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Application of Smoothing Methods for Determining of the Effecting Factors on the Survival Rate of Gastric Cancer Patients

AUTHORS

Hoda Noorkojuri 1 , Ebrahim Hajizadeh 1 , * , Ahmadreza Baghestani 2 , Mohamadamin Pourhoseingholi 3

AUTHORS INFORMATION

1 Department of Biostatistics, Faculty of Medical Sciences,Tarbiat Modares University, Tarbiat Modares University, Tehran, IR Iran

2 2. Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran

3 Department of Biostatistics, Gastroenterology and Liver Diseases Research Center, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran

How to Cite: Noorkojuri H, Hajizadeh E, Baghestani A, Pourhoseingholi M. Application of Smoothing Methods for Determining of the Effecting Factors on the Survival Rate of Gastric Cancer Patients, Iran Red Crescent Med J. Online ahead of Print ; 15(2):166-72. doi: 10.5812/ircmj.8649.

ARTICLE INFORMATION

Iranian Red Crescent Medical Journal: 15 (2); 166-72
Published Online: February 4, 2013
Article Type: Research Article
Received: October 16, 2012
Accepted: January 1, 2013
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Abstract

Background: Smoothing methods are widely used to analyze epidemiologic data, particularly in the area of environmental health where non-linear relationships are not uncommon. This study focused on three different smoothing methods in Cox models: penalized splines, restricted cubic splines and fractional polynomials.

Objectives: The aim of this study was to assess the effects of prognostic factors on survival of patients with gastric cancer using the smoothing methods in Cox model and Cox proportional hazards. Also, all models were compared to each other in order to find the best one.

Materials and Methods: We retrospectively studied 216 patients with gastric cancer who were registered in one referral cancer registry center in Tehran, Iran. Age at diagnosis, sex, presence of metastasis, tumor size, histology type, lymph node metastasis, and pathologic stages were entered in to analysis using the Cox proportional hazards model and smoothing methods in Cox model. The SPSS version 18.0 and R version 2.14.1 were used for data analysis. These models compared with Akaike information criterion.

Results: In this study, The 5 year survival rate was 30%. The Cox proportional hazards, penalized spline and fractional polynomial models let to similar results and Akaike information criterion showed a better performance for these three models comparing to the restricted cubic spline. Also, P-value and likelihood ratio test in restricted cubic spline was greater than other models. Note that the best model is indicated by the lowest Akaike information criterion.

Conclusions: The use of smoothing methods helps us to eliminate non-linear effects but it is more appropriate to use Cox proportional hazards model in medical data because of its ease of interpretation and capability of modeling both continuous and discrete covariates. Also, Cox proportional hazards model and smoothing methods analysis identified that age at diagnosis and tumor size were independent prognostic factors for the survival of patients with gastric cancer (P < 0.05). According to these results the early detection of patients at younger age and in primary stages may be important to increase survival.

Keywords

Proportional Hazards Models Survival Stomach Neoplasms

© 2013, Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

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