Introducing an optimal liver allocation system for liver cirrhosis patients

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

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.

Improving Quality of Care in Patients with Liver Cirrhosis

Liver cirrhosis is a major chronic disease in the field of digestive diseases. It causes more than one million deaths per year. Despite established evidence based guidelines, the adherence to standard of care or quality indicators are variable. Complete adherence to the recommendations of guidelines is less than 50%. To improve the quality of care in patients with cirrhosis, we need a more holistic view. Because of high rate of death due to cardiovascular disease and neoplasms, the care of comorbid conditions and risk factors such as smoking, hypertension, high blood sugar or cholesterol, would be important in addition to the management of primary liver disease. Despite a holistic multidisciplinary approach for this goal, the management of such patients should be patient centered and individualized. The diagnosis of underlying etiology and its appropriate treatment is the most important step. Definition and customizing the quality indicators for quality measure in patients are needed. Because most suggested quality indicators are designed for measuring the quality of care in decompensated liver cirrhosis, we need special quality indicators for compensated and milder forms of chronic liver disease as well. Training the patients for participation in their own management, design of special clinics with dedicated health professionals in a form of chronic disease model, is suggested for improvement of quality of care in this group of patients. Special day care centers by a dedicated gastroenterologist and a trained nurse may be a practical model for better management of such patients.