Disease markers · 2020
A Simplified Diagnostic Classification Scheme of Chemotherapy-Induced Peripheral Neuropathy.
Клиническое исследованиеСтатьяНазвание и аннотация: Перевод пока не подготовлен
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Huang Han-Wei, Wu Pei-Ying, Su Pei-Fang, Li Chung-I, Yeh Yu-Min, Lin Peng-Chan, Hsu Keng-Fu, Shen Meng-Ru, Chang Jang-Yang, Lin Chou-Ching K
Аннотация
UNLABELLED: Background and Objective. The main purpose of this study was to develop a simple automatic diagnostic classification scheme for chemotherapy-induced peripheral neuropathy.
METHODS: This was a prospective cohort study that enrolled patients with colorectal or gynecologic cancer post chemotherapy for more than 1 year. The patients underwent laboratory examinations (nerve conduction studies and quantitative sensory tests), and a questionnaire about the quality of life. An unsupervised classification algorithm was used to classify the patients into groups using a small number of variables derived from the laboratory tests. A panel of five neurologists also diagnosed the types of neuropathies according to the laboratory tests. The results by the unsupervised classification algorithm and the neurologists were compared.
RESULTS: The neurologists' diagnoses showed much higher rates of entrapment syndromes (66.1%) and radiculopathies (55.1%) than polyneuropathy (motor/sensory: 33.1%/29.7%). A multivariate analysis showed that the questionnaire was not significantly correlated with the results of quantitative sensory tests (r = 0.27) or the neurologists' diagnoses (r = 0.27) or the neurologists' diagnoses (.
CONCLUSION: The results of our unsupervised classification algorithm based on three variables of laboratory tests correlated well with the neurologists' diagnoses.
METHODS: This was a prospective cohort study that enrolled patients with colorectal or gynecologic cancer post chemotherapy for more than 1 year. The patients underwent laboratory examinations (nerve conduction studies and quantitative sensory tests), and a questionnaire about the quality of life. An unsupervised classification algorithm was used to classify the patients into groups using a small number of variables derived from the laboratory tests. A panel of five neurologists also diagnosed the types of neuropathies according to the laboratory tests. The results by the unsupervised classification algorithm and the neurologists were compared.
RESULTS: The neurologists' diagnoses showed much higher rates of entrapment syndromes (66.1%) and radiculopathies (55.1%) than polyneuropathy (motor/sensory: 33.1%/29.7%). A multivariate analysis showed that the questionnaire was not significantly correlated with the results of quantitative sensory tests (r = 0.27) or the neurologists' diagnoses (r = 0.27) or the neurologists' diagnoses (.
CONCLUSION: The results of our unsupervised classification algorithm based on three variables of laboratory tests correlated well with the neurologists' diagnoses.