BMC Medical Research Methodology

Abstract Background In the EvaCoM project, a retrospective cohort study of Germany-wide health insurance data of 29607 geriatric patients with fractures, the use of different time scales led to contradicting estimates in the Cox proportional hazards model. Here, the impact of quality audit, resulting in certification, of healthcare providers was of interest, with possible time scales being calend…

Abstract Extracting temporal information from unstructured clinical narratives is a foundational step toward automated patient timeline generation, a capability that has been proposed as having potential for rare disease diagnosis and care coordination, though prospective clinical validation remains future work. We present a comprehensive framework for temporal relation extraction from French cli…

Surrogate endpoints are often utilized to support drug efficacy claims. Hence, it is of paramount importance to validate the effectiveness of surrogate endpoints in correctly predicting clinical benefit, in order to ensure a fast and safe access to new drugs. This study aimed to explore the applicability of Receiver Operating Characteristic (ROC) curve and its Area Under Curve (AUC) for trial-lev…

Accurate measurement of smoking in population-based administrative health data (AHD) poses challenges due to the indirect nature of smoking-related information collection. While most studies use rule-based algorithms (RBAs) based on diagnosis codes, model-based algorithms (MBAs) utilizing machine learning (ML) with diverse data features might have better sensitivity and accuracy. We developed ML …

Futility analysis is a critical component of phase III oncology trials, enabling early termination of ineffective treatments to save resources and time. However, these interim analyses are often challenged by insufficient data for long-term primary endpoints, such as overall survival. A comprehensive simulation study was conducted to model various phase III trial scenarios. This simulation study …

Large electronic datasets do not always correctly identify women (defined as individuals whose sex assigned at birth was female, although we acknowledge that biological sex does not always correlate with gender identity) experiencing menopause or their symptoms, making it challenging to generate robust evidence on the burden of menopause. This study aimed to construct and characterize cohorts of …

Mixture cure models are widely used in survival analysis to represent populations comprising both cured and susceptible subgroups. Moving beyond conventional approaches that address isolated challenges, this study introduces an integrated systems framework for analyzing complex survival data. The proposed model simultaneously accounts for three interdependent components: (1) the existence of a cu…

The use of artificial intelligence (AI) in research has become one of the most hotly debated topics. This is particularly true for the field of evidence synthesis where automation through AI may lead to substantial time and resource savings. Many researchers see the potential benefits of using AI technologies, yet there is hesitation around embedding AI in practice. We explored the concerns of th…

Missing data may induce bias when analysing longitudinal population surveys. We aimed to tackle this problem in the 1970 British Cohort Study (BCS70). We utilised a data-driven approach to address missing data issues in BCS70. Our method consisted of a 3-step process to identify important predictors of non-response from a pool of ~ 20,000 variables from 9 sweeps in 18,037 individuals. We used par…

In-service examinations are widely used to monitor knowledge acquisition during postgraduate medical training. However, longitudinal interpretation of examination scores is limited by heterogeneity in test difficulty and the lack of psychometric calibration across assessments. Without appropriate adjustment, observed score changes may reflect examination variability rather than true learning prog…