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

Hyun Jong Park, Eun Ji Nam, Sun Young Rha, Sunghoon Kim, Sang Wun Kim, Jae Wook Kim, Young Tae Kim

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5 Citations (Scopus)


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 prognosis 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 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.

Original languageEnglish
Pages (from-to)357-363
Number of pages7
JournalGynecologic Oncology
Issue number3
Publication statusPublished - 2012 Sept

Bibliographical note

Funding Information:
This study was supported by the Brain Korea (BK) 21 Project for Medical Science , Yonsei University , and by a grant from the Korea Healthcare Technology R&D Project, Ministry for Health, Welfare and Family Affairs, Republic of Korea ( A084120 ).

All Science Journal Classification (ASJC) codes

  • Oncology
  • Obstetrics and Gynaecology


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