Developing a Simple Conceptual Causal Model for Predicting Early Recurrence and Mortality after Curative Surgery for Colorectal Cancer Patients
-
Samira Ahmadi
,
Shayesteh Alinia
,
Zahra Mohammadi
,
Farzaneh Rastkar Shirvandeh
,
Mohammad Asghari-Jafarabadi
,
Leila Mahmoudi
,
Malihe Safari
,
Ghodratollah Roshanaei
Abstract
Introduction: Colorectal cancer (CRC) represents the second leading cause of cancer-related mortality. This study focused on the development of a robust conceptual causal model designed to predict early recurrence and mortality following curative surgery in colorectal cancer patients.
Methods: In this retrospective cohort study, we included 284 patients with colorectal cancer (CRC) who underwent surgery at the Imam Khomeini (RA) Clinic in Hamadan, Iran, between 2001 and 2017. Demographic characteristics, treatment modalities, and other relevant data were extracted from patient records. Predictors were analyzed using Generalized Structural Equation Modeling (GSEM) for survival analysis, employing an accelerated failure time (AFT) approach. Both unadjusted and adjusted time ratios (TRs) were calculated using STATA software.
Results: The results of our developed causal model indicated that receiving chemotherapy was significantly associated with a shorter survival time ratio (TR = 0.415, 95% CI: 0.290-0.593), and recurrence time (TR = 0.363, 95% CI: 0.190-0.696). Conversely, patients who underwent multiple chemotherapy sessions exhibited a longer survival time (TR = 2.130, 95% CI: 1.790-2.534) and recurrence time (TR = 2.206, 95% CI: 1.609-3.023). Age had a direct impact on the recurrence time (TR = 0.758, 95% CI: 0.602-0.955). Additionally, age had a significant direct effect on the receipt of chemotherapy, the cancer site, and the receipt of radiotherapy.
Conclusion: In summary, our study's causal model reveals that chemotherapy shortens survival time but multiple sessions can extend both survival and recurrence times. Age significantly affects recurrence time and chemotherapy receipt. These findings highlight the importance of personalized treatment strategies in colorectal cancer management.
Keywords: Generalized Structural Equation Model, Conceptual causal model, Accelerated failure time, Early recurrence, Colorectal cancer
References
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32. Gottschalk A, Ford JG, Regelin CC, You J, Mascha EJ, Sessler DI, et al. Association between epidural analgesia and cancer recurrence after colorectal cancer surgery. Anesthesiology. 2010;113(1):27–34.
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1. Keum N, Giovannucci E. Global burden of colorectal cancer: emerging trends, risk factors and prevention strategies. Nat Rev Gastroenterol Hepatol. 2019;16(12):713–32.
2. Mármol I, Sánchez-de-Diego C, Dieste AP, Cerrada E, Yoldi MJR. Colorectal Carcinoma: A General Overview and Future Perspectives in Colorectal Cancer. Int J Mol Sci 2017, Vol 18, Page 197 [Internet]. 2017 Jan 19 [cited 2023 May 17];18(1):197. Available from: https://www.mdpi.com/1422- 0067/18/1/197/htm.
3. Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut. 2017;66(4):683–91.
4. Onyoh EF, Hsu WF, Chang LC, Lee YC, Wu MS, Chiu HM. The rise of colorectal cancer in Asia: epidemiology, screening, and management1. Onyoh EF, Hsu WF, Chang LC, Lee YC, Wu MS, Chiu HM. The rise of colorectal cancer in Asia: epidemiology, screening, and management. Curr Gastroenterol Rep. 2019;21:1–10. Curr Gastroenterol Rep. 2019;21:1–10.
5. Cardoso R, Guo F, Heisser T, Hackl M, 220 Vol 10 No 2 (2024) Developing a Simple Conceptual Causal Model for Predicting ... Ahmadi S et al. Ihle P, De Schutter H, et al. Colorectal cancer incidence, mortality, and stage distribution in European countries in the colorectal cancer screening era: an international population based study. Lancet Oncol. 2021;22(7):1002– 13.
6. Alves CMM, Souza VGB, Bastos RR. Colorectal cancer mortality in mato grosso, brazil: Spatiotemporal trends. Geospat Health. 2020;15(1):123–30.
7. Ryuk JP, Choi GS, Park JS, Kim HJ, Park SY, Yoon GS, et al. Predictive factors and the prognosis of recurrence of colorectal cancer within 2 years after curative resection. Ann Surg Treat Res. 2014;86(3):143–51.
8. O’Reilly M, Linehan A, Krstic A, Kolch W, Sheahan K, Winter DC, et al. Oncotherapeutic Strategies in Early Onset Colorectal Cancer. Cancers (Basel). 2023;15(2).
9. Kim SE, Paik HY, Yoon H, Lee JE, Kim N, Sung MK. Sex- and gender-specific disparities in colorectal cancer risk. World J Gastroenterol. 2015;21(17):5167–75.
10. Koroukian SM, Booker BD, Vu L, Schumacher FR, Rose J, Cooper GS, et al. Receipt of Targeted Therapy and Survival Outcomes in Patients With Metastatic Colorectal Cancer. JAMA Netw Open. 2023;6(1):e2250030.
11. Mahmoudi L, Fallah R, Roshanaei G, Asghari-Jafarabadi M. A bayesian approach to model the underlying predictors of early recurrence and postoperative death in patients with colorectal Cancer. BMC Med Res Methodol. 2022;22(1).
12. Yagyu T, Yamamoto M, Tanio A, Hara K, Sugezawa K, Uejima C, et al. Risk factors for recurrence in elderly patients with stage II colorectal cancer: a multicenter retrospective study. BMC Cancer. 2022 Apr;22(1):390.
13. Tsikitis VL, Larson DW, Huebner M, Lohse CM, Thompson PA. Predictors of recurrence free survival for patients with stage II and III colon cancer. BMC Cancer. 2014;14(1):1–7.
14. Majek O, Gondos A, Jansen L, Emrich K, Holleczek B, Katalinic A, et al. Sex differences in colorectal cancer survival: population-based analysis of 164,996 colorectal cancer patients in Germany. PLoS One. 2013;8(7):e68077.
15. Chandio A, Chandio M, Shaikh Z, Khichi Z, Memon N, Brown MK. Does Gender Matter in Colorectal Cancer ? 2023;1–7.
16. Kang BM, Baek JH, Park SJ, Baek SK, Park KJ, Choi HJ, et al. Impact of Adjuvant Therapy Type on Survival in Stage II/III Rectal Cancer Without Preoperative Chemoradiation: A Korean Multicenter Retrospective Study. Ann Coloproctol. 2018 Jun;34(3):144–51.
17. Du XL, Cai Y, Symanski E. Association between chemotherapy and cognitive impairments in a large cohort of patients with colorectal cancer. Int J Oncol. 2013;42(6):2123–33.
18. Lund CM, Vistisen KK, Dehlendorff 221 Vol 10 No 2 (2024) Developing a Simple Conceptual Causal Model for Predicting ... Ahmadi S et al. C, Rønholt F, Johansen JS, Nielsen DL. Age-dependent differences in first-line chemotherapy in patients with metastatic colorectal cancer: the DISCO study. Acta Oncol (Madr). 2018;57(11):1445–54.
19. Li P, Xiao Z, Braciak TA, Ou Q, Chen G, Oduncu FS. A relationship to survival is seen by combining the factors of mismatch repair status, tumor location and age of onset in colorectal cancer patients. PLoS One. 2017;12(3):e0172799.
20. Wang CB, Shahjehan F, Merchea A, Li Z, Bekaii-Saab TS, Grothey A, et al. Impact of tumor location and variables associated with overall survival in patients with colorectal cancer: A mayo clinic colon and rectal cancer registry study. Front Oncol. 2019 Feb 19;9(FEB):76.
21. Maniragaba VN, Atuhaire LK, Rutayisire PC. Modeling the Risk Factors of Undernutrition among Children below Five Years of Age in Uganda Using Generalized Structural Equation Models. Children. 2023;10(12):1926.
22. Chou YJ, Lin HY, Cooper BA, Lin BR, Jiang JK, Yang HY, et al. A resilience model for patients with colorectal cancer: A structural equation modeling analysis. Cancer Nurs. 2022;45(1):E83–90.
23. Cohen M, Baziliansky S, Beny A. The association of resilience and age in individuals with colorectal cancer: an exploratory cross sectional study. J Geriatr Oncol. 2014;5(1):33– 9.
24. Austin JD, Allicock M, Atem F, Lee SC, Fernandez ME, Balasubramanian BA. A structural equation modeling approach to understanding pathways linking survivorship care plans to survivor-level outcomes. J Cancer Surviv. 2020;14:834–46.
25. Siddiqui K. Heuristics for sample size determination in multivariate statistical techniques. World Appl Sci J. 2013;27(2):285– 7.
26. Stata. STata Structural Equation Modeling Reference Manual. Release 17. 2015. 1-26 p.
27. Atuhaire L, Rutayisire PC. WHEN SEX MATTERS: A COMPARATIVE GENERALISED STRUCTURAL EQUATION MODEL (GSEM) FOR THE DETERMINANTS OF STUNTING AMONGST UNDER-FIVES IN UGANDA. 2022;
28. Chabner BA RT. Timeline: Chemotherapy and the war on cancer. Nat Rev Cancer. 2005;5(1):65–72.
29. Di Maio M, Gridelli C, Gallo C, Shepherd F, Piantedosi FV, Cigolari S, Manzione L, Illiano A, Barbera S, Robbiati SF, Frontini L, Piazza E, Ianniello GP, Veltri E, Castiglione F, Rosetti F, Gebbia V, Seymour L, Chiodini P PF. Chemotherapy-induced neutropenia and treatment efficacy in advanced non-small-cell lung cancer: a pooled analysis of three randomised trials. Lancet Oncol. 6(9):669–77.
30. Halabi M El, Horanieh R, Tamim H, Mukherji D, Jdiaa S, Temraz S, et al. The 222 Vol 10 No 2 (2024) Developing a Simple Conceptual Causal Model for Predicting ... Ahmadi S et al. impact of age on prognosis in patients with gastric cancer: experience in a tertiary care centre. J Gastrointest Oncol [Internet]. 2020 Dec 1 [cited 2023 Oct 6];11(6):1233. Available from: /pmc/articles/PMC7807276/.
31. Song YX, Gao P, Wang ZN, Tong LL, Xu YY, Sun Z, Xing CZ XH. Which is the most suitable classification for colorectal cancer, log odds, the number or the ratio of positive lymph nodes? PLoS One. 2011;6(12):e28937.
32. Gottschalk A, Ford JG, Regelin CC, You J, Mascha EJ, Sessler DI, et al. Association between epidural analgesia and cancer recurrence after colorectal cancer surgery. Anesthesiology. 2010;113(1):27–34.
33. Aryaie M, Roshandel G, Semnani S, Asadi-Lari M, Aarabi M, Vakili MA, et al. Predictors of Colorectal Cancer Survival in Golestan, Iran: A Population-based Study. Epidemiol Health. 2013;35:e2013004.
34. Group EBCTC. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;365(9472):1687–717.
35. Pacetti P, Paganini G, Orlandi M, Mambrini A, Pennucci MC, Del Freo A, et al. Chemotherapy in the last 30 days of life of advanced cancer patients. Support Care Cancer. 2015;23:3277–80.
36. Błogowski W, Bodnarczuk T, Starzyńska T. Concise Review: Pancreatic Cancer and Bone Marrow-Derived Stem Cells. Stem Cells Transl Med. 2016 Jul;5(7):938–45
37. Chang GJ, Skibber JM, Feig BW, Rodriguez-Bigas M. Are we undertreating rectal cancer in the elderly? An epidemiologic study. Ann Surg. 2007 Aug;246(2):215–21. 38. Pesapane F, Rotili A, Botta F, Raimondi S, Bianchini L, Corso F, et al. Radiomics of MRI for the Prediction of the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients: A Single Referral Centre Analysis. Cancers (Basel). 2021 Aug;13(17).
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| Issue | Vol 10 No 2 (2024) | |
| Section | Articles | |
| DOI | https://doi.org/10.18502/jbe.v10i2.17645 | |
| Keywords | ||
| Generalized Structural Equation Model Conceptual causal model Accelerated failure time Early recurrence Colorectal cancer | ||
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How to Cite
1.
Ahmadi S, Alinia S, Mohammadi Z, Rastkar Shirvandeh F, Asghari-Jafarabadi M, Mahmoudi L, Safari M, Roshanaei G. Developing a Simple Conceptual Causal Model for Predicting Early Recurrence and Mortality after Curative Surgery for Colorectal Cancer Patients. JBE. 2024;10(2):209-222.
