The use of population-based health datasets in the research of gastrointestinal and liver diseases

Abstract

This thesis investigated how population-based health datasets can be utilized in the research of gastrointestinal and liver diseases. Utilization of population-based health datasets is one of the Big Data approaches in medical research to improve health and health system performance. Its application in gastric cancer research was described in the first seven studies, colorectal cancer in next three studies, and liver diseases in last study. All studies utilized the territory-wide healthcare database, known as Clinical Data Analysis and Reporting System (CDARS), managed by the Hong Kong Hospital Authority which is the sole public healthcare provider. The first study compared the gastric cancer risk of the cohort of Helicobacter pylori (H. pylori)-infected adults who had received clarithromycin-based triple therapy (which was the first-line therapy in Hong Kong during the study period) with the matched general population in Hong Kong, showing that H. pylori eradication reduced gastric cancer risk 10 years after treatment, in particular older subjects. The following four studies identified a cohort of adults who had received clarithromycin-based triple therapy for H. pylori infection. The first study showed that long term use of proton pump inhibitors (PPIs) was associated with an increased gastric cancer risk even after H. pylori eradication therapy. The second study showed that aspirin was associated with a reduced gastric cancer risk. This is followed by the third study investigating the interaction between PPIs and aspirin on gastric cancer, demonstrating the potential harmful effects of PPIs on gastric cancer was limited to non-aspirin users. The fourth study showed that statins were also potential chemopreventive agents against gastric cancer. The next two studies focused on the role of diabetes mellitus (DM) and metformin in gastric cancer development after H. pylori eradication therapy. Type II DM was found to be a risk factor for gastric cancer, and metformin was associated with a lower gastric cancer risk among patients with DM, effect of which was independent of glycemic control. The next three studies investigated the epidemiology, characteristics, and survival of post-colonoscopy colorectal cancer (PCCRC) in Hong Kong, as well as the role of statins and non-steroidal anti-inflammatory drugs (NSAIDs) in PCCRC development. The rate of PCCRC for an interval of 3 years (PCCRC-3y) was 7.9%, with a high proportion of distal colon cancer and higher cancer-specific mortality compared with detected CRC. Both statins and NSAIDs were found to be associated with a lower PCCRC risk. The final study investigated the epidemiology of Wilson’s disease. It was found that there was a decrease in the incidence but an increase in the prevalence of Wilson’s disease between 2000 and 2016. Different clinical manifestations and adverse outcomes were described. Cirrhosis and concurrent chronic viral hepatitis were factors affecting survival. This series of studies demonstrate how Big Data approach using population-based health datasets addresses important clinical questions in the field of gastroenterology and hepatology in a cost-effective manner, which would not be otherwise achievable by traditional clinical study designs like case-control study, prospective cohort study, or randomized controlled trial.