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CC BY-NC-ND 4.0 · South Asian J Cancer 2016; 05(01): 23-26
DOI: 10.4103/2278-330X.179703
GI CANCER Original Article

Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis

Amal Saki Malehi
Research Center of Thalassemia and Hemoglobinopathy, Health Research Institute, Ahvaz Jundishapur University of Medical Sciences
Department of Biostatistics and Epidemiology, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
,
Fakher Rahim
Research Center of Thalassemia and Hemoglobinopathy, Health Research Institute, Ahvaz Jundishapur University of Medical Sciences
› Author Affiliations Source of Support: Nill.
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Abstract

Aims: The aim of this study was to determine the prognostic index for separating homogenous subgroups in colorectal cancer (CRC) patients based on clinicopathological characteristics using survival tree analysis. Methods: The current study was conducted at the Research Center of Gastroenterology and Liver Disease, Shahid Beheshti Medical University in Tehran, between January 2004 and January 2009. A total of 739 patients who already have been diagnosed with CRC based on pathologic report were enrolled. The data included demographic and clinical-pathological characteristic of patients. Tree-structured survival analysis based on a recursive partitioning algorithm was implemented to evaluate prognostic factors. The probability curves were calculated according to the Kaplan-Meier method, and the hazard ratio was estimated as an interest effect size. Result: There were 526 males (71.2%) of these patients. The mean survival time (from diagnosis time) was 42.46± (3.4). Survival tree identified three variables as main prognostic factors and based on their four prognostic subgroups was constructed. The log-rank test showed good separation of survival curves. Patients with Stage I-IIIA and treated with surgery as the first treatment showed low risk (median = 34 months) whereas patients with stage IIIB, IV, and more than 68 years have the worse survival outcome (median = 9.5 months). Conclusion: Constructing the prognostic classification index via survival tree can aid the researchers to assess interaction between clinical variables and determining the cumulative effect of these variables on survival outcome.

Key words

Classification - colorectal cancer - Iran - prognostic index - survival tree


Publication History

Article published online:
30 December 2020

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  • References

  • 1 Ferlay JS, Ervik M, Dikshit R, Eser S, Mathers C, Rebelo M, et al. GLOBOCAN Cancer Incidence and Mortality Worldwide: IARC CancerBase. Lyon, France: International Agency for Research on Cancer; 2013.
  • 2 Mousavi SM, Gouya MM, Ramazani R, Davanlou M, Hajsadeghi N, Seddighi Z. Cancer incidence and mortality in Iran. Ann Oncol 2009;20:556-63.
  • 3 Malekzadeh R, Bishehsari F, Mahdavinia M, Ansari R. Epidemiology and molecular genetics of colorectal cancer in Iran: A review. Arch Iran Med 2009;12:161-9.
  • 4 Kolahdoozan S, Sadjadi A, Radmard AR, Khademi H. Five common cancers in Iran. Arch Iran Med 2010;13:143-6.
  • 5 Hassanzade J, Molavi E Vardanjani H, Farahmand M, Rajaiifard AR. Incidence and mortality rate of common gastrointestinal cancers in South of Iran, a population based study. Iran J Cancer Prev 2011;4:163-9.
  • 6 Moghimi-Dehkordi B, Safaee A, Zali MR. Prognostic factors in 1,138 Iranian colorectal cancer patients. Int J Colorectal Dis 2008;23:683-8.
  • 7 Safaee A, Moghimi-Dehkordi B, Fatemi S, Ghiasi S, Zali M. Pathology and prognosis of colorectal cancer. Iran J Cancer Prev 2009;2:137-41.
  • 8 Bou-Hamad I, Larocque D, Ben-Ameur H. A review of survival trees. Stat Surv 2011;5:44-71.
  • 9 Zhang H, Singer BH. Recursive Partitioning and Applications. 2nd ed. New York: Springer; 2010.
  • 10 Breiman L, Friedman J, Stone CJ, Olshen RA. Classification and Regression Trees. New York: Chapman and Hall/CRC; 1984.
  • 11 Banerjee M, Noone AM. Tree-based methods for survival data. In: Biswas A, editor. Statistical Advances in the Biomedical Sciences. New Jersey: John Wiley and Sons, Inc.; 2008. p. 265-81.
  • 12 Ibrahim NA, Kudus A, Daud I, Abu Bakar MR. Decision tree for competing risks survival probability in breast cancer study. Int J Biol Med Sci 2008;3:25-9.
  • 13 Al-Nachawati H, Ismail M, Almohisen A. Tree-structured analysis of survival data and its application using SAS software. J King Saud Univ (Science) 2010;22:251-5.
  • 14 Schumacher M, Holländer N, Schwarzer G, Sauerbrei W. Prognostic factor studies. In: Crowley J, editor. Handbook of Statistics in Clinical Oncology. New York: Marcel Dekker, Inc.; 2001. p. 321-78.
  • 15 Edge S, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A. AJCC Cancer Staging Manual. 7th ed. New York: Springer; 2010.
  • 16 Elsamany SA, Alzahrani AS, Mohamed MM, Elmorsy SA, Zekri JE, Al-Shehri AS, et al. Clinico-pathological patterns and survival outcome of colorectal cancer in young patients: Western Saudi Arabia experience. Asian Pac J Cancer Prev 2014;15:5239-43.
  • 17 Forones NM, Tanaka M, Falcão JB. CEA as a prognostic index in colorectal cancer. Sao Paulo Med J 1997;115:1589-92.
  • 18 Moghimi-Dehkordi B, Safaee A. An overview of colorectal cancer survival rates and prognosis in Asia. World J Gastrointest Oncol 2012;4:71-5.
  • 19 Henry KA, Niu X, Boscoe FP. Geographic disparities in colorectal cancer survival. Int J Health Geogr 2009;8:48.
  • 20 Barnholtz-Sloan JS, Guan X, Zeigler-Johnson C, Meropol NJ, Rebbeck TR. Decision tree-based modeling of androgen pathway genes and prostate cancer risk. Cancer Epidemiol Biomarkers Prev 2011;20:1146-55.
  • 21 Shen C, Yang H, Chang Y. A decision tree-based approach for cervical smears. Int J Innov Comput Inf Control 2012;8:3251-63.
  • 22 Malehi AS. Diagnostic classification scheme in Iranian breast cancer patients using a decision tree. Asian Pac J Cancer Prev 2014;15:5593-6.
  • 23 Valera VA, Walter BA, Yokoyama N, Koyama Y, Iiai T, Okamoto H, et al. Prognostic groups in colorectal carcinoma patients based on tumor cell proliferation and classification and regression tree (CART) survival analysis. Ann Surg Oncol 2007;14:34-40.
  • 24 Oñate-Ocaña LF, Montesdeoca R, López-Graniel CM, Aiello-Crocifoglio V, Mondragón-Sánchez R, Cortina-Borja M, et al. Identification of patients with high-risk lymph node-negative colorectal cancer and potential benefit from adjuvant chemotherapy. Jpn J Clin Oncol 2004;34:323-8.
  • 25 Coutinho AK, Rocha Lima CM. Metastatic colorectal cancer: Systemic treatment in the new millennium. Cancer Control 2003;10:224-38.
  • 26 Shayanfar N, Shahzadi SZ. Immunohistochemical assessment of neuroendocrine differentiation in colorectal carcinomas and its relation with age, sex and grade plus stage. Iran J Pathol 2009;4:167-71.
  • 27 Oh HS, Chung HJ, Kim HK, Choi JS. Differences in overall survival when colorectal cancer patients are stratified into new TNM staging strategy. Cancer Res Treat 2007;39:61-4.
  • 28 Aghili M, Izadi S, Madani H, Mortazavi H. Clinical and pathological evaluation of patients with early and late recurrence of colorectal cancer. Asia Pac J Clin Oncol 2010;6:35-41.
  • 29 Molaei M, Mansoori BK, Ghiasi S, Khatami F, Attarian H, Zali M. Colorectal cancer in Iran: Immunohistochemical profiles of four mismatch repair proteins. Int J Colorectal Dis 2010;25:63-9.