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Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer
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논문 기본 정보

Type
Academic journal
Author
Journal
대한암학회 Cancer Research and Treatment Cancer Research and Treatment 제51권 제3호 KCI Accredited Journals
Published
2019.1
Pages
1,144 - 1,155 (12page)

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Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer
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Purpose Discovery of models predicting the exact prognosis of epithelial ovarian cancer (EOC) is necessary as the first step of implementation of individualized treatment. This study aimed to develop nomograms predicting treatment response and prognosis in EOC. Materials and Methods We comprehensively reviewed medical records of 866 patients diagnosed with and treated for EOC at two tertiary institutional hospitals between 2007 and 2016. Patients’ clinicopathologic characteristics, details of primary treatment, intra-operative surgical findings, and survival outcomes were collected. To construct predictive nomograms for platinum sensitivity, 3-year progression-free survival (PFS), and 5-year overall survival (OS), we performed stepwise variable selection by measuring the area under the receiver operating characteristic curve (AUC) with leave-one-out cross-validation. For model validation, 10-fold cross-validation was applied. Results The median length of observation was 42.4 months (interquartile range, 25.7 to 69.9 months), during which 441 patients (50.9%) experienced disease recurrence. The median value of PFS was 32.6 months and 3-year PFS rate was 47.8% while 5-year OS rate was 68.4%. The AUCs of the newly developed nomograms predicting platinum sensitivity, 3-year PFS, and 5-year OS were 0.758, 0.841, and 0.805, respectively. We also developed predictive nomograms confined to the patients who underwent primary debulking surgery. The AUCs for platinum sensitivity, 3-year PFS, and 5-year OS were 0.713, 0.839, and 0.803, respectively. Conclusion We successfully developed nomograms predicting treatment response and prognosis of patients with EOC. These nomograms are expected to be useful in clinical practice and designing clinical trials.

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Siegel RL / 2017 / Cancer statistics, 2017 / CA Cancer J Clin 67:7~30 google schola Howlader N / SEER cancer statistics review, 1975-2014 google schola Global Burden of Disease Cancer Collaboration / 2015 / The global burden of cancer 2013 / JAMA Oncol 1:505~527 google schola 임명철 / 2013 / Incidence of cervical, endometrial, and ovarian cancer in Korea, 1999-2010 / Journal of Gynecologic Oncology 24(4):298~302 google schola Smith LH / 2005 / Romano PS. Ovarian cancer: can we make the clinical diagnosis earlier? / Cancer 104:1398~1407 google schola

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