Predictors of the residual disease of high-grade lesions and microinvasive squamous cell carcinoma of the cervix following conization

Autor: Nungrutai, Saeaib, Sathana, Boonyapipat, Kobkul, Tungsinmunkong, Tippawan, Liabsuetrakul
Rok vydání: 2009
Předmět:
Zdroj: Journal of the Medical Association of Thailand = Chotmaihet thangphaet. 92(11)
ISSN: 0125-2208
Popis: To determine the predictors of residual disease of high-grade lesion (HGL) and microinvasive squamous cell carcinoma of the cervix (MICA) in subsequent hysterectomy following conization.The medical records of women who underwent any conizations diagnosed of HGL and MICA and followed by subsequent hysterectomy within 6 months were retrospectively reviewed. A case and control was defined as whether or not a residual disease of HGL or more was detected in cervical tissue from hysterectomy after conization. Demographic characteristics and pathological features of cases and controls were recorded independently and blindly. Univariate and multivariate analysis were used. The Receiver Operating Characteristics curve of predictors was created using the fitting value obtained from a logistic regression model.A total of 185 women were diagnosed during January 1, 1997 and July 31, 2008 including 102 women without a residual disease and 83 with residual disease at cervical tissue from hysterectomy. The multivariate analysis showed that postmenopausal status (OR = 3.5, 95% CI = 1.8-6.7), number of quadrant involvement (OR = 3.8, 95% CI = 1.8-8.3), internal margin involvement (OR = 3.8, 95% CI = 1.7-8.2), severe nuclear atypia (OR = 2.0, 95% CI = 1.1-3.8) and high mitotic activity (OR = 2.1, 95% CI = 1.1-3.7) were the predictors of residual disease in hysterectomy specimens after conization. Three or more predictors involved predicted the detection of residual disease.The presence of postmenopause, three or four quadrants involved, positive internal margin, severe nuclear atypia and high mitotic activity could be used to predict residual lesions after conization.
Databáze: OpenAIRE