Xiaolong Ma1, Xu Guan1, Chenxi Ma1, Jichuan Quan1, Zhixun Zhao1, Haipeng Chen1, Haiyang Huang1, Ran Wei1, Zheng Liu1, Zheng Jiang1, Yinggang Chen2, Xishan Wang1. 1. Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 2. Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Abstract
BACKGROUND: Our understanding in prognosis of bone metastasis (BM) from colorectal cancer (CRC) is limited. We aimed to establish a clinical risk stratification for individually predicting the survival of CRC patients with BM. METHODS: A total of 200 CRC patients with BM were included in this study. Survival time from BM diagnosis was estimated using the Kaplan-Meier method. The multivariable COX regression model identified the risk factors on cancer specific survival (CSS). Based on weighted scoring system, the stratification model was constructed to classify patients with BM according to prognostic risk. Discrimination power and calibration ability of risk stratification were measured. RESULTS: The median CSS time was 11 months after BM diagnosis. Lymph node metastasis, Carbohydrate antigen 199 (CA199) levels, bone involvement, Karnofsky Performance Status (KPS) scores, primary tumor resection, bisphosphonates therapy and radiotherapy were identified as predictors of CSS. Four risk groups were stratified according to weighted scoring system, including low risk, medium risk, medium-high risk and high risk group, with 35, 16, 9 and 5 months of median CSS, respectively (P=0.000). The risk stratification displayed good accuracy in predicting CSS, with acceptable discrimination and calibration. CONCLUSIONS: This novel risk stratification predicts CSS in CRC patient with BM using easily accessible clinicopathologic factors, which is recommended for use in individualized clinical decision making in patient with BM. 2021 Journal of Gastrointestinal Oncology. All rights reserved.
BACKGROUND: Our understanding in prognosis of bone metastasis (BM) from colorectal cancer (CRC) is limited. We aimed to establish a clinical risk stratification for individually predicting the survival of CRC patients with BM. METHODS: A total of 200 CRC patients with BM were included in this study. Survival time from BM diagnosis was estimated using the Kaplan-Meier method. The multivariable COX regression model identified the risk factors on cancer specific survival (CSS). Based on weighted scoring system, the stratification model was constructed to classify patients with BM according to prognostic risk. Discrimination power and calibration ability of risk stratification were measured. RESULTS: The median CSS time was 11 months after BM diagnosis. Lymph node metastasis, Carbohydrate antigen 199 (CA199) levels, bone involvement, Karnofsky Performance Status (KPS) scores, primary tumor resection, bisphosphonates therapy and radiotherapy were identified as predictors of CSS. Four risk groups were stratified according to weighted scoring system, including low risk, medium risk, medium-high risk and high risk group, with 35, 16, 9 and 5 months of median CSS, respectively (P=0.000). The risk stratification displayed good accuracy in predicting CSS, with acceptable discrimination and calibration. CONCLUSIONS: This novel risk stratification predicts CSS in CRC patient with BM using easily accessible clinicopathologic factors, which is recommended for use in individualized clinical decision making in patient with BM. 2021 Journal of Gastrointestinal Oncology. All rights reserved.
Entities:
Keywords:
Colorectal cancer (CRC); bone metastasis (BM); prognostic factors; risk stratification
Authors: Vincenzo Valentini; Ruud G P M van Stiphout; Guido Lammering; Maria Antonietta Gambacorta; Maria Cristina Barba; Marek Bebenek; Franck Bonnetain; Jean-Francois Bosset; Krzysztof Bujko; Luca Cionini; Jean-Pierre Gerard; Claus Rödel; Aldo Sainato; Rolf Sauer; Bruce D Minsky; Laurence Collette; Philippe Lambin Journal: J Clin Oncol Date: 2011-07-11 Impact factor: 44.544
Authors: Hyung Soon Park; Sun Young Rha; Hyo Song Kim; Woo Jin Hyung; Ji Soo Park; Hyun Cheol Chung; Sung Hoon Noh; Hei-Cheul Jeung Journal: Oncology Date: 2011-06-15 Impact factor: 2.935
Authors: David Choi; Zoe Fox; Todd Albert; Mark Arts; Laurent Balabaud; Cody Bunger; Jacob M Buchowski; Maarten H Coppes; Bart Depreitere; Michael G Fehlings; James Harrop; Norio Kawahara; Juan A Martin-Benlloch; Eric M Massicotte; Christian Mazel; Fetullah C Oner; Wilco Peul; Nasir Quraishi; Yasuaki Tokuhashi; Katsuro Tomita; Jorit Jan Verlaan; Michael Wang; H Alan Crockard Journal: Neurosurgery Date: 2015-11 Impact factor: 4.654
Authors: Freddie Bray; Jacques Ferlay; Isabelle Soerjomataram; Rebecca L Siegel; Lindsey A Torre; Ahmedin Jemal Journal: CA Cancer J Clin Date: 2018-09-12 Impact factor: 508.702
Authors: Rachel McDonald; Keyue Ding; Michael Brundage; Ralph M Meyer; Abdenour Nabid; Pierre Chabot; Genevieve Coulombe; Shahida Ahmed; Joda Kuk; A Rashid Dar; Aamer Mahmud; Alysa Fairchild; Carolyn F Wilson; Jackson S Y Wu; Kristopher Dennis; Carlo DeAngelis; Rebecca K S Wong; Liting Zhu; Stephanie Chan; Edward Chow Journal: JAMA Oncol Date: 2017-07-01 Impact factor: 31.777
Authors: J H Park; T-Y Kim; K-H Lee; S-W Han; D-Y Oh; S-A Im; G H Kang; E K Chie; S W Ha; S-Y Jeong; K J Park; J-G Park; T-Y Kim Journal: Br J Cancer Date: 2013-03-12 Impact factor: 7.640