Incidence of Diabetes After Cancer Development

Chen

et al. 2020

Gynecologic Oncology

h i g h l i g h t sEndometrial cancer survivors in all BMI groups had an increased risk of diabetes. 29.5% of endometrial cancer patients were diagnosed with diabetes after diagnosis of endometrial cancer. Obesity was the most important risk factor for type II diabetes among endometrial cancer survivors. Overall, endometrial cancer survivors had a twofold higher risk of type II diabetes compared to the general population. Gynecologic Oncology 156 (2020) 185e193 Conclusions: In conclusion, endometrial cancer survivors had a higher risk of diabetes than women in the general population. These results suggest that long term monitoring for diabetes is indicated for endometrial cancer survivors.

Section: Discussionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 92%

Long-term diabetes risk among endometrial cancer survivors in a population-based cohort study

Kim

Chen

et al. 2020

Gynecologic Oncology

“…Finally, data on clinical outcomes were based on claims data and there might be misclassification of COPD or lung cancer. However, the NHIS routinely audits the claims6 and the data for cancer outcomes are considered highly reliable and have been used in numerous peer-reviewed publications 8 9…”

Section: Discussionmentioning

confidence: 99%

“…NHIS claims for inpatient visits, outpatient visits, procedures and prescriptions were coded using the International Classification of Diseases, 10th Revision and the Korean Drug and Anatomical Therapeutic Chemical Codes 7. Lung cancer was defined as the presence of the same C33 or C34 code more than three times within a year or an inpatient hospitalisation with a C33 or C34 code 8. COPD was defined as the presence of J43-J44 (except J43.0) codes and use of COPD medications at least twice within a year 9.…”

Section: Methodsmentioning

confidence: 99%

Chronic obstructive pulmonary disease and lung cancer incidence in never smokers: a cohort study

Kang

Shin

et al. 2020

Thorax

Self Cite

There has been limited evidence for the association between chronic obstructive pulmonary disease (COPD) and the incidence of lung cancer among never smokers. We aimed to estimate the risk of lung cancer incidence in never smokers with COPD, and to compare it with the risk associated with smoking. This cohort study involved 338 548 subjects, 40 to 84 years of age with no history of lung cancer at baseline, enrolled in the National Health Insurance Service National Sample Cohort. During 2 355 005 person-years of follow-up (median follow-up 7.0 years), 1834 participants developed lung cancer. Compared with never smokers without COPD, the fully-adjusted hazard ratios (95% CI) for lung cancer in never smokers with COPD, ever smokers without COPD, and ever smokers with COPD were 2.67 (2.09 to 3.40), 1.97 (1.75 to 2.21), and 6.19 (5.04 to 7.61), respectively. In this large national cohort study, COPD was also a strong independent risk factor for lung cancer incidence in never smokers, implying that COPD patients are at high risk of lung cancer, irrespective of smoking status.

“…Type 2 diabetes was defined as either ≥2 visits for which type 2 diabetes-related diagnostic codes (E11 [Type 2 diabetes], E12 [Malnutrition-related diabetes mellitus], E13 [Other specified diabetes mellitus], and E14 [Unspecified diabetes mellitus]) were assigned between 2002 and 2013 or 1 visit with a type 2 diabetes diagnosis and a filled prescription for diabetes-related medications, including metformin, nateglinide, repaglinide, insulin, sitagliptin, saxagliptin, linagliptin, alogliptin, acarbose, glimepiride, glibenclamide, gliclazide, glipizide, rosiglitazone, pioglitazone, dapagliflozin, ertugliflozin, liraglutide, exenatide, and dulaglutide. This definition of type 2 diabetes was adopted from Yul et al51 .…”

mentioning

confidence: 99%

Temporal trajectories of accompanying comorbidities in patients with type 2 diabetes: a Korean nationwide observational study

Jeong

Kim

et al. 2020

Sci Rep

production of advanced glycation end products [AGEs], a proinflammatory microenvironment, and the induction of oxidative stress 8,9. These mechanisms can lead to diabetic nephropathy, neuropathy, and retinopathy 10. Macrovascular complications, which affect the large vessels of the body, are usually caused by atherosclerosis and may lead to stroke, acute myocardial infarction, or vessel blockage in the legs (i.e., peripheral vascular disease). A recent review suggested that although microvascular complications distinctly precede macrovascular complications, both progress simultaneously on a continuum 11. Most type 2 diabetes-related complications progress over a period of years. Therefore, it would be useful to know the expected clinical trajectories as these data would not only guide the decisions regarding and delivery of early preventive care, but may also help physicians to explain the course of type 2 diabetes and warn their patients about complications. Moreover, the prevalence of type 2 diabetes-related complications is known to differ with respect to age, sex, ethnicity and duration of diabetes 12-19. Therefore, an analysis of the factors affecting the trajectories of complications could provide new insights into patient management, prevention, or treatment. However, most published studies on the complications of type 2 diabetes were limited to one or a few complications and applied large-scale approaches without time considerations. For example, Jeong et al. developed a diagnostic progression network based on claims data with the aim of determining the global patterns of diagnosis in South Korea 20. However, this network provided only information about the associations between diagnosis pairs, rather than the sequential trajectories. Furthermore, Jensen et al. used electronic patient records from a Danish population to suggest temporal trajectory clusters of various diseases, including diabetes, and thus predict disease evolution over time 21. However, these trajectories were only evaluated using full population data, rather than data stratified by different combinations of sex and age. In this study, we aimed to construct time-dependent type 2 diabetes trajectories based on population-wide claim data. These trajectories would be expected to reveal time-critical associations between type 2 diabetes and other diseases and identify differences in the patterns of progression among various age and sex groups. To overcome the insufficient definition of a diagnosis simply as a direct complication of type 2 diabetes according to sequential patterns from claims data, we used the term "accompanying comorbidity" rather than "complication" to encompass all possible relationships with type 2 diabetes. Results Clinical and demographic characteristics of participants in the case-control study. A total of 49,893,982 incidence records and 396,777,916 prescription records for 1,113,655 patients were recorded between January 2002 and December 2013. Among them, 225,406 patients met our defined criteria for a type 2 diabete...