A Simplified Diagnostic Classification Scheme of Chemotherapy-Induced Peripheral Neuropathy

Background and Objective. The main purpose of this study was to develop a simple automatic diagnostic classification scheme for chemotherapy-induced peripheral neuropathy.

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.

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 (.

The results of our unsupervised classification algorithm based on three variables of laboratory tests correlated well with the neurologists' diagnoses.