Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer

Autor: Petersen, J.F., Stuiver, M.M., Timmermans, A.J., Chen, A., Zhang, H., O'Neill, J.P., Deady, S., Vander Poorten, V., Meulemans, J., Wennerberg, J., Skroder, C., Day, A.T., Koch, W., van den Brekel, M.W.M.
Přispěvatelé: Maxillofacial Surgery (AMC), MKA AMC (OII, ACTA), ACLC (FGw)
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: The Laryngoscope, 128(5), 1140-1145. John Wiley and Sons Inc.
Petersen, J F, Stuiver, M M, Timmermans, A J, Chen, A, Zhang, H, O'Neill, J P, Deady, S, Vander Poorten, V, Meulemans, J, Wennerberg, J, Skroder, C, Day, A T, Koch, W & van den Brekel, M W M 2018, ' Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer ', The Laryngoscope, vol. 128, no. 5, pp. 1140-1145 . https://doi.org/10.1002/lary.26990
The Laryngoscope, 128(5), 1140-1145. Wiley-Blackwell
ISSN: 0023-852X
DOI: 10.1002/lary.26990
Popis: Objectives/Hypothesis: TNM‐classification inadequately estimates patient‐specific overall survival (OS). We aimed to improve this by developing a risk‐prediction model for patients with advanced larynx cancer. Study Design: Cohort study. Methods: We developed a risk prediction model to estimate the 5‐year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. Results: We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P < .001). The model was able to distinguish well among three risk groups based on tertiles of the risk score. Adding treatment modality to the model did not decrease the predictive power. As a post hoc analysis, we tested the added value of comorbidity as scored by American Society of Anesthesiologists score in a subsample, which increased the C statistic to 0.68. Conclusions: A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5‐year survival rate when compared to a model based on T and N classification alone.
Databáze: OpenAIRE
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