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Predicting the risk of neurocognitive decline after brain irradiation in adult patients with a primary brain tumor

Articolo
Data di Pubblicazione:
2024
Citazione:
Predicting the risk of neurocognitive decline after brain irradiation in adult patients with a primary brain tumor / Tohidinezhad, F., Zegers, C.M.L., Vaassen, F., Dijkstra, J., Anten, M., Van Elmpt, W., De Ruysscher, D., Dekker, A., Eekers, D.B.P., Traverso, A.. - In: NEURO-ONCOLOGY. - ISSN 1522-8517. - 26:8(2024), pp. 1467-1478. [10.1093/neuonc/noae035]
Abstract:
Background: Deterioration of neurocognitive function in adult patients with a primary brain tumor is the most concerning side effect of radiotherapy. This study aimed to develop and evaluate normal-tissue complication probability (NTCP) models using clinical and dose-volume measures for 6-month, 1-year, and 2-year Neurocognitive Decline (ND) postradiotherapy. Methods: A total of 219 patients with a primary brain tumor treated with radical photon and/or proton radiotherapy (RT) between 2019 and 2022 were included. Controlled oral word association test, Hopkins verbal learning test-revised, and trail making test were used to objectively measure ND. A comprehensive set of potential clinical and dose-volume measures on several brain structures were considered for statistical modeling. Clinical, dose-volume and combined models were constructed and internally tested in terms of discrimination (area under the curve, AUC), calibration (mean absolute error, MAE), and net benefit. Results: Fifty percent, 44.5%, and 42.7% of the patients developed ND at 6-month, 1-year, and 2-year time points, respectively. The following predictors were included in the combined model for 6-month ND: age at radiotherapy > 56 years (OR = 5.71), overweight (OR = 0.49), obesity (OR = 0.35), chemotherapy (OR = 2.23), brain V20Gy ≥ 20% (OR = 3.53), brainstem volume ≥ 26 cc (OR = 0.39), and hypothalamus volume ≥ 0.5 cc (OR = 0.4). Decision curve analysis showed that the combined models had the highest net benefits at 6-month (AUC = 0.79, MAE = 0.021), 1-year (AUC = 0.72, MAE = 0.027), and 2-year (AUC = 0.69, MAE = 0.038) time points. Conclusions: The proposed NTCP models use easy-to-obtain predictors to identify patients at high risk of ND after brain RT. These models can potentially provide a base for RT-related decisions and post-therapy neurocognitive rehabilitation interventions.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Tohidinezhad, F.; Zegers, C. M. L.; Vaassen, F.; Dijkstra, J.; Anten, M.; Van Elmpt, W.; De Ruysscher, D.; Dekker, A.; Eekers, D. B. P.; Traverso, A.
Autori di Ateneo:
TRAVERSO ALBERTO
Link alla scheda completa:
https://iris.unisr.it/handle/20.500.11768/207583
Link al Full Text:
https://iris.unisr.it//retrieve/handle/20.500.11768/207583/375505/noae035.pdf
Pubblicato in:
NEURO-ONCOLOGY
Journal
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URL

https://academic.oup.com/neuro-oncology/article/26/8/1467/7643141?login=true
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