Mingyu Chen1,2, Shijie Li1, Win Topatana3, Xiaozhong Lv4, Jiasheng Cao1, Jiahao Hu1, Jian Lin5, Sarun Juengpanich3, Jiliang Shen1, Xiujun Cai1,3. 1. Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China. 2. Engineering Research Center of Cognitive Healthcare of Zhejiang Province, Hangzhou, China. 3. Zhejiang University School of Medicine, Hangzhou, China. 4. Department of General Surgery, First People's Hospital, Mudanjiang, China. 5. Department of General Surgery, Longyou People's Hospital, Quzhou, China.
Abstract
BACKGROUND: The management of gallbladder cancer (GBC) patients with recurrence who need additional therapy or intensive follow-up remains controversial. Therefore, we aim to develop a nomogram to predict survival in GBC patients with recurrence after surgery. METHODS: A total of 313 GBC patients with recurrence from our center was identified as a primary cohort, which were randomly divided into a training cohort (N = 209) and an internal validation cohort (N = 104). In addition, 105 patients from other centers were selected as an external validation cohort. Independent prognostic factors, identified by univariate and multivariable analysis, were used to construct a nomogram. The performance of this nomogram was measured using Harrell's concordance index (C-index) and calibration curves. RESULTS: Our nomogram was established by four factors, including time-to-recurrence, site of recurrence, CA19-9 at recurrence, and treatment of recurrence. The C-index of this nomogram in the training, internal and external validation cohort was 0.871, 0.812, and 0.754, respectively. The calibration curves showed an optimal agreement between nomogram prediction and actual observation. Notably, this nomogram could accurately stratify patients into different risk subgroups, which allowed more significant distinction of Kaplan-Meier curves than that of using T category. The 3-year post-recurrence survival (PRS) rates in the low-, medium-, and high-risk subgroups from the external validation cohort were 53.3, 26.2, and 4.1%, respectively. CONCLUSION: This nomogram provides a tool to predict 1- and 3-year PRS rates in GBC patients with recurrence after surgery.
BACKGROUND: The management of gallbladder cancer (GBC) patients with recurrence who need additional therapy or intensive follow-up remains controversial. Therefore, we aim to develop a nomogram to predict survival in GBC patients with recurrence after surgery. METHODS: A total of 313 GBC patients with recurrence from our center was identified as a primary cohort, which were randomly divided into a training cohort (N = 209) and an internal validation cohort (N = 104). In addition, 105 patients from other centers were selected as an external validation cohort. Independent prognostic factors, identified by univariate and multivariable analysis, were used to construct a nomogram. The performance of this nomogram was measured using Harrell's concordance index (C-index) and calibration curves. RESULTS: Our nomogram was established by four factors, including time-to-recurrence, site of recurrence, CA19-9 at recurrence, and treatment of recurrence. The C-index of this nomogram in the training, internal and external validation cohort was 0.871, 0.812, and 0.754, respectively. The calibration curves showed an optimal agreement between nomogram prediction and actual observation. Notably, this nomogram could accurately stratify patients into different risk subgroups, which allowed more significant distinction of Kaplan-Meier curves than that of using T category. The 3-year post-recurrence survival (PRS) rates in the low-, medium-, and high-risk subgroups from the external validation cohort were 53.3, 26.2, and 4.1%, respectively. CONCLUSION: This nomogram provides a tool to predict 1- and 3-year PRS rates in GBC patients with recurrence after surgery.
Authors: Samuel J Wang; Andrew Lemieux; Jayashree Kalpathy-Cramer; Celine B Ord; Gary V Walker; C David Fuller; Jong-Sung Kim; Charles R Thomas Journal: J Clin Oncol Date: 2011-11-07 Impact factor: 44.544
Authors: Jacques Ferlay; Hai-Rim Shin; Freddie Bray; David Forman; Colin Mathers; Donald Maxwell Parkin Journal: Int J Cancer Date: 2010-12-15 Impact factor: 7.396