Login / Signup

Does the SORG Machine-learning Algorithm for Extremity Metastases Generalize to a Contemporary Cohort of Patients? Temporal Validation From 2016 to 2020.

Tom M de GrootDuncan RamseyOlivier Q GrootMitchell S FourmanAditya V KarhadePeter K TwiningEmily A BernerBrian P FennAustin Keith CollinsKevin RaskinSantiago A Lozano CalderónEric NewmanMarco FerroneJob N DoornbergJoseph H Schwab
Published in: Clinical orthopaedics and related research (2023)
The SORG MLA to predict survival after surgical treatment of extremity metastatic disease showed decreased performance on temporal validation. Moreover, in patients undergoing innovative immunotherapy, the possibility of mortality risk was overestimated in varying severity. Clinicians should be aware of this overestimation and discount the prediction of the SORG MLA according to their own experience with this patient population. Generally, these results show that temporal reassessment of these MLA-driven probability calculators is of paramount importance because the predictive performance may decline over time as treatment regimens evolve. The SORG-MLA is available as a freely accessible internet application at https://sorg-apps.shinyapps.io/extremitymetssurvival/.Level of Evidence Level III, prognostic study.
Keyphrases