Ontology highlight
ABSTRACT: 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.
SUBMITTER: Huang HW
PROVIDER: S-EPMC7008270 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Huang Han-Wei HW Wu Pei-Ying PY Su Pei-Fang PF Li Chung-I CI Yeh Yu-Min YM Lin Peng-Chan PC Hsu Keng-Fu KF Shen Meng-Ru MR Chang Jang-Yang JY Lin Chou-Ching K CK
Disease markers 20200125
<i>Background and Objective</i>. The main purpose of this study was to develop a simple automatic diagnostic classification scheme for chemotherapy-induced peripheral neuropathy.<h4>Methods</h4>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 ...[more]