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. 2017 Oct 31:22:115.
doi: 10.4103/jrms.JRMS_6_17. eCollection 2017.

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes

Sadegh Kargarian-Marvasti  1 , Shahnaz Rimaz  2 , Jamileh Abolghasemi  3 , Iraj Heydari  4   5
Affiliations

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes

Sadegh Kargarian-Marvasti et al. J Res Med Sci. .

Abstract

Background: Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes.

Materials and methods: This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model (P < 0.20) were entered into the multivariate Cox and parametric models (P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS).

Results: Using Kaplan-Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy (P < 0.05).

Conclusion: According to AIC, "log-normal" model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model.

Keywords: Cox proportional hazards model; Kaplan–Meier; diabetes; neuropathy; parametric models.

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Conflict of interest statement

The authors have no conflicts of interest.

Figures

Figure 1
Figure 1
Number and annual trend of diabetic patients and event of neuropathy
Figure 2
Figure 2
Cumulative hazard function of neuropathy in patients with type 2 diabetes
Figure 3
Figure 3
Accuracy of semi-parametric and parametric models by the area under operating characteristics curve in the prediction of event time of diabetic neuropathy in patients with type 2 diabetes
See this image and copyright information in PMC

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