The 5 SPADE symptoms (sleep, pain, anxiety, depression, and low energy/fatigue) are among the most prevalent and disabling symptoms in clinical practice. This study evaluates the minimally important difference (MID) of PROMIS measures and their correspondence with other brief measures to assess SPADE symptoms.
To demonstrate how decision analytic models (DAM) can be used to quantify impact of using a (diagnostic or prognostic) prediction model in clinical practice, and provide general guidance on how to perform such assessments.
In the scientific literature, ‘spin’ refers to reporting practices that make the study findings appear more favourable than results justify. The practice of ‘spin’ or misrepresentation and overinterpretation, may lead to an imbalanced and unjustified optimism in the interpretation of study results about performance of putative biomarkers. We aimed to classify spin (i.e., misrepresentation and overinterpretation of study findings), in recent clinical studies evaluating the performance of biomarkers in ovarian cancer.
The objective of this study was to assess the uptake of the rheumatoid arthritis core outcome set (RA-COS) using data from multiple data providers, and to investigate factors that may influence this uptake.
Data Abstraction Assistant (DAA) is a software for linking items abstracted into a data collection form for a systematic review to their locations in a study report. We conducted a randomized crossover trial that compared DAA-facilitated single data abstraction plus verification (“DAA verification”), single data abstraction plus verification (“regular verification”), and independent dual data abstraction plus adjudication (“independent abstraction”).
Patient recruitment in clinical trials is challenging with failure to recruit to time and target sample size common. This may be caused by unanticipated problems or by overestimation of the recruitment rate. This study is a systematic review of statistical models to predict recruitment at the design stage of clinical trials.