title: Prognostic estimation of survival of colorectal cancer patients with the quantitative histochemical assay of G6PDH activity and the multiparameter classification program CLASSIF1.
abstract: Prognosis of colorectal cancer patients that show similar histopathology may vary substantially. An attempt was made to improve prognosis by the self-learning classification program CLASSIF1, based on automated multiparameter analysis of quantitative histochemical and clinical parameters of 64 colorectal carcinomas and adjacent normal mucosae. The histochemical parameters applied were the oxygen-insensitivity assay of glucose-6-phosphate dehydrogenase (G6PDH) activity, a valid discriminator between normal and cancerous mucosae, and related parameters CuZn- and Mn-superoxide dismutase (SOD) levels, and lipid peroxidation (LPO) capacity. Data were processed on the basis of a postoperative follow-up of minimally 32 and maximally 56 months. CLASSIF1 selected the parameters oxygen insensitivity of G6PDH activity, CuZn-SOD and Mn-SOD levels, LPO capacity, lymph node metastasis, Dukes' stage, and age for the highest prognostic value. On the basis of these selected parameters, CLASSIF1 correctly predicted favorable outcome in 100% of the surviving patients and fatal outcome in 64% of the deceased patients. G6PDH activity appeared to be the major information carrier for CLASSIF1. On the basis of G6PDH activity parameters alone, 96% of the surviving patients and 55% of the deceased patients were correctly classified. In comparison, estimation of prognosis on the basis of Dukes' stage alone resulted in 71% correctly classified surviving patients and 61% of patients who died. It is concluded that the self-learning classification program CLASSIF1, on the basis of quantitative histochemical and clinical parameters, is the best prognostic estimator for colon cancer patients yet available.
authors.affiliation: Department of Cell Biology and Histology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: B E
authors.initials: BE
authors.lastname: Van Driel
authors.forename: G K
authors.initials: GK
authors.lastname: Valet
authors.forename: H
authors.initials: H
authors.lastname: Lyon
authors.forename: U
authors.initials: U
authors.lastname: Hansen
authors.forename: J Y
authors.initials: JY
authors.lastname: Song
authors.forename: C J
authors.initials: CJ
authors.lastname: Van Noorden
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002277:Carcinoma / Q000201:enzymology* / Q000401:mortality / Q000473:pathology; D015331:Cohort Studies; D003106:Colon / Q000737:chemistry; D015179:Colorectal Neoplasms / Q000201:enzymology* / Q000401:mortality / Q000473:pathology; D001330:Electronic Data Processing / Q000379:methods*; D005260:Female; D005500:Follow-Up Studies; D005954:Glucosephosphate Dehydrogenase / Q000032:analysis*; D006801:Humans; D007150:Immunohistochemistry; D015227:Lipid Peroxidation; D008297:Male; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000032:analysis*; D011379:Prognosis; D012007:Rectum / Q000737:chemistry; D013482:Superoxide Dismutase / Q000032:analysis*
chemical_list: D009363:Neoplasm Proteins; D005954:Glucosephosphate Dehydrogenase; D013482:Superoxide Dismutase