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A new prognostic index model using meta-analysis in early-stage epithelial ovarian cancer

Other Titles
 초기 병기 상피성 난소암에서 메타분석을 이용한 새로운 예후지표 모델의 제시 
Authors
 박현종 
Department
 Dept. of Obstetrics and Gynecology (산부인과학교실) 
Issue Date
2013
Description
Dept. of Medicine/석사
Abstract
Objectives: To construct a novel prognostic index (PI) model of early-stage epithelial ovarian cancer (EOC). Methods: The PI model was constructed through meta-analyses. The methodological quality of the studies was assessed using the modified Jadad scale for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale for non-RCTs. The prognostic factors of the PI model that had a significant impact on the recurrence-free survival (RFS) of patients with early-stage ovarian cancer were chosen. A total of 177 patients with early-stage ovarian cancer who were treated at Severance Hospital from January 1999 to September 2011 were analyzed using the new PI model to test its utility. Results: The equation PI = 2 × age + 86 (if grade 2) or 105 (if grade 3) + 53 (if stage Ib or Ic) or 130 (if stage II) + 53 (if no lymphadenectomy) - 43 (for adjuvant chemotherapy of 3 times or more) + 10 (calibrating constant) was derived. Based on PI values, the high-risk group showed a significant 5 year-RFS difference compared to the low-risk group (P-value <0.01 by log-rank test) and a borderline significance in comparison to the intermediate-risk group (P-value=0.08). When the cutoff level of PI values was set at 211, the low- and high-risk groups of recurrence within 5 years were also identified by Cox regression analysis (HR=7.25, 95% CI: 2.98-17.65) .Conclusions: Our PI model was predictive in this study and may be effective in clinical practice. Further prospective studies should be conducted to confirm the predictive ability of the new PI model for early-stage EOC recurrence.
Files in This Item:
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Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Obstetrics and Gynecology (산부인과학교실) > 2. Thesis
Yonsei Authors
Park, Hyun Jong(박현종)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/134454
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