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

被引:15
作者
Borumandnia, Nasrin [1 ]
Doosti, Hassan [2 ]
Jalali, Amirhossein [3 ]
Khodakarim, Soheila [4 ]
Charati, Jamshid Yazdani [5 ]
Pourhoseingholi, Mohamad Amin [6 ]
Talebi, Atefeh [7 ]
Agah, Shahram [7 ]
机构
[1] Shahid Beheshti Univ Med Sci, Urol & Nephrol Res Ctr, Tehran 1666663111, Iran
[2] Macquarie Univ, Dept Math & Stat, Sydney, NSW 2109, Australia
[3] Univ Coll Cork, Sch Math Sci, Cork T12 XF62, Ireland
[4] Shiraz Univ Med Sci, Sch Med, Dept Biostat, Shiraz 7188614228, Iran
[5] Mazandaran Univ Med Sci, Hlth Sci Res Ctr, Sch Publ Hlth, Addict Inst,Biostat Dept, Sari 1353447416, Iran
[6] Shahid Beheshti Univ Med Sci, Gastroenterol & Liver Dis Res Ctr, Res Inst Gastroenterol & Liver Dis, Tehran 1985717413, Iran
[7] Iran Univ Med Ctr, Colorectal Res Ctr, Tehran 1445613131, Iran
关键词
colorectal cancer; cox proportional hazards; nomogram; overall survival; risk factors; VALIDATION; OUTCOMES;
D O I
10.3390/ijerph18157734
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
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页数:11
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