title: A statistical model for predicting response of breast cancer patients to cytotoxic chemotherapy.
abstract: A binary logistic model is used for predicting response to cytotoxic chemotherapy for a breast cancer patient on the basis of her tumor enzyme activity profile. The enzymes used in the model are lactate dehydrogenase, nicotinamide adenine dinucleotide phosphate-isocitrate dehydrogenase, and phosphoglucomutase, all of which were measured on primary tumor specimens from each patient. The statistical model provides an estimate of the probability that an individual will respond to treatment. Chemotherapeutic treatment consisting of combination cytotoxic drugs and subsequent evaluation of patient response followed cooperative group protocol guidelines, including outside review to confirm the patient evaluation. The model based on this study, which represents 5 years of patient follow-up, correctly predicts clinical outcome in 32 of the 37 cases available.
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use*; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000201:enzymology; D004359:Drug Therapy, Combination; D005260:Female; D006801:Humans; D007521:Isocitrate Dehydrogenase / Q000378:metabolism; D007770:L-Lactate Dehydrogenase / Q000378:metabolism; D008954:Models, Biological; D010733:Phosphoglucomutase / Q000378:metabolism; D012075:Remission, Spontaneous; D013223:Statistics as Topic
chemical_list: D000970:Antineoplastic Agents; D007770:L-Lactate Dehydrogenase; D007521:Isocitrate Dehydrogenase; D010733:Phosphoglucomutase