OBJECTIVE: The aim of this study was to develop a nomogram for predicting the 5-year disease-free survival (DFS) after radical hysterectomy for early-stage cervical cancer. PATIENTS AND METHODS: An institutional database of 275 consecutive patients treated at Seoul National University Hospital for stage I to stage IIA cervical cancer was used to develop a nomogram based on Cox proportional hazards regression model. The developed nomogram was internally validated with bootstrapping, and performance was assessed by concordance index and a calibration curve. External validation was also performed using an independent data set of patients from Asan Medical Center. RESULTS: From Cox regression analysis, disease stage, number of positive lymph nodes, parametrial involvement, and depth of invasion were identified as independent risk factors for disease recurrence (P < 0.05). The nomogram incorporating these factors appeared to be accurate and predicted the outcomes better than the International Federation of Gynecology and Obstetrics stage alone (concordance index, 0.858 compared with 0.719; P = 0.001). When applied to a separate validation set, the nomogram also showed similar predictive accuracy (concordance index, 0.879). CONCLUSION: We have developed a nomogram that can predict the recurrence risk in patients with early-stage cervical cancer after surgery, which was internally and externally validated.
OBJECTIVE: The aim of this study was to develop a nomogram for predicting the 5-year disease-free survival (DFS) after radical hysterectomy for early-stage cervical cancer. PATIENTS AND METHODS: An institutional database of 275 consecutive patients treated at Seoul National University Hospital for stage I to stage IIA cervical cancer was used to develop a nomogram based on Cox proportional hazards regression model. The developed nomogram was internally validated with bootstrapping, and performance was assessed by concordance index and a calibration curve. External validation was also performed using an independent data set of patients from Asan Medical Center. RESULTS: From Cox regression analysis, disease stage, number of positive lymph nodes, parametrial involvement, and depth of invasion were identified as independent risk factors for disease recurrence (P < 0.05). The nomogram incorporating these factors appeared to be accurate and predicted the outcomes better than the International Federation of Gynecology and Obstetrics stage alone (concordance index, 0.858 compared with 0.719; P = 0.001). When applied to a separate validation set, the nomogram also showed similar predictive accuracy (concordance index, 0.879). CONCLUSION: We have developed a nomogram that can predict the recurrence risk in patients with early-stage cervical cancer after surgery, which was internally and externally validated.
Authors: David Cibula; Lukáš Dostálek; Jiri Jarkovsky; Constantijne H Mom; Aldo Lopez; Henrik Falconer; Anna Fagotti; Ali Ayhan; Sarah H Kim; David Isla Ortiz; Jaroslav Klat; Andreas Obermair; Fabio Landoni; Juliana Rodriguez; Ranjit Manchanda; Jan Kosťun; Ricardo Dos Reis; Mehmet M Meydanli; Diego Odetto; Rene Laky; Ignacio Zapardiel; Vit Weinberger; Klára Benešová; Martina Borčinová; Darwin Pari; Sahar Salehi; Nicolò Bizzarri; Huseyin Akilli; Nadeem R Abu-Rustum; Rosa A Salcedo-Hernández; Veronika Javůrková; Jiří Sláma; Luc R C W van Lonkhuijzen Journal: Eur J Cancer Date: 2021-10-16 Impact factor: 10.002
Authors: S Polterauer; C Grimm; G Hofstetter; N Concin; C Natter; A Sturdza; R Pötter; C Marth; A Reinthaller; G Heinze Journal: Br J Cancer Date: 2012-08-07 Impact factor: 7.640
Authors: Hee Jung Kim; Dae Woo Lee; Ga Won Yim; Eun Ji Nam; Sunghoon Kim; Sang Wun Kim; Young Tae Kim Journal: Int J Oncol Date: 2014-11-17 Impact factor: 5.650
Authors: Won Sup Yoon; Dae Sik Yang; Jung Ae Lee; Nam Kwon Lee; Young Je Park; Chul Yong Kim; Nak Woo Lee; Jin Hwa Hong; Jae Kwan Lee; Jae Yun Song Journal: Biomed Res Int Date: 2017-04-27 Impact factor: 3.411