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Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study

Author

Listed:
  • Nasrin Borumandnia

    (Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran 1666663111, Iran)

  • Hassan Doosti

    (Department of Mathematics and Statistics, Macquarie University, Sydney, NSW 2109, Australia)

  • Amirhossein Jalali

    (School of Mathematical Sciences, University College Cork, T12 XF62 Cork, Ireland)

  • Soheila Khodakarim

    (Department of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz 7188614228, Iran)

  • Jamshid Yazdani Charati

    (Health Sciences Research Center, Biostatistics Department, Addiction Institute, School of Public Health, Mazandaran University of Medical Sciences, Sari 1353447416, Iran)

  • Mohamad Amin Pourhoseingholi

    (Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Disease, Shahid Beheshti University of Medical Sciences, Tehran 1985717413, Iran)

  • Atefeh Talebi

    (Colorectal Research Center, Iran University of Medical Center, Tehran 1445613131, Iran)

  • Shahram Agah

    (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.

Suggested Citation

  • Nasrin Borumandnia & Hassan Doosti & Amirhossein Jalali & Soheila Khodakarim & Jamshid Yazdani Charati & Mohamad Amin Pourhoseingholi & Atefeh Talebi & Shahram Agah, 2021. "Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study," IJERPH, MDPI, vol. 18(15), pages 1-11, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:15:p:7734-:d:598345
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    References listed on IDEAS

    as
    1. Alexander Zlotnik & Victor Abraira, 2015. "A general-purpose nomogram generator for predictive logistic regression models," Stata Journal, StataCorp LP, vol. 15(2), pages 537-546, June.
    2. Yilong Zhang & Xiaoxia Han & Yongzhao Shao, 2021. "The ROC of Cox proportional hazards cure models with application in cancer studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(2), pages 195-215, April.
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