Comparison of Artificial Neural Network and Logistic Regression Models for Predicting In-Hospital Mortality after Primary Liver Cancer Surgery

Abstract

BackgroundSince most published articles comparing the performance of artificial neural network (ANN) models and logistic regression (LR) models for predicting hepatocellular carcinoma (HCC) outcomes used only a single dataset, the essential issue of internal validity (reproducibility) of the models has not been addressed. The study purposes to validate the use of ANN model for predicting in-hospital mortality in HCC surgery patients in Taiwan and to compare the predictive accuracy of ANN with that of LR model.Methodology/Principal FindingsPatients who underwent a HCC surgery during the period from 1998 to 2009 were included in the study. This study retrospectively compared 1,000 pairs of LR and ANN models based on initial clinical data for 22,926 HCC surgery patients. For each pair of ANN and LR models, the area under the receiver operating characteristic (AUROC) curves, Hosmer-Lemeshow (H-L) statistics and accuracy rate were calculated and compared using paired T-tests. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and the relative importance of variables. Compared to the LR models, the ANN models had a better accuracy rate in 97.28% of cases, a better H-L statistic in 41.18% of cases, and a better AUROC curve in 84.67% of cases. Surgeon volume was the most influential (sensitive) parameter affecting in-hospital mortality followed by age and lengths of stay.Conclusions/SignificanceIn comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data.

Artificial Neural Network Model for Predicting 5-year Mortality after Surgery for Hepatocellular Carcinoma and Performance Comparison with Logistic Regression Model: A Nationwide Taiwan Database Study

“…The findings are consistent with an earlier retrospective study by Shi et al, in which comparisons of 1,000 pairs of LR and ANN models generated from initial clinical data for 22,926 HCC surgery patients showed that the ANN models were more accurate in predicting in-hospital mortality and had higher overall performance indices [19].…”

Comparison of the Performance of Log-logistic Regression and Artificial Neural Networks for Predicting Breast Cancer Relapse

“…The results is showed In comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices (Shi et al, 2012).…”

Trends and predictors of outcomes after surgery for hepatocellular carcinoma: A nationwide population-based study in Taiwan

“…Finally, the low in-hospital mortality and low 5-year mortality observed in patients treated by surgeons who had performed a high volume of HCCs in the previous year and the positive association observed between HCC outcomes and volume of surgeries performed by the surgeon and by the hospital in the past year are consistent with other longitudinal studies. 10,11 In the current study, the trend analysis of HCC revealed an increasing hospital treatment cost, a decreasing LOS, and an increasing temporal trend in the prevalence of HCC, especially in elderly patients. All three trends were simultaneous and consistent over time.…”

“…Previous studies reveal several clinical parameters that are strongly associated with hospital resource utilization. 10,11,31,32 However, the limited availability of claims data in the current study precluded analysis of many clinical parameters. Table 4 shows that LOS significantly differed between males and females.…”