S-Space College of Medicine/School of Medicine (의과대학/대학원) Obstetrics & Gynecology (산부인과전공) Journal Papers (저널논문_산부인과학전공)
A hospital-based case-control study of identifying ovarian cancer using symptom index
- Kim, Mi-Kyung; Kim, Kidong; Kim, Sun Min; Kim, Jae Weon; Song, Yong-Sang; Kang, Soon-Beom; Park, Noh-Hyun
- Issue Date
- JOURNAL OF GYNECOLOGIC ONCOLOGY; Vol.20 4; 238-242
- Objective: Recently, a symptom index for identification of ovarian cancer, based on specific symptoms along with their frequency and duration, was proposed. The current study aimed at validation of this index in Korean population. Methods: A case-control study of 116 women with epithelial ovarian cancer and 209 control women was conducted using questionnaires on eight symptoms. These included pelvic/abdominal pain, urinary urgency/frequency, increased abdominal size/bloating, difficulty eating/feeling full. The symptom index was considered positive if any of the 8 symptoms present for < 1 year that occurred > 12 times per month. The symptoms were compared between ovarian cancer group and control group using chi-square test. Logistic regression analysis was used to determine whether the index predicted cancer. Sensitivity and specificity of the symptom index were also determined. Results: The symptom index was positive in 65.5% of women with ovarian cancer, in 31.1% of women with benign cysts, and in 6.7% of women on routine screening (ps < 0.001). Significantly higher proportion of ovarian cancer patients were positive for each symptom as compared with control group (ps < 0.001). Results from the logistic regression indicated that the symptom index independently predicted cancer (p < 0.001; OR, 10.51; 95% Cl, 6.14 to 17.98). Overall, the sensitivity and specificity of the symptom index were 65.5% and 84.7%, respectively. Analyses of sensitivity by stage showed that the index was positive in 44.8% of patients with stage I/II disease and in 72.9% of patients with stage III/IV disease. Conclusion: The current study supported previous studies suggesting that specific symptoms were useful in identifying women with ovarian cancer.