International Journal of Molecular Medicine is an international journal devoted to molecular mechanisms of human disease.
International Journal of Oncology is an international journal devoted to oncology research and cancer treatment.
Covers molecular medicine topics such as pharmacology, pathology, genetics, neuroscience, infectious diseases, molecular cardiology, and molecular surgery.
Oncology Reports is an international journal devoted to fundamental and applied research in Oncology.
Experimental and Therapeutic Medicine is an international journal devoted to laboratory and clinical medicine.
Oncology Letters is an international journal devoted to Experimental and Clinical Oncology.
Explores a wide range of biological and medical fields, including pharmacology, genetics, microbiology, neuroscience, and molecular cardiology.
International journal addressing all aspects of oncology research, from tumorigenesis and oncogenes to chemotherapy and metastasis.
Multidisciplinary open-access journal spanning biochemistry, genetics, neuroscience, environmental health, and synthetic biology.
Open-access journal combining biochemistry, pharmacology, immunology, and genetics to advance health through functional nutrition.
Publishes open-access research on using epigenetics to advance understanding and treatment of human disease.
An International Open Access Journal Devoted to General Medicine.
The incidence of gynecological cancers (GC) has increased in Japan, with an estimated 30,964 newly diagnosed patients in 2009. In recent years, the incidence of GC has increased among younger patients, as well as among older patients (1). The risk factors for GC differ by organ. For example, the development of invasive cervical cancer (CC) requires persistent infection by human papillomavirus (2,3). Several occurrence risk factors for endometrial cancer (EM) have been established, including excess body weight (4) and diabetes mellitus (DM) (5). The occurrence risk factors for ovarian cancer (OV) include age at diagnosis, family history of OV, infertility treatment and assisted fertilization, obesity and metabolic syndromes (6). Recently, metabolic conditions, such as obesity, hyperlipidemia and DM, have been attracting increasing attention with respect to OV incidence (7,8). Therefore, the onset of EM and OV appears to be associated with lifestyle and behavioral factors, such as dietary habits, physical activity, smoking and alcohol consumption.
Chronic diseases (CD) and cancer share common risk factors, including aging and unhealthy habits, such as smoking, poor diet, sedentary lifestyle, obesity and alcohol intake. CD include hypertension (HT), DM, dyslipidemia (DL), heart disease (HD) and cerebrovascular disease (CVD), and constitute >20% of the occurrence risk factors for various cancers (9). In 2017, the Japanese Ministry of Health, Labour and Welfare reported that 108,000 CD patients were aged <35 years, 3,141,000 CD patients were aged 35-64 years, and 11,458,000 CD patients were aged ≥65 years among women without cancer in Japan (10).
The development rates of CD are rapidly increased by excess body weight (11), but there are no published details of the effect of CD on GC. Therefore, the aim of the present study was to investigate the correlations between CD and GC, including CC.
The present retrospective study reviewed the medical records of 1,590 GC patients who were treated at the Department of Obstetrics and Gynecology of Okayama University Hospital (Okayama, Japan) between April 2004 and December 2017. The study protocol was approved by the Institutional Review Board of Okayama University Hospital (1904-05). Several studies reported that the threshold for lowest risk of all-cause mortality was ~100 g alcohol/week and <10 cigarettes/day (12,13). All patients underwent a review of their medical history and lifestyle habits (smoking-positive: Current smokers of ≥10 cigarettes/day; alcohol intake-positive: Alcohol intake of ≥14 g/day), physical examination and routine clinical staging. The patients were treated according to the Japan Society of Gynecologic Oncology clinical guidelines (14-16). The treatment options for gynecological cancer included surgery, radiotherapy and/or chemotherapy, depending on tumor stage and additional risk factors.
The patients were asked to complete questionnaires on their history of cardiac disease, lifestyle habits (smoking and alcohol intake), and medications for HT, DM and DL. The measurements included standard medical examinations, such as height, weight, blood pressure, fasting blood glucose, hemoglobin A1c and serum lipid profile, including triglyceride (TG), serum high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels. Patients with HT were defined as those with blood pressure ≥140/90 mmHg, or those on antihypertensive medication. Patients with DM were defined as those with hemoglobin A1c ≥6.5%, or those receiving antidiabetic medication. Patients with DL were determined as those with TG ≥150 mg/dl, HDL-C <40 mg/dl, and LDL-C ≥140 mg/dl, or those receiving medication for DL. The presence of HD and CVD were assessed based on self-reports. Height and weight were measured on admission, prior to any therapeutic intervention. Body mass index (BMI) was defined according to the 2015 World Health Organization classification as follows: Underweight, <18.5 kg/m2; normal weight, 18.5-24.99 kg/m2; overweight, 25.0-29.99 kg/m2; and obese, ≥30.0 kg/m2.
Data were analyzed using χ2 and Mann-Whitney U-tests for comparisons, and by one-way analysis of variance followed by Fisher's protected least significant difference test for all pairwise comparisons. Survival curves were constructed using the Kaplan-Meier method, and differences between survival curves were examined using the log-rank test. Analyses were performed using SPSS software, version 23.0 (IBM Corp.), with the significance level set at 0.05.
CC, EM and OV patients were aged 25-92, 23-91 and 15-84 years, respectively (median CC age, 55.0 years; median EM age, 59.0 years; and median OC age, 57.0 years). Age was divided into four groups: <50, 50-59, 60-69 and ≥70 years. The <50 years group included 277 CC (40.4%), 120 EM (19.6%) and 78 OV (26.7%) patients; the 50-59 years group included 138 CC (20.2%), 200 EM (32.6%) and 87 OV (29.8%) patients; the 60-69 years group included 133 CC (19.4%), 168 EM (27.4%) and 82 OV (28.1%) patients; and the ≥70 years group included 137 CC (20.0%), 125 EM (20.4%) and 45 OV (15.4%) patients.
The HT, DM, DL, HD and CVD patients in the <50 years group included 9, 4, 2, 2 and 3 CC patients, respectively (3.2, 1.4, 0.7, 0.7 and 1.1%, respectively); 12, 13, 5, 4 and 0 EM patients, respectively (10.0, 10.8, 4.2, 3.3 and 0%, respectively); and 1, 2, 0, 1 and 0 OV patients, respectively (1.3, 2.6, 0, 1.3 and 0%, respectively). The HT, DM, DL, HD and CVD patients in the 50-59 years group included 16, 10, 4, 2 and 2 CC patients, respectively (11.6, 7.2, 2.9, 1.4 and 1.4%, respectively); 34, 17, 18, 6 and 5 EM patients, respectively (17.0, 8.5, 9.0, 3.0 and 2.5%, respectively); and 13, 3, 8, 2 and 0 OV patients, respectively (14.9, 3.4, 9.2, 2.3 and 0%, respectively). The HT, DM, DL, HD and CVD patients in the 60-69 years group included 43, 15, 14, 4 and 6 CC patients, respectively (32.3, 11.2, 10.5, 3.0 and 4.5%, respectively); 61, 20, 27, 13 and 6 EM patients, respectively (48.8, 16.0, 21.6, 10.4 and 4.8%, respectively); and 19, 4, 8, 1 and 3 OV patients, respectively (23.2, 4.9, 9.8, 1.2 and 3.7%, respectively). Finally, the HT, DM, DL, HD and CVD patients in the ≥70 years group included 57, 12, 14, 15 and 13 CC patients, respectively (41.6, 8.8, 10.2, 10.9 and 9.5%, respectively); 67, 31, 42, 8 and 6 EM patients, respectively (39.9, 18.5, 25.0, 4.8 and 3.6%, respectively); and 13, 6, 7, 2 and 3 OV patients, respectively (28.9, 13.3, 15.6, 4.4 and 6.7%, respectively) (Table I).
The associations of each GC type [CC (n=685), EM (n=613) and OV (n=292)] with clinical characteristics (cancer stage, HT, DM, DL, HD, CVD, BMI, smoking and alcohol intake) were assessed (Table II). Regarding FIGO stage, there were significantly more EM patients with early-stage disease compared with CC patients (P<0.001). Conversely, the number of advanced-stage OV patients was significantly higher compared with CC patients (P<0.001). The incidence of HT, DM, DL and high BMI were significantly higher in EM patients compared with CC patients (all P<0.001). Furthermore, significantly more CC patients were smoking- and alcohol intake-positive compared with EM and OV patients (P<0.001, P<0.001, P<0.001 and P=0.026, respectively).
The effect of CD was examined by determining how many of CC, EM and OV patients in each of the four age groups had CD. CD patients were divided into 189 CC (27.6%), 265 EM (43.2%) and 72 OV (24.7%) patients. Patients in the <50 years group with CD included 19 CC (6.9%), 27 EM (22.5%) and 4 OV (5.1%) patients. CD patients in the 50-59 years group included 29 CC (21.0%), 57 EM (28.5%) and 21 OV (24.1%) patients. CD patients in the 60-69 years group included 60 CC (45.1%), 98 EM (58.3%), and 25 OV (30.5%) patients. Finally, CD patients in the ≥70 years group included 81 CC (59.1%), 83 EM (66.4%) and 22 OV (48.9%) patients. CC patients aged ≥70 years and EM patients aged 60-69 and ≥70 years accounted for >50% of those with CD. Therefore, the number of patients with CD aged ≥70 years was 8.6-fold higher in the CC group, 3.0-fold higher in the EM group, and 9.6-fold higher in the OV group compared with patients aged <50 years (Fig. 1).
CD was examined for its association with BMI, smoking and alcohol intake at any age in CC, EM and OV patients. BMI and CD were significantly associated in CC patients aged <50 and 50-59 years (P=0.025 and P=0.010, respectively). BMI and CD were significantly associated in all age groups in EM patients (P<0.001, P<0.001, P<0.001 and P=0.014, respectively). BMI and CD were significantly associated in OV patients aged 50-59 and ≥70 years (P=0.043 and P=0.004, respectively; Fig. 2). However, there was no association between CD and smoking or alcohol intake at any age in CC, EM or OV patients.
In the present study, the median overall survival (OS) rates for patients with CC, EM and OV were 44.0, 40.0 and 32.5 months, respectively. The follow-up period was 1-174, 1-146 and 1-132 months, respectively. The OS curves for the 1,590 GC patients according to their CD are shown in Fig. 3. There was no significant correlation between CD and survival at any age in CC, EM or OV patients.
The occurrence risk factors for cancer include smoking, an unhealthy diet, obesity, sedentary lifestyle, DM, HT and alcohol abuse, either alone or in combination. Accumulating evidence has suggested that obesity is an important occurrence risk factor for EM, and BMI is significantly associated with symptoms in EM patients (17). Zhang et al also demonstrated that DM is associated with EM (5), and several studies have reported the association of metabolic markers of obesity, including elevated blood glucose, TG and total cholesterol levels, with EM (18).
CD and cancer share common risk factors, particularly those associated with an unhealthy lifestyle, such as smoking, an unhealthy diet, physical inactivity, obesity and alcohol intake. CD is known to contribute to >20% of occurrence risk factors for various cancers (9); however, to the best of our knowledge, this is the first study to describe an association between CD and GC, including CC.
In the present study, CD, including HT, DM, DL, HD and CVD, were examined in patients with CC, EM and OV. For all diseases, we observed a high frequency of EM, CC and OV, in decreasing order. For example, HT was observed in 18.2, 28.4 and 15.8% of CC, EM and OV patients, respectively; DL was observed in 5.0, 15.0 and 7.9% of CC, EM and OV patients, respectively; DM occurred in 6.0, 13.2 and 5.1% of CC, EM and OV patients, respectively; HD was diagnosed in 3.4, 5.1 and 2.1% of CC, EM and OV patients, respectively; and CVD was recorded in 3.5, 2.8 and 2.1% of CC, EM and OV patients, respectively. Among the CD patients, 27.6, 43.2 and 24.7% had CC, EM and OV, respectively. The incidence of CD was found to increase with age in GC patients, with CC patients aged >70 years and EM patients aged >60 years accounting for >50% of patients with CD. Moreover, the numbers of any disease increased with increasing age, regardless of the number of CD.
CD were examined for their association with lifestyle factors, such as obesity, smoking and alcohol intake, at any age in all GC patients. In the present study, CD were more prevalent among EM patients compared with CC and OV patients. Among the CD patients, 27.6, 43.2 and 24.7% had CC, EM and OV, respectively. Of note, occurrence risk factors for EM have been established, including HT, DM and DL.
However, there was no association of smoking and alcohol intake with CD. We also determined whether CD were associated with outcome in GC patients, and found that the presence of CD was not a prognostic predictor for CC, EM or OV patients.
There were certain limitations to the present study. The number of patients was relatively small, and the examinations were performed at a single institution. Further prospective studies involving more patients and multiple institutions should provide more definitive data to verify the significance of our findings.
In conclusion, the presence of CD appears to contribute to >24% of the occurrence risk factors for GC patients in Japan.
The authors would like to thank all those who contributed to the present study, particularly the statisticians and colleagues of Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences. We appreciate their help with data management and statistical support. We would also like to thank Sarah Williams, PhD, and H. Nikki March, PhD for editing a draft of this manuscript.
No funding was received.
The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.
KN and KO contributed to the conception, design and conduction of the study, and analysis and interpretation of the data. HM, YM, JH, CO and HM contributed to data collection and the conduction of the study. All the authors have read and approved the final version of this manuscript.
The present study was performed according to the principles set out in the Declaration of Helsinki 1964 and all subsequent revisions, and was approved by the Institutional Review Board of Okayama University Hospital (IRB approval no. 1904-005).
Not applicable.
All the authors declare that they have no competing interests to disclose.
|
Hori M, Matsuda T, Shibata A, Katanoda K, Sobue T and Nishimoto H: Japan Cancer Surveillance Research Group: Cancer incidence and incidence rates in Japan in 2009: A study of 32 population-based cancer registries for the monitoring of cancer incidence in Japan (MCIJ) project. Jpn J Clin Oncol. 45:884–891. 2015.PubMed/NCBI View Article : Google Scholar | |
|
de Sanjose S, Quint WG, Alemany L, Geraets DT, Klaustermeier JE, Lloveras B, Tous S, Felix A, Bravo LE, Shin HR, et al: Human papillomavirus genotype attribution in invasive cervical cancer: A retrospective cross-sectional worldwide study. Lancet Oncol. 11:1048–1056. 2010.PubMed/NCBI View Article : Google Scholar | |
|
Al Moustafa AE, Ghabreau L, Akil N, Rastam S, Alachkar A and Yasmeen A: High-risk HPVs and human carcinomas in the Syrian population. Front Oncol. 4(68)2014.PubMed/NCBI View Article : Google Scholar | |
|
Aune D, Navarro Rosenblatt DA, Chan DS, Vingeliene S, Abar L, Vieira AR, Greenwood DC, Bandera EV and Norat T: Anthropometric factors and endometrial cancer risk: A systematic review and dose-response meta-analysis of prospective studies. Ann Oncol. 26:1635–1648. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Zhang Y, Liu Z, Yu X, Zhang X, Lü S, Chen X and Lü B: The association between metabolic abnormality and endometrial cancer: A large case-control study in China. Gynecol Oncol. 117:41–46. 2010.PubMed/NCBI View Article : Google Scholar | |
|
Xie H, Hou Y, Cheng J, Openkova MS, Xia B, Wang W, Li A, Yang K, Li J, Xu H, et al: Metabolic profiling and novel plasma biomarkers for predicting survival in epithelial ovarian cancer. Oncotarget. 8:32134–32146. 2017.PubMed/NCBI View Article : Google Scholar | |
|
Chen Y, Zhang L, Liu W and Wang K: Case-control study of metabolic syndrome and ovarian cancer in Chinese population. Nutr Metab (Lond). 14(21)2017.PubMed/NCBI View Article : Google Scholar | |
|
Nagle CM, Dixon SC, Jensen A, Kjaer SK, Modugno F, deFazio A, Fereday S, Hung J, Johnatty SE; Australian Ovarian Cancer Study Group, et al: Obesity and survival among women with ovarian cancer: Results from the Ovarian cancer association consortium. Br J Cancer. 113:817–826. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Tu H, Wen CP, Tsai SP, Chow WH, Wen C, Ye Y, Zhao H, Tsai MK, Huang M, Dinney CP, et al: Cancer risk associated with chronic diseases and disease markers: Prospective cohort study. BMJ. 360(k134)2018.PubMed/NCBI View Article : Google Scholar | |
|
Ministry of Health labor and Welfare reports. Patient survey overview in 2017 year in Japan, pp16-32, 2017 (Japanese). | |
|
Chen Y, Copeland WK, Vedanthan R, Grant E, Lee JE, Gu D, Gupta PC, Ramadas K, Inoue M, Tsugane S, et al: Association between body mass index and cardiovascular disease mortality in east Asians and south Asians: Pooled analysis of prospective data from the Asia Cohort Consortium. BMJ. 347(f5446)2013.PubMed/NCBI View Article : Google Scholar | |
|
Wood AM, Kaptoge S, Butterworth AS, Willeit P, Warnakula S, Bolton T, Paige E, Paul DS, Sweeting M, Burgess S, et al: Risk thresholds for alcohol consumption: Combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies. Lancet. 391:1513–1523. 2018.PubMed/NCBI View Article : Google Scholar | |
|
Whitfield JB, Heath AC, Madden PAF, Landers JG and Martin NG: Effects of high alcohol intake, alcohol-related symptoms and smoking on mortality. Addiction. 113:158–166. 2018.PubMed/NCBI View Article : Google Scholar | |
|
Ebina Y, Mikami M, Nagase S, Tabata T, Kaneuchi M, Tashiro H, Mandai M, Enomoto T, Kobayashi Y, Katabuchi H, et al: Japan Society of Gynecologic Oncology guidelines 2017 for the treatment of uterine cervical cancer. Int J Clin Oncol. 24:1–19. 2019.PubMed/NCBI View Article : Google Scholar | |
|
Ebina Y, Katabuchi H, Mikami M, Nagase S, Yaegashi N, Udagawa Y, Kato H, Kubushiro K, Takamatsu K, Ino K and Yoshikawa H: Japan Society of Gynecologic Oncology guidelines 2013 for the treatment of uterine body neoplasms. Int J Clin Oncol. 21:419–434. 2016.PubMed/NCBI View Article : Google Scholar | |
|
Komiyama S, Katabuchi H, Mikami M, Nagase S, Okamoto A, Ito K, Morishige K, Suzuki N, Kaneuchi M, Yaegashi N, et al: Japan Society of Gynecologic Oncology guidelines 2015 for the treatment of ovarian cancer including primary peritoneal cancer and fallopian tube cancer. Int J Clin Oncol. 21:435–446. 2016.PubMed/NCBI View Article : Google Scholar | |
|
Jenabi E and Poorolajal J: The effect of body mass index on endometrial cancer: A meta-analysis. Public Health. 129:872–880. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Friedenreich CM, Biel RK, Lau DC, Csizmadi I, Courneya KS, Magliocco AM, Yasui Y and Cook LS: Case-control study of the metabolic syndrome and metabolic risk factors for endometrial cancer. Cancer Epidemiol Biomarkers Prev. 20:2384–2395. 2011.PubMed/NCBI View Article : Google Scholar |