Abstract:
: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.
journal_name
Dis Markersjournal_title
Disease markersauthors
Huang HW,Wu PY,Su PF,Li CI,Yeh YM,Lin PC,Hsu KF,Shen MR,Chang JY,Lin CKdoi
10.1155/2020/3402108subject
Has Abstractpub_date
2020-01-25 00:00:00pages
3402108eissn
0278-0240issn
1875-8630journal_volume
2020pub_type
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