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Adverse effects of drugs are often identified after market introduction. Post-marketing pharmacovigilance aims to detect them as early as possible and relies on spontaneous reporting systems collecting suspici...
There is an unmet need for review methods to support priority-setting, policy-making and strategic planning when a wide variety of interventions from differing disciplines may have the potential to impact a he...
Coronavirus disease (COVID-19) presents an unprecedented threat to global health worldwide. Accurately predicting the mortality risk among the infected individuals is crucial for prioritizing medical care and ...
Long-term behavioral and health risk factors constitute a primary focus of research on the etiology of chronic diseases. Yet, identifying critical time-windows during which risk factors have the strongest impa...
Questionnaires remain one of the most common forms of data collection in epidemiology, psychology and other human-sciences. However, results can be badly affected by non-response. One way to potentially reduce...
Eligibility guidelines in research trials are necessary to minimise confounds and reduce bias in the interpretation of potential treatment effects. There is limited extant research investigating how being deem...
Estimates of future survival can be a key evidence source when deciding if a medical treatment should be funded. Current practice is to use standard parametric models for generating extrapolations. Several eme...
Multi-state models are used in complex disease pathways to describe a process where an individual moves from one state to the next, taking into account competing states during each transition. In a multi-state...
AMSTAR-2 (‘A Measurement Tool to Assess Systematic Reviews, version 2’) and ROBIS (‘Risk of Bias in Systematic Reviews’) are independent instruments used to assess the quality of conduct of systematic reviews/...
Markov system dynamic (MSD) model has rarely been used in medical studies. The aim of this study was to evaluate the performance of MSD model in prediction of metabolic syndrome (MetS) natural history.
Missing outcome data can lead to bias in the results of systematic reviews. One way to address missing outcome data is by requesting the data from the trial authors, but non-response is common. One way to pote...
In many applications of instrumental variable (IV) methods, the treatments of interest are intrinsically time-varying and outcomes of interest are failure time outcomes. A common example is Mendelian randomiza...
Individual-patient data meta-analysis (IPD-MA) is an increasingly popular approach because of its analytical benefits. IPD-MA of observational studies must overcome the problem of confounding, otherwise biased...
Propensity score matching is a statistical method that is often used to make inferences on the treatment effects in observational studies. In recent years, there has been widespread use of the technique in the...
The COVID-19 pandemic has severely affected health systems and medical research worldwide but its impact on the global publication dynamics and non-COVID-19 research has not been measured. We hypothesized that...
Clinical trials routinely have patients lost to follow up. We propose a methodology to understand their possible effect on the results of statistical tests by altering the concept of the fragility index to tre...
The natural indirect effect (NIE) and mediation proportion (MP) are two measures of primary interest in mediation analysis. The standard approach for mediation analysis is through the product method, which inv...
The Oslo Sport Trauma Research Centre Questionnaire on Health Problems (OSTRC-H) has become a popular tool to monitor health status in athletes. Originally developed for adult athletes, the tool is today also ...
For valid accelerometer-assessed physical activity (PA) data, several methodological aspects should be considered. We aimed to 1) visualize the applicability of absolute accelerometer cut-offs to classify PA i...
Novartis and the University of Oxford’s Big Data Institute (BDI) have established a research alliance with the aim to improve health care and drug development by making it more efficient and targeted. Using a ...
Scleroderma is a serious chronic autoimmune disease in which a patient’s disease state manifests in several irregularly spaced longitudinal measures of lung, heart, skin, and other organ systems. Threshold cro...
Not all research findings are translated to clinical practice. Reasons for lack of applicability are varied, and multiple frameworks and criteria exist to appraise the general applicability of epidemiological ...
Participation of general practitioners is crucial for health care studies. However, recruiting them is an ongoing challenge and participation rates of general practitioners around the globe are often low. One ...
Although discontinuation is common in clinical trials, no study has been conducted to analyse the current situation and reasons for the suspension or discontinuation of drug clinical trials in China. This stud...
Multilevel logistic regression models are widely used in health sciences research to account for clustering in multilevel data when estimating effects on subject binary outcomes of individual-level and cluster...
Graphical displays and data visualization are essential components of statistical analysis that can lead to improved understanding of clinical trial adverse event (AE) data. Correspondence analysis (CA) has be...
The purpose of a conference abstract is to summarize the main points of a research-related report that will be presented at an academic conference. However, some conferences accept and publish abstracts withou...
Identifying successful strategies to improve participant retention in longitudinal studies remains a challenge. In this study we evaluated whether non-traditional fieldworker shifts (after hours during the wee...
Major adverse cardiovascular events (MACE) are increasingly used as composite outcomes in randomized controlled trials (RCTs) and observational studies. However, it is unclear how observational studies most co...
Previous research on data extraction methods in systematic reviews has focused on single aspects of the process. We aimed to provide a deeper insight into these methods by analysing a current sample of reviews.
Longitudinal assessments of usage are often conducted for multiple substances (e.g., cigarettes, alcohol and marijuana) and research interests are often focused on the inter-substance association. We propose a...
The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) can be used to transform observational health data to a common format. CDM transformation allows for analysis across disparate data...
While well-conducted systematic reviews (SRs) can provide the best evidence on the potential effectiveness of acupuncture, limitations on the methodological rigour of SRs may impact the trustworthiness of thei...
Research on germline genetic variants relies on enough eligible participants which is difficult to achieve for rare diseases such as childhood cancer. With self-collection kits, participants can contribute gen...
Re-randomisation trials involve re-enrolling and re-randomising patients for each new treatment episode they experience. They are often used when interest lies in the average effect of an intervention across a...
Electronic health records (EHRs) are widely used in epidemiological research, but the validity of the results is dependent upon the assumptions made about the healthcare system, the patient, and the provider. ...
Retaining participants over time is a frequent challenge in research studies evaluating long-term health outcomes. This study’s objective was to compare the impact of prepaid and postpaid incentives on respons...
Childhood malnutrition is a major cause of child mortality under the age of 5 in the sub-Saharan Africa region. This study sought to identify the risk factors and spatial distribution of the composite index of...
The COVID-19 public health crisis has produced an immense and quickly evolving body of evidence. This research speed and volume, along with variability in quality, could overwhelm public health decision-makers...
Patient satisfaction or experience with colorectal cancer screening can determine adherence to screening programs. An evaluation of validated patient reported outcome measures (PROMs) for measuring experience ...
This research work is elaborated investigation of COVID-19 data for Weibull distribution under indeterminacy using time truncated repetitive sampling plan. The proposed design parameters like sample size, acce...
After activation of the Hospital Readmission Reduction Program (HRRP) in 2012, hospitals nationwide experimented broadly with the implementation of Transitional Care (TC) strategies to reduce hospital readmiss...
Data harmonization is a powerful method to equilibrate items in measures that evaluate the same underlying construct. There are multiple measures to evaluate dementia related behavioral symptoms. Pre-statistic...
Mediation analysis methodology underwent many advancements throughout the years, with the most recent and important advancement being the development of causal mediation analysis based on the counterfactual fr...
There is a growing need for methods that acknowledge and successfully capture the dynamic interaction between context and implementation of complex interventions. Case study research has the potential to provi...
Network meta-analysis (NMA) has attracted growing interest in evidence-based medicine. Consistency between different sources of evidence is fundamental to the reliability of the NMA results. The purpose of the...
An increasing number of systematic reviews assessed the safety of surgical interventions over time. How well these systematic reviews were designed and conducted determines the reliability of evidence. In this...
Randomized controlled trials (RCTs), especially multicentric, with complex interventions are methodically challenging. Careful planning under everyday conditions in compliance with the relevant international q...
Statistical inference based on small datasets, commonly found in precision oncology, is subject to low power and high uncertainty. In these settings, drawing strong conclusions about future research utility is...
Patient Reported Outcomes (PROs) are subjective outcomes of disease and/or treatment in clinical research. For effective evaluations of PROs, high response rates are crucial. This study assessed the impact of ...
2022 Citation Impact
4.0 - 2-year Impact Factor
7.0 - 5-year Impact Factor
2.055 - SNIP (Source Normalized Impact per Paper)
1.778 - SJR (SCImago Journal Rank)
2023 Speed
40 days submission to first editorial decision for all manuscripts (Median)
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