title: Knowledge discovery processing and data mining in karyometry.
abstract: OBJECTIVE
  To present the rationale for applying different sequences of multivariate analysis algorithms to determine if and where, in the large and high-dimensional data space, events have led to change in karyometric features.
  
  
  METHODS
  Clinical materials and results from the analysis of 4 studies were used: the demonstration of chemopreventive efficacy of letrozole in a situation where only a small subset of cells is affected, the detection of a preneoplastic lesion in colorectal tissue, data processing to document clues that predict risk of recurrence of a bladder lesion and the use of metafeatures and second-order discriminant analysis in a study of efficacy of vitamin A in the chemoprevention of skin lesions.
  
  
  RESULTS
  Evidence for chemopreventive efficacy was demonstrated in the first example only after processing identified the small subpopulation of affected nuclei in a study of breast epithelial cells. Detection of a preneoplastic development is linked to a progression curve connecting nuclei from normal tissue to nuclei from premalignant colorectal lesions. The prediction of risk of recurrence of papillary bladder lesions is possible by detecting changes in nuclei of a certain phenotype. Efficacy of vitamin A as a chemopreventive agent for skin cancer could be demonstrated with a dose-response curve after a second-order discriminant analysis was employed.
  
  
  CONCLUSIONS
  In none of these instances would the information of biologic interest have been revealed by a straightforward, single algorithmic analysis.
authors.affiliation: College of Optical Sciences and Arizona Cancer Center, University of Arizona, Tucson, Arizona 85724-5024, USA.
authors.forename: Peter H
authors.initials: PH
authors.lastname: Bartels
authors.forename: Rodolfo
authors.initials: R
authors.lastname: Montironi
authors.forename: Marina
authors.initials: M
authors.lastname: Scarpelli
authors.forename: Hubert G
authors.initials: HG
authors.lastname: Bartels
authors.forename: David S
authors.initials: DS
authors.lastname: Alberts
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D001943:Breast Neoplasms / Q000473:pathology / Q000517:prevention & control; D002291:Carcinoma, Papillary / Q000473:pathology / Q000517:prevention & control; D002467:Cell Nucleus / Q000648:ultrastructure*; D003110:Colonic Neoplasms / Q000473:pathology / Q000517:prevention & control; D019295:Computational Biology; D005260:Female; D006801:Humans; D007620:Karyometry; D000077289:Letrozole; D009364:Neoplasm Recurrence, Local / Q000517:prevention & control; D009570:Nitriles / Q000627:therapeutic use*; D011230:Precancerous Conditions / Q000188:drug therapy* / Q000473:pathology*; D014230:Triazoles / Q000627:therapeutic use*; D001749:Urinary Bladder Neoplasms / Q000473:pathology / Q000517:prevention & control
chemical_list: D000970:Antineoplastic Agents; D009570:Nitriles; D014230:Triazoles; D000077289:Letrozole