment methods in a real world case study BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-22 Nicholas R Latimer, Alice Dewdney, Marco Campioni
Treatment switching in randomised controlled trials (RCTs) is a problem for health technology assessment when substantial proportions of patients switch onto effective treatments that would not be available in standard clinical practice. Often statistical methods are used to adjust for switching: these can be applied in different ways, and performance has been assessed in simulation studies, but not
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Predicting lung cancer survival prognosis based on the conditional survival bayesian network BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-22 Lu Zhong, Fan Yang, Shanshan Sun, Lijie Wang, Hong Yu, Xiushan Nie, Ailing Liu, Ning Xu, Lanfang Zhang, Mingjuan Zhang, Yue Qi, Huaijun Ji, Guiyuan Liu, Huan Zhao, Yinan Jiang, Jingyi Li, Chengcun Song, Xin Yu, Liu Yang, Jinchao Yu, Hu Feng, Xiaolei Guo, Fujun Yang, Fuzhong Xue
Lung cancer is a leading cause of cancer deaths and imposes an enormous economic burden on patients. It is important to develop an accurate risk assessment model to determine the appropriate treatment for patients after an initial lung cancer diagnosis. The Cox proportional hazards model is mainly employed in survival analysis. However, real-world medical data are usually incomplete, posing a great
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Extension of a conditional performance score for sample size recalculation rules to the setting of binary endpoints BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-19 Björn Bokelmann, Geraldine Rauch, Jan Meis, Meinhard Kieser, Carolin Herrmann
Sample size calculation is a central aspect in planning of clinical trials. The sample size is calculated based on parameter assumptions, like the treatment effect and the endpoint’s variance. A fundamental problem of this approach is that the true distribution parameters are not known before the trial. Hence, sample size calculation always contains a certain degree of uncertainty, leading to the risk
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Evaluation and comparison of spatial cluster detection methods for improved decision making of disease surveillance: a case study of national dengue surveillance in Thailand BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-19 Chawarat Rotejanaprasert, Kawin Chinpong, Andrew B. Lawson, Peerut Chienwichai, Richard J. Maude
Dengue is a mosquito-borne disease that causes over 300 million infections worldwide each year with no specific treatment available. Effective surveillance systems are needed for outbreak detection and resource allocation. Spatial cluster detection methods are commonly used, but no general guidance exists on the most appropriate method for dengue surveillance. Therefore, a comprehensive study is needed
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Novel linkage approach to join community-acquired and national data BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-17 Claire Tochel, Emma Pead, Alice McTrusty, Fiona Buckmaster, Tom MacGillivray, Andrew J. Tatham, Niall C. Strang, Baljean Dhillon, Miguel O. Bernabeu
Community optometrists in Scotland have performed regular free-at-point-of-care eye examinations for all, for over 15 years. Eye examinations include retinal imaging but image storage is fragmented and they are not used for research. The Scottish Collaborative Optometry-Ophthalmology Network e-research project aimed to collect these images and create a repository linked to routinely collected healthcare
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Seamless phase 2/3 design for trials with multiple co-primary endpoints using Bayesian predictive power BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-17 Jiaying Yang, Guochun Li, Dongqing Yang, Juan Wu, Junqin Wang, Xingsu Gao, Pei Liu
Seamless phase 2/3 design has become increasingly popular in clinical trials with a single endpoint. Trials that define success based on the achievement of all co-primary endpoints (CPEs) encounter the challenge of inflated type 2 error rates, often leading to an overly large sample size. To tackle this challenge, we introduced a seamless phase 2/3 design strategy that employs Bayesian predictive power
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Implementing the time-to-event continual reassessment method in the presence of partial orders in a phase I head and neck cancer trial BMC Med. Res. Methodol. (IF 4.0) Pub Date : 2024-01-13 Amit Patel, Kristian Brock, Daniel Slade, Claire Gaunt, Anthony Kong, Hisham Mehanna, Lucinda Billingham, Piers Gaunt
In this article we describe the methodology of the time-to-event continual reassessment method in the presence of partial orders (PO-TITE-CRM) and the process of implementing this trial design into a phase I trial in head and neck cancer called ADePT-DDR. The ADePT-DDR trial aims to find the maximum tolerated dose of an ATR inhibitor given in conjunction with radiotherapy in patients with head and