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Impact of Prognostic Factors on Survival Rates in Patients with Ovarian Carcinoma
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  • Impact of Prognostic Factors on Survival Rates in Patients with Ovarian Carcinoma
  • Impact of Prognostic Factors on Survival Rates in Patients with Ovarian Carcinoma
저자명
Arikan. Sevim Kalsen,Kasap. Burcu,Yetimalar. Hakan,Yildiz. Askin,Sakarya. Derya Kilic,Tatar. Sumeyra
간행물명
Asian Pacific journal of cancer prevention : APJCP
권/호정보
2014년|15권 15호|pp.6087-6094 (8 pages)
발행정보
아시아태평양암예방학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Purpose: The aim of the present study was to invesitigate the impact of significant clinico-pathological prognostic factors on survival rates and to identify factors predictive of poor outcome in patients with ovarian carcinoma. Materials and Methods: A retrospective chart review of 74 women with pathologically proven ovarian carcinoma who were treated between January 2006 and April 2011 was performed. Patients were investigated with respect to survival to find the possible effects of age, gravida, parity, menstruel condition, pre-operative Ca-125, treatment period, cytologic washings, presence of ascites, tumor histology, stage and grade, maximal tumor diameter, adjuvan chemotherapy and cytoreductive success. Also 55 ovarian carcinoma patients were investigated with respect to prognostic factors for early 2-year survival. Results: The two-year survival rate was 69% and the 5-year survival rate was 25.5% for the whole study population. Significant factors for 2-year survival were preoperative CA-125 level, malignant cytology and FIGO clinical stage. Significant factors for 5-year survival were age, preoperative CA-125 level, residual tumor, lymph node metastases, histologic type of tumor, malignant cytology and FIGO clinical stage. Logistic regression revealed that independent prognostic factors of 5-year survival were patient age, lymph node metastasis and malignant cytology. Conclusions: We consider quality registries with prospectively collected data to be one important tool in monitoring treatment effects in population-based cancer research.