title: A simple index using video image analysis to predict disease outcome in primary breast cancer.
abstract: Image analysis was used to investigate the prognostic significance of immunostaining for oestrogen receptor (ER), p53 tumour-suppressor protein and tumour cell proliferation (MIB-1) in a random cohort of 200 primary breast cancer patients with between 4 and 7 years of clinical follow-up. Image measurements of the percentage of immunopositive cancer cell nuclei (% positive nuclear area) were recorded for the above tumour features for each patient. Assessment of relative risk using Cox's univariate analysis indicated that tumour size, number of cancer-involved nodes, MIB-1 and ER % positive nuclear area were significantly associated with breast cancer disease outcome, i.e., relapse-free survival and overall survival. In multivariate analysis, tumour size, number of involved nodes, ER and MIB-1 % positive nuclear area were retained as independent predictors of prognosis, depending on the image measurement cut-point used. A prognostic model, which can be used without reference to nodal involvement, was constructed for tumour size, ER cut-point of 30% positive nuclear area and MIB-1 cut-point of 10% positive nuclear area. Kaplan-Meier analysis of this image-based prognostic index identified 4 risk groups with predicted 5-year overall survival rates of 93%, 83%, 76.7% and 61.5%. We conclude that image measurements of ER and proliferative rate can be combined with tumour size to construct a prognostic index which reliably predicts disease outcome in primary breast cancer without knowledge of the nodal status of the patient.
authors.affiliation: Department of Surgery, Flinders University School of Medicine and Flinders Cancer Centre, Flinders Medical Centre, Bedford Park, South Australia.
authors.forename: C A
authors.initials: CA
authors.lastname: Lockwood
authors.forename: C
authors.initials: C
authors.lastname: Ricciardelli
authors.forename: W A
authors.initials: WA
authors.lastname: Raymond
authors.forename: R
authors.initials: R
authors.lastname: Seshadri
authors.forename: K
authors.initials: K
authors.lastname: McCaul
authors.forename: D J
authors.initials: DJ
authors.lastname: Horsfall
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D034961:Antigens, Nuclear; D001943:Breast Neoplasms / Q000737:chemistry / Q000401:mortality* / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D019394:Ki-67 Antigen; D008875:Middle Aged; D015999:Multivariate Analysis; D009687:Nuclear Proteins / Q000032:analysis*; D011379:Prognosis; D011960:Receptors, Estrogen / Q000032:analysis*; D015996:Survival Rate; D016159:Tumor Suppressor Protein p53 / Q000032:analysis
chemical_list: D034961:Antigens, Nuclear; D019394:Ki-67 Antigen; D009687:Nuclear Proteins; D011960:Receptors, Estrogen; D016159:Tumor Suppressor Protein p53