YGYNO-975566; No. of pages: 5; 4C: Gynecologic Oncology xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Gynecologic Oncology journal homepage: www.elsevier.com/locate/ygyno
3Q1
Hua-Fen Chen a, Ya-Hui Chang b, Ming-Chung Ko c,d,e,⁎,1, Chung-Yi Li b,f,⁎⁎,1 a
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a r t i c l e
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Keywords: Diabetes Ovarian cancer Cohort studies Incidence rate Relative risk Cox model
Department of Endocrinology, Far-Eastern Memorial Hospital, New Taipei City, Taiwan Department and Institute of Public Health, College of Medical, National Cheng-Kung University, Tainan, Taiwan Department of Surgery, Zhong-Xing Branch of Taipei City Hospital, Taipei, Taiwan d Department of Health Care Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan e Institute of Public Health, School of Medicine, National Yang-Ming University, Taipei, Taiwan f Department of Public Health, College of Public Health, China Medical University, Tainan, Taiwan b
a b s t r a c t
Objective. To investigate whether the risk of developing ovarian cancer is elevated in women with diabetes mellitus. Methods. The study is a population-based cohort study. Women with type 2 diabetes (n = 319,310) and agematched controls (n = 319,308) were selected from the ambulatory care claims and beneficiary registry in 2000, respectively. Selected patients were linked to the in-patient claims (2000–2008) to identify admissions due to ovarian (ICD-9-CM: 183.xx) cancer. The person-year approach with Poisson assumption was used to estimate the incidence density rate. The age-specific hazard ratios (HRs) of ovarian cancer in relation to diabetes were calculated using multivariate Cox proportional hazard regression model. Results. The overall incidence density rate of ovarian cancer was estimated at 1.87 (95% confidence interval (CI) 1.70–2.05) per 10,000 patient-years for patients with diabetes. The corresponding figures for controls were slightly lower at 1.79 per 10,000 patient-years. The incidence density of ovarian cancer was increased with age in diabetes but not in controls. The covariate-adjusted HR for ovarian cancer was statistically compared with null (adjusted HR = 1.06, 95% CI = 0.92–1.22) in women with diabetes. Moderately elevated HR was noted in women with diabetes aged b 50 (adjusted HR = 1.17, 95% CI = 0.82–1.65) and in women with diabetes aged N 65 (adjusted HR = 1.10, 95% CI = 0.92–1.42). The null association between diabetes and ovarian cancer remains true regardless of the disease duration of diabetes. Conclusion. This large-scale cohort study provides little support on the putative association between type 2 diabetes and the risk of ovarian cancer. © 2014 Published by Elsevier Inc.
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Patients with type 2 DM have increased the risk of developing certain cancers. In 2009, the American Cancer Society and American Diabetes Association reviewed the scientific evidence on the relationship between DM and cancer risk and concluded that the relative risks imparted by diabetes (primarily type 2 DM) are the greatest (approximately twofold or higher) for cancers of the liver, pancreas, and endometrium and lesser (approximately 1.2-fold to 1.5-fold) for cancers of the colon/rectum, breast, and bladder. The increased risk for developing other cancers (e.g., lung) does not appear to be associated with diabetes. Whether diabetes is associated with the risk of developing kidney cancer and non-Hodgkin's lymphoma is inconclusive [4]. The potential link between type 2 DM and ovarian cancer has rarely been investigated, and the results are inconclusive. A recent study that reviewed 7 case–control studies and 11 cohort studies summarized their study findings to evaluate the epidemiological associations between diabetes and ovarian cancer [5]. Combining data from all 18 studies, diabetes was found to be associated with a modestly increased risk of ovarian cancer.
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Article history: Received 23 April 2014 Accepted 1 July 2014 Available online xxxx
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A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus
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Introduction
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Diabetes mellitus (DM) is a worldwide epidemic. Marked changes in human health behavior and lifestyle have resulted in increasing incidence and prevalent rates of DM [1]. The prevalence of diabetes for all age groups worldwide was estimated to be 2.8% in 2000 and is predicted to be 4.4% in 2030 [2]. The number of people with diabetes is increasing because of population growth, aging, urbanization, nutritional changes, and increasing prevalence of obesity and physical inactivity [2,3].
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⁎ Correspondence to: M.-C. Ko, Department of Surgery, Taipei City Hospital, 145 Zheng Zhou Road, Taipei 103, Taiwan. ⁎⁎ Correspondence to: C.-Y. Li, Department and Institute of Public Health, College of Medical, National Cheng-Kung University, Tainan, Taiwan. E-mail address: [email protected] (M.-C. Ko). 1 Ming-Chung Ko and Chung-Yi Li contributed to this article equally.
http://dx.doi.org/10.1016/j.ygyno.2014.07.001 0090-8258/© 2014 Published by Elsevier Inc.
Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
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Source of data
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The data analyzed in this study were retrospectively retrieved from the claims of the National Health Insurance Research Database (NHIRD) provided by the Bureau of National Health Insurance (BNHI). The NHIRD provided all inpatient and ambulatory medical claims for around 99% of Taiwanese people [12]. To ensure the accuracy of claim files, the BNHI performs quarterly expert reviews on a random sample for every 50 to 100 ambulatory and inpatient claims [13]. Therefore, information from the NHIRD on diabetes and cancer diagnoses is considered to be complete and accurate [14]. We used several NHIRD data sets in this study, including ambulatory care visit claims, inpatient claims, major illness/injury certificates, and registry for beneficiaries. Access to research data has been reviewed and approved by the Review Committee of the National Health Research Institutes.
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Study design and populations
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Our study utilizes a population-based cohort design. Details of the NHI claim data and the methods of selection used for patients with diabetes and control subjects were described in our previous report [15]. Briefly, we considered a patient to be diabetic if she or he was diagnosed as having diabetes (ICD-9-CM: 250 or A-code: 181) in 2000 and again within the subsequent 12 months (n = 715,734). To avoid accidental inclusion of miscoded patients, we selected only patients with first and last outpatient visits at least 30 days apart (n = 639,804). To accurately estimate the incidence rate of ovarian cancer, we excluded patients who were admitted to the hospital for any malignant neoplasm (ICD-9-CM: 140–208) between 1997 and the date of initial ambulatory care visit (i.e., the indexed date) for diabetes treatment in 2000. Because major illness/injury certificates are issued to all patients with malignant neoplasms in Taiwan, we excluded only cancer patients with a major illness/injury certificates prior to the index date (n = 24,272) in order to avoid incorrect exclusion of cancer patients. For the specific purpose of this study, we selected only females with
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118 119 120 121 122 123 124 Q7 125 126 127 128 129 130 131 Q8132
133 134 135 136 137 138 139 140 141 142 Q9 143 144 145 146 147 148 149 150
End-points and covariates
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We used the unique personal identification number (PIN) of each insurer in both groups. We then linked the PIN of each insurer to the inpatient claims of 2000 to 2008 to identify the primary or secondary diagnoses of ovarian cancer (ICD-9-CM: 183), which was the endpoint in this study. To avoid incorrect assessment of malignant neoplasm, we included only patients who possessed major illness/injury certificates for admissions. The day of hospitalization of the patients was considered the date when the clinical endpoint of interest occurred. The study period was from January 1, 2000, to December 31, 2008. The geographic location of each individual's NHI unit, either the location of employment or residential area, was classified as north, central, south, or east or according to the level of urbanization (i.e., urban or rural), as per the National Statistics of Regional Standard Classification [16]. Information on a study subject's underlying illness was retrieved from the inpatient and outpatient claims from the first day of 1997 to the index date of 2000. Recorded illnesses included endometriosis (ICD-9-CM: 617.9), cardiovascular disease (ICD-9-CM: 410–414), pelvic inflammatory disease (ICD-9-CM: 614–616), chronic liver disease (ICD9-CM: 571–572), and rheumatic disease (ICD-9-CM: 714) [17]. In the analysis of ovarian neoplasm in relation to diabetes, we calculated the Charlson's score to indicate an individual's level of co-morbidity. The Charlson comorbidity index is a weighted summary measure of clinically important concomitant diseases that has been adapted for use with ICD-9-CM coded administrative databases [18,19]. Patients with diabetes are more likely to frequently seek medical care compared with their control counterparts, leading to a spuriously elevated risk of ovarian neoplasm in diabetes. Therefore, we also adjusted for the frequency of outpatient visits for each study subject to avoid disease surveillance bias.
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Statistical analysis
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The age-specific incidence density rate was first calculated with person-year as the denominator under the Poisson assumption. The incidence density rate was used when the denominator was the sum of the person-time values (person-year in the current study) of the atrisk population. To assess the independent effects of diabetes on the risks of ovarian cancer, we used Cox proportional hazard regression models and adjusted the data for age, geographic area, urbanization status, Charlson's score, and selected underlying illnesses. Taking into account both geographic area and urbanization status, adjustments for possible geographic variations in cancer incidence and mortality in Taiwan were made [20]. The study participants who encountered inhospital mortality for causes other than ovarian neoplasm or those who underwent bilateral oophorectomy were considered censored
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Material and methods
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diabetes and excluded males with diabetes (n = 289,915). Females aged 20 years or less (n = 5592) were also excluded to ensure that the patients had type 2 DM. We further excluded women who had bilateral oophorectomy (n = 715). Thus, the final cohort consisted of 319,310 female patients with diabetes. The date of the first outpatient visit in 2000 was the index date for each patient. The control subjects were identified from the RB. We excluded patients with claims for ambulatory care for diabetes or hospitalized for any type of malignancy (ICD-9-CM: 140–208) along with patients with major illness/injury certificates issued between 1997 and 1999. We selected age-matched and sex-matched control subjects by using the frequency matching procedure. Given that information on the age or sex of 661 patients with diabetes is missing, we selected only 614,871 control subjects. We again limited our control subjects to females (n = 319,308). The index date for subjects in the control group was the date of their enrollment to NHI. If their date of enrollment was before January 1, 2000, the index date was set to January 1, 2000, which was the starting point for the follow-up of controls.
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The summarized relative risk of ovarian cancer incidence was estimated at 1.17 (95% confidence interval (CI), 1.02–1.33). Only one case–control study [6] and one cohort study [7] showed a significantly increased risk for ovarian cancer in patients with diabetes. In addition to such inconsistency in Results, the results of previous studies also varied with respect to age range of diabetic patients, potential confounders, and method of diabetes ascertainment. For cohort studies, the follow-up duration also varied, ranging from 3.5 years to 11.8 years. The dissimilarities in findings made it difficult to interpret the summarized results on the relationship between diabetes and ovarian cancer. Moreover, very few studies [8,9] censored follow-up at the time of bilateral oophorectomy, which in turn became a source of bias that could have attenuated an association because of misclassifications made over time. No analyses on age-specific and disease duration-specific risks of ovarian cancer in relation to diabetes were performed by previous studies, primarily because of the limited sample size [6–9]. In accordance with the global trend for DM, more than 70% increase in the total diabetic population or a 35% increase in the standardized prevalence rate was observed in Taiwan from 2000 to 2009 [10]. A recent study that investigated the incidence of epithelial ovarian cancer in Taiwanese women from 1979 to 2008 reported that the age-adjusted incidence of epithelial ovarian cancer were 1.01, 1.37, 2.37, 3.24, 4.18, and 6.33 per 100,000 person-years at every five-year period from 1979 to 2008 [11]. The figures highlighted the clinical and public health importance of both diabetes and ovarian cancer in Taiwan. By using a national representative sample of patients with diabetes, we conducted a long-term follow-up study to investigate the age-specific and disease duration-specific risks of ovarian cancer in women with diabetes.
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Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
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from the survival analysis. The date of censoring was the date of patient deaths or surgeries. If a study subject had no in-hospital mortality, the date of censoring was either the date of his/her withdrawal from NHI or the date of study termination (i.e., December 31, 2008). All statistical analyses were performed using the Statistical Analysis Software (version 9.3; SAS Institute, Cary, NC). A P value of b0.05 was considered statistically significant in two-tailed tests.
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Results
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Geographic area Northern Central Southern Eastern Urbanization status Urban area Rural area Comorbidity Charlson's score
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0
t1:25 t1:26 t1:27 t1:28 t1:29
1
t1:30 t1:31 t1:32 t1:33 t1:34 t1:35 t1:36
Diabetic group (n = 319,310)
N
%
n
1605 53,997 128,389 135,317 60.95
0.50 1604 16.91 53,997 40.21 128,389 42.38 135,318 (±12.49) 61.06
≥2 Mean (±SD) Endometriosis (617.9) Cardiovascular disease (410–414) Pelvic inflammatory disease (614–616) Chronic liver disease (571–572) Rheumatic disease (714) Mean number of ambulatory visit in 2000 (SD)
%
0.50 16.91 40.21 42.38 (±12.35)
138,308 88,554 79,969 8942
43.31 27.73 25.04 2.80
137,620 92,314 76,101 9511
43.10 28.91 23.83 2.98
208,851 107,879
65.41 33.79
209,184 107,103
65.51 33.54
N C O
Age (years) b20 20–49 50–64 ≥65 Mean (±SD)
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t1:5 t1:6 t1:7 t1:8 t1:9 t1:10 t1:11 t1:12 t1:13 t1:14 t1:15 t1:16 t1:17 t1:18 t1:19 t1:20 t1:21 t1:22 t1:23
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Control group (n = 319,308)
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Characteristicsa
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Table 1 Characteristics and comorbidity of the study subjects.
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t1:1 t1:2 Q5
308,685 6387
96.67
274,062
85.83
2.00
22,815
7.15
4236 0.07 1695 127,682
1.33 (±0.57) 0.53 39.99
22,433 0.33 1614 187,267
7.03 (±1.21) 0.51 58.65
124,709
39.06
145,696
45.63
100,259 31.40 150,507 47.14 29,171 9.14 32,595 10.21 20.76 (±18.08) 34.17 (±20.84)
a Inconsistency between total population and population summed for individual variables was due to missing information.
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With a large and nationally representative sample of patients with diabetes, our cohort study provided little evidence on the putative link between diabetes and the risk of ovarian cancer, regardless of age and duration of diabetes. A recent study [21] that systematically reviewed 7 case–control studies and 11 cohort studies revealed a modestly elevated summarized relative risk (RR) estimate of ovarian cancer at 1.17 (95% CI = 1.02–1.33) and 1.16 (95% CI = 1.01–1.33). Only one case–control study [6] and one cohort study [7] revealed a significantly positive association between diabetes and ovarian cancer, with a relative risk estimate of 2.13 and 2.39, respectively. Furthermore, individuals with diabetes did not have a statistically significant increased risk of ovarian cancer compared with those without diabetes (RR: 1.15; 95% CI = 0.84–1.59) in case–control studies. Moreover, minimally increased risks among cohort studies (RR: 1.16; 95% CI = 1.01–1.33) in the above meta-analysis was observed [21]. Additionally, very few cohort studies [9,22,23] covered a follow-up period of 10 or more years, except one prior study from Taiwan [24] that employed more than 455,000 diabetic patients in their analysis. Most studies are limited in their study sample and thus suffer from inadequate statistical power. Although the sample size in the study by Lo et al. was large [24], the median follow-up duration was only 3.5 years, and this particular study did not adjust for any clinical risk factors for ovarian cancer in the analysis. Our findings were consistent with the results from most previous studies, suggesting that no significant association existed between type 2 DM and the risk of ovarian cancer. Type 2 DM, compensatory hyperinsulinemia [25], subsequent increase in IGF-1 bioavailability [26], and associated chronic inflammation [25] may affect ovarian tumorigenesis. However, given the fact that incessant ovulation is a known risk factor for ovarian cancer, insulin resistance and chronic anovulation associated with type 2 DM may also be a factor that can reduce the risk of ovarian cancer in diabetic patients [27]. Further studies are needed to document the association between diabetes and ovarian neoplastic transformation. Our study had several methodological strengths. First, both diabetic and control groups were collected from the NHI database, which is population-based. A nationwide insurance coverage also minimizes the potential for selection bias due to the loss of samples during follow-up. Additionally, minimal likelihood of recall and information bias exists because all cancer patients were confirmed to have major illness/injury certificates, which required pathological confirmation of cancer. Second, insurance claim records provided access to the longitudinal records for demographically dispersed patients. Such a large number of study subjects also made it possible for us to make detailed and age-stratified analyses in young patients. Third, we excluded patients with any type of malignancies that was diagnosed three years before the index date, thus enabling us to obtain accurate estimates of incidence and relative risk for ovarian cancer. Fourth, adjustment of geographical area and urbanization status might have reduced arearelated confounding factors. The potential confounding factors brought about by prior illnesses and co-morbidities were also controlled in our study. Despite the above strengths, several limitations were also noted in our study. First, exclusive reliance on the claim data might have caused potential misclassification bias. Although the accuracy of a single diabetes diagnosis in the NHI claim data in 2000 was reported to be 74.6% [28], we used at least two diabetes-related diagnoses with the first and last visits at N30 days apart, which might have reduced the possibility of disease misclassification. The control group might have also consisted of new onset or undiagnosed diabetes. Selection of ovarian cancer in patients with major illness/injury certificates might have excluded some patients who had been waiting for pathological diagnosis. Such misclassification bias, however, was likely to be non-differential, which tends to underestimate rather than overestimate the true relative
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Diabetic and control groups were similar with respect to age, geographic area, and urbanization status. The prevalence rates of selected 205 comorbidities, except endometriosis, prevailed in patients with diabe206 tes. The mean Charlson's score was much greater in diabetic group 207 than in the control group (0.33 vs. 0.07). The mean number of ambula208 tory care visits in 2000 was also higher in the diabetic group than in the 209 control group (34.17 vs. 20.76) (Table 1). 210 Over a nine-year follow-up period, 458 patients with diabetes and 211 477 controls developed ovarian cancer, representing an incidence den212 sity of 1.87 and 1.79 per 10,000 person-years, respectively. The overall 213 covariate-adjusted HR of ovarian cancer in relation to diabetes was esti214 mated at 1.06 (95% confidence interval (CI) 0.92–1.22). Similarly, no 215 significantly elevated age-specific adjusted HR was noted in women 216 with diabetes from all age stratifications (Table 2). The interaction of di217 abetes with age was also non-significant, with an interactive coefficient 218 of 0.09214, P value = 0.3097. 219 Table 3 shows the disease duration-specific incidence densities and 220 Q10 relative hazards of ovarian cancer in the diabetic group. The adjusted 221 HRs of ovarian cancer were all compared with null for patients with 222 diabetes, regardless of disease duration (Table 3).
Discussion
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Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
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Table 2 Overall and age-specific incidence densities and relative hazards of ovarian cancer (ICD-9: 183) in the diabetic and control groups. Age (years)
t2:4 t2:5 t2:6 t2:7 t2:8 t2:9
b50 50–64 ≥65 Total
Control group
Diabetic group
No. of subjects
No. of person-years
No. of events
IDa (per 10,000 patient-years) (95% CI)
No. of subjects
No. of person-years
No. of events
IDa (per 10,000 patient-years) (95% CI)
55,602 128,389 135,317 319,308
490,780 1,123,806 1,056,897 2,671,483
85 212 180 477
1.73 (1.38–2.14) 1.89 (1.64–2.16) 1.70 (1.46–1.97) 1.79 (1.63–1.95)
55,601 128,389 135,318 319,310
471,282 1,048,789 930,764 2,450,855
82 185 191 458
1.74 (1.38–2.16) 1.76 (1.52–2.04) 2.05 (1.77–2.37) 1.87 (1.70–2.05)
Crude HR (95% CI) in association with diabetic group
Adjusted HRb (95% CI) in association with diabetic group
1.01 (0.74–1.36) 0.94 (0.77–1.14) 1.20 (0.98–1.48) 1.05 (0.92–1.19)
1.17 (0.82–1.65) 0.97 (0.78–1.20) 1.14 (0.92–1.42) 1.06 (0.92–1.22)
ID, incidence density; CI, confidence interval; HR, hazard ratio; and AHR, adjusted hazard ratio. a Based on Poisson assumption. b Based on Cox proportional hazard regression with adjustment for age, geographic area, urbanization status, Charlson's score, history of endometriosis, cardiovascular disease, pelvic inflammatory disease, chronic liver disease, rheumatic disease, and frequency of medical visit.
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risks [29]. Second, some control subjects might develop diabetes during the follow-up period, which could entail certain degrees of exposure misclassification bias in our study. To address this potential problem, we conducted a sensitivity analysis by including only those control subjects free from diabetes during the study period. The size of control group thus reduced from 319,308 persons to 237,596 persons. We reanalyzed the data and found that the re-analytical results were essentially the same as the original results. Third, as we described previously, our inability to differentiate between type 1 and type 2 diabetes in our study limited the interpretation of the results. However, an earlier survey in 2001 reported that type 2 DM constitutes 98.2% of all diabetes in Taiwan [30]. A recent national study indicated that type 1 DM was present in less than 1% of the diabetic population in Taiwan [10], suggesting that the majority of the patients with diabetes in our study were likely to have type 2 DM. Fourth, we could not determine the BMI, duration and treatment regimens of diabetes, and other socioeconomic characteristics in our study population from the limited information presented in Taiwan's NHI claim data. Certain risk factors for ovarian cancer, including familial cancer history and reproductive variables, are also not included in the claim data. Failure to control for potential confounders might have biased the results. Fifth, screening or surveillance bias might be a concern in our study because diabetic patients are likely to make frequent contacts with physicians. To address the potential problem of overascertainment of ovarian cancer in diabetes, we have adjusted the number of ambulatory care visits made by each study subject in 2000. Last, a recent systematic review of 12 randomized controlled trials (21,595 patients) and 41 observational studies (1,029,389 patients) found that in observational studies there was a significant association of exposure to metformin with the risk of cancer death (odds ratio (OR): 0.65, 95% CI: 0.53–0.80), all malignancies (OR: 0.73, 95% CI: 0.61–0.88), liver (OR: 0.34; 95% CI: 0.19–0.60), colorectal (OR: 0.83, 95% CI: 0.74–0.92), pancreatic (OR: 0.56, 95% CI: 0.36–
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Table 3 Overall and duration-specific incidence densities and relative hazards of ovarian cancer (ICD-9: 183) in the diabetic and control groups.
308 309 310 311 312 313 314 315 316 317 318 319
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Conflict of interest
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The authors declare no conflict of interest associated with this 335 manuscript. 336 Acknowledgments
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Our study was supported by a grant from the National Science Council Taiwan (NSC101-2314-B-006-076-MY3) located in Taipei, Taiwan. The National Science Council Taiwan had no role in both conducting the study and interpreting the results. The interpretation and conclusions contained herein do not represent those of the Bureau of National Health Insurance, the Department of Health, or the National Health Research Institutes.
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References
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Controls Diabetes Disease duration b1 year 1–2 years ≥3 years Overall
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[1] Zimmet P, Alberti KG, Shaw J. Global and societal implications of the diabetes epi- 346 demic. Nature 2001;414:782–7. 347
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0.86), stomach (OR: 0.83, 95% CI: 0.76–0.91), and esophagus (OR: 0.90, 95% CI: 0.83–0.98) cancers. No significant difference of risk was observed in randomized trials. Additionally, metformin was not associated with the risks of: breast cancer, lung cancer, ovarian cancer, uterus cancer, prostate cancer, bladder cancer, kidney cancer, and melanoma (31). Because our study was not designed initially to assess the effects of medications on the risk of cancer, we did not apply for data of medical orders from the BNHI. Thus, we are unable to assess whether metformin or other medications may modify the risk of ovarian cancer in patients with diabetes. In conclusion, over a nine-year follow-up period and after adjusting for confounding factors, women with diabetes in Taiwan did not have significantly elevated risk of developing ovarian cancer.
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No. of subjects
No. of person-years
No. of events
IDa (per 10,000 patient-years) (95% CI)
Crude HR (95% CI) in association with diabetic group
Adjusted HRb (95% CI) in association with diabetic group
319,308
2,671,483
477
1.79 (1.63–1.95)
1.00
1.00
43,426 73,736 202,148 319,310
340,244 587,891 1,522,720 2,450,855
57 113 288 458
1.68 (1.27–2.17) 1.92 (1.58–2.31) 1.89 (1.68–2.12) 1.87 (1.70–2.05)
0.94 (0.71–1.24) 1.07 (0.88–1.32) 1.06 (0.92–1.23) 1.05 (0.92–1.19)
0.89 (0.67–1.18) 1.00 (0.81–1.25) 1.07 (0.91–1.25) 1.06 (0.92–1.22)
ID, incidence density; CI, confidence interval; HR, hazard ratio; and AHR, adjusted hazard ratio. a Based on Poisson assumption. b Based on Cox proportional hazard regression with adjustment for age, geographic area, urbanization status, Charlson's score, history of endometriosis, cardiovascular disease, pelvic inflammatory disease, chronic liver disease, rheumatic disease, and frequency of medical visit.
Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
H.-F. Chen et al. / Gynecologic Oncology xxx (2014) xxx–xxx
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[16] Chen HF, Chen P, Li CY. Risk of malignant neoplasm of pancreas in relation to diabetes: a population-based study in Taiwan. Diabetes Care 2011;34:1177–9. [17] Lin HW, Tu YY, Lin SY, Su WJ, Lin WL, Lin WZ, et al. Risk of ovarian cancer in women with pelvic inflammatory disease: a population-based study. Lancet Oncol 2011;12:900–4. [18] Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–83. [19] Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45:613–9. [20] Chen CJ, You SL, Lin LH, Hsu WL, Yang YW. Cancer epidemiology and control in Taiwan: a brief review. Jpn J Clin Oncol 2002;32:S66–81. [21] Lee JY, Jeon I, Kim JW, Song YS, Yoon JM, Park SM. Diabetes mellitus and ovarian cancer risk: a systematic review and meta-analysis of observational studies. Int J Gynecol Cancer 2013;23:402–12. [22] Inoue M, Iwasaki M, Otani T, Sasazuki S, Noda M, Tsugane S. Diabetes mellitus and the risk of cancer: results from a large-scale population-based cohort study in Japan. Arch Intern Med 2006;166:1871–7. [23] Bjørge T, Lukanova A, Tretli S, Manjer J, Ulmer H, Stocks T, et al. Metabolic risk factors and ovarian cancer in the metabolic syndrome and cancer project. Int J Epidemiol 2011;40:1667–77. [24] Lo SF1, Chang SN, Muo CH, Chen SY, Liao FY, Dee SW, et al. Modest increase in risk of specific types of cancer types in type 2 diabetes mellitus patients. Int J Cancer 2013;132:182–8. [25] Giovannucci E, Harlan DM, Archer MC, Bergenstal RM, Gapstur SM, Habel LA, et al. Diabetes and cancer: a consensus report. Diabetes Care 2010;33:1674–85. [26] Kellenberger LD, Bruin JE, Greenaway J, Campbell NE, Moorehead RA, Holloway AC, et al. The role of dysregulated glucose metabolism in epithelial ovarian cancer. J Oncol 2010;2010:514310. [27] Legro RS. Insulin resistance in polycystic ovary syndrome: treating a phenotype without a genotype. Mol Cell Endocrinol 1998;145:103–10. [28] Lin CC, Lai MS, Syu CY, Chang SC, Tseng FY. Accuracy of diabetes diagnosis in health insurance claims data in Taiwan. J Formos Med Assoc 2005;104:157–63. [29] Gordis L. Epidemiology. 2nd ed. Philadelphia: W.B. Saunders Company; 2000. [30] Chuang LM, Tsai ST, Huang BY, Tai TY. DIABCARE (Taiwan) Study Group. The current state of diabetes management in Taiwan. Diabetes Res Clin Pract 2001;54:S55–65.
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[2] Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27:1047–53. [3] Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 2010;87:4–14. [4] Giovannucci E, Harlan DM, Archer MC, Bergenstal RM, Gapstur SM, Habel LA, et al. Diabetes and cancer: a consensus report. CA Cancer J Clin 2010;60:207–21. [5] Lee JY, Jeon I, Kim JW, Song YS, Yoon JM, Park SM. Diabetes mellitus and ovarian cancer risk: a systematic review and meta-analysis of observational studies. Int J Gynecol Cancer 2013;23:402–12. [6] Reis N, Kizilkaya Beji N. Risk factors for ovarian cancer: results from a hospital-based case–control study. Turk Klin J Med Sci 2010;30:79–87. [7] Chodick G, Heymann AD, Rosenmann L, Green MS, Flash S, Porath A, et al. Diabetes and risk of incident cancer: a large population-based cohort study in Israel. Cancer Causes Control 2010;21:879–87. [8] Lambe M, Wigertz A, Garmo H, Walldius G, Jungner I, Hammar N. Impaired glucose metabolism and diabetes and the risk of breast, endometrial, and ovarian cancer. Cancer Causes Control 2011;22:1163–71. [9] Gapstur SM, Patel AV, Diver WR, Hildebrand JS, Gaudet MM, Jacobs EJ, et al. Type 2 diabetes mellitus and the incidence of epithelial ovarian cancer in the Cancer Prevention Study-II Nutrition Cohort. Cancer Epidemiol Biomarkers Prev 2012;21:2000–5. [10] Jiang YD, Chang CH, Tai TY, Chen JF, Chuang LM. Incidence and prevalence rates of diabetes mellitus in Taiwan: analysis of the 2000–2009 Nationwide Health Insurance database. J Formos Med Assoc 2012;111:599–604. [11] Chiang YC, Chen CA, Chiang CJ, Hsu TH, Lin MC, You SL, et al. Trends in incidence and survival outcome of epithelial ovarian cancer: 30-year national population-based registry in Taiwan. J Gynecol Oncol 2013;24:31–342. [12] Lu JFR, Hsiao WC. Does universal health insurance make health care unaffordable? Lessons from Taiwan. Health Aff 2003;22:77–88. [13] Bureau of National Health Insurance. Regulations governing contracting and management of National Health Insurance medical care institutions. http://www. nhi.gov.tw/English/webdata/webdata.aspx?menu=11&menu_id=295&WD_ ID=295&webdata_id=3284; 2012. [14] Chen HF, Chen P, Li CY. Risk of malignant neoplasms of liver and biliary tract in diabetic patients with different age and gender stratifications. Hepatology 2010;52:155–63. [15] Chen HF, Liu MD, Chen P, Chen LH, Chang YH, Wen PC, et al. Risks of breast and endometrial neoplasm in women with diabetes: a population-based cohort study. PLoS One 2013;8:e67420.
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Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
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Contents lists available at ScienceDirect
Gynecologic Oncology journal homepage: www.elsevier.com/locate/ygyno
3Q1
Hua-Fen Chen a, Ya-Hui Chang b, Ming-Chung Ko c,d,e,⁎,1, Chung-Yi Li b,f,⁎⁎,1 a
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Keywords: Diabetes Ovarian cancer Cohort studies Incidence rate Relative risk Cox model
Department of Endocrinology, Far-Eastern Memorial Hospital, New Taipei City, Taiwan Department and Institute of Public Health, College of Medical, National Cheng-Kung University, Tainan, Taiwan Department of Surgery, Zhong-Xing Branch of Taipei City Hospital, Taipei, Taiwan d Department of Health Care Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan e Institute of Public Health, School of Medicine, National Yang-Ming University, Taipei, Taiwan f Department of Public Health, College of Public Health, China Medical University, Tainan, Taiwan b
a b s t r a c t
Objective. To investigate whether the risk of developing ovarian cancer is elevated in women with diabetes mellitus. Methods. The study is a population-based cohort study. Women with type 2 diabetes (n = 319,310) and agematched controls (n = 319,308) were selected from the ambulatory care claims and beneficiary registry in 2000, respectively. Selected patients were linked to the in-patient claims (2000–2008) to identify admissions due to ovarian (ICD-9-CM: 183.xx) cancer. The person-year approach with Poisson assumption was used to estimate the incidence density rate. The age-specific hazard ratios (HRs) of ovarian cancer in relation to diabetes were calculated using multivariate Cox proportional hazard regression model. Results. The overall incidence density rate of ovarian cancer was estimated at 1.87 (95% confidence interval (CI) 1.70–2.05) per 10,000 patient-years for patients with diabetes. The corresponding figures for controls were slightly lower at 1.79 per 10,000 patient-years. The incidence density of ovarian cancer was increased with age in diabetes but not in controls. The covariate-adjusted HR for ovarian cancer was statistically compared with null (adjusted HR = 1.06, 95% CI = 0.92–1.22) in women with diabetes. Moderately elevated HR was noted in women with diabetes aged b 50 (adjusted HR = 1.17, 95% CI = 0.82–1.65) and in women with diabetes aged N 65 (adjusted HR = 1.10, 95% CI = 0.92–1.42). The null association between diabetes and ovarian cancer remains true regardless of the disease duration of diabetes. Conclusion. This large-scale cohort study provides little support on the putative association between type 2 diabetes and the risk of ovarian cancer. © 2014 Published by Elsevier Inc.
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Patients with type 2 DM have increased the risk of developing certain cancers. In 2009, the American Cancer Society and American Diabetes Association reviewed the scientific evidence on the relationship between DM and cancer risk and concluded that the relative risks imparted by diabetes (primarily type 2 DM) are the greatest (approximately twofold or higher) for cancers of the liver, pancreas, and endometrium and lesser (approximately 1.2-fold to 1.5-fold) for cancers of the colon/rectum, breast, and bladder. The increased risk for developing other cancers (e.g., lung) does not appear to be associated with diabetes. Whether diabetes is associated with the risk of developing kidney cancer and non-Hodgkin's lymphoma is inconclusive [4]. The potential link between type 2 DM and ovarian cancer has rarely been investigated, and the results are inconclusive. A recent study that reviewed 7 case–control studies and 11 cohort studies summarized their study findings to evaluate the epidemiological associations between diabetes and ovarian cancer [5]. Combining data from all 18 studies, diabetes was found to be associated with a modestly increased risk of ovarian cancer.
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Article history: Received 23 April 2014 Accepted 1 July 2014 Available online xxxx
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A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus
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Introduction
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Diabetes mellitus (DM) is a worldwide epidemic. Marked changes in human health behavior and lifestyle have resulted in increasing incidence and prevalent rates of DM [1]. The prevalence of diabetes for all age groups worldwide was estimated to be 2.8% in 2000 and is predicted to be 4.4% in 2030 [2]. The number of people with diabetes is increasing because of population growth, aging, urbanization, nutritional changes, and increasing prevalence of obesity and physical inactivity [2,3].
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⁎ Correspondence to: M.-C. Ko, Department of Surgery, Taipei City Hospital, 145 Zheng Zhou Road, Taipei 103, Taiwan. ⁎⁎ Correspondence to: C.-Y. Li, Department and Institute of Public Health, College of Medical, National Cheng-Kung University, Tainan, Taiwan. E-mail address: [email protected] (M.-C. Ko). 1 Ming-Chung Ko and Chung-Yi Li contributed to this article equally.
http://dx.doi.org/10.1016/j.ygyno.2014.07.001 0090-8258/© 2014 Published by Elsevier Inc.
Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
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Source of data
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The data analyzed in this study were retrospectively retrieved from the claims of the National Health Insurance Research Database (NHIRD) provided by the Bureau of National Health Insurance (BNHI). The NHIRD provided all inpatient and ambulatory medical claims for around 99% of Taiwanese people [12]. To ensure the accuracy of claim files, the BNHI performs quarterly expert reviews on a random sample for every 50 to 100 ambulatory and inpatient claims [13]. Therefore, information from the NHIRD on diabetes and cancer diagnoses is considered to be complete and accurate [14]. We used several NHIRD data sets in this study, including ambulatory care visit claims, inpatient claims, major illness/injury certificates, and registry for beneficiaries. Access to research data has been reviewed and approved by the Review Committee of the National Health Research Institutes.
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Study design and populations
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Our study utilizes a population-based cohort design. Details of the NHI claim data and the methods of selection used for patients with diabetes and control subjects were described in our previous report [15]. Briefly, we considered a patient to be diabetic if she or he was diagnosed as having diabetes (ICD-9-CM: 250 or A-code: 181) in 2000 and again within the subsequent 12 months (n = 715,734). To avoid accidental inclusion of miscoded patients, we selected only patients with first and last outpatient visits at least 30 days apart (n = 639,804). To accurately estimate the incidence rate of ovarian cancer, we excluded patients who were admitted to the hospital for any malignant neoplasm (ICD-9-CM: 140–208) between 1997 and the date of initial ambulatory care visit (i.e., the indexed date) for diabetes treatment in 2000. Because major illness/injury certificates are issued to all patients with malignant neoplasms in Taiwan, we excluded only cancer patients with a major illness/injury certificates prior to the index date (n = 24,272) in order to avoid incorrect exclusion of cancer patients. For the specific purpose of this study, we selected only females with
97 98
103 104 105 106 107 108 109 110 111 112
118 119 120 121 122 123 124 Q7 125 126 127 128 129 130 131 Q8132
133 134 135 136 137 138 139 140 141 142 Q9 143 144 145 146 147 148 149 150
End-points and covariates
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We used the unique personal identification number (PIN) of each insurer in both groups. We then linked the PIN of each insurer to the inpatient claims of 2000 to 2008 to identify the primary or secondary diagnoses of ovarian cancer (ICD-9-CM: 183), which was the endpoint in this study. To avoid incorrect assessment of malignant neoplasm, we included only patients who possessed major illness/injury certificates for admissions. The day of hospitalization of the patients was considered the date when the clinical endpoint of interest occurred. The study period was from January 1, 2000, to December 31, 2008. The geographic location of each individual's NHI unit, either the location of employment or residential area, was classified as north, central, south, or east or according to the level of urbanization (i.e., urban or rural), as per the National Statistics of Regional Standard Classification [16]. Information on a study subject's underlying illness was retrieved from the inpatient and outpatient claims from the first day of 1997 to the index date of 2000. Recorded illnesses included endometriosis (ICD-9-CM: 617.9), cardiovascular disease (ICD-9-CM: 410–414), pelvic inflammatory disease (ICD-9-CM: 614–616), chronic liver disease (ICD9-CM: 571–572), and rheumatic disease (ICD-9-CM: 714) [17]. In the analysis of ovarian neoplasm in relation to diabetes, we calculated the Charlson's score to indicate an individual's level of co-morbidity. The Charlson comorbidity index is a weighted summary measure of clinically important concomitant diseases that has been adapted for use with ICD-9-CM coded administrative databases [18,19]. Patients with diabetes are more likely to frequently seek medical care compared with their control counterparts, leading to a spuriously elevated risk of ovarian neoplasm in diabetes. Therefore, we also adjusted for the frequency of outpatient visits for each study subject to avoid disease surveillance bias.
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Statistical analysis
181
The age-specific incidence density rate was first calculated with person-year as the denominator under the Poisson assumption. The incidence density rate was used when the denominator was the sum of the person-time values (person-year in the current study) of the atrisk population. To assess the independent effects of diabetes on the risks of ovarian cancer, we used Cox proportional hazard regression models and adjusted the data for age, geographic area, urbanization status, Charlson's score, and selected underlying illnesses. Taking into account both geographic area and urbanization status, adjustments for possible geographic variations in cancer incidence and mortality in Taiwan were made [20]. The study participants who encountered inhospital mortality for causes other than ovarian neoplasm or those who underwent bilateral oophorectomy were considered censored
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Material and methods
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diabetes and excluded males with diabetes (n = 289,915). Females aged 20 years or less (n = 5592) were also excluded to ensure that the patients had type 2 DM. We further excluded women who had bilateral oophorectomy (n = 715). Thus, the final cohort consisted of 319,310 female patients with diabetes. The date of the first outpatient visit in 2000 was the index date for each patient. The control subjects were identified from the RB. We excluded patients with claims for ambulatory care for diabetes or hospitalized for any type of malignancy (ICD-9-CM: 140–208) along with patients with major illness/injury certificates issued between 1997 and 1999. We selected age-matched and sex-matched control subjects by using the frequency matching procedure. Given that information on the age or sex of 661 patients with diabetes is missing, we selected only 614,871 control subjects. We again limited our control subjects to females (n = 319,308). The index date for subjects in the control group was the date of their enrollment to NHI. If their date of enrollment was before January 1, 2000, the index date was set to January 1, 2000, which was the starting point for the follow-up of controls.
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The summarized relative risk of ovarian cancer incidence was estimated at 1.17 (95% confidence interval (CI), 1.02–1.33). Only one case–control study [6] and one cohort study [7] showed a significantly increased risk for ovarian cancer in patients with diabetes. In addition to such inconsistency in Results, the results of previous studies also varied with respect to age range of diabetic patients, potential confounders, and method of diabetes ascertainment. For cohort studies, the follow-up duration also varied, ranging from 3.5 years to 11.8 years. The dissimilarities in findings made it difficult to interpret the summarized results on the relationship between diabetes and ovarian cancer. Moreover, very few studies [8,9] censored follow-up at the time of bilateral oophorectomy, which in turn became a source of bias that could have attenuated an association because of misclassifications made over time. No analyses on age-specific and disease duration-specific risks of ovarian cancer in relation to diabetes were performed by previous studies, primarily because of the limited sample size [6–9]. In accordance with the global trend for DM, more than 70% increase in the total diabetic population or a 35% increase in the standardized prevalence rate was observed in Taiwan from 2000 to 2009 [10]. A recent study that investigated the incidence of epithelial ovarian cancer in Taiwanese women from 1979 to 2008 reported that the age-adjusted incidence of epithelial ovarian cancer were 1.01, 1.37, 2.37, 3.24, 4.18, and 6.33 per 100,000 person-years at every five-year period from 1979 to 2008 [11]. The figures highlighted the clinical and public health importance of both diabetes and ovarian cancer in Taiwan. By using a national representative sample of patients with diabetes, we conducted a long-term follow-up study to investigate the age-specific and disease duration-specific risks of ovarian cancer in women with diabetes.
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Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
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from the survival analysis. The date of censoring was the date of patient deaths or surgeries. If a study subject had no in-hospital mortality, the date of censoring was either the date of his/her withdrawal from NHI or the date of study termination (i.e., December 31, 2008). All statistical analyses were performed using the Statistical Analysis Software (version 9.3; SAS Institute, Cary, NC). A P value of b0.05 was considered statistically significant in two-tailed tests.
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Results
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Geographic area Northern Central Southern Eastern Urbanization status Urban area Rural area Comorbidity Charlson's score
t1:24
0
t1:25 t1:26 t1:27 t1:28 t1:29
1
t1:30 t1:31 t1:32 t1:33 t1:34 t1:35 t1:36
Diabetic group (n = 319,310)
N
%
n
1605 53,997 128,389 135,317 60.95
0.50 1604 16.91 53,997 40.21 128,389 42.38 135,318 (±12.49) 61.06
≥2 Mean (±SD) Endometriosis (617.9) Cardiovascular disease (410–414) Pelvic inflammatory disease (614–616) Chronic liver disease (571–572) Rheumatic disease (714) Mean number of ambulatory visit in 2000 (SD)
%
0.50 16.91 40.21 42.38 (±12.35)
138,308 88,554 79,969 8942
43.31 27.73 25.04 2.80
137,620 92,314 76,101 9511
43.10 28.91 23.83 2.98
208,851 107,879
65.41 33.79
209,184 107,103
65.51 33.54
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Age (years) b20 20–49 50–64 ≥65 Mean (±SD)
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t1:5 t1:6 t1:7 t1:8 t1:9 t1:10 t1:11 t1:12 t1:13 t1:14 t1:15 t1:16 t1:17 t1:18 t1:19 t1:20 t1:21 t1:22 t1:23
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t1:4 Q2 Q3
Control group (n = 319,308)
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Characteristicsa
R
t1:3
Table 1 Characteristics and comorbidity of the study subjects.
R
t1:1 t1:2 Q5
308,685 6387
96.67
274,062
85.83
2.00
22,815
7.15
4236 0.07 1695 127,682
1.33 (±0.57) 0.53 39.99
22,433 0.33 1614 187,267
7.03 (±1.21) 0.51 58.65
124,709
39.06
145,696
45.63
100,259 31.40 150,507 47.14 29,171 9.14 32,595 10.21 20.76 (±18.08) 34.17 (±20.84)
a Inconsistency between total population and population summed for individual variables was due to missing information.
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With a large and nationally representative sample of patients with diabetes, our cohort study provided little evidence on the putative link between diabetes and the risk of ovarian cancer, regardless of age and duration of diabetes. A recent study [21] that systematically reviewed 7 case–control studies and 11 cohort studies revealed a modestly elevated summarized relative risk (RR) estimate of ovarian cancer at 1.17 (95% CI = 1.02–1.33) and 1.16 (95% CI = 1.01–1.33). Only one case–control study [6] and one cohort study [7] revealed a significantly positive association between diabetes and ovarian cancer, with a relative risk estimate of 2.13 and 2.39, respectively. Furthermore, individuals with diabetes did not have a statistically significant increased risk of ovarian cancer compared with those without diabetes (RR: 1.15; 95% CI = 0.84–1.59) in case–control studies. Moreover, minimally increased risks among cohort studies (RR: 1.16; 95% CI = 1.01–1.33) in the above meta-analysis was observed [21]. Additionally, very few cohort studies [9,22,23] covered a follow-up period of 10 or more years, except one prior study from Taiwan [24] that employed more than 455,000 diabetic patients in their analysis. Most studies are limited in their study sample and thus suffer from inadequate statistical power. Although the sample size in the study by Lo et al. was large [24], the median follow-up duration was only 3.5 years, and this particular study did not adjust for any clinical risk factors for ovarian cancer in the analysis. Our findings were consistent with the results from most previous studies, suggesting that no significant association existed between type 2 DM and the risk of ovarian cancer. Type 2 DM, compensatory hyperinsulinemia [25], subsequent increase in IGF-1 bioavailability [26], and associated chronic inflammation [25] may affect ovarian tumorigenesis. However, given the fact that incessant ovulation is a known risk factor for ovarian cancer, insulin resistance and chronic anovulation associated with type 2 DM may also be a factor that can reduce the risk of ovarian cancer in diabetic patients [27]. Further studies are needed to document the association between diabetes and ovarian neoplastic transformation. Our study had several methodological strengths. First, both diabetic and control groups were collected from the NHI database, which is population-based. A nationwide insurance coverage also minimizes the potential for selection bias due to the loss of samples during follow-up. Additionally, minimal likelihood of recall and information bias exists because all cancer patients were confirmed to have major illness/injury certificates, which required pathological confirmation of cancer. Second, insurance claim records provided access to the longitudinal records for demographically dispersed patients. Such a large number of study subjects also made it possible for us to make detailed and age-stratified analyses in young patients. Third, we excluded patients with any type of malignancies that was diagnosed three years before the index date, thus enabling us to obtain accurate estimates of incidence and relative risk for ovarian cancer. Fourth, adjustment of geographical area and urbanization status might have reduced arearelated confounding factors. The potential confounding factors brought about by prior illnesses and co-morbidities were also controlled in our study. Despite the above strengths, several limitations were also noted in our study. First, exclusive reliance on the claim data might have caused potential misclassification bias. Although the accuracy of a single diabetes diagnosis in the NHI claim data in 2000 was reported to be 74.6% [28], we used at least two diabetes-related diagnoses with the first and last visits at N30 days apart, which might have reduced the possibility of disease misclassification. The control group might have also consisted of new onset or undiagnosed diabetes. Selection of ovarian cancer in patients with major illness/injury certificates might have excluded some patients who had been waiting for pathological diagnosis. Such misclassification bias, however, was likely to be non-differential, which tends to underestimate rather than overestimate the true relative
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Diabetic and control groups were similar with respect to age, geographic area, and urbanization status. The prevalence rates of selected 205 comorbidities, except endometriosis, prevailed in patients with diabe206 tes. The mean Charlson's score was much greater in diabetic group 207 than in the control group (0.33 vs. 0.07). The mean number of ambula208 tory care visits in 2000 was also higher in the diabetic group than in the 209 control group (34.17 vs. 20.76) (Table 1). 210 Over a nine-year follow-up period, 458 patients with diabetes and 211 477 controls developed ovarian cancer, representing an incidence den212 sity of 1.87 and 1.79 per 10,000 person-years, respectively. The overall 213 covariate-adjusted HR of ovarian cancer in relation to diabetes was esti214 mated at 1.06 (95% confidence interval (CI) 0.92–1.22). Similarly, no 215 significantly elevated age-specific adjusted HR was noted in women 216 with diabetes from all age stratifications (Table 2). The interaction of di217 abetes with age was also non-significant, with an interactive coefficient 218 of 0.09214, P value = 0.3097. 219 Table 3 shows the disease duration-specific incidence densities and 220 Q10 relative hazards of ovarian cancer in the diabetic group. The adjusted 221 HRs of ovarian cancer were all compared with null for patients with 222 diabetes, regardless of disease duration (Table 3).
Discussion
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Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
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Table 2 Overall and age-specific incidence densities and relative hazards of ovarian cancer (ICD-9: 183) in the diabetic and control groups. Age (years)
t2:4 t2:5 t2:6 t2:7 t2:8 t2:9
b50 50–64 ≥65 Total
Control group
Diabetic group
No. of subjects
No. of person-years
No. of events
IDa (per 10,000 patient-years) (95% CI)
No. of subjects
No. of person-years
No. of events
IDa (per 10,000 patient-years) (95% CI)
55,602 128,389 135,317 319,308
490,780 1,123,806 1,056,897 2,671,483
85 212 180 477
1.73 (1.38–2.14) 1.89 (1.64–2.16) 1.70 (1.46–1.97) 1.79 (1.63–1.95)
55,601 128,389 135,318 319,310
471,282 1,048,789 930,764 2,450,855
82 185 191 458
1.74 (1.38–2.16) 1.76 (1.52–2.04) 2.05 (1.77–2.37) 1.87 (1.70–2.05)
Crude HR (95% CI) in association with diabetic group
Adjusted HRb (95% CI) in association with diabetic group
1.01 (0.74–1.36) 0.94 (0.77–1.14) 1.20 (0.98–1.48) 1.05 (0.92–1.19)
1.17 (0.82–1.65) 0.97 (0.78–1.20) 1.14 (0.92–1.42) 1.06 (0.92–1.22)
ID, incidence density; CI, confidence interval; HR, hazard ratio; and AHR, adjusted hazard ratio. a Based on Poisson assumption. b Based on Cox proportional hazard regression with adjustment for age, geographic area, urbanization status, Charlson's score, history of endometriosis, cardiovascular disease, pelvic inflammatory disease, chronic liver disease, rheumatic disease, and frequency of medical visit.
288 289
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risks [29]. Second, some control subjects might develop diabetes during the follow-up period, which could entail certain degrees of exposure misclassification bias in our study. To address this potential problem, we conducted a sensitivity analysis by including only those control subjects free from diabetes during the study period. The size of control group thus reduced from 319,308 persons to 237,596 persons. We reanalyzed the data and found that the re-analytical results were essentially the same as the original results. Third, as we described previously, our inability to differentiate between type 1 and type 2 diabetes in our study limited the interpretation of the results. However, an earlier survey in 2001 reported that type 2 DM constitutes 98.2% of all diabetes in Taiwan [30]. A recent national study indicated that type 1 DM was present in less than 1% of the diabetic population in Taiwan [10], suggesting that the majority of the patients with diabetes in our study were likely to have type 2 DM. Fourth, we could not determine the BMI, duration and treatment regimens of diabetes, and other socioeconomic characteristics in our study population from the limited information presented in Taiwan's NHI claim data. Certain risk factors for ovarian cancer, including familial cancer history and reproductive variables, are also not included in the claim data. Failure to control for potential confounders might have biased the results. Fifth, screening or surveillance bias might be a concern in our study because diabetic patients are likely to make frequent contacts with physicians. To address the potential problem of overascertainment of ovarian cancer in diabetes, we have adjusted the number of ambulatory care visits made by each study subject in 2000. Last, a recent systematic review of 12 randomized controlled trials (21,595 patients) and 41 observational studies (1,029,389 patients) found that in observational studies there was a significant association of exposure to metformin with the risk of cancer death (odds ratio (OR): 0.65, 95% CI: 0.53–0.80), all malignancies (OR: 0.73, 95% CI: 0.61–0.88), liver (OR: 0.34; 95% CI: 0.19–0.60), colorectal (OR: 0.83, 95% CI: 0.74–0.92), pancreatic (OR: 0.56, 95% CI: 0.36–
t3:1 t3:2
Table 3 Overall and duration-specific incidence densities and relative hazards of ovarian cancer (ICD-9: 183) in the diabetic and control groups.
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t3:3 t3:4 t3:5 t3:6 t3:7 t3:8 t3:9 t3:10 t3:11 t3:12 t3:13 t3:14 t3:15
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Conflict of interest
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The authors declare no conflict of interest associated with this 335 manuscript. 336 Acknowledgments
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Our study was supported by a grant from the National Science Council Taiwan (NSC101-2314-B-006-076-MY3) located in Taipei, Taiwan. The National Science Council Taiwan had no role in both conducting the study and interpreting the results. The interpretation and conclusions contained herein do not represent those of the Bureau of National Health Insurance, the Department of Health, or the National Health Research Institutes.
338 339 Q12
References
345
Controls Diabetes Disease duration b1 year 1–2 years ≥3 years Overall
340 341 342 343 344
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0.86), stomach (OR: 0.83, 95% CI: 0.76–0.91), and esophagus (OR: 0.90, 95% CI: 0.83–0.98) cancers. No significant difference of risk was observed in randomized trials. Additionally, metformin was not associated with the risks of: breast cancer, lung cancer, ovarian cancer, uterus cancer, prostate cancer, bladder cancer, kidney cancer, and melanoma (31). Because our study was not designed initially to assess the effects of medications on the risk of cancer, we did not apply for data of medical orders from the BNHI. Thus, we are unable to assess whether metformin or other medications may modify the risk of ovarian cancer in patients with diabetes. In conclusion, over a nine-year follow-up period and after adjusting for confounding factors, women with diabetes in Taiwan did not have significantly elevated risk of developing ovarian cancer.
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t2:10 t2:11 t2:12 t2:13
No. of subjects
No. of person-years
No. of events
IDa (per 10,000 patient-years) (95% CI)
Crude HR (95% CI) in association with diabetic group
Adjusted HRb (95% CI) in association with diabetic group
319,308
2,671,483
477
1.79 (1.63–1.95)
1.00
1.00
43,426 73,736 202,148 319,310
340,244 587,891 1,522,720 2,450,855
57 113 288 458
1.68 (1.27–2.17) 1.92 (1.58–2.31) 1.89 (1.68–2.12) 1.87 (1.70–2.05)
0.94 (0.71–1.24) 1.07 (0.88–1.32) 1.06 (0.92–1.23) 1.05 (0.92–1.19)
0.89 (0.67–1.18) 1.00 (0.81–1.25) 1.07 (0.91–1.25) 1.06 (0.92–1.22)
ID, incidence density; CI, confidence interval; HR, hazard ratio; and AHR, adjusted hazard ratio. a Based on Poisson assumption. b Based on Cox proportional hazard regression with adjustment for age, geographic area, urbanization status, Charlson's score, history of endometriosis, cardiovascular disease, pelvic inflammatory disease, chronic liver disease, rheumatic disease, and frequency of medical visit.
Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
H.-F. Chen et al. / Gynecologic Oncology xxx (2014) xxx–xxx
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Please cite this article as: Chen H-F, et al, A large scale population-based cohort study on the risk of ovarian neoplasm in patients with type 2 diabetes mellitus, Gynecol Oncol (2014), http://dx.doi.org/10.1016/j.ygyno.2014.07.001
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