Publication: Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort
Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort
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Pamporaki, C., Berends, A. M. A., Filippatos, A., Prodanov, T., Meuter, L., Prejbisz, A., Beuschlein, F., Fassnacht, M., Timmers, H. J. L. M., Nölting, S., Abhyankar, K., Constantinescu, G., Kunath, C., de Haas, R. J., Wang, K., Remde, H., Bornstein, S. R., Januszewicz, A., Robledo, M., … Eisenhofer, G. (2023). Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort. The Lancet Digital Health, 5(9), e551–e559. https://doi.org/10.1016/S2589-7500(23)00094-8
Abstract
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Abstract
BACKGROUND Pheochromocytomas and paragangliomas have up to a 20% rate of metastatic disease that cannot be reliably predicted. This study prospectively assessed whether the dopamine metabolite, methoxytyramine, might predict metastatic disease, whether predictions might be improved using machine learning models that incorporate other features, and how machine learning-based predictions compare with predictions made by specialists in the field.
METHODS In this machine learning modelling study, we used cross-sectional cohort data from
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Creators (Authors)
- Pamporaki, Christina
- Berends, Annika M A
- Filippatos, Angelos
- Prodanov, Tamara
- Meuter, Leah
- Prejbisz, Alexander
- Fassnacht, Martin
- Timmers, Henri J L M
- Nölting, Svenja
- Abhyankar, Kaushik
- Constantinescu, Georgiana
- Kunath, Carola
- de Haas, Robbert J
- Wang, Katharina
- Remde, Hanna
- Bornstein, Stefan R
- Januszewicz, Andrzeij
- Robledo, Mercedes
- Lenders, Jacques W M
- Kerstens, Michiel N
- Pacak, Karel
- Eisenhofer, Graeme
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Citations
Pamporaki, C., Berends, A. M. A., Filippatos, A., Prodanov, T., Meuter, L., Prejbisz, A., Beuschlein, F., Fassnacht, M., Timmers, H. J. L. M., Nölting, S., Abhyankar, K., Constantinescu, G., Kunath, C., de Haas, R. J., Wang, K., Remde, H., Bornstein, S. R., Januszewicz, A., Robledo, M., … Eisenhofer, G. (2023). Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort. The Lancet Digital Health, 5(9), e551–e559. https://doi.org/10.1016/S2589-7500(23)00094-8
