title: Ovulation and ovarian cancer: a comparison of two methods for calculating lifetime ovulatory cycles (United States).
abstract: OBJECTIVE
  To compare two methods for calculating lifetime ovulatory cycles (LOC) to determine if more detailed menstrual cycle information results in stronger associations with ovarian cancer.
  
  
  METHODS
  Using data from 232 cases and 242 controls in a population-based study of ovarian cancer, we compared a standard method for calculating LOC with a second method that had more detailed information on menstrual characteristics. Odds ratios for ovarian cancer by number of LOC were estimated using unconditional logistic regression.
  
  
  RESULTS
  The average number of LOC was 29 fewer for the second method that had more detailed menstrual cycle information, as compared to the standard method (p < 0.0001). The difference was due primarily to the second method considering episodes of missed/irregular periods. Associations between LOC and ovarian cancer were weaker for the second method than the standard method. Further analyses suggested that a reduced number of ovulatory cycles due to menstrual irregularity was associated with increased ovarian cancer risk, in contrast to the protective effects observed for fewer ovulatory cycles due to pregnancy or oral contraceptive use.
  
  
  CONCLUSIONS
  Obtaining additional details on menstrual factors that affect LOC, particularly missed or irregular cycles, provides important information on ovarian cancer risk. Our data suggest that episodes of anovulation due to menstrual disturbances should be evaluated separately from anovulation due to pregnancy or oral contraceptive use.
authors.affiliation: Cancer Prevention, Detection, and Control Research Program, Department of Community and Family Medicine, Duike Universiti' Medical Center, Durham, NC 27710, USA. patricia.moorman@duke.edu
authors.forename: Patricia G
authors.initials: PG
authors.lastname: Moorman
authors.forename: Joellen M
authors.initials: JM
authors.lastname: Schildkraut
authors.forename: Brian
authors.initials: B
authors.lastname: Calingaert
authors.forename: Susan
authors.initials: S
authors.lastname: Halabi
authors.forename: Marilyn F
authors.initials: MF
authors.lastname: Vine
authors.forename: Andrew
authors.initials: A
authors.lastname: Berchuck
mesh_terms: D016022:Case-Control Studies; D016001:Confidence Intervals; D005260:Female; D006801:Humans; D016015:Logistic Models; D008487:Medical History Taking; D008599:Menstruation Disturbances / Q000453:epidemiology*; D008875:Middle Aged; D016017:Odds Ratio; D010051:Ovarian Neoplasms / Q000453:epidemiology* / Q000503:physiopathology; D010060:Ovulation; D018570:Risk Assessment / Q000379:methods; D014481:United States / Q000453:epidemiology