Kolon Kanserli Hastalarda Yaşam Analizi
Year 2021,
Volume: 11 Issue: 3, 374 - 379, 24.05.2021
Ayse Ulgen
,
Şirin Çetin
,
İsa Dede
Abstract
Amaç: Bu çalışmanın amacı kolon kanseri (KK) tanısı almış hastaların sağkalımını etkileyen prognostik ve demografik faktörlerin risk derecesini ve önemini araştırmaktır. Gereç ve Yöntem: Mustafa Kemal Üniversitesi Onkoloji Kliniği'nde 01/2018 – 01/2021 arasında metastaz KK tanısı almış 80 hastanın tıbbi kayıtları gözden geçirilerek yapılan retrospektif bir çalışmadır. KK'ni etkileyen prognostik ve demografik faktörleri belirlemek için Cox regresyon analizi yapıldı ve genel sağkalımı (GS) tahmin etmek için Kaplan-Meier yöntemi kullanıldı. Sağkalım olasılıkları açısından değişken düzeyler arasındaki fark, log-rank testi kullanılarak araştırıldı.
Bulgular: Hastaların ortalama yaşı 56.72 ± 12.42 idi. Kolon kanseri olan hastaların medyan yaşam süresi 48.42 aydı (% 95 güven aralığı (CI) = 41.97-54.87). Cox regresyon analizi, yaş, tip 2 diabetes mellitus (DB) ve ailede KK öyküsünün GS ile anlamlı şekilde ilişkili olduğunu gösterdi (p <0.005). 50 yaşındaki KK hastaları; DB'li hastalar ve ailesinde KK öyküsü olan hastalar, sırasıyla <50 yaşındaki hastalara; DB olmayan hastalara ve ailesinde KK olmayan hastalara kıyasla yaklaşık 3 kat daha fazla risk altındaydı.
Sonuç ve Tartışma: KK'li hastaların sağkalımını etkileyen prognostik ve demografik faktörlerin etkisi değerlendirildi. Bulgularımız KK'nin yaş, DB ve aile öyküsünün KK'li hastaların sağkalımlarını tahmin etmek için kullanılabileceğini gösterdi. Sonuçlarımızın, metastatik KK teşhisi konan hastaların tedavisi için klinisyenlere rehberlik edeceğine inanıyoruz.
References
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https://doi.org/10.3322/caac.21660. [Epub ahead of print].
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https://doi.org/10.1111/j.1440-1746.2006.04774.x
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(14) Miłek T, Forysiński K, Myrcha P, Ciostek P. Diabetes association of polyps and colon cancer. Pol Przegl Chir 2019;28;91(4):9-12. https://doi.org/10.5604/01.3001.0013.2588.PMID: 31481646
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2017 update on the relationship between diabetes and colorectal cancer: epidemiology, potential molecular mechanisms and therapeutic implications. Diabetes Cancer Connect Consortium. Oncotarget. 2017;14;8(11):18456-18485.
https://doi.org/10.18632/oncotarget.14472.PMID: 28060743
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Survival Analysis in Colon Cancer Patients
Year 2021,
Volume: 11 Issue: 3, 374 - 379, 24.05.2021
Ayse Ulgen
,
Şirin Çetin
,
İsa Dede
Abstract
Introduction: The aim of this study is to investigate the degree of risk and significance of prognostic and demographic factors affecting the survival of patients diagnosed with colon cancer (CC).
Material and Method: This was a retrospective study conducted by reviweing the medical records of 80 patients diagnosed with metastatic CC at the Oncology Clinic at the Mustafa Kemal University between 01/2018 – 01/2021. Cox regression analysis was performed to determine the prognostic and demographic factors affecting the CC and Kaplan-Meier method was used to estimate the overall survival (OS). Difference between the variable levels in terms of survival probabilities was investigated using the log-rank test.
Results: The average age of the patients was 56.72 ± 12.42. The median survival time of patients with colon cancer was 48.42 months (95% confidence interval (CI) = 41.97-54.87). Cox regression analysis showed that age, incident type 2 diabetes mellitus (DB), and family history of CC were significantly associated with OS (p <0.005). Patients with CC aged 50 years; patients with DB and patients with a family history of CC were approximately 3 times more at risk compared to patients <50 years; patients without DB and patients without CC in the family, consecutively.
Discussion and Conclusion: The effect of prognostic and demographic factors affecting the survival of patients with CC was evaluated. Our findings showed that age, DB and family history of CC can be used to estimate the survial of patients with CC. We believe that our results will help guide practitioners for the treatment of patients diagnosed with metastatic CC.
References
- (1) Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021; Feb 4.
https://doi.org/10.3322/caac.21660. [Epub ahead of print].
- (2) Dekker E, Tanis PJ, Vleguels JLA, Kasi PM, Wallace MB. Colorectal Cancer. Lancet 2019;394(10207):1467-1480. https://doi.org/10.1016/S0140-6736(19)32319-0.
- (3) Boyle P., Leon ME. Epidemiology of colorectal cancer. British Medical Bulletin 2002;64(1):25-26. https://doi.org/10.1093/bmb/64.1.1
- (4) Mollahaliloğlu, S., Başara, B. B., & Eryılmaz, Z. TC Sağlık Bakanlığı Sağlık İstatistikleri Yıllığı. Ankara: Kalkan Matbaacılık, 2010;1-100.
- (5) International Agency For Research On Cancer, Cancer Tomorrow. Available from: http://gco.iarc.fr/tomorrow/graphic-line?type=0&population=900&mode= population &sex=0&cancer=39&age_group=value&apc_male=0&apc_female=0. Accessed on 20th October 2020.
- (6) Otake, S., Takeda, H., Suzuki, Y., Fukui, T., Watanabe, S., Ishihama, K., ... & Kawata, Association of visceral fat accumulation and plasma adiponectin with colorectal adenoma: evidence for participation of insulin resistance. Clinical Cancer Research, S 2005;11(10):3642-3646. https://doi.org/10.1158/1078-0432.CCR-04-1868
- (7) Ve Giovannucci, E., Ascherio, A., Rimm, E. B., Colditz, G. A., Stampfer, M. J., & Willett, W. C. Physical activity, obesity, and risk for colon cancer and adenoma in men. Annals of internal medicine 1995;22(5):327-334.
https://doi.org/10.7326/0003-4819-122-5-199503010-00002
- (8) Cox DR. Regression models and Life-Tables. Breakthroughs in statistics. Springer Series in Statistics, New York, NY, 1992. 527-541. https://doi.org/10.1007/978-1-4612-4380-9
- (9) Lee ET, Go OT. Survival analysis in public health research. Annu Rev Public Health 1997;18:105-134. https://doi.org/10.1146/annurev.publhealth.18.1.105
- (10) Therneau TM, grambsch PM Modelling Survival Data: Extending the Cox Model. (1st Ed), Springer, New York, 2000; 1-229
- (11) Choe JW, Chang HS, Yang SK, Myung SJ, Byeon JS, Lee D, et al. Screening colonoscopy in asymptomatic averagerisk Koreans: Analysis in relation to age and sex. Journal of gastroenterology and hepatology 2007;22(7): 1003-1008.
https://doi.org/10.1111/j.1440-1746.2006.04774.x
- (12) Von Herbay, A., Sieg, B., & Otto, H. F. Solid-cystic tumour of the pancreas. Virchows Archiv A Pathol Anat 1990; 416(6): 535-538.
- (13) Wojciechowska J , Krajewski W, Bolanowski M, Kręcicki T , Zatoński T. Diabetes and Cancer: a Review of Current Knowledge. Exp Clin Endocrinol Diabetes 2016;124(5):263-75.
- https://doi.org/10.1055/s-0042-100910. Epub 2016 May 24.
(14) Miłek T, Forysiński K, Myrcha P, Ciostek P. Diabetes association of polyps and colon cancer. Pol Przegl Chir 2019;28;91(4):9-12. https://doi.org/10.5604/01.3001.0013.2588.PMID: 31481646
- (15) González N, Prieto I, Del Puerto-Nevado L, Portal-Nuñez S, Ardura JA, Corton M, et al.
2017 update on the relationship between diabetes and colorectal cancer: epidemiology, potential molecular mechanisms and therapeutic implications. Diabetes Cancer Connect Consortium. Oncotarget. 2017;14;8(11):18456-18485.
https://doi.org/10.18632/oncotarget.14472.PMID: 28060743
- (16) Larsson, S. C., Orsini, N., & Wolk, A. Diabetes mellitus and risk of colorectal cancer: a meta-analysis. Journal of the National Cancer Institute 2005;97(22): 1679-1687.
- (17) La Vecchia, C., Negri, E., Gentile, A., & Franceschi, S. Family history and the risk of stomach and colorectal cancer. Cancer 1992; 70(1): 50-55.
- (18) Garland, C., Barrett-Connor, E., Rossof, A., Shekelle, R., Criqui, M., & Paul, O. Dietary vitamin D and calcium and risk of colorectal cancer: a 19-year prospective study in men. The Lancet 1985; 325(8424): 307-309.