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External validation of the SORG 90-day and 1-year machine learning algorithms for survival in spinal metastatic disease

The Spine Journal Oct 29, 2019

Karhade AV, Ahmed AK, Pennington Z, et al. - In this retrospective study at a large, tertiary care center of individuals 18 years or older who underwent surgery between 2003 and 2016, experts externally authenticated these algorithms in an independent population from another institution. Overall, 176 individuals underwent surgery for spinal metastatic disease, of which 44 encountered 90-day mortality and 99 1-year mortality. Relative to primary tumor histology, metastatic tumor burden, former systemic therapy, overall comorbidity burden, and preoperative laboratory features, the validation cohort significantly varied from the developmental cohort. Irrespective of these variations, the SORG ML algorithms generalized well to the validation cohort on discrimination, calibration, Brier score, and decision curve analysis. In summary, for survival prognostication in spinal metastatic disease, initial results from external validation of the SORG ML 90-day and 1-year algorithms propose the potential use of these digital decision helps in clinical practice.
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