Seung-Hyuk Shim1, Sun Joo Lee1, Seon-Ok Kim2, Soo-Nyung Kim1, Dae-Yeon Kim3, Jong Jin Lee4, Jong-Hyeok Kim5, Yong-Man Kim5, Young-Tak Kim5, Joo-Hyun Nam5. 1. Department of Obstetrics and Gynecology, Konkuk University School of Medicine, Seoul, Republic of Korea. 2. Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea. 3. Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea. Electronic address: nastassja@naver.com. 4. Department of Nuclear Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea. 5. Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
Abstract
OBJECTIVE: Accurately predicting cytoreducibility in advanced-ovarian cancer is needed to establish preoperative plans, consider neoadjuvant chemotherapy, and improve clinical trial protocols. We aimed to develop a positron-emission tomography/computed tomography-based nomogram for predicting incomplete cytoreduction in advanced-ovarian cancer patients. METHODS: Between 2006 and 2012, 343 consecutive advanced-ovarian cancer patients underwent positron-emission tomography/computed tomography before primary cytoreduction: 240 and 103 patients were assigned to the model development or validation cohort, respectively. After reviewing the detailed surgical documentation, incomplete cytoreduction was defined as a remaining gross residual tumor. We evaluated each individual surgeon's surgical aggressiveness index (number of high-complex surgeries/total number of surgeries). Possible predictors, including surgical aggressiveness index and positron-emission tomography/computed tomography features, were analyzed using logistic regression modeling. A nomogram based on this model was developed and externally validated. RESULTS: Complete cytoreduction was achieved in 120 patients (35%). Surgical aggressiveness index and five positron-emission tomography/computed tomography features were independent predictors of incomplete cytoreduction. Our nomogram predicted incomplete cytoreduction by incorporating these variables and demonstrated good predictive accuracy (concordance index = 0.881; 95% CI = 0.838-0.923). The predictive accuracy of our validation cohort was also good (concordance index = 0.881; 95% CI = 0.790-0.932) and the predicted probability was close to the actual observed outcome. Our model demonstrated good performance across surgeons with varying degrees of surgical aggressiveness. CONCLUSION: We have developed and validated a nomogram for predicting incomplete cytoreduction in advanced-ovarian cancer patients which may help stratify patients for clinical trials, establish meticulous preoperative plans, and determine if neoadjuvant chemotherapy is warranted.
OBJECTIVE: Accurately predicting cytoreducibility in advanced-ovarian cancer is needed to establish preoperative plans, consider neoadjuvant chemotherapy, and improve clinical trial protocols. We aimed to develop a positron-emission tomography/computed tomography-based nomogram for predicting incomplete cytoreduction in advanced-ovarian cancerpatients. METHODS: Between 2006 and 2012, 343 consecutive advanced-ovarian cancerpatients underwent positron-emission tomography/computed tomography before primary cytoreduction: 240 and 103 patients were assigned to the model development or validation cohort, respectively. After reviewing the detailed surgical documentation, incomplete cytoreduction was defined as a remaining gross residual tumor. We evaluated each individual surgeon's surgical aggressiveness index (number of high-complex surgeries/total number of surgeries). Possible predictors, including surgical aggressiveness index and positron-emission tomography/computed tomography features, were analyzed using logistic regression modeling. A nomogram based on this model was developed and externally validated. RESULTS: Complete cytoreduction was achieved in 120 patients (35%). Surgical aggressiveness index and five positron-emission tomography/computed tomography features were independent predictors of incomplete cytoreduction. Our nomogram predicted incomplete cytoreduction by incorporating these variables and demonstrated good predictive accuracy (concordance index = 0.881; 95% CI = 0.838-0.923). The predictive accuracy of our validation cohort was also good (concordance index = 0.881; 95% CI = 0.790-0.932) and the predicted probability was close to the actual observed outcome. Our model demonstrated good performance across surgeons with varying degrees of surgical aggressiveness. CONCLUSION: We have developed and validated a nomogram for predicting incomplete cytoreduction in advanced-ovarian cancerpatients which may help stratify patients for clinical trials, establish meticulous preoperative plans, and determine if neoadjuvant chemotherapy is warranted.
Authors: Tuulia Vallius; Johanna Hynninen; Jukka Kemppainen; Victor Alves; Kari Auranen; Jaakko Matomäki; Sinikka Oksa; Johanna Virtanen; Seija Grénman; Annika Auranen; Marko Seppänen Journal: Eur J Nucl Med Mol Imaging Date: 2018-02-23 Impact factor: 9.236
Authors: Dirk Timmerman; François Planchamp; Tom Bourne; Chiara Landolfo; Andreas du Bois; Luis Chiva; David Cibula; Nicole Concin; Daniela Fischerova; Wouter Froyman; Guillermo Gallardo Madueño; Birthe Lemley; Annika Loft; Liliana Mereu; Philippe Morice; Denis Querleu; Antonia Carla Testa; Ignace Vergote; Vincent Vandecaveye; Giovanni Scambia; Christina Fotopoulou Journal: Int J Gynecol Cancer Date: 2021-06-10 Impact factor: 3.437
Authors: Joline F Roze; Jacob P Hoogendam; Fleur T van de Wetering; René Spijker; Leen Verleye; Joan Vlayen; Wouter B Veldhuis; Rob Jpm Scholten; Ronald P Zweemer Journal: Cochrane Database Syst Rev Date: 2018-10-08