Improving Clinical Utility of Real-World Prediction Models: Updating Through Recalibration

被引:0
作者
Bullock, Garrett S. [1 ,2 ]
Shanley, Ellen [3 ,4 ,5 ]
Thigpen, Charles A. [3 ,4 ]
Arden, Nigel K. [2 ]
Noonan, Thomas K. [6 ,7 ]
Kissenberth, Michael J. [8 ]
Wyland, Douglas J. [5 ]
Collins, Gary S. [9 ,10 ]
机构
[1] Wake Forest Sch Med, Dept Orthopaed Surg & Rehabil, Winston Salem, NC 27101 USA
[2] Univ Oxford, Ctr Sport Exercise & Osteoarthritis Res Versus Art, Oxford, England
[3] Univ South Carolina, Ctr Rehabil & Reconstruct Sci, Greenville, SC USA
[4] ATI Phys Therapy, Greenville, SC USA
[5] Steadman Hawkins Clin Carolinas, Greenville, SC USA
[6] Univ Colorado, Dept Orthopaed Surg, Sch Med, Boulder, CO USA
[7] Univ Colorado Hlth, Steadman Hawkins Clin, Englewood, CO USA
[8] PRISMA Hlth, Greenville, SC USA
[9] Univ Oxford, Ctr Stat Med, Nuffield Dept Orthopaed Rheumatol & Musculoskeleta, Oxford, England
[10] Oxford Univ Hosp NHS Fdn Trust, Oxford, England
关键词
decision curve; net benefit; algorithm; intercept; SPORTS-MEDICINE; SHOULDER RANGE; ELBOW INJURY; RISK; MOTION; PREVENTION; YOUTH; CLASSIFICATION; VALIDATION; DIAGNOSIS;
D O I
10.1519/JSC.0000000000004369
中图分类号
G8 [体育];
学科分类号
04 ; 0403 ;
摘要
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.
引用
收藏
页码:1057 / 1063
页数:7
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