Risk of relapse and death from colorectal cancer and its related factors using non-Markovian Multi-State model
Gastroenterology and Hepatology from Bed to Bench,
2 June 2020
Aim: This study aimed at modeling the risk of local relapse and death from colorectal cancer after the first treatment and its related factors using multi-state models.
Background: In cancer studies modeling the course of disease regarding events which happen to patients is of great importance. By considering death as the final endpoint while incorporating the intermediate events, multi-state models have been developed.
Methods: This was a historical cohort study in which 235 patients with colorectal cancer, who referred to Omid Hospital in Mashhad between 2006 and 2011, were studied and followed up until 2017. The transition probabilities to death due to metastasis with or without experiencing local relapse and variables related to them were determined using the non-Markovian multi-state model in three states of disease, local relapse and death.
Results: The probability of not experiencing either of the events, just relapse and death in the first 5 years were 0.45, 0.09 and 0.46 respectively. If patients did not experience any event in the first year of treatment, the probability of relapse and death before the fifth year were 0.04 and 0.33 respectively and if they did experience relapse during this time, the probability of death by the fifth year was 0.62. The stage of cancer was associated with relapse and death, while ethnicity and history of addiction were related to death without relapse and BMI had a significant relationship with death after relapse (p<0.05).
Conclusion: Risk of death in patients with colorectal cancer depends on local relapse and the time between them.
Keywords: Non-Markovian Multi-State Model, Colorectal cancer, Local relapse, Death.
(Please cite as: Hajebi Khaniki S, Fakoor V, Shahid Sales S, Esmaily H, Heidarian Miri H. Risk of relapse and death from colorectal cancer and its’ related factors using non-Markovian Multi-State model. Gastroenterol Hepatol Bed Bench 2020;13(3):200-208).
- Non-markovian multi-state models
- Colorectal cancer
- local relapse
WHO. Cancer February 2018. Available from: http://www.who.int/mediacentre/factsheets/fs297/en/.
Gandomani HS, Aghajani M, Mohammadian-Hafshejani A, Tarazoj AA, Pouyesh V, Salehiniya H. Colorectal cancer in the world: incidence, mortality and risk factors. Biomed Res Ther 2017;4:1656-75.
Karsa L, Lignini T, Patnick J, Lambert R, Sauvaget C. The dimensions of the CRC problem. Best Pract Res Clin Gastroenterol 2010;24:381-96.
São Julião GP, Habr-Gama A, Vailati BB, Araujo SEA, Fernandez LM, Perez RO. New Strategies in Rectal Cancer. Surg Clin 2017;97:587-604.
Desantis C, Siegel R, Jemal A. Cancer treatment & survivorship facts & figures 2012-2013. CA Cancer J Clin 2012;62:220-41.
Beyersmann J, Allignol A, Schumacher M. Competing risks and multistate models with R. London: Springer Science & Business Media; 2011.
Masoudi S, Pourdanesh F, Biglarian A, Rahgozar M. Investigation of the follow up and prognosis of patients with squamous cell carcinoma of the mouth using the Markov multistate model. J Epidemiol 2015;11:55-62.
Geskus RB. Data analysis with competing risks and intermediate states: CRC Press; 2015.
de Uña-Álvarez J, Meira-Machado L. Nonparametric estimation of transition probabilities in the non‐Markov illness‐death model: A comparative study. Biometrics 2015;71:364-75.
Jones MP, Crowley J. Nonparametric tests of the Markov model for survival data. Biometrika 1992;79:513-22.
Rodríguez‐Girondo M, de Uña‐Álvarez J. A nonparametric test for Markovianity in the illness‐death model. Stat Med 2012;31:4416-27.
Rodríguez‐Girondo M, Uña‐Álvarez Jd. Methods for testing the Markov condition in the illness-death model: a comparative study. Stat Med 2016;35:3549-62.
Aalen OO, Johansen S. An empirical transition matrix for non-homogeneous Markov chains based on censored observations. Scand J Stat 1978:141-50.
Datta S, Satten GA. Validity of the Aalen–Johansen estimators of stage occupation probabilities and Nelson–Aalen estimators of integrated transition hazards for non-Markov models. Stat Prob Lett 2001;55:403-11.
Klein JP, Van Houwelingen HC, Ibrahim JG, Scheike TH. Handbook of survival analysis: CRC Press; 2016.
Gelfand AE, Diggle P, Guttorp P, Fuentes M. Handbook of spatial statistics: CRC press; 2010.
Pietra N, Sarli L, Thenasseril B, Costi R, Sansebastiano G, Peracchia A. Risk factors of local recurrence of colorectal cancer: a multivariate study. Hepatol Gastroenterol 1998;45:1573-8.
Abaspour S. The rate and type of relapse of colorectal cancer in patients undergoing surgery referring to Jundishapur Medical Sciences Hospitals in Ahvaz, 997-2007. Jundishapur University: Jundishapur University; 2010.
Fatemi SR, Pourhoseingholi MA, Asadi F, Vahedi M, Pasha S, Alizadeh L, et al. Recurrence and five-year survival in colorectal cancer patients after surgery. Iran J Cancer Prev 2015;8.
Gilard-Pioc S, Abrahamowicz M, Mahboubi A, Bouvier A-M, Dejardin O, Huszti E, et al. Multi-state relative survival modelling of colorectal cancer progression and mortality. Cancer Epidemiol 2015;39:447-55.
Dancourt V, Quantin C, Abrahamowicz M, Binquet C, Alioum A, Faivre J. Modeling recurrence in colorectal cancer. J Clin Epidemiol 2004;57:243-51.
Huszti E, Abrahamowicz M, Alioum A, Binquet C, Quantin C. Relative survival multistate Markov model. Stat Med 2012;31:269-86.
Cyvoct C, Quantin C, Broet P, Benhamiche A, Brunet-Lecomte P, D'athis P, et al. Prognostic factors of recurrence and/or death in colorectal cancer: multistate modeling. Rev Epidemiol Sante Publique 1999;47:619-25.
Parsaei R, Fekri N, Shahid Sales S, Afzal aghaei M, Sherbaf A, Esmaily H. Prognostic factors in the survival of patients with colorectal cancer. J North Khorasan Univ Med Sci 2015;7:45-53.
Moghimi, Dehkordi B, Safaei A, Zali Mr. Survival rates and prognostic factors in colorectal cancer patients. Sci J Med 2008;16:33-43.
Chao-Hsien L, Cheng S-C, Hong-Yi T, Chang S-C, Ching C-Y, Shu-Fen W. The Risk Factors Affecting Survival in Colorectal Cancer in Taiwan. Iran J Public Health 2018;47:519.
Huang Y, Alzahrani NA, Liauw W, Arrowaili A, Morris DL. Survival difference between mucinous vs. non-mucinous colorectal cancer following cytoreductive surgery and intraperitoneal chemotherapy. Int J Hyperthermia 2018;35:298-304.
Prasanna T, Karapetis CS, Roder D, Tie J, Padbury R, Price T, et al. The survival outcome of patients with metastatic colorectal cancer based on the site of metastases and the impact of molecular markers and site of primary cancer on metastatic pattern. Acta Oncologica 2018;57:1438-44.
Chiu KW, Lam KO, An H, Cheung GT, Lau JK, Choy TS, et al. Long-term outcomes and recurrence pattern of 18F-FDG PET-CT complete metabolic response in the first-line treatment of metastatic colorectal cancer: a lesion-based and patient-based analysis. BMC Cancer 2018;18:776.
Newland RC, Chan C, Chapuis PH, Keshava A, Rickard MJ, Young CJ, et al. Competing risks analysis of the effect of local residual tumour on recurrence and cancer-specific death after resection of colorectal cancer: implications for staging. Pathology 2018;50:600-6.
Yamano T, Yamauchi S, Tsukamoto K, Noda M, Kobayashi M, Hamanaka M, et al. Evaluation of appropriate follow-up after curative surgery for patients with colorectal cancer using time to recurrence and survival after recurrence: a retrospective multicenter study. Oncotarget 2018;9:25474.
Yazilitas D, Özdemir N, Hocazade C, Demirci NS, Zengin N. The clinical and pathological features affecting the time of relapse in patients with early stage colorectal cancer. J Cancer Res Ther 2016;12:1257.
- Abstract Viewed: 42 times
- PDF Downloaded: 0 times