A net-elastic penalized logistic regression model predicted 5-year survival in myxoid liposarcoma patients with an AUC of 0.85 in SEER testing data and 0.76 in an external institutional cohort.
Observational
Yes
Does a machine learning model accurately predict 5-year survival in patients with myxoid liposarcoma?
A newly developed machine-learning algorithm can predict 5-year survival in myxoid liposarcoma patients with good discrimination, providing a tool for prognostic assessment.
Effect estimate: AUC 0.85
BACKGROUND: Predicting survival in myxoid liposarcoma (MLS) patients is very challenging given its propensity to metastasize and the controversial role of adjuvant therapy. The purpose of this study was to develop a machine-learning algorithm for the prediction of survival at five years for patients with MLS and externally validate it using our institutional cohort. METHODS: Two databases, the surveillance, epidemiology, and end results program (SEER) database and an institutional database, were used in this study. Five machine learning models were created based on the SEER database and performance was rated using the TRIPOD criteria. The model that performed best on the SEER data was again tested on our institutional database. RESULTS: The net-elastic penalized logistic regression model was the best according to our performance indicators. This model had an area under the curve (AUC) of 0. 85 when compared to the SEER testing data and an AUC of 0. 76 when tested against institutional database. An application to use this calculator is available at https: //sorg-apps. shinyapps. io/myxoidₗiposarcoma/. CONCLUSION: MLS is a soft-tissue sarcoma with adjunct treatment options that are, in part, decided by prognostic survival. We developed the first machine-learning predictive algorithm specifically for MLS using the SEER registry that retained performance during external validation with institutional data.
Kamalapathy et al. (2021) conducted an observational in Myxoid liposarcoma (MLS). Machine-learning predictive algorithm (net-elastic penalized logistic regression) was evaluated on 5-year survival (AUC 0.85). A net-elastic penalized logistic regression model predicted 5-year survival in myxoid liposarcoma patients with an AUC of 0.85 in SEER testing data and 0.76 in an external institutional cohort.