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From Chronic to Acute Pain: Evaluating the baseline prognostic covariates in Severe Acute Lower Back Pain
The FDA’s 2023 guidance on baseline covariate adjustment highlights the importance of incorporating prognostic covariates into randomized clinical…
Predicting drop-out in early-stage Type 1 Diabetes clinical trials to improve retention through Personalized Engagement Strategies
Background: Patient non-adherence and drop-out increase the time and cost of clinical trials. A tool that predicts, at…
Improving Precision of Clinical Trials Results in T1 Diabetes with Transferrable Prognostic Models
Background: In randomized controlled trials (RCTs), assay sensitivity issues can affect both statistical power and the confidence in…
Predicting Patient Drop-Out in Clinical Trials: A First Step Toward Personalized Engagement Strategies
Objective: Patient non-adherence and drop-out significantly extend the duration and cost of clinical trials. A predictive tool identifying…
Prediction of the response to repetitive transcranial magnetic stimulation of the motor cortex in peripheral neuropathic pain and validation of a new algorithm
Abstract: Motor cortex repetitive transcranial magnetic stimulation (M1-rTMS) induces analgesic effects in neuropathic pain, but not all patients…
Self-Training in Pain Assessment as a Mediator of the Prognostic Performance of Pain Variability
Background and Aims Baseline Pain Variability (PV) is often cited as a key predictor of placebo response (1-3)….
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