Risk factors of hepatocellular carcinoma in type 2 diabetes patients: A two-centre study in a developing country

Abstract

Type 2 diabetes mellitus (T2DM) is increasingly known as a risk factor of hepatocellular carcinoma (HCC). In this study, we determined the risk factors associated with HCC in T2DM patients. This was a matched case-control study conducted at two hepatobiliary referral centres in a developing country. Patients’ sociodemographic, clinical, and biochemical characteristics between 1 January 2012 and 30 June 2018 were extracted from the electronic medical records and analysed using multivariate logistic regression analysis. A total of 212 case-control pairs were included. Significant risk factors included Chinese and Malay ethnicities that interacted with viral hepatitis (adjusted odds ratio [AOR] = 11.77, 95% confidence interval [CI]: 1.39–99.79) and (AOR = 37.94, 95% CI: 3.92–367.61) respectively, weight loss (AOR = 5.28, 95% CI: 2.29–12.19), abdominal pain/ discomfort (AOR = 6.73, 95% CI: 3.34–13.34), alcohol (AOR = 4.08, 95% CI: 1.81–9.22), fatty liver (AOR = 3.29, 95% CI: 1.40–7.76), low platelet (AOR = 4.03, 95% CI:1.90–8.55), raised alanine transaminase (AOR = 2.11, 95% CI: 1.16–3.86). and alkaline phosphatase (ALP) levels (AOR = 2.17, 95% CI: 1.17–4.00). Statins reduced the risk of HCC by 63% (AOR = 0.37, 95% CI: 0.21–0.65). The identification of these factors aids the risk stratification for HCC among T2DM patients for early detection and decision-making in patient management in the primary care setting.

Prediction of hepatocellular carcinoma risk in patients with type-2 diabetes using supervised machine learning classification model

“…The variance inflation factor (VIF) of all included variables ranges from 1.18-1.79, suggested no multicollinearity problem among the included variables [ 26 ]. This finding had been discussed in detail in the previous literature [ 19 ].…”

“…The multiple logistic regression (MLR) analysis showed that ten variables were significantly associated with HCC development after adjustment for age, sex, race, DM duration, blood transfusion, smoking, traditional medication, metformin, gliclazide, insulin, HbA1c, RBC, WBC, total bilirubin, and creatinine. These independent factors are; weight loss (adjusted odd ratio [AOR] = 5.28, 95% CI: 2.29; 12.19), having abdominal pain/discomfort (AOR = 6.73, 95% CI: 3.34; 13.34), viral hepatitis infection which interacted with Malay (AOR = 11.77, 95% CI: 1.39; 99.79) and Chinese race (AOR = 37.94, 95% CI: 3.92; 367.61), non-alcoholic fatty liver disease (AOR = 3.29, 95% CI: 1.40; 7.76), statins usage (AOR = 0.37, 95% CI: 0.21; 0.65), history of alcohol consumption (AOR = 4.08, 95% CI: 1.81–9.22), reduced platelet level <150 × 103/μL (AOR = 4.03, 95% CI:1.90; 8.55), ALP level >129 IU/L (AOR = 2.17, 95% CI:1.17; 4.00) and raised ALT ≥25 IU/L (AOR = 2.11, 95% CI: 1.16; 3.86) [ 19 ]. The variance inflation factor (VIF) of all included variables ranges from 1.18-1.79, suggested no multicollinearity problem among the included variables [ 26 ].…”

“…Patients diagnosed with cancer or without DM treatment records were excluded. The detailed methodology of this study was previously described elsewhere [ 19 ].…”

“…A fully conditional specification (FCS) method was employed to generate five imputed datasets. The missing data analysis was previously presented elsewhere [ 19 ]. The multiply imputed dataset was compressed into a single dataset using the “bar procedure”.…”

“…Missing data management was unnecessary since the dataset was derived from previously imputed data [ 19 ]. All the values were legitimate for processing and there were no duplicates or outliers.…”