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The validity of self-reported chronic conditions has been assessed by comparing them with medical records or register data in several studies. However, the reliability of self-reports of chronic diseases has l...
Meta-analysis poses a challenge when original study results have been expressed in a non-uniform manner, such as when regression results from some original studies were based on a log-transformed key independe...
In the last decades, medical research fields studying rare conditions such as spinal cord injury (SCI) have made extensive efforts to collect large-scale data. However, most analysis methods rely on complete d...
Identification of difficult laryngoscopy is a frequent demand in cervical spondylosis clinical surgery. This work aims to develop a hybrid architecture for identifying difficult laryngoscopy based on new indexes.
In any single-arm trial on novel treatments, assessment of toxicity plays an important role as occurrence of adverse events (AEs) is relevant for application in clinical practice. In the presence of a non-fata...
Estimation of mortality rates and mortality rate ratios (MRR) of diseased and non-diseased individuals is a core metric of disease impact used in chronic disease epidemiology. Estimation of mortality rates is ...
Effective care coordination may increase clinical efficiency, but its measurement remains difficult. The established metric “care density” (CD) measures care coordination based on patient-sharing among physici...
Implications for research (IfR) sections are an important part of systematic reviews (SRs) to inform health care researchers and policy makers. PRISMA 2020 recommends reporting IfR, while Cochrane Reviews requ...
To demonstrate bioequivalence between two drug formulations, a pilot trial is often conducted prior to a pivotal trial to assess feasibility and gain preliminary information about the treatment effect. Due to ...
Non-compliance is a common challenge for researchers and may reduce the power of an intention-to-treat analysis. Whilst a per protocol approach attempts to deal with this issue, it can result in biased estimat...
We recently developed a novel, preference-based method (Better-Worse, BW) for measuring health status, expressed as a single metric value. We have since expanded it by developing the Drop-Down (DD) method. Thi...
The Maximum Likelihood Estimator (MLE) for parameters of the gamma distribution is commonly used to estimate models of right-skewed variables such as costs, hospital length of stay, and appointment wait times ...
Across studies of average treatment effects, some population subgroups consistently have lower representation than others which can lead to discrepancies in how well results generalize.
Studying clinician-patient communication can be challenging, particularly when research seeks to explore cause-and-effect relationships. Video vignettes – hypothetical yet realistic scenarios – offer advantage...
Prospective cohorts may be vulnerable to bias due to attrition. Inverse probability weights have been proposed as a method to help mitigate this bias. The current study used the “All Our Families” longitudinal...
This research-on-research substudy uses a data-driven approach to investigate the range of appraisal tools in non-Cochrane systematic reviews and meta-analyses registered in the International Prospective Regis...
Using four case studies, we aim to provide practical guidance and recommendations for the analysis of cluster randomised controlled trials.
Complete reporting is essential for clinical research. However, the endorsement of reporting guidelines in radiological journals is still unclear. Further, as a field extensively utilizing artificial intellige...
This study introduces a novel method for estimating the variance of life expectancy since diagnosis (LEC) and loss in life expectancy (LLE) for cancer patients within a relative survival framework in situations w...
Indigenous experiences and perspectives of resilience, healing and recovery from trauma is gaining increasing attention, with a growing qualitative literature that spans multiple indigenous cultural groups. Ho...
In the past two decades, there has been a growing recognition of the need to establish indigenous standards or reference growth charts, particularly following the WHO multicenter growth study in 2006. The avai...
With continuous outcomes, the average causal effect is typically defined using a contrast of expected potential outcomes. However, in the presence of skewed outcome data, the expectation (population mean) may ...
Case-cohort studies are conducted within cohort studies, with the defining feature that collection of exposure data is limited to a subset of the cohort, leading to a large proportion of missing data by design...
Utilizing the traditional Cox regression model to identify the factors affecting the risk of mortality due to microinvasive cutaneous squamous cell carcinoma (micSCC) may produce skewed results. Since cause-sp...
Deep learning models have had a lot of success in various fields. However, on structured data they have struggled. Here we apply four state-of-the-art supervised deep learning models using the attention mechan...
Qualitative longitudinal research (QLR) is an emerging methodology used in health research. The method literature states that the change in a phenomenon through time should be the focus of any QLR study, but i...
Clinical practice guidelines (CPGs) are evaluated for quality with the Appraisal of Guidelines for Research and Evaluation (AGREE) tool, and this is increasingly done for different countries and regional group...
Health policy decisions are often informed by estimates of long-term survival based primarily on short-term data. A range of methods are available to include longer-term information, but there has previously b...
This study aimed to assess the methodological quality of the systematic reviews/meta-analyses (SRs/MAs) of chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) using A Measurement Tool to Assess systemat...
Automated feature selection methods such as the Least Absolute Shrinkage and Selection Operator (LASSO) have recently gained importance in the prediction of quality-related outcomes as well as the risk-adjustm...
Clinical trials often seek to determine the superiority, equivalence, or non-inferiority of an experimental condition (e.g., a new drug) compared to a control condition (e.g., a placebo or an already existing ...
Factors influencing the health of populations are subjects of interdisciplinary study. However, datasets relevant to public health often lack interdisciplinary breath. It is difficult to combine data on health...
The interrupted time series (ITS) design is widely used to examine the effects of large-scale public health interventions and has the highest level of evidence validity. However, there is a notable gap regardi...
Assessing malignancy risk is important to choose appropriate management of ovarian tumors. We compared six algorithms to estimate the probabilities that an ovarian tumor is benign, borderline malignant, stage ...
For certain conditions, treatments aim to lessen deterioration over time. A trial outcome could be change in a continuous measure, analysed using a random slopes model with a different slope in each treatment ...
Since 1997, research on Gulf War illness (GWI) has predominantly used 3 case definitions—the original Research definition, the CDC definition, and modifications of the Kansas definition—but they have not been ...
In most African countries, confirmed COVID-19 case counts underestimate the number of new SARS-CoV-2 infection cases. We propose a multiplying factor to approximate the number of biologically probable new infe...
Real world evidence is now accepted by authorities charged with assessing the benefits and harms of new therapies. Clinical trials based on real world evidence are much less expensive than randomized clinical ...
This systematic review aimed to identify effective methods to increase adolescents’ response to surveys about mental health and substance use, to improve the quality of survey information.
The design of clinical trials in rare diseases is often complicated by a lack of real-world translational knowledge. Fibrodysplasia ossificans progressiva (FOP) is an ultra-rare genetic disorder characterized ...
Despite the interest in machine learning (ML) algorithms for analyzing real-world data (RWD) in healthcare, the use of ML in predicting time-to-event data, a common scenario in clinical practice, is less explo...
Planning the design of a new trial comparing two treatments already in a network of trials with an a-priori plan to estimate the effect size using a network meta-analysis increases power or reduces the sample ...
There is growing interest in whether linked administrative data have the potential to aid analyses subject to missing data in cohort studies.
Suboptimal or slow recruitment affects 30–50% of trials. Education and training of trial recruiters has been identified as one strategy for potentially boosting recruitment to randomised controlled trials (her...
Consensus methods are crucial in developing clinical guidelines. Different methods, such as the Delphi and nominal group techniques, are commonly used, but there is a lack of detailed instructions on how to im...
Abstracts provide readers a concise and readily accessible information of the trials. However, poor reporting quality and spin (misrepresentation of research findings) can lead to an overestimation in trial va...
The concept of intersectionality proposes that demographic and social constructs intersect with larger social structures of oppression and privilege to shape experiences. While intersectionality is a widely ac...
Standard outcome sets enable the value-based evaluation of health care delivery. Whereas the attainment of expert opinion has been structured using methods such as the modified-Delphi process, standardized gui...
The original article was published in BMC Medical Research Methodology 2023 23:230
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