OBJECTIVE: To estimate the predictive factors for persistent/recurrent disease before and after conization for cervical intraepithelial neoplasia III. METHODS: Patients who received conization due to histologic diagnosis of cervical intraepithelial neoplasia III from 1998 to 2000 and who had at least one cytologic/histologic follow-up within one year of conization (n = 449) were enrolled in our study. All available demographic and pathologic parameters were analyzed. RESULTS: We performed multivariable logistic regression analysis to identify predictive factors for cervical intraepithelial neoplasia III persistence/recurrence. Age (greater than 50 years) was the only preoperative predictor and had an odds ratio equaling 3.070 (95% confidence interval [CI] 1.421-6.630, P = .004). Post-cone endocervical curettage was found to be the most statistically significant factor for predicting persistent disease (odds ratio 7.940, 95% CI 3.428-18.390, P < .001). Positive endocervical curettage was associated with 65.5% (36/55) of persistent disease, whereas negative endocervical curettage was associated with only 7.6% (26/342). Positive endocervical resection margins and multiple-quadrant disease also had predictive values with odds ratios equaling 2.972 (95% CI 1.401-6.281, P = .004) and 2.180 (95% CI 1.014-4.689, P = .046), respectively. The positive predictive values for age (> 50 years), positive endocervical curettage, positive endocervical resection margin, and multiple quadrant disease were 31.7%, 65.5%, 40.0%, and 21.9%, respectively. CONCLUSION: We found that age is the only preoperative predictive factor. Pathologic parameters, including endocervical curettage, endocervical resection margins, and multiple-quadrant disease are the only postoperative predictive factors for cervical intraepithelial neoplasia persistence or recurrence found in our study. These factors should be considered in patient management before and after therapeutic conization for cervical intraepithelial neoplasia III. LEVEL OF EVIDENCE: II-3.
OBJECTIVE: To estimate the predictive factors for persistent/recurrent disease before and after conization for cervical intraepithelial neoplasia III. METHODS:Patients who received conization due to histologic diagnosis of cervical intraepithelial neoplasia III from 1998 to 2000 and who had at least one cytologic/histologic follow-up within one year of conization (n = 449) were enrolled in our study. All available demographic and pathologic parameters were analyzed. RESULTS: We performed multivariable logistic regression analysis to identify predictive factors for cervical intraepithelial neoplasia III persistence/recurrence. Age (greater than 50 years) was the only preoperative predictor and had an odds ratio equaling 3.070 (95% confidence interval [CI] 1.421-6.630, P = .004). Post-cone endocervical curettage was found to be the most statistically significant factor for predicting persistent disease (odds ratio 7.940, 95% CI 3.428-18.390, P < .001). Positive endocervical curettage was associated with 65.5% (36/55) of persistent disease, whereas negative endocervical curettage was associated with only 7.6% (26/342). Positive endocervical resection margins and multiple-quadrant disease also had predictive values with odds ratios equaling 2.972 (95% CI 1.401-6.281, P = .004) and 2.180 (95% CI 1.014-4.689, P = .046), respectively. The positive predictive values for age (> 50 years), positive endocervical curettage, positive endocervical resection margin, and multiple quadrant disease were 31.7%, 65.5%, 40.0%, and 21.9%, respectively. CONCLUSION: We found that age is the only preoperative predictive factor. Pathologic parameters, including endocervical curettage, endocervical resection margins, and multiple-quadrant disease are the only postoperative predictive factors for cervical intraepithelial neoplasia persistence or recurrence found in our study. These factors should be considered in patient management before and after therapeutic conization for cervical intraepithelial neoplasia III. LEVEL OF EVIDENCE: II-3.
Authors: Nae Ry Kim; Zee Hae Baek; A Jin Lee; Eun Jung Yang; Yung-Taek Ouh; Mi Kyung Kim; Seung-Hyuk Shim; Sun Joo Lee; Tae Jin Kim; Kyeong A So Journal: J Clin Med Date: 2022-05-25 Impact factor: 4.964
Authors: Emmanuel A Oga; Jessica P Brown; Clayton Brown; Eileen Dareng; Victor Adekanmbi; Michael Odutola; Olayinka Olaniyan; Richard Offiong; Kayode Obende; Ayodele Stephen Adewole; Achara Peter; Patrick Dakum; Clement Adebamowo Journal: BMC Womens Health Date: 2016-05-11 Impact factor: 2.809