Related Experiment Video
Updated: Aug 12, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Improving Clinical Utility of Real-World Prediction Models: Updating Through Recalibration
Garrett S Bullock1,2, Ellen Shanley3,4,5, Charles A Thigpen3,4
1Department of Orthopaedic Surgery and Rehabilitation, Wake Forest School of Medicine, North Carolina.
Abstract:
Bullock, GS, Shanley, E, Thigpen, CA, Arden, NK, Noonan, TK, Kissenberth, MJ, Wyland, DJ, and Collins, GS. Improving clinical utility of real-world prediction models: updating through recalibration. J Strength Cond Res 37(5): 1057-1063, 2023-Prediction models can aid clinicians in identifying at-risk athletes. However, sport and clinical practice patterns continue to change, causing predictive drift and potential suboptimal prediction model performance. Thus, there is a need to temporally recalibrate previously developed baseball arm injury models. The purpose of this study was to perform temporal recalibration on a previously developed injury prediction model and assess model performance in professional baseball pitchers. An arm injury prediction model was developed on data from a prospective cohort from 2009 to 2019 on minor league pitchers. Data for the 2015-2019 seasons were used for temporal recalibration and model performance assessment. Temporal recalibration constituted intercept-only and full model redevelopment. Model performance was investigated by assessing Nagelkerke's R-square, calibration in the large, calibration, and discrimination. Decision curves compared the original model, temporal recalibrated model, and current best evidence-based practice. One hundred seventy-eight pitchers participated in the 2015-2019 seasons with 1.63 arm injuries per 1,000 athlete exposures. The temporal recalibrated intercept model demonstrated the best discrimination (0.81 [95% confidence interval [CI]: 0.73, 0.88]) and R-square (0.32) compared with original model (0.74 [95% CI: 0.69, 0.80]; R-square: 0.32) and the redeveloped model (0.80 [95% CI: 0.73, 0.87]; R-square: 0.30). The temporal recalibrated intercept model demonstrated an improved net benefit of 0.34 compared with current best evidence-based practice. The temporal recalibrated intercept model demonstrated the best model performance and clinical utility. Updating prediction models can account for changes in sport training over time and improve professional baseball arm injury outcomes.
Related Concept Videos
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Improving Translational Accuracy
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Errors occurring during blood pressure monitoring
Several factors...
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...

