title: Reducing misclassification bias in cervical dysplasia risk factor analysis with p16-based diagnoses.
abstract: OBJECTIVE
  Conventional hematoxylin and eosin (HE)-based diagnoses have been the reference standard for cervical cancer risk factor analyses. However, this HE-based method is known to have modest interobserver reproducibility and only moderate predictive value. In contrast, more recent immunohistochemical-based diagnoses using the neoplastic marker p16 are known to improve diagnostic accuracy. Our objective was to test whether p16-based diagnoses would significantly affect high-grade dysplasia (cervical intraepithelial neoplasia 2+) risk factor analysis compared with the current reference standard (HE).
  
  
  METHODS
  Retrospective cohort of 500 index cases were randomly selected from a series of more than 5,000 cervical biopsies performed at Kaiser Permanente Northwest from 1997 to 2003 after a patient's first abnormal cervical Pap smear (positive for atypical squamous cells of undetermined significance). Subjects were subsequently excluded if they did not have at least 5 years of clinical follow-up, including cervical biopsies, or 3 reproducibly negative Pap smears. This yielded 358 cases for risk factor analysis. The index biopsies and all follow-up biopsies were immunostained for p16 and the proliferation marker Ki-67, which were then independently reviewed by 2 pathologists blinded to clinical outcomes. Data were analyzed by χ test and logistic regression modeling.
  
  
  RESULTS
  We observed clinically significant diagnostic errors in 22% of index biopsies. Improved accuracy using p16 strengthened the risk estimate of low family income for cervical intraepithelial neoplasia 2+ (odds ratio = 1.71, 95% confidence interval = 1.09-2.63) compared with HE-based diagnoses (odds ratio = 1.12, 95% confidence interval = 0.72-1.72). The addition of Ki-67 staining did not significantly influence these results.
  
  
  CONCLUSIONS
  p16-based diagnoses may affect the power of risk factor analysis, especially when using small cohorts.
authors.affiliation: Departments of 1Pathology, 2Obstetrics & Gynecology, and 3Medical Informatics & Clinical Epidemiology at Oregon Health & Science University; and 4Pathology at Kaiser Permanente Northwest, Portland, OR.
authors.forename: Emily
authors.initials: E
authors.lastname: Meserve
authors.forename: Michelle
authors.initials: M
authors.lastname: Berlin
authors.forename: Tomi
authors.initials: T
authors.lastname: Mori
authors.forename: Robert
authors.initials: R
authors.lastname: Krum
authors.forename: Terry K
authors.initials: TK
authors.lastname: Morgan
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D019941:Cyclin-Dependent Kinase Inhibitor p16; D003951:Diagnostic Errors; D005260:Female; D006801:Humans; D007150:Immunohistochemistry / Q000379:methods*; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000032:analysis*; D012189:Retrospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis*; D055815:Young Adult
chemical_list: C000614131:CDKN2A protein, human; D019941:Cyclin-Dependent Kinase Inhibitor p16; D009363:Neoplasm Proteins