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Mismeasured Covariate in the Long-Term Survival of Colorectal Cancer

Mehdi Azizmohammad Looha, Mohamad Amin Pourhoseingholi, Seyyed Vahid Hosseini, Soheila Khodakarim
Background: Colorectal cancer (CRC) is one of the most important causes of morbidity and mortality worldwide. This study aimed to determine the effect of measurement error of risk factors on the cure fraction of CRC patients. Materials and Methods: This study was conducted using the medical records of 346 patients with CRC, who were followed up between 2006 and 2017 in Shiraz, Iran. In our data, lymph node ratio (LNR) was a characteristic measuring with error. This variable was used in the model with 0.04 and 0.8 of error variance. Nonmixture nonparametric cure rate model and its corrected forms, simulation-extrapolation (SIMEX) and corrected score (CS), were applied to the data. Results: In noncured cases, the mean survival time was 1115.45 (95% confidence interval, 1043.60-1187.30) days. The 1-, 3-, and 5-year survival rates were 0.93, 0.71, and 0.65, respectively. The proportion of cured patients was 65.2%. The SIMEX method did not change the effect of LNR substantially on cure fraction as compared with the naive method when the variance of measurement error was 0.04 and 0.80. The CS method changed the effect of LNR on cure fraction even when the variance of measurement error was 0.04. Conclusion: The best method to assess the effect of LNR on cure fraction was the naive method, and the CS method was not deemed to be a valid method to correct the measurement error in LNR. [GMJ.2019;8:e1413]  

 

Colorectal Cancer; Errors; Survival Rate; Survival Analysis

Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin s. 2018;68(6):394-424.

https://doi.org/10.3322/caac.21492

PMid:30207593

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.

https://doi.org/10.1136/gutjnl-2015-310912

PMid:26818619

Gandomani HS, yousefi SM, Aghajani M, Mohammadian-Hafshejani A, Tarazoj AA, Pouyesh V et al. Colorectal cancer in the world: incidence, mortality and risk factors. BMRAT. 2017;4(10):1656-75.

https://doi.org/10.15419/bmrat.v4i10.372

Tsoi KKF, Hirai HW, Chan FCH, Griffiths S, Sung JJY. Predicted Increases in Incidence of Colorectal Cancer in Developed and Developing Regions, in Association With Ageing Populations. Clin Gastroenterol Hepatol . 2017;15(6):892-900.e4.

https://doi.org/10.1016/j.cgh.2016.09.155

PMid:27720911

Watanabe T, Muro K, Ajioka Y, Hashiguchi Y, Ito Y, Saito Y et al. Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2016 for the treatment of colorectal cancer. Int J Clin Oncol. 2018;23(1):1-34.

https://doi.org/10.1007/s10147-017-1101-6

PMid:28349281 PMCid:PMC5809573

Johnson CM, Wei C, Ensor JE, Smolenski DJ, Amos CI, Levin B et al. Meta-analyses of Colorectal Cancer Risk Factors. Cancer Causes Control. 2013;24(6):1207-22.

https://doi.org/10.1007/s10552-013-0201-5

PMid:23563998 PMCid:PMC4161278

American Cancer Society. Colorectal Cancer Risk Factors 2017. https://www.cancer.org/cancer/colon-rectal-cancer/causes-risks-prevention/risk-factors.html#references. Accessed 4 October 2017.

Kolahdoozan S, Sadjadi A, Radmard AR, Khademi H. Five common cancers in Iran. Arch Iran Med. 2010;13(2):143-6.

Barouni M, Larizadeh MH, Sabermahani A, Ghaderi H. Markov's modeling for screening strategies for colorectal cancer. Asian Pac J Cancer Prev. 2012;13(10):5125-9.

https://doi.org/10.7314/APJCP.2012.13.10.5125

PMid:23244122

Moghimi-Dehkordi B, Safaee A, Zali MR. Prognostic factors in 1,138 Iranian colorectal cancer patients. Int J Colorectal Dis. 2008;23(7):683-8.

https://doi.org/10.1007/s00384-008-0463-7

PMid:18330578

Abdifard E, Amini S, Bab S, Masroor N, Khachian A, Heidari M. Incidence trends of colorectal cancer in Iran during 2000-2009: A population-based study. Med J Islam Repub Iran. 2016;30:382-.

Haghdoost AA CG, Zarei MR, Rad M, Hashemipoor M, Marzban M. Low Incidence of Colorectal Cancer in Kerman Province, Iran. Iran J Cancer Prev. 2011;4(1):33-7

Atkin WS, Edwards R, Kralj-Hans I, Wooldrage K, Hart AR, Northover JM et al. Once-only flexible sigmoidoscopy screening in prevention of colorectal cancer: a multicentre randomised controlled trial. Lancet (London, England). 2010;375(9726):1624-33.

https://doi.org/10.1016/S0140-6736(10)60551-X

Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin. 2010;60(5):277-300.

https://doi.org/10.3322/caac.20073

PMid:20610543

Miller KD, Siegel RL, Lin CC, Mariotto AB, Kramer JL, Rowland JH et al. Cancer treatment and survivorship statistics, 2016. CA Cancer J Clin. 2016;66(4):271-89.

https://doi.org/10.3322/caac.21349

PMid:27253694

Moghimi-Dehkordi B, Safaee A. An overview of colorectal cancer survival rates and prognosis in Asia. World J Gastrointest Oncol. 2012;4(4):71-5.

https://doi.org/10.4251/wjgo.v4.i4.71

PMid:22532879 PMCid:PMC3334382

Amico M, Keilegom IV. Cure Models in Survival Analysis. Annual Review of Statistics and Its Application. 2018;5(1):311-42.

https://doi.org/10.1146/annurev-statistics-031017-100101

Lambert PC, Thompson JR, Weston CL, Dickman PW. Estimating and modeling the cure fraction in population-based cancer survival analysis. Biostatistics (Oxford, England). 2007;8(3):576-94.

https://doi.org/10.1093/biostatistics/kxl030

PMid:17021277

Carroll RJ, Ruppert D, Stefanski LA, Crainiceanu CM. Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition. CRC Press; 2006.

https://doi.org/10.1201/9781420010138

Cook JR, Stefanski LA. Simulation-Extrapolation Estimation in Parametric Measurement Error Models. J Am Stat Assoc. 1994;89(428):1314-28.

https://doi.org/10.1080/01621459.1994.10476871

Ibrahim JG, Chen MH, Sinha D. Bayesian Survival Analysis. Springer New York; 2013.

https://doi.org/10.1002/9781118445112.stat06003

Tsodikov AD, Ibrahim JG, Yakovlev AY. Estimating Cure Rates From Survival Data: An Alternative to Two-Component Mixture Models. J Am Stat Assoc. 2003;98(464):1063-78.

https://doi.org/10.1198/01622145030000001007

PMid:21151838 PMCid:PMC2998771

Bertrand A, Legrand C, Léonard D, Van Keilegom I. Robustness of estimation methods in a survival cure model with mismeasured covariates. Comput Stat Data Anal. 2017;113:3-18.

https://doi.org/10.1016/j.csda.2016.11.013

Ma Y, Yin G. Cure Rate Model with Mismeasured Covariates under Transformation. J Am Stat Assoc. 2008;103(482):743-56.

https://doi.org/10.1198/016214508000000319

Bertrand A, Legrand C, Carroll RJ, de Meester C, Van Keilegom I. Inference in a survival cure model with mismeasured covariates using a simulation-extrapolation approach. Biometrika. 2017;104(1):31-50.

https://doi.org/10.1093/biomet/asw054

PMid:29151774 PMCid:PMC5693403

Białek EJ, Jakubowski W. Mistakes in ultrasound diagnosis of superficial lymph nodes. J Ultrason. 2017;17(68):59-65.

https://doi.org/10.15557/JoU.2017.0008

PMid:28439430 PMCid:PMC5392555

Derwinger K, Gustavsson B. A study of lymph node ratio in stage IV colorectal cancer. World J Surg Oncol. 2008;6:127-.

https://doi.org/10.1186/1477-7819-6-127

PMid:19046414 PMCid:PMC2633268

Lee HY, Choi HJ, Park KJ, Shin JS, Kwon HC, Roh MS et al. Prognostic significance of metastatic lymph node ratio in node-positive colon carcinoma. Ann Surg Oncol. 2007;14(5):1712-7.

https://doi.org/10.1245/s10434-006-9322-3

PMid:17253102

Campbell PT, Newton CC, Dehal AN, Jacobs EJ, Patel AV, Gapstur SM. Impact of body mass index on survival after colorectal cancer diagnosis: the Cancer Prevention Study-II Nutrition Cohort. J Clin Oncol. 2012;30(1):42-52.

https://doi.org/10.1200/JCO.2011.38.0287

PMid:22124093

Moamer S, Baghestani A, Pourhoseingholi MA, Hajizadeh N, Ahmadi F, Norouzinia M. Evaluation of prognostic factors effect on survival time in patients with colorectal cancer, based on Weibull Competing-Risks Model. Gastroenterol Hepatol Bed Bench. 2017;10(1):54-9.

https://doi.org/10.5812/ijcm.7352

Simkens LHJ, Koopman M, Mol L, Veldhuis GJ, Ten Bokkel Huinink D, Muller EW et al. Influence of body mass index on outcome in advanced colorectal cancer patients receiving chemotherapy with or without targeted therapy. Eur J Cancer. 2011;47(17):2560-7.

https://doi.org/10.1016/j.ejca.2011.06.038

PMid:21803570

Wan S, Lai Y, Myers RE, Li B, Palazzo JP, Burkart AL et al. Post-diagnosis hemoglobin change associates with overall survival of multiple malignancies - results from a 14-year hospital-based cohort of lung, breast, colorectal, and liver cancers. BMC Cancer. 2013;13(1):340.

https://doi.org/10.1186/1471-2407-13-340

PMid:23841898 PMCid:PMC3710492

Liebig C, Ayala G, Wilks J, Verstovsek G, Liu H, Agarwal N et al. Perineural Invasion Is an Independent Predictor of Outcome in Colorectal Cancer. J Clin Oncol. 2009;27(31):5131-7.

https://doi.org/10.1200/JCO.2009.22.4949

PMid:19738119 PMCid:PMC2773472

Akagi Y, Adachi Y, Ohchi T, Kinugasa T, Shirouzu K. Prognostic impact of lymphatic invasion of colorectal cancer: a single-center analysis of 1,616 patients over 24 years. Anticancer Res. 2013;33(7):2965-70.

Khan MR, Bari H, Zafar SN, Raza SA. Impact of age on outcome after colorectal cancer surgery in the elderly - a developing country perspective. BMC Surg. 2011;11(1):17.

https://doi.org/10.1186/1471-2482-11-17

PMid:21849062 PMCid:PMC3175436

Akbari ME. Survival of Colorectal Cancer Patients in Iran. Gastrointest Cancer Res. 2011;4(4 Suppl 1):S21-S.

Lu T. Simultaneous inference for semiparametric mixed-effects joint models with skew distribution and covariate measurement error for longitudinal competing risks data analysis. J Biopharm Stat. 2017;27(6):1009-27.

https://doi.org/10.1080/10543406.2017.1293080

PMid:28272995

Khudyakov P, Gorfine M, Zucker D, Spiegelman D. The impact of covariate measurement error on risk prediction. Stat Med. 2015;34(15):2353-67.

https://doi.org/10.1002/sim.6498

PMid:25865315 PMCid:PMC4480422

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