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Having an appropriate sample size is important when developing a clinical prediction model. We aimed to review how sample size is considered in studies developing a prediction model for a binary outcome.
Machine learning models promise to support diagnostic predictions, but may not perform well in new settings. Selecting the best model for a new setting without available data is challenging. We aimed to invest...
When conducting randomised controlled trials is impractical, an alternative is to carry out an observational study. However, making valid causal inferences from observational data is challenging because of the...
The current Evidence-Based-Medicine (EBM) approach is generally based on data coming from Randomized Clinical Trials or and, epidemiological observational studies. However, the past few years, with the explosi...
Declining response proportions in surveys have been observed internationally. Improving response proportions is important for the generalizability of the outcome. The aim of this study was to examine the poten...
The non-inferiority test is a reasonable approach to assessing a new treatment in a three-arm trial. The three-arm trial consists of a placebo, reference, and an experimental treatment. The non-inferiority is ...
Bayesian models have been applied throughout the Covid-19 pandemic especially to model time series of case counts or deaths. Fewer examples exist of spatio-temporal modeling, even though the spatial spread of ...
Longitudinal matching can mitigate confounding in observational, real-world studies of time-dependent treatments. To date, these methods have required iterative, manual re-specifications to achieve covariate b...
Electronic health records (EHRs) are widely accepted to enhance the health care quality, patient monitoring, and early prevention of various diseases, even when there is incomplete or missing information in them.
Historically, a priori power and sample size calculations have not been routinely performed cost-effectiveness analyses (CEA), partly because the absence of published cost and effectiveness correlation and var...
The Targeted Learning roadmap provides a systematic guide for generating and evaluating real-world evidence (RWE). From a regulatory perspective, RWE arises from diverse sources such as randomized controlled t...
Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations depends on the quality of data. Even thoug...
The original article was published in BMC Medical Research Methodology 2023 23:166
The main objective of this study is to evaluate the methodological quality and reporting quality of living systematic reviews (LSRs) on Coronavirus disease 2019 (COVID-19), while the secondary objective is to ...
Care pathways are increasingly being used to enhance the quality of care and optimize the use of resources for health care. Nevertheless, recommendations regarding the sequence of care are mostly based on cons...
The COVID-19 pandemic saw a steep increase in the number of rapidly published scientific studies, especially early in the pandemic. Some have suggested COVID-19 trial reporting is of lower quality than typical...
Efficient measurement of the receipt of cancer screening has been attempted with electronic health records (EHRs), but EHRs are commonly implemented within a single health care setting. However, health informa...
COVID-19 brought enormous challenges to public health surveillance and underscored the importance of developing and maintaining robust systems for accurate surveillance. As public health data collection effort...
In a potential epidemic of an emerging infection, representative population-based serologic studies are required to determine the extent of immunity to the infectious agent, either from natural infection or va...
Machine learning (ML) methods to build prediction models starting from electrocardiogram (ECG) signals are an emerging research field. The aim of the present study is to investigate the performances of two ML ...
Safety is an essential part of the evaluation of new medications and competing risks that occur in most clinical trials are a well identified challenge in the analysis of adverse events. Two statistical framew...
Medication adherence is usually defined as the extent of the agreement between the medication regimen agreed to by patients with their healthcare provider and the real-world implementation. Proactive identific...
Frailty, neurodegeneration and geriatric syndromes cause a significant impact at the clinical, social, and economic level, mainly in the context of the aging world. Recently, Information and Communication Tech...
The Correction to this article has been published in BMC Medical Research Methodology 2023 23:176
Measuring the performance of models that predict individualized treatment effect is challenging because the outcomes of two alternative treatments are inherently unobservable in one patient. The C-for-benefit ...
Adversity occurring during development is associated with detrimental health and quality of life outcomes, not just following exposure but throughout the lifespan. Despite increased research, there exists both...
The length of hospital stay (LOHS) caused by COVID-19 has imposed a financial burden, and cost on the healthcare service system and a high psychological burden on patients and health workers. The purpose of th...
Adaptive interventions are often used in individualized health care to meet the unique needs of clients. Recently, more researchers have adopted the Sequential Multiple Assignment Randomized Trial (SMART), a t...
Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for the first ...
Standard stepped wedge trials, where clusters switch from the control to the intervention condition in a staggered manner, can be costly and burdensome. Recent work has shown that the amount of information con...
Orofacial pain (OFP) is a highly prevalent disorder in mainland China that predisposes to an associated physical and psychological disability. There is lack of a good properties mainland Chinese version of ins...
The Oxford Elbow Score (OES) and the short version of Disabilities of Arms, Shoulder and Hand (QuickDASH) are common patient-reported outcomes for people with elbow problems. Our primary objective was to defin...
This study was conducted to evaluate the effect of alcohol consumption on breast cancer, adjusting for alcohol consumption misclassification bias and confounders.
No algorithms exist to identify important osteoarthritis (OA) patient subgroups (i.e., moderate-to-severe disease, inadequate response to pain treatments) in electronic healthcare data, possibly due to the com...
In the causal analysis of observational studies, covariates should be carefully balanced to approximate a randomized experiment. Numerous covariate balancing methods have been proposed for this purpose. Howeve...
Many scientific papers are published each year and substantial resources are spent to develop biomarker-based tests for precision oncology. However, only a handful of tests is currently used in daily clinical ...
The Correction to this article has been published in BMC Medical Research Methodology 2023 23:202
The rule of thumb that there is little gain in statistical power by obtaining more than 4 controls per case, is based on type-1 error α = 0.05. However, association studies that evaluate thousands or millions ...
Real-world data (RWD) and real-world evidence (RWE) have been paid more and more attention in recent years. We aimed to evaluate the reporting quality of cohort studies using real-world data (RWD) published be...
Clinical trial design must consider the specific resource constraints and overall goals of the drug development process (DDP); for example, in designing a phase I trial to evaluate the safety of a drug and rec...
Meta-analyses can be a powerful tool but need to calibrate potential unrepresentativeness of the included trials to a target population. Estimating target population average treatment effects (TATE) in meta-an...
Active-control trials, where an experimental treatment is compared with an established treatment, are performed when the inclusion of a placebo control group is deemed to be unethical. For time-to-event outcom...
Pragmatic clinical trials (PCTs) are designed to reflect how an investigational treatment would be applied in clinical practice. As such, unlike their explanatory counterparts, they measure therapeutic effecti...
To produce quality data that informs valid clinical trial results and withstands regulatory inspection, trial sites should adhere to many complex and dynamic requirements. Understanding non-conformance to requ...
Cochran’s Q statistic is routinely used for testing heterogeneity in meta-analysis. Its expected value (under an incorrect null distribution) is part of several popular estimators of the between-study variance,
To develop and validate a screening tool to identify patients with a high likelihood for Spondyloarthritis (SpA) in the Democratic Republic of the Congo (DR Congo).
Machine learning tools such as random forests provide important opportunities for modeling large, complex modern data generated in medicine. Unfortunately, when it comes to understanding why machine learning mode...
Up to 8% of the general population have a rare disease, however, for lack of ICD-10 codes for many rare diseases, this population cannot be generically identified in large medical datasets. We aimed to explore fr...
Improving the health and well-being of young people is a public health priority. Schools present an ideal setting to implement strategies to improve young people’s health and well-being. A key strategy involve...
The WHO model has laboratory-based and non-laboratory-based versions for 10-year risk prediction of cardiovascular diseases. Due to the fact that in some settings, there may not be the necessary facilities for...
Network meta-analysis (NMA) allows estimating and ranking the effects of several interventions for a clinical condition. Component network meta-analysis (CNMA) is an extension of NMA which considers the indivi...
Days alive without life support (DAWOLS) and similar outcomes that seek to summarise mortality and non-mortality experiences are increasingly used in critical care research. The use of these outcomes is challe...
Citation Impact 2023
Journal Impact Factor: 3.9
5-year Journal Impact Factor: 6.5
Source Normalized Impact per Paper (SNIP): 1.701
SCImago Journal Rank (SJR): 1.632
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Submission to first editorial decision (median days): 18
Submission to acceptance (median days): 210
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