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Getting access to administrative health data for research purposes is a difficult and time-consuming process due to increasingly demanding privacy regulations. An alternative method for sharing administrative ...
Combination therapies directed at multiple targets have potentially improved treatment effects for cancer patients. Compared to monotherapy, targeted combination therapy leads to an increasing number of subgro...
Overweight and obesity are severe public health problems worldwide. Obesity can lead to chronic diseases such as type 2 diabetes mellitus. Environmental factors may affect lifestyle aspects and are therefore e...
The effectiveness of malaria vector control interventions is often evaluated using cluster randomized trials (CRT) with outcomes assessed using repeated cross-sectional surveys. A key requirement for appropria...
‘A Measurement Tool to Assess Systematic Reviews, version 2’ (AMSTAR 2) is a validated 16-item scale designed to appraise systematic reviews (SRs) of healthcare interventions and to rate the overall confidence...
To control emerging diseases, governments often have to make decisions based on limited evidence. The effective or temporal reproductive number is used to estimate the expected number of new cases caused by an...
In evidence synthesis practice, dealing with studies with no cases in both arms has been a tough problem, for which there is no consensus in the research community. In this study, we propose a method to measur...
Baseline imbalance in covariates associated with the primary outcome in clinical trials leads to bias in the reporting of results. Standard practice is to mitigate that bias by stratifying by those covariates ...
The original article was published in BMC Medical Research Methodology 2010 10:1
Latent class models are increasingly used to estimate the sensitivity and specificity of diagnostic tests in the absence of a gold standard, and are commonly fitted using Bayesian methods. These models allow u...
Combinations of drugs are becoming increasingly common in oncology treatment. In some cases, patients can benefit from the interaction between two drugs, although there is usually a higher risk of developing t...
Science is becoming increasingly data intensive as digital innovations bring new capacity for continuous data generation and storage. This progress also brings challenges, as many scientific initiatives are ch...
Safe and effective vaccines are crucial for the control of Covid-19 and to protect individuals at higher risk of severe disease. The test-negative design is a popular option for evaluating the effectiveness of...
Longitudinal studies are critical to informing evolving responses to COVID-19 but can be hampered by attrition bias, which undermines their reliability for guiding policy and practice. We describe recruitment ...
The study aimed to explore reporting characteristics of scoping reviews in dental public health and the impact of some factors on the reporting quality.
A basket trial is a type of clinical trial in which eligibility is based on the presence of specific molecular characteristics across subpopulations with different cancer types. The existing basket designs wit...
In health research, several chronic diseases are susceptible to competing risks (CRs). Initially, statistical models (SM) were developed to estimate the cumulative incidence of an event in the presence of CRs....
Commercial activity trackers are increasingly used in research and compared with research-based accelerometers are often less intrusive, cheaper, with improved storage and battery capacity, although typically ...
Treatment switching, also called crossover, is common in clinical trials because of ethical concerns or other reasons. When it occurs and the primary objective is to identify treatment effects, the most widely...
The original article was published in BMC Medical Research Methodology 2022 22:219
Limited information is available about neonates’ critical conditions data quality. The study aim was to measure the agreement regarding presence of neonatal critical conditions between Medicaid Analytic eXtrac...
Multi-institution electronic health records (EHR) are a rich source of real world data (RWD) for generating real world evidence (RWE) regarding the utilization, benefits and harms of medical interventions. The...
Data-generating processes are key to the design of Monte Carlo simulations. It is important for investigators to be able to simulate data with specific characteristics.
Systematic reviews of studies of clinical prediction models are becoming increasingly abundant in the literature. Data extraction and risk of bias assessment are critical steps in any systematic review. CHARMS...
Researchers are cautioned against misinterpreting the conventional P value, especially while implementing the popular t test. Therefore, this study evaluated the agreement between the P value and Bayes factor (BF
Despite recent advances in causal inference methods, outcome regression remains the most widely used approach for estimating causal effects in epidemiological studies with a single-point exposure and outcome. ...
Propensity score analysis is increasingly used to control for confounding factors in observational studies. Unfortunately, unavoidable missing values make estimating propensity scores extremely challenging. We...
Multi-state models are complex stochastic models which focus on pathways defined by the temporal and sequential occurrence of numerous events of interest. In particular, the so-called illness-death models are ...
Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimati...
The original article was published in BMC Medical Research Methodology 2023 23:14
When quantifying differences in health outcomes between immigrants and non-immigrants, it is common practice to adjust for observed differences in outcome risk factors between the groups being compared. Howeve...
Patient-reported outcomes such as health-related quality of life (HRQoL) are increasingly used as endpoints in randomized cancer clinical trials. However, the patients often drop out so that observation of the...
Composite endpoints for estimating treatment efficacy are routinely used in several therapeutic areas and have become complex in the number and types of component outcomes included. It is assumed that its comp...
This analysis addresses the characteristics of two emergency department (ED) patient populations defined by three model diseases (hip fractures, respiratory, and cardiac symptoms) making use of survey (primary...
There is increasing interest in clinical prediction models for rare outcomes such as suicide, psychiatric hospitalizations, and opioid overdose. Accurate model validation is needed to guide model selection and...
The original article was published in BMC Medical Research Methodology 2023 23:8
A previously developed decision model to prioritize surgical procedures in times of scarce surgical capacity used quality of life (QoL) primarily derived from experts in one center. These estimates are key inp...
Diagnostic tests are important in clinical medicine. To determine the test performance indices — test sensitivity, specificity, likelihood ratio, predictive values, etc. — the test results should be compared a...
There are an estimated 460,000 Armenians in the United States, and more than half live in California. Armenian-Americans are generally represented within the ‘White’ or ‘Some Other Race’ race categories in pop...
The original article was published in BMC Medical Research Methodology 2023 23:10
The registration of clinical trials is required by law in Switzerland. We investigated (1) the proportion of registered and prospectively registered clinical trials, (2) the availability of results for ethical...
The original article was published in BMC Medical Research Methodology 2023 23:1
Numerous clinical trials have been initiated to find effective treatments for COVID-19. These trials have often been initiated in regions where the pandemic has already peaked. Consequently, achieving full enr...
One of the main challenges of the COVID-19 pandemic is to make sense of available, but often heterogeneous and noisy data. This contribution presents a data-driven methodology that allows exploring the hospita...
Multivariate longitudinal data are under-utilized for survival analysis compared to cross-sectional data (CS - data collected once across cohort). Particularly in cardiovascular risk prediction, despite availa...
The Pooled Cohort Equations (PCEs) are race- and sex-specific Cox proportional hazards (PH)-based models used for 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction with acceptable discrimi...
Patient-reported physical function (PF) is a key endpoint in cancer clinical trials. Using complex statistical methods, common metrics have been developed to compare scores from different patient-reported outc...
Reporting quality is a critical issue in health sciences. Adopting the reporting guidelines has been approved to be an effective way of enhancing the reporting quality and transparency of clinical research. In...
Advantages of meta-analysis depend on the assumptions underlying the statistical procedures used being met. One of the main assumptions that is usually taken for granted is the normality underlying the populat...
To have confidence in one's interpretation of treatment effects assessed by comparing trial results to external controls, minimizing bias is a critical step. We sought to investigate different methods for caus...
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