Discussion
We applied trajectory analysis to examine changes in FBG levels at three different time points between 2002 and 2007, which enabled us to identify four distinct trajectory groups. The most prevalent group was the low-stable group, which constituted 87.78% of the sample population. The elevated-stable, high-stable, and elevated-high groups accounted for 7.17%, 3.22%, and 1.82% of the population, respectively. Notably, previous research exploring FBG trajectories reported varying numbers of trajectories, typically ranging from four to five.22 23 29 Similarly, a prior study conducted in Korea by Jeon et al also investigated FBG trajectories and identified four distinct patterns.23 However, the distribution and proportion of each trajectory group in our study differed from those observed in the aforementioned study. Specifically, four groups included low-stable, moderate-stable, elevated-upward, and high-upward with the percentage of each group were 47.9%, 44.1%, 6.7%, and 14.0%, respectively.23 This difference is due to dissimilarities in the targeted population, sample size, and follow-up duration. Notably, our study used a larger sample size and included participants aged between 40 and 79 years who were at high risk, whereas the study of Jeon et al recruited examinees starting from 20 years of age.23
Our analysis identified positive relations between FBG trajectories and the risks of overall cancers, gastrointestinal cancer, as well as several specific cancers (multiple myeloma and malignant plasma cell neoplasms, oral, stomach, liver, and pancreatic cancer). A previous study in China also explored FBG trajectories and their association with overall cancers and digestive cancers.22 Significant associations with all cancers and digestive cancers were observed in low-stable and elevated-stable groups.22 However, because of the limited number of cancer cases, a detailed analysis of site-specific cancers could not be extensively conducted.22
An elevated risk for overall cancers was observed in the elevated-stable group, which provides a potential suggestion for further investigations into the prediabetic population in the future. While past research consistently indicates a positive association between a history of diabetes and cancer risk, suggesting that the high-stable group may be closely linked to an elevated risk of total cancer, our study produced conflicting results.4 5 This discrepancy may be attributed to the predominance of diabetic individuals in this group, comprising over 90% of the sample. While both adjusted HR for all cancer combined in model 1 and model 2 in table 2 showed significant results, this became non-significant after adjusting for diabetes diagnosis. Regarding increase cancer risk in patients with elevated FBG, a prospective cohort study found a significant association between FBG levels ranging from 110 to 125 mg/dL and cancer risk in males, but not in females.30 Other studies have also documented an elevated risk of cancer in prediabetic individuals, accompanied by higher mortality from certain types of cancer.12 19 31 Several biological mechanisms underlie this association. Hyperglycemia-induced accumulation of advanced glycation end-products and the generation of oxidative stress may promote cancer development.32 Furthermore, hyperinsulinemia and increased level of bioavailable IGF, which are associated with insulin resistance,33 may contribute to cancer cell proliferation.34
Few studies may evaluate the association with specific cancers such as multiple myeloma and malignant plasma cell neoplasms because of insufficient numbers of cancer cases. In this study, we observed a strong positive association with high-stable group for these specific cancers; however, the estimations were based on the small number of cases. To our knowledge, positive associations between FBG and oral cancer have not been described previously, which is required for further investigation.
Gastrointestinal cancers, including pancreatic, stomach, and liver cancer, are widely acknowledged to be closely linked to elevated FBG levels.13 15 16 In line with previous research, our study revealed significant findings in these specific cancer types, although the patterns varied among different groups. The potential results may be contributed by the high number of patients with diabetes in high-stable group. Furthermore, some individuals may have diabetes but may not have sought medical attention, leading to an underdiagnosis despite displaying elevated FBG level in those patients. These may affect to the estimation in final model after adjusting for diabetes diagnosis covariate.
Our subgroup analysis revealed a high overall cancer risk in the elevated-stable group among subjects without a diagnosis of DM. The risk increased in individuals with elevated FBG levels but did not meet the diagnostic criteria for DM, according to the current American Diabetes Association definition of pre-diabetes.11 It suggests that individuals with persistently uncontrolled high glucose levels over an extended period may have an increased risk of cancer. This finding has important public health implications because, in the Korean population, the prevalence of pre-diabetes tended to increase over time from 21.5% in 2006 to 25.0% in 2013.2 Considering the substantial prevalence of pre-diabetes and its association with cancer risk, implementing interventions targeting this large population could have a major impact on public health.
The cancer risk among the diabetic population may be influenced by certain therapies used for diabetic treatment, potentially through their impact on insulin levels.35 In the case of acarbose, treatment did not show significant differences in cancer incidence in previous studies.35 Contrastingly, we did not find a significant association between cancer risk and most types of therapy, except for that with acarbose. We observed that patients with DM in the elevated-high group had a greater risk of cancer than those in the low-stability group, even when using acarbose to manage their blood sugar levels. Acarbose blocks the breakdown of starches in the intestine, thereby slowing the rise in blood glucose levels after a meal.11 However, acarbose is not a primary choice in clinical practice, following the guidelines for using glucose-lowering medication use,36 which may explain the limited number of cases using acarbose in our research. Thus, our evaluation was limited and lacked sufficient statistical power, resulting in divergent findings compared with the findings of previous research.
In our analysis, cancer risk did not increase when treating metformin in all FBG patterns. Numerous studies have suggested that metformin plays a protective role in cancer development. A nested case-control study involving female users of oral antidiabetic drugs conducted in the UK reported that prolonged use of metformin linked with a reduced risk of developing breast cancer, compared with non-use of metformin.37 Additionally, each gram added to the metformin dose has been associated with a 42% decline in cancer mortality.37 The mechanism is far from clear, but it has been observed that adenosine monophosphate-activated protein kinase (AMPK)—activated by metformin— leads to a strong suppression of cell proliferation in malignant as well as non-malignant cells.38 This effect may be mediated through cell-cycle regulation and inhibition of protein synthesis.38
Our study had several notable strengths. First, we used data from the NHIS-HEALS, which covered a large sample size and a long follow-up duration (7.6 years). Second, we employed trajectory analysis, specifically the GBTM, to identify the FBG patterns. Moreover, this study was based on measuring FBG, rather than self-reported information, which helped to mitigate recall bias or misclassification. Furthermore, our study stands out as one of the few to incorporate medication use as a covariate in the analysis.
However, this study had some limitations. The first was the relatively short timeframe over which FBG changes were measured (6 years—three waves). Although no existing publications have captured lifelong FBG measurements, this limitation should be acknowledged. It is important to note that certain cancer types, such as breast, prostate, or testicular cancer, were not available in the NHIS-HEALS dataset owing confidentiality, thus limiting our analysis in these specific cancer categories. However, this is one of the few studies to assess cancer risk related to FBG trajectories. Third, associations with DM diagnosis as well as antidiabetic medications may not have been fully evaluated, as the limited number of cases after subgroup analysis could not provide enough statistical power. Fourth, although some important covariates were adjusted, residual confounders may exist, for example, family history of cancer. Fifth, our dataset lacked certain tests that reflect long-term glucose metabolism, such as HbA1c or oral glucose tolerance tests, which may result in misclassifications within the pre-diabetes and diabetes groups. Lastly, our cohort study’s population may not fully represent the entire Korean population because it included participants aged greater than 40 who underwent multiple check-ups between 2002 and 2007. Thus, the characteristics of patients who participated in screening programs may differ from those of patients who did not participate.
In conclusion, our analysis will contribute to the understanding of the link between cancer risk and changes in FBG levels. Our findings revealed relationships between FBG patterns and the risk of overall cancer, especially gastrointestinal cancer, and several specific types of cancer such as multiple myeloma and malignant plasma cell neoplasms, oral, liver, stomach, and pancreatic cancer. These results suggested that individuals in the pre-diabetes stage may be at an increased risk of developing cancer. Future studies should consider longer follow-up times, larger sample sizes, and more frequent FBG measurements to gain a more comprehensive understanding of this area.