Abstract
OBJECTIVE: To determine whether CA-125 velocity is a statistically significant predictor of ovarian cancer and develop a classification rule to screen for ovarian cancer. METHODS: In the ovarian component of the PLCO cancer screening trial, 28,038 women aged 55-74 had at least two CA-125 screening tests. Ovarian cancer was diagnosed in 72 (0.26%) women. A multiple logistic regression model was developed to evaluate CA-125 velocity and other related covariates as predictors of ovarian cancer. Predictive accuracy was assessed by the concordance index and measures of discrimination and calibration while the fit of the model was assessed by the Hosmer and Lemeshow's goodness-of-fit χ(2)test. RESULTS: CA-125 velocity decreased as the number of CA-125 measurements increased but was unaffected by age at baseline screen and family history of ovarian cancer. The average velocity (19.749U/ml per month) of the cancer group was more than 500 times the average velocity (0.035U/ml per month) of the non-cancer group. CONCLUSION: Among six covariates used in the model, CA-125 velocity and time intervals between baseline and second to last screening test and between last two screening tests were statistically significant predictors of ovarian cancer. The chance of having ovarian cancer increased as velocity increased, and the chance decreased when the time intervals between baseline and the second to last screening test and between last two screening tests of an individual increased.