Nasrin Borumandnia1, Hassan Doosti2, Amirhossein Jalali3, Soheila Khodakarim4, Jamshid Yazdani Charati5, Mohamad Amin Pourhoseingholi6, Atefeh Talebi7, Shahram Agah7. 1. Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran 1666663111, Iran. 2. Department of Mathematics and Statistics, Macquarie University, Sydney, NSW 2109, Australia. 3. School of Mathematical Sciences, University College Cork, T12 XF62 Cork, Ireland. 4. Department of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz 7188614228, Iran. 5. Health Sciences Research Center, Biostatistics Department, Addiction Institute, School of Public Health, Mazandaran University of Medical Sciences, Sari 1353447416, Iran. 6. Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Disease, Shahid Beheshti University of Medical Sciences, Tehran 1985717413, Iran. 7. Colorectal Research Center, Iran University of Medical Center, Tehran 1445613131, Iran.
Abstract
BACKGROUND: Colorectal cancer (CRC) is the third foremost cause of cancer-related death and the fourth most commonly diagnosed cancer globally. The study aimed to evaluate the survival predictors using the Cox Proportional Hazards (CPH) and established a novel nomogram to predict the Overall Survival (OS) of the CRC patients. MATERIALS AND METHODS: A historical cohort study, included 1868 patients with CRC, was performed using medical records gathered from Iran's three tertiary colorectal referral centers from 2006 to 2019. Two datasets were considered as train set and one set as the test set. First, the most significant prognostic risk factors on survival were selected using univariable CPH. Then, independent prognostic factors were identified to construct a nomogram using the multivariable CPH regression model. The nomogram performance was assessed by the concordance index (C-index) and the time-dependent area under the ROC curve. RESULTS: The age of patients, body mass index (BMI), family history, tumor grading, tumor stage, primary site, diabetes history, T stage, N stage, and type of treatment were considered as significant predictors of CRC patients in univariable CPH model (p < 0.2). The multivariable CPH model revealed that BMI, family history, grade and tumor stage were significant (p < 0.05). The C-index in the train data was 0.692 (95% CI, 0.650-0.734), as well as 0.627 (0.670, 0.686) in the test data. CONCLUSION: We improved a novel nomogram diagram according to factors for predicting OS in CRC patients, which could assist clinical decision-making and prognosis predictions in patients with CRC.
BACKGROUND:Colorectal cancer (CRC) is the third foremost cause of cancer-related death and the fourth most commonly diagnosed cancer globally. The study aimed to evaluate the survival predictors using the Cox Proportional Hazards (CPH) and established a novel nomogram to predict the Overall Survival (OS) of the CRCpatients. MATERIALS AND METHODS: A historical cohort study, included 1868 patients with CRC, was performed using medical records gathered from Iran's three tertiary colorectal referral centers from 2006 to 2019. Two datasets were considered as train set and one set as the test set. First, the most significant prognostic risk factors on survival were selected using univariable CPH. Then, independent prognostic factors were identified to construct a nomogram using the multivariable CPH regression model. The nomogram performance was assessed by the concordance index (C-index) and the time-dependent area under the ROC curve. RESULTS: The age of patients, body mass index (BMI), family history, tumor grading, tumor stage, primary site, diabetes history, T stage, N stage, and type of treatment were considered as significant predictors of CRCpatients in univariable CPH model (p < 0.2). The multivariable CPH model revealed that BMI, family history, grade and tumor stage were significant (p < 0.05). The C-index in the train data was 0.692 (95% CI, 0.650-0.734), as well as 0.627 (0.670, 0.686) in the test data. CONCLUSION: We improved a novel nomogram diagram according to factors for predicting OS in CRCpatients, which could assist clinical decision-making and prognosis predictions in patients with CRC.