Journal article
The preoperative machine learning algorithm for extremity metastatic disease can predict 90-day and 1-year survival: An external validation study
Journal of surgical oncology, Vol.125(2), pp.282-289
02/01/2022
DOI: 10.1002/jso.26708
PMID: 34608991
Abstract
Background The prediction of survival is valuable to optimize treatment of metastatic long-bone disease. The Skeletal Oncology Research Group (SORG) machine-learning (ML) algorithm has been previously developed and internally validated. The purpose of this study was to determine if the SORG ML algorithm accurately predicts 90-day and 1-year survival in an external metastatic long-bone disease patient cohort. Methods A retrospective review of 264 patients who underwent surgery for long-bone metastases between 2003 and 2019 was performed. Variables used in the stochastic gradient boosting SORG algorithm were age, sex, primary tumor type, visceral/brain metastases, systemic therapy, and 10 preoperative laboratory values. Model performance was calculated by discrimination, calibration, and overall performance. Results The SORG ML algorithms retained good discriminative ability (area under the cure [AUC]: 0.83; 95% confidence interval [CI]: 0.76-0.88 for 90-day mortality and AUC: 0.84; 95% CI: 0.79-0.88 for 1-year mortality), calibration, overall performance, and decision curve analysis. Conclusion The previously developed ML algorithms demonstrated good performance in the current study, thereby providing external validation. The models were incorporated into an accessible application () that may be freely utilized by clinicians in helping predict survival for individual patients and assist in informative decision-making discussion before operative management of long bone metastatic lesions.
Details
- Title: Subtitle
- The preoperative machine learning algorithm for extremity metastatic disease can predict 90-day and 1-year survival: An external validation study
- Creators
- Mary Kate Skalitzky - University of IowaTrevor R. Gulbrandsen - University of Iowa Hospitals and ClinicsOlivier Q. Groot - Massachusetts General HospitalAditya Karhade - Massachusetts General HospitalJorrit-Jan Verlaan - University Medical Center UtrechtJoseph H. Schwab - Massachusetts General HospitalBenjamin J. Miller - University of Iowa Hospitals and Clinics
- Resource Type
- Journal article
- Publication Details
- Journal of surgical oncology, Vol.125(2), pp.282-289
- Publisher
- Wiley
- DOI
- 10.1002/jso.26708
- PMID
- 34608991
- ISSN
- 0022-4790
- eISSN
- 1096-9098
- Number of pages
- 8
- Language
- English
- Date published
- 02/01/2022
- Academic Unit
- Orthopedics and Rehabilitation
- Record Identifier
- 9984303969402771
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