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In cardiovascular (CV) trials, analyzing the total number of events, rather than just time-to-first event, enhances understanding of participants' health. Adapting Cox models to account for between-subject het...
To develop a Chinese visual analogue scale (VAS) value set for Europe Quality of Life Questionnaire (EQ-5D-3L) and compare it with the time trade-off (TTO) value set which was constructed based on the same sam...
Difference in Restricted Mean Survival Time (DRMST) has attracted attention and is increasingly used in non-inferiority (NI) trials because of its superior power in detecting treatment effects compared to haza...
Whilst interest in efficient trial design has grown with the use of electronic health records (EHRs) to collect trial outcomes, practical challenges remain. Commonly raised concerns often revolve around data a...
Accumulating evidence demonstrates that miRNAs exhibit enhanced diagnostic sensitivity and specificity compared to the conventional hepatocellular carcinoma (HCC) biomarker alpha-fetoprotein (AFP), particularl...
Identifying and understanding disease risk factors is crucial in epidemiology, particularly for chronic and noncommunicable diseases that often have complex interrelationships. Traditional statistical methods ...
Value-adaptive designs for clinical trials are a novel set of emerging methods for delivering greater value for clinical research. There is increasing interest in using them within publicly funded health syste...
There is still demand for algorithms that can be used at the point of care, especially when dealing with events that do not present with a single obvious clinical indicator. The Spiegelhalter-Knill-Jones (SKJ)...
Gold standards used in validation of new tests may be imperfect, with sensitivity or specificity less than 100%. The impact of imperfection in a gold standard on measured test attributes has been demonstrated ...
With the rise of large language models, the application of artificial intelligence in research is expanding, possibly accelerating specific stages of the research processes. This study aims to compare the accu...
Multiple treatment options frequently exist for a single medical condition with no single standard of care (SoC), rendering a classic randomised trial comparing a specific treatment to a control treatment infe...
This article describes how withdrawals and exclusions of study participants can be managed in COVID-19-cohort studies by NUKLEUS (German: NUM Klinische Epidemiologie- und Studienplattform), using NAPKON (Germa...
Most diagnostic accuracy studies have applied a complete case analysis (CCA) or single imputation approach to address missing values in the index test, which may lead to biased results. Therefore, this simulat...
The widespread use of long-term pharmacological treatments for chronic conditions has led to polypharmacy, raising concerns about adverse effects and interactions. Deprescribing, the discontinuation of drugs w...
Population-based, age-standardized net survival estimates provide valuable insights for comparing the effectiveness of cancer treatment and the prospects of cure in an international context. Although numerous ...
In biomedical research, the calculation of sample size is a critical component of study design. Adequate sample size ensures the reliability of statistical tests, including the chi-square test. This manuscript...
In a wide range of diseases, it is necessary to utilize multiple data sources to obtain enough data for model training. However, performing centralized pooling of multiple data sources, while protecting each p...
Evaluating recurrent events within a time-to-event analysis framework effectively utilizes all relevant information to address the clinical question of interest fully and has certain advantages in randomized c...
The standard regulatory approach to assess replication success is the two-trials rule, requiring both the original and the replication study to be significant with effect estimates in the same direction. The s...
Sharing clinical study data is endorsed by many funders and journals, international policy frameworks, and patients. Reuse of clinical study data demonstrably improves health research, and emerging technologie...
Time-to-event data is commonly used in non-inferiority clinical trials. While the hazard ratio is a popular summary measure in this context, the difference in restricted mean survival time has been theoretical...
Codelists play a crucial role in ensuring accurate and standardized communication within healthcare. However, preparation of high-quality codelists is a rigorous and time-consuming process. The literature focu...
Herein we coin the terms non-Markovian error and biased Markovian error to describe categories of scientific errors for which general progress within a field of study may be unlikely to result in scientific self-...
Many segments of the population are underrepresented in biomedical research (UBR). Lack of diversity in health research limits understanding of individual and population level differences and risks the general...
Understanding dose-response relationships is crucial in optimizing clinical outcomes, particularly in complex interventions such as psychotherapy. While dose-response research is common in pharmaceutical conte...
Supervised machine learning is increasingly being used to estimate clinical predictive models. Several supervised machine learning models involve hyper-parameters, whose values must be judiciously specified to...
Consolidation of treatment effects from randomized controlled trials (RCT) is considered one of the highest forms of evidence in research. Cluster randomized trials (CRT) are increasingly used in the assessmen...
Finite mixture models have been recently applied in time-to-event data to identify subgroups with distinct hazard functions, yet they often assume differing covariate effects on failure times across latent cla...
Indirect treatment comparisons can provide evidence of relative efficacy for novel therapies when implementation of a randomised controlled trial is infeasible. However, such comparisons are vulnerable to unme...
Systematic reviews (SRs) are essential to formulate evidence-based guidelines but require time-consuming and costly literature screening. Large Language Models (LLMs) can be a powerful tool to expedite SRs.
The demand for rehabilitation services is rising due to the aging population and increasing number of chronic conditions. High-quality research is essential to address these challenges, with recent mandates em...
The Cass Review aimed to provide recommendations for the delivery of services for gender diverse children and young people in England. The final product of this project, the Cass report, relied on commissioned...
Staircase designs are incomplete stepped wedge designs that, unlike standard stepped wedge designs, require clusters to contribute data for only a limited number of trial periods. Previous work has provided fo...
Vulnerable subgroups of the population, such as care home residents, often face elevated mortality risks during crises like pandemics or wars. To correctly model and interpret the excess mortality of vulnerabl...
To perform a quantitative and qualitative analysis of spin bias in randomized clinical trials (RCTs) focusing on botulinum toxin (BTX-A) for managing bruxism.
Missing data are common in longitudinal studies. Multiple imputation (MI) is widely used to handle missing data. However, most of the MI methods assume various missing data types as missing at random (MAR) in ...
Restricted mean survival time (RMST) quantifies survival benefits in single-endpoint analysis, while restricted mean time lost (RMTL) measures event-related time loss in competing risks settings. Both provide ...
Diverse populations are more exposed to life course influences on adverse ageing, including brain ageing. Research into dementia in the United Kingdom inadvertently lacks diversity. Therefore, there is a need ...
REFRACT is a randomised trial aimed at rapidly evaluating multiple novel therapies against standard treatment for relapsed or refractory follicular lymphoma (rrFL) using a minimal number of patients. To this e...
The cluster randomised trial (CRT) design is increasingly used to evaluate the impact of school-based interventions for improving social-emotional functioning outcomes in pupils. Good knowledge is required on ...
Choice of survey administration features in surveys mapping population health may influence the participation and the generalizability of the results. This randomized study aimed to investigate whether three d...
There has been extensive debate about the role of social media and smartphone use in youth mental health and self-harm. Research to date lacks sufficient detail to determine the mechanisms underpinning any ass...
Pregnancy and birth cohort studies are essential for studying the social and biological determinants of human health, yet racial and ethnic minority populations are underrepresented due to low recruitment and ...
Large language models (LLMs) like ChatGPT showed great potential in aiding medical research. A heavy workload in filtering records is needed during the research process of evidence-based medicine, especially m...
Self-report methods are widely used to assess energy intake but are prone to measurement errors. We aimed to identify under-reported, over-reported, and plausible self-reported energy intake by dietary recalls...
Rare events data have proven difficult to explain and predict. Standard statistical procedures can sharply underestimate the probability of rare events, such as intravenous immune globulin therapy (IVIg) for b...
The aim of equality, equity, diversity, and inclusion (EDI) is to ensure fair treatment, equal opportunities, equitable outcomes, and representation. The NIHR Research Design Service (RDS) EDI toolkit (
Ecological analysis utilizes group-level aggregate measures to investigate the complex relationships between individuals or groups and their environment. Despite its extensive applications across various disci...
Machine learning models have been employed to predict COVID-19 infections and mortality, but many models were built on training and testing sets from different periods. The purpose of this study is to investig...
Expert panels are often used as a reference standard when no gold standard is available in diagnostic test accuracy research. It is often unclear what study and expert panel characteristics produce the best es...
Citation Impact
Journal Impact Factor: 3.9 (2023)
5-year Journal Impact Factor: 6.5 (2023)
Source Normalized Impact per Paper (SNIP): 1.732 (2024)
SCImago Journal Rank (SJR): 1.669 (2024)
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