Computational Modeling of Neuropsychological Test Performance to Disentangle Impaired Cognitive Processes in Cancer Patients

利用神经心理测试表现的计算模型来解析癌症患者受损的认知过程

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Abstract

There is a need to better identify impaired cognitive processes to increase our understanding of cognitive dysfunction caused by cancer and cancer treatment and to improve interventions. The Trail Making Test is frequently used for evaluating information-processing speed (part A) and executive function (part B), but interpretation of its outcomes is challenging because performance depends on many cognitive processes. To disentangle processes, we collected high-resolution data from 192 non-central nervous system cancer patients who received systemic therapy and 192 cancer-free control participants and fitted a Shifted-Wald computational model. Results show that cancer patients were more cautious than controls (Cohen d = 0.16). Patients were cognitively slower than controls when the task required task switching (Cohen d = 0.16). Our results support the idea that cancer and cancer treatment accelerate cognitive aging. Our approach allows more precise assessment of cognitive dysfunction in cancer patients and can be extended to other instruments and patient populations.

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