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Validation of Nomograms for Survival and Metastases after Hysterectomy and Adjuvant Therapy in Uterine Cervical Cancer with Risk Factors

Authors
Yoon, Won SupYang, Dae SikLee, Jung AeLee, Nam KwonPark, Young JeKim, Chul YongLee, Nak WooHong, Jin HwaLee, Jae KwanSong, Jae Yun
Issue Date
2017
Publisher
HINDAWI LTD
Citation
BIOMED RESEARCH INTERNATIONAL, v.2017
Indexed
SCIE
SCOPUS
Journal Title
BIOMED RESEARCH INTERNATIONAL
Volume
2017
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/132434
DOI
10.1155/2017/2917925
ISSN
2314-6133
Abstract
Background. Three nomogram models for early stage uterine cervical cancer have been developed (KROG 13-03 for overall survival [OS], SNUH/AMC for disease-free survival[DES], and KROG 12-08 for distant metastases-free survival[DMFS]) after radical hysterectomy (RH) and pelvic lymph node dissection (PLND). This study aimed to validate these models using our cohort with adjuvant radiotherapy. Methods. According to the eligibility criteria of nomogram studies, patients were enrolled in Group A (N = 109) for the two KROG models (RH with PLND and whole pelvic irradiation) and Group B (N = 101) for the SNUH/AMC model (RH with PLND and squamous histology). Using Cox-regression hazard models, the prognostic factors of our cohorts were evaluated. The risk probabilities induced from published nomogram scores were calculated and the concordance indices were evaluated. Results. Group A had 88.1% 5-year OS and 86.0% 5-year DMFS. Group B had 83.0% 5-year DES. In multivariate analyses, large tumor size for OS (HR 8.62, P < 0.001) and DMFS (HR 5.13, P = 0.003), young age (<= 40 versus 41-64 years) for OS (HR 4.63, P = 0.097) and DES (HR 3.44, P = 0.051), and multiple lymph node metastases (0 versus >= 3) for DMFS (HR 4.03, P = 0.031) and DES (HR 3.90, P = 0.038) were significantly correlated. The concordance indices for OS, DMFS, and DES were 0.612 (P = 0.002), 0.597 (P = 0.014), and 0.587 (P = 0.020), respectively: Conclusion. The developed nomogram models after RH and PEND are clinically useful in predicting various types of survival with significance.
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