Type 2 diabetes mellitus and colorectal cancer: Meta-analysis on sex-specific differences

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1 E U R O P E A N J O U R N A L O F CA N C E R48 (2012) available at journal homepage: Review Type 2 diabetes mellitus and colorectal cancer: Meta-analysis on sex-specific differences Heike U. Krämer, Ben Schöttker, Elke Raum, Hermann Brenner * Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Im Neuenheimer Feld 581, Heidelberg, Germany ARTICLE INFO ABSTRACT Article history: Available online 31 August 2011 Keywords: Colorectal cancer Colorectal neoplasms Type 2 diabetes mellitus Gender Meta-analysis Review Although there is consent concerning a higher risk for colorectal cancer (CRC) amongst patients with type 2 diabetes mellitus (T2DM), there remains uncertainty regarding potential sex differences in the strength of this association. We reviewed and summarised epidemiological studies assessing the sex-specific association of T2DM with the risk for CRC. All relevant studies published until 14th February 2011 were identified by a systematic search of MEDLINE, EMBASE, BIOSIS Previews and ISI Web of Knowledge databases and cross-referencing. We included observational studies that reported relative risk (RR) or odds ratio (OR) estimates with 95% confidence intervals (CIs) for the association between T2DM and CRC. Two authors independently extracted data and assessed study quality of each study in a standardised manner. Study-specific estimates were pooled for both sexes separately using random-effects models. A total of 29 eligible studies were used for meta-analysis. Overall estimates of relative risk (RR) were very similar amongst men (RR = 1.29; 95%-confidence interval (CI): ) and (RR = 1.34; 95%-CI: ). In both men and, risk estimates from case-control studies were slightly higher than those from cohort studies. Overall, T2DM is associated with a moderate increase in CRC risk in both men and. Ó 2011 Elsevier Ltd. All rights reserved. 1. Introduction Type 2 diabetes mellitus (T2DM) and colorectal cancer (CRC) are common diseases at old age in Westernised countries and also share several risk factors such as overweight and lack of physical inactivity. 1 T2DM incidence and prevalence are increasing due to demographic changes and as unhealthy diets and sedentary lifestyles become more frequent. 2,3 Recent data show that approximately 285 million people worldwide suffer from diabetes and this number may increase up to 439 million by In Europe in 2010, it was estimated that about 55.4 millions (8.5%) of the European population have diabetes. 5 Due to multiple effects of T2DM on various organ systems, all-cause mortality is about twice as high amongst diabetics than amongst people without the disease. 6,7 CRC is one of the most common cancers worldwide. 8 The lifetime risk of developing CRC is slightly below 6% for the US-general population; risk is rising with age and there is higher risk for men than for. 9,10 Furthermore, differences in incidence between men and are undergoing a leftward shift, i.e. an increase of gender differences in the * Corresponding author. Tel.: ; fax: addresses: h.brenner@dkfz.de, h.brenner@dkfz-heidelberg.de (H. Brenne) /$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi: /j.ejca

2 1270 E U RO P E A N J O U R NA L O F CA N C E R48 (2012) more distal sites which is shown by a greater decrease for the more distal subsites in. 11 Since the 1990s when the hyperinsulinemia-hypothesis was stated by Giovannucci and McKeown-Eyssen proposing a promitotic and antiapoptotic effect of insulin on carcinogenesis 12,13, it has been suspected that T2DM might also promote carcinogenesis. By now, there is consent that T2DM is an independent risk factor for CRC incidence and mortality. 1,14 However, despite numerous studies on CRC risk for patients with T2DM, there are inconsistencies regarding the strength of the association especially when stratifying for gender: several studies reported higher risk for male patients with T2DM 15 18, others for female patients with T2DM Potential gender differences are of particular interest in the light of suggestions of the second independent biological pathway associated with CRC development which involves endogenous oestradiol/oestrogen. 24 To provide a systematic overview of the impact of T2DM on CRC risk in men and, we conducted a meta-analysis of epidemiological studies investigating the sex-specific association between T2DM and CRC. 2. Material and methods 2.1. Search strategy We performed a literature search to 14th February Searches of the MEDLINE, EMBASE, BIOSIS Previews and ISI Web of Knowledge databases with the following (medical subject heading) terms and/or text words were employed: ( type 2 diabetes OR NIDDM ) AND ( colorectal cancer OR colon cancer OR rectum cancer OR colorectal carcinoma ) AND ( association OR risk OR incidence ). We selected only those studies which were either conducted in one sex only or provided sexspecific results. Duplicate and overlapping publications were deleted. Each title and abstract was checked for relevance and full texts were reviewed if the abstract indicated that sexspecific associations between T2DM and CRC or both colon and rectal cancer were reported. Only original studies conducted amongst humans were considered for the review. We also screened reference lists of identified publications (cross-referencing) for additional pertinent studies in order to complement the study identification process. This systematic review was planned, conducted and reported in adherence to standards of quality for reporting meta-analyses Eligibility criteria Studies were included if they analysed CRC incidence, had an observational study design, the exposure of interest was diabetes mellitus (either given by participants self-report by a self-administered questionnaire or via in-person interview or by medical/physician records or registries) and if the outcome of interest was colorectal, colon or rectal cancer. Study results had to be reported stratified for sex or for one sex only. Furthermore, relative risk (RR) estimates with 95% confidence intervals (CIs) (or data to calculate these) had to be reported. Studies were restricted to English and German articles (including also first access publication or e-papers). Studies on CRC mortality were not included for the analyses. Type 2 diabetes mellitus was assumed if verified by medical/physician records or registries or if the diagnosis of diabetes was combined with age-limitations (e.g. age at diagnosis >30 years) to minimise potential inclusion of patients with type 1 diabetes mellitus. Studies reporting diabetes without risk assessment for our outcome of interest or which analysed a highly selected T2DM population (e.g. a population of T2DM patients with insulin therapy) or a CRC population without a control group were excluded. Medication-, food-intake- or nutrition-focused publications as well as in vitro- or molecular-focused studies or studies using surrogate parameters for diabetes (e.g. C-peptide or IGF-I) were not considered Data extraction From eligible studies, the first author (HUK) and the second author (BS) independently extracted the following data in a standardised manner: first author, publication year, study design, country, study period, age range (mean or median age for men and separately), net-sample size (number of included men and separately), number of CRC cases, exposure definition, measures of association with their corresponding 95% confidence intervals (CIs) and variables matched or adjusted for. Generally, risk estimates that showed the most comprehensive control for potential confounding were chosen Statistical analysis Major outcome variables were quantitative measures of the association between T2DM and CRC incidence. Since CRC is a rare disease, ORs from case-control studies and RRs from cohort studies produce comparable estimates. Sex-specific summary RR estimates and their corresponding 95% CIs were calculated according to DerSimonian and Laird. 26 Separate and combined analyses were carried out for case-control studies and for cohort studies. Sub-group analyses were carried out focusing on studies which adjusted for the most important confounding variables, i.e. age, body mass index (BMI) and physical activity. Furthermore, subgroup analyses were conducted for major geographical regions (USA, Europe, Asia). The random-effects model was used, taking into account the possibility of statistical heterogeneity between studies, which was tested with Cochran s Q test (p < 0.10 was considered indicative of statistically significant heterogeneity) and the I 2 statistic (values of 25%, 50% and 75% are considered to represent low, moderate and high inconsistency, respectively). 27 Kendall s tau and Egger weighted regression methods (one-tailed) were used to statistically assess publication bias (p < 0.05 was considered indicative of statistically significant publication bias). 28 The Comprehensive meta-analysis program (V2.0, Biostat, Englewood, NJ, USA) was used for the analysis. 3. Results 3.1. Study characteristics As shown in Fig. 1, a total of 658 articles published in English or German were identified. After the removal of 349 duplicates, 309 titles and abstracts were assessed and 257 were

3 E U R O P E A N J O U R N A L O F CA N C E R48 (2012) Literature search Databases: MEDLINE, EMBASE, BIOSIS Previews and ISI Web of Knowledge Limits: English- and German-language articles only published until 14 th February 2011 Medline search: 60 BIOSIS search: 246 EMBASE search: 136 ISI search: 216 Search results combined: 658 Duplicates: 349 Articles screened on basis of title and abstract: 309 Excluded articles based on screening of titles and/ or abstracts using general criteria: 257 Full articles reviewed: 52 Excluded articles: 38 Not stratified by gender: 11 Metabolic syndrome: 3 Mortality analysis: 5 Polyp-/ adenoma-focused: 6 Screening complications: 2 Therapy-related: 4 Metabolic syndrome/ diabetes risk score: 4 Hyperinsulinaemia: 2 Nutrition: 1 Articles identified by crossreferencing: 15 Included original articles: 29 Case-control studies: 8 Cohort studies: 21 Fig. 1 Flow diagram of the literature search process. excluded (according to the in- and exclusion-criteria). After reviewing the total manuscript, another 38 studies did not comply with the defined in- and exclusion criteria, 15 were identified by cross-referencing and 29 articles were finally selected for this review. In total, 8 case-control studies (Table 1) 15,17,19 21,29 31 and 21 cohort studies (Table 2) 16,18,22,23,32 48 analysing the sexspecific association between T2DM and CRC risk were identified. Ascertainment of T2DM differed between studies: 22 studies relied either on self-reports only or on self-reports together with other diabetes-specific information (e.g. self-reported age at onset, diabetes duration) 15,17 20,23,29,31 34,36,37,39 46,48, two defined diabetes status via medical records 21,38 and two other studies via a medical registry or surveillance system 22,30, and three studies used HbA 1c - or FG-levels to define diabetes participants. 16,35,47 Amongst the eight case-control studies, four were conducted in Europe 15,20,21,31, one in Australia, 29 one in USA, 19 one in Japan 17 and one in Iran. 30 The number of CRC cases of the studies ranged between and 11, participants. Amongst the 21 cohort studies, 10 were conducted in the USA 18,23,32 35,38,40,45,48, seven in Europe, one in Korea, 41 one in China, 43 one in Japan 44 and one in Israel. 22 Cohort studies differed in the number of exposed participants (ranging between and 62,924, 41 ) mean age of the participants at baseline (ranging between 42.2 years 34 and 73.0 years 35 ) and time of follow-up (ranging between 4 years 36 and 24 years 48 ). This meta-analysis considered several articles of large well-known studies, such as the National Health and Nutrition Survey I (USA), 32 the EPIC-Norfolk-Study (UK) 36,39,47, the Cancer Prevention Study I (USA), 33 the Nurse s Health Study (USA), 34 the Iowa Women s Health Study (USA), 40 the Physician s Health Study (USA) 45 and the Cancer Prevention Study II Nutrition Cohort, USA Results of meta-analyses on CRC risk The results of the meta-analyses of the 29 studies assessing the association between T2DM and CRC risk separately for men and are shown in Figs. 2 and 3.

4 Table 1 Characteristics of case-control studies of diabetes and colorectal cancer risk. First author (year), country; study name, [Ref. No.] Kune et al. (1988), Australia; The Melbourne Colorectal Cancer Study, [26] La Vecchia et al. (1997), Italy;[13] Le Marchand et al. (1997), USA;[17] Levi et al. (2002), Switzerland;[18] Age range (mean/ median age in general or for men/ ) N/A (mean: men: 65.0; : 65.0) Cases: (mean: 62.0); controls: (mean: 58.0) <84 (mean: cases: men: 67.0, : 65.0; controls: men: 65.0, : 65.0) Cases: (median: 65.0); controls: (median: 59.0) No. CRC cases: men/ No. controls: men/ (selection method) Definition of diabetes 388/ /329 (PBC) Self-reported DM via interview 1125/ /2081 (HBC) Self-reported DM via interview 688/ /494 (PBC) Self-reported DM via interview 174/ /281 (HBC) Self-reported DM via interview Yang et al. (2005), UK; [19] N/A 5488/ ,918/60,511 (PBC) Kuriki et al. (2007), Japan; HERPACC [15] (mean: cases: men: 64.3, : 60.6; controls: men: 60.6, : 57.0) 5341/ ,199/33,569 (HBC) T2DM via medical records (General Practice Research Database) Self-reported DM via questionnaire and checked by trained interviewer Safaee et al. (2009), Iran; [27] P40 (N/A) 521/ / DM via cancer registry and Department of Health System Research (HSR) Pelucchi et al. (2010), Italy and Switzerland; [28] (median: cases: 61.0, controls: 57.0) 1310/ /2297 (PBC) Self-reported T2DM via interview Diabetes-related risk of CRC OR (95% CI) Men Women Adjusted/matched 1.28 ( ) 0.75 ( ) Matched by age and sex 1.4 ( ) 1.2 ( ) Age, BMI, physical activity, area of residence, education, family history of CRC and intakes of total energy, fat, dietary fibre and alcohol 1.2 ( ) 1.8 ( ) Age, BMI, physical activity, family history of CRC, smoking, total energy intake, egg, dietary fibre, calcium and alcohol; matched by age, sex and ethnicity 1.30 ( ) 3.56 ( ) Age, BMI, education, family history of CRC, smoking status and alcohol 1.36 ( ) 1.38 ( ) Age at enrolment, calendar year of enrolment and duration of follow-up 1.30 ( ) 1.13 ( ) Age, BMI, alcohol, smoking, physical activity, bowel movement, family history of diabetes, dietary restrictions, raw vegetable intake, snacking, greasy foods intake 6.19 ( ) 6.52 ( ) Age, smoking and BMI 1.27 ( ) 1.20 ( ) Age, study-centre, education, smoking habit, alcohol, occupational physical activity and non-alcohol energy intake CRC = colorectal cancer; DM = diabetes mellitus; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus; BMI = body mass index; N/A = not available; Ref.No.=reference number; OR = odds ratio; CI = confidence interval; PBC = population-based controls; HBC = hospital-based controls; CCS = case-control study E U RO P E A N J O U R NA L O F CA N C E R48 (2012)

5 Table 2 Characteristics of cohort studies of diabetes and colorectal cancer risk. Author (year), country; study name, (follow-up period) [Ref. No.] Age range at baseline (mean age) Exposed group;men/ Comparison group;men/ Number of CRC cases; men/ Definition of diabetes Diabetes-related risk of CRC RR (95% CI) Men Women Adjusted for Steenland et al. (1995), USA; National Health and Nutrition Survey I, ( ) [29] Will et al. (1998), USA; Cancer Prevention Study I, ( ) [30] Hu et al. (1999), USA; The Nurse s Health Study, ( ) [31] Schoen et al. (1999), USA; Cardiovascular Health Study, ( ) [32] Sandhu et al. (2001), UK; EPIC-Norfolk- Study, ( ) [33] 1 74 (49.2) 429; N/A 12,625; N/A 176; 94/82 Self-reported DM via interview P30 (men: 53.0, : 52.0) 15,487; 7229/ ,212 volunteers; 345,620/502, ; 3218/ (42.2) , Self-reported DM via questionnaire Self-reported T2DM validated by treatment of DM, medical records, questionnaires and diagnostic tests; exclusion if diagnosis <30 years P65 (73.0) 1161; 531/ ; 1085/ ; 53/40 DM defined by baseline fasting glucose, medication history and oral glucose load (N/A) 561; 346/215 28,782; 12,847/ 15, ; 78/69 Self-reported T2DM via questionnaire; exclusion if diagnosis < ( ) 1.30 ( ) 1.40 ( ) 1.16 ( ) 1.43 ( ) Age, BMI, physical activity, income, smoking and alcohol Age, BMI, physical activity, education, race, family history of CRC, history of constipation, smoking, aspirin, and intakes of fruits, vegetables, cereals, meat, milk, coffee, tea and alcohol Age, time periods, BMI, smoking, menopausal status, multivitamin supplement, alcohol, physical activity, aspirin, parental history of CRC and red meat 1.6 ( ) 1.1 ( ) Age, physical activity 3.11 ( ) 2.53 ( ) Age, smoking, BMI, further education and alcohol (continued on next page) E U R O P E A N J O U R N A L O F CA N C E R48 (2012)

6 Table 2 (continued) Author (year), country; study name, (follow-up period) [Ref. No.] Lund Nilsen et al. (2001), Norway; Nord-Trondelag Health Survey, ( ) [34] Ferrara et al. (2003); USA, ( ) [35] Khaw et al. (2004), UK; European Prospective Investigation into Cancer Norfolk Study, ( ) [36] Limburg et al. (2005), USA; Iowa Women s Health Study, ( ) [37] Jee et al. (2005), Korea; National Health Insurance Corp, ( ) [38] Larsson et al. (2005), Sweden; Cohort of Swedish men (COSM), ( ) [39] Seow et al. (2006), China; Singapore Chinese Health Study, ( ) [40] Inoue et al. (2006), Japan; Japan Public Health Center-based Prospective Study, ( ) [41] Age range at baseline (mean age) P20 (men: 48.5, : 49.8) Exposed group;men/ 14,712 PYs; 6510 PYs men, 8202 PYs Comparison group;men/ 734,701 PYs; 357,986 PYs men, 376,715 PYs Number of CRC cases; men/ Definition of diabetes 726; 359/367 Self-reported DM via questionnaire NN (60.4) 33,118 18, ; N/A Medical Records (Kaiser Permanente) (men: 59.0; : 59.0) 221 known diabetes; 149/ with no selfreported diabetes and HbA 1c< 5.0; 4296/ ; 36/31 Self-reported DM via questionnaire (N/A) , Self-reported T2DM via questionnaire, exclusion if diagnosis <30 years (men: 45.3, : 49.6) 62,924; 41,868/ 21, ,461 with FG < 90 mg/dl; 787,902/447,559 53,833; 37,759/ 16,074 Self-reported DM medication (N/A) 22,549 men 261,263 PYs 411 men Self-reported T2DM via questionnaire, exclusion if diagnosis <30 years (56.4) 5469; 2363/ ,851; 24,965/30, ; 352/284 Self-reported medical history of T2DM (men: 51.4, : 51.8) 4668; 3097/ ,103; 43,451/49, ; 734/ 759 Self-reported DM via questionnaire Diabetes-related risk of CRC RR (95% CI) Men Women Adjusted for 0.66 ( ) 1.55 ( ) Age, BMI, physical activity, education and marital status ( ) Age, obesity, ethnicity, education, smoking and alcohol 3.37( ) 1.71 ( ) Age, BMI and smoking 1.4 ( ) Age, BMI, total energy intake, calcium intake, vitamin E intake 1.11 ( ) 1.17 ( ) Age, smoking and alcohol 1.49 ( ) Age, BMI, education, family history of CRC, physical activity, smoking, multivitamin supplement, aspirin, consumption of fruits, vegetables, dairy foods and red meat 1.5 ( ) 1.4 ( ) Age, year of enrolment, sex, dialect, education, BMI, smoking, alcohol, family history of CRC and physical activity 1.09 ( ) a 1.16 ( ) a Age, study area, history of cerebrovascular disease or ischaemic heart disease, smoking, ethanol intake, BMI, physical activity, green vegetable and coffee 1274 E U RO P E A N J O U R NA L O F CA N C E R48 (2012)

7 Stürmer et al. (2006), USA; The Physician s Health Study, ( ) [42] Rapp et al. (2006), Austria; VHM&PP, ( ) [14] Bowers et al. (2006), Finland; Alpha- Tocopherol, Beta- Carotene Cancer Prevention Study, ( ) [43] Rinaldi (2008), 10 European countries; EPIC-study, ( ) [44] He et al. (2010), USA; Multiethnic Cohort Study, ( /2006) [45] Chodick et al. (2010), Isreal; ) [21] Flood et al. (2010), USA; Breast Cancer Detection Demonstration Project (BCDDP), ( ) [46] (53.8) 2495 men 161,735 PYs with no metabolic abnormality (men: 43.0, : 43.0) 4758; 2467/ ,720 with mmol/l; 30,510/39, ; N/A Self-reported T2DM via questionnaire and FG > 110 mg/dl 677; 333/344 DM defined by fasting glucose P 7.0 mmol/l (57.0) 1210 men 27,923 men 410; N/A Self-reported DM via questionnaire 1.5 ( ) - Age, physical activity, smoking, alcohol, multivitamin us, NSAIDs, history of arthritis, fruits and vegetables 1.19 ( ) 0.88 ( ) Smoking, age, occupational group and BMI 0.92 ( ) - Age, number of cigarettes smoked per day (59.0) 208; N/A 1844; N/A 1026; 561/465 DM via HbA 1c > 6.5% 1.25 ( ) 1.40 ( ) WHR and alcohol; matched by study centre, gender, age, time at blood collection, fasting glucose, follow-up time; also matched for menopausal status or phase of menstrual cycle (men: 60.2, : 59.7) 20,145; 9716/ 10,429 P21 (61.6) 16,721; 8795/ ,997; 79,762/ 99,235 83,874; 44,118/ 39, ; 1921/1628 Self-reported DM via questionnaire (59.0) , Self-reported DM via questionnaire 1.12 ( ) 1.28 ( ) Age, entry of the cohort, race, BMI, smoking, NSAIDs, education, alcohol, (un- )saturated fat intake, dietary fibre, physical activity and family history of CRC 1430; 814/616 DM via medical registry 1.13 ( ) a 1.35 ( ) a Age, region, SES level, use of healthcare services a year prior to index date, BMI and history of cardiovascular disease ( ) Age, physical activity, energy intake, alcohol, HRT, smoking, multi-vitamin use, education, ethnicity, NSAIDs, calcium from supplement or from diet. (continued on next page) E U R O P E A N J O U R N A L O F CA N C E R48 (2012)

8 1276 E U RO P E A N J O U R NA L O F CA N C E R48 (2012) Table 2 (continued) Definition of diabetes Diabetes-related risk of CRC RR (95% CI) Adjusted for Men Women Number of CRC cases; men/ Comparison group;men/ Exposed group;men/ Age range at baseline (mean age) Author (year), country; study name, (follow-up period) [Ref. No.] 1.24 ( ) 1.01 ( ) Age, education, BMI, physical activity, NSAIDS, alcohol, family history of CRC and endoscopy history. 2809; 1567/1242 Self-reported DM via questionnaire and review of medical records of a sample of CRC cases 143,640; 66,783/ 76, (63.0) 11,335; 6529/ 4806 Campbell et al. (2010), USA; Cancer Prevention Study II Nutrition Cohort, ( ) [16] CRC = colorectal cancer; DM = diabetes mellitus; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus; BMI = body mass index; WHR = waist-hip-ratio; HRT = hormone replacement therapy; NSAIDs = non-steroidal anti-inflammatory drug use; FG = fasting glucose; HbA1c = glycosylated haemoglobin; SES = socioeconomic status; N/A = not available; Ref.No.=reference number; RR = relative risk/relative rate; CI = confidence interval; PYs = person-years. a RR is a pooled risk estimate of colon and rectum estimate Case-control studies Four studies found a statistically significant positive association between T2DM and CRC risk (a < 0.05) for men 15,17,21,30 and four for, 19 21,30, respectively (Figs. 2a and 3a). Two studies did not find any association in men or. 29,31 A significant positive association was observed in the pooled analyses using a random effects model: The pooled ORs were slightly larger for than for men, but CIs were overlapping widely (men: random OR = 1.39, 95%-CI: ; : random OR = 1.57, 95%-CI: ). In men, moderate inconsistency (Q = 13.00, p = 0.07, I 2 = 46.15%) and in, statistically significant heterogeneity and high inconsistency between studies (Q = 23.93, p = 0.001; I 2 = 70.75%) were observed. There was no evidence of publication bias in both gender-specific analyses (men: Kendall s tau = 0.18, p = 0.27; Egger s t value = 1.19, p = 0.14; : Kendall s tau = 0.18, p = 0.27; Egger s t value = 1.00, p = 0.18) Cohort studies Eight studies found a statistically significant positive association between T2DM and CRC risk (p < 0.05) for men 18,33,36,39,41 43,45 and seven studies for 34,37,38,40,43,48,49 (Figs. 2b and 3b). Both pooled sex-specific risk estimates using a random effects model were statistically significant: The pooled RR estimates were lower than those from case-control studies (but CIs were overlapping widely) and similar for men (RR = 1.24, 95%-CI: ) and (random RR = 1.29, 95%-CI: ), again with widely overlapping confidence intervals. There was indication of heterogeneity and moderate inconsistency in men (men: Q = 24.77, p = 0.07; I 2 = 35.41%) whereas in, no heterogeneity or inconsistency was found (: Q = 17.06, p = 0.45; I 2 = 0.37%) (Figs. 2b and 3b). There was no evidence or indication of publication bias for -specific analyses, whereas for menspecific analyses there was some indication for publication bias (men: Kendall s tau = 0.24, p = 0.09; Egger s t value = 2.00, p = 0.03; : Kendall s tau = 0.09, p = 0.30; Egger s t value = 0.92, p = 0.19) Pooled risk estimate of all considered studies The meta-analysis of all considered studies for men and separately showed very small differences between the summary risk estimates between both genders (men: RR = 1.29, 95%-CI: ; : RR = 1.34, 95%-CI: ) (no figure). However, we found moderate heterogeneity and inconsistency (men: Q = 42.03, p = 0.01; I 2 = 42.90%; : Q = 42.54, p = 0.02; I 2 = 41.27%). There was some indication for publication bias in men but not in (men: Kendall s tau = 0.20, p = 0.08; Egger s t value = 2.68, p = 0.01; : Kendall s tau = 0.12, p = 0.20; Egger s t value = 1.49, p = 0.07) Sensitivity analyses In a next step we performed sensitivity analyses in order to explore the detected heterogeneity amongst studies of

9 E U R O P E A N J O U R N A L O F CA N C E R48 (2012) a Model Study name Odds ratio and 95% CI Odds Lower Upper ratio limit limit Kune et al. (1988) 1,28 0,67 2,46 La Vecchia et al. (1997) 1,45 1,05 2,00 Le Marchand et al. (1997) 1,20 0,83 1,73 Levi et al. (2002) 1,30 0,63 2,68 Yang et al. (2005) 1,36 1,15 1,60 Kuriki et al. (2007) 1,30 1,00 1,68 Safaee et al. (2009) 6,19 2,63 14,58 Pelucchi et al. (2010) 1,27 0,95 1,69 Random 1,39 1,17 1,65 Q=13.00, p=0.07, I²=46.15% 0,1 0,2 0, b Model Study name Risk Relative ratio risk and and 95% 95% CI CI Risk Rel. Lower Upper risk ratio limit limit Steenland et al. (1995) 1,43 0,61 3,33 Will et al. (1998) 1,30 1,03 1,65 Schoen et al. (1999) 1,60 0,81 3,15 Sandhu et al. (2001) 3,11 1,32 7,33 Lund Nilsen et al. (2001) 0,66 0,35 1,24 Khaw et al. (2004) 3,37 1,17 9,71 Jee et al. (2005) 1,11 1,00 1,24 Larsson et al. (2005) 1,49 1,14 1,95 Seow et al. (2006) 1,54 1,14 2,08 Inoue et al. (2006) 1,09 0,65 1,82 Stürmer et al. (2006) 1,50 1,11 2,02 Rapp et al. (2006) 1,19 0,79 1,80 Bowers et al. (2006) 0,92 0,41 2,07 Rinaldi et al. (2008) 1,25 0,84 1,87 He et al. (2010) 1,12 0,99 1,26 Chodick et al (2010) 1,13 0,93 1,38 Campbell et al (2010) 1,24 1,07 1,43 Random 1,24 1,14 1,35 Q=24.77, p=0.07, I²=35.41% 0,1 0,2 0, Fig. 2 Meta-analysis of case-control studies (a) and cohort studies (b) assessing the association between type 2 diabetes mellitus and colorectal cancer risk amongst men. T2DM and colorectal cancer. A sensitivity analysis omitting one study at a time and calculating the pooled ORs or RRs, respectively, for the remainder of the studies showed that the studies by Safaee et al. 30 and by Khaw et al. 39 substantially influenced the pooled risk estimates in case control studies and cohort studies, respectively. By excluding these studies, heterogeneity and inconsistency decreased dramatically for both study types amongst men and (Table 3). The included case control studies resulted in summary ORs of 1.33 (95%-CI: ) in men and 1.36 (95%-CI: ) in. The included cohort studies resulted in summary RRs of 1.23 (95%-CI: ) in men and 1.29 (95%-CI: ) in. In both study types no publication bias was evident or indicated for studies of females. But cohort studies of males showed a moderate inconsistency (28.87%) and an indication for publication bias. The summary RRs of the total remaining 19 studies decreased to 1.24 (95%-CI: ) in men and to 1.30 (95%-CI: ) in. No heterogeneity and inconsistency were evident or indicated amongst men and. Further restriction of the meta-analysis was to studies adjusting for age, BMI and physical activity 15,17 19,32 34,37,42 44,49, the most important potential confounders of the association between T2DM and CRC, did not materially change the results (Table 3) Geographical differences In a next step we analysed potential differences in study results between geographical areas, namely the USA, 18,19,23,32 35,38,40,45,48 Europe, 15,16,20 22,31,36,37,39,42,46,47 and Asia 17,30,41,43,44 (Table 4). After excluding Safaee et al. 30 from Asian studies and Khaw et al. 39 from European studies, we found the pooled risk estimates to be highly consistent across geographical regions. 4. Discussion Our meta-analysis supports the hypothesis of a significant positive, albeit rather modest association between T2DM and CRC in men and. The differences in relative risk between men and were found to be marginal. We found slightly higher relative risks for case-control studies than for cohort studies. Furthermore, there were higher

10 1278 E U RO P E A N J O U R NA L O F CA N C E R48 (2012) a Model Study name Odds ratio and 95% CI Odds Lower Upper ratio limit limit Kune et al. (1988) 0,75 0,35 1,61 La Vecchia et al. (1997) 1,49 1,00 2,23 Le Marchand et al. (1997) 1,80 1,14 2,85 Levi et al. (2002) 3,56 1,05 12,09 Yang et al. (2005) 1,38 1,14 1,67 Kuriki et al. (2007) 1,13 0,72 1,77 Safaee et al. (2009) 6,52 3,10 13,71 Pelucchi et al. (2010) 1,20 0,82 1,75 Random 1,57 1,16 2,13 Q=23.93, p=0.001, I²=70.75% 0,1 0,2 0, b Model Study name Risk Relative ratio risk and 95% and CI 95% CI Risk Rel. Lower Upper ratio risk limit limit Steenland et al. (1995) 1,40 0,64 3,08 Will et al. (1998) 1,16 0,87 1,54 Hu et al. (1999) 1,43 1,10 1,86 Schoen et al. (1999) 1,10 0,48 2,51 Sandhu et al. (2001) 2,53 0,77 8,32 Lund Nilsen et al. (2001) 1,55 1,04 2,31 Ferrara et al. (2003) 1,80 1,28 2,53 Khaw et al. (2004) 1,71 0,23 12,68 Limburg et al. (2005) 1,40 1,09 1,79 Jee et al. (2005) 1,17 0,89 1,54 Seow et al. (2006) 1,40 1,04 1,88 Inoue et al. (2006) 1,16 0,59 2,27 Rapp et al. (2006) 0,88 0,52 1,48 Rinaldi et al. (2008) 1,40 0,87 2,25 He et al. (2010) 1,28 1,12 1,46 Chodick et al. (2010) 1,35 0,98 1,86 Flood et al. (2010) 1,49 1,08 2,06 Campbell et al (2010) 1,01 0,82 1,24 Random 1,29 1,20 1,38 Q=17.06, p=0.45, I²=0.37% 0,1 0,2 0, Fig. 3 Meta-analysis of case-control studies (a) and cohort studies (b) assessing the association between type 2 diabetes mellitus and colorectal cancer risk amongst. heterogeneity and inconsistency in case-control studies than in cohort studies. Sensitivity analysis revealed that the observed heterogeneity in men and was mainly explained by one case-control study 30 and one cohort study, 39 which found exceptionally strong associations between T2DM and CRC risk. While the exceptionally high risk estimates in the cohort study by Khan et al. 39 might have occurred by chance given the small number of CRC cases and the very wide confidence intervals, the high risk estimates in the case-control study from Iran by Safaee et al. appear to be mainly due to the exceptionally low diabetes prevalence in the control group. According to the authors, controls were randomly selected amongst the healthy participants (age > 40 years) in a health survey 30 (page 190), and their diabetes prevalence was substantially lower than estimates of the prevalence in the general population 30 (page 192). Therefore, the associations of T2DM and CRC might have been substantially overestimated in that study. To our knowledge, our meta-analysis is the first focusing on sex-specific differences in the T2DM-CRC association which has been investigated by several epidemiological studies. Our results are in accordance with a previous meta-analysis by Larsson et al. on the pre 2005 literature. 50 In contrast to Larsson et al., we explicitly excluded studies with type 1 diabetes mellitus and studies on CRC mortality, and we were able to include a number of more recently published original studies on CRC incidence. With the large number of study participants contributed by the 29 eligible studies, sex-specific estimates could now be derived with high levels of precision. Furthermore, additional sensitivity analyses were employed that underlined the robustness of the sex-specific associations. We could not employ analyses on CRC subsites (i.e. proximal/distal colon, rectum) due to a lack of a sufficient number of studies which analysed gender-specific CRC subsites differences. Therefore, we could neither confirm nor contradict the assumption of a leftward shift in gender differences, i.e. a greater decrease in incidence rates of distal colon cancer and rectal cancer for than for men. 11 Our study has several limitations. First, as in any other meta-analysis, residual confounding inherent to the original studies cannot be controlled in the meta-analysis, which have led to either over- or under-estimation of risk estimates. Nevertheless, our sensitivity analyses excluding studies that did not adjust for age, BMI and physical activity, three important potential confounders, did not materially change the results.

11 Table 3 Results of sensitivity analyses. Study type Exclusions Sex OR a or RR b (95% CI) Heterogeneity/Inconsistency Publication bias Q (p-value) I 2 Kendall s tau (p-value) Egger s t value (p-value) Case-control None (main analysis) Men 1.39 ( ) (0.07) 46.15% 0.18 (0.27) 1.19 (0.14) Women 1.57 ( ) (0.001) 70.75% 0.18 (0.27) 1.00 (0.18) Outlier c Men 1.33 ( ) 0.80 (0.99) 0% 0 (0.50) 0.85 (0.22) Women 1.36 ( ) 7.45 (0.28) 19.48% 0.09 (0.38) 0.18 (0.43) Outlier c and limited adjustment f Men 1.32 ( ) 0.61 (0.74) 0% 0 (0.50) 0.20 (0.44) Women 1.45 ( ) 2.07 (0.36) 3.3% 0 (0.50) 0.05 (0.48) Cohort None (main analysis) Men 1.24 ( ) (0.07) 35.41% 0.24 (0.09) 2.00 (0.03) Women 1.29 ( ) (0.45) 0.37% 0.09 (0.30) 0.92 (0.19) Outlier d Men 1.23 ( ) (0.13) 28.87% 0.16 (0.20) 1.53 (0.07) Women 1.29 ( ) (0.39) 5.81% 0.11 (0.27) 0.86 (0.20) Outlier d and limited adjustment f Men 1.22 ( ) (0.20) 27.69% 0.04 (0.45) 0.26 (0.40) Women 1.25 ( ) 7.64 (0.47) 0% 0.11 (0.36) 0.50 (0.32) Both None (main analysis) Men 1.29 ( ) (0.01) 42.90% 0.20 (0.08) 2.68 (0.01) Women 1.34 ( ) (0.02) 41.27% 0.12 (0.20) 1.49 (0.07) Outlier e Men 1.24 ( ) (0.31) 11.36% 0.06 (0.34) 1.75 (0.05) Women 1.30 ( ) (0.38) 5.86% 0.07 (0.32) 0.81 (0.21) Outlier e and limited adjustment f Men 1.25 ( ) (0.30) 15.69% (0.38) 0.53 (0.31) Women 1.26 ( ) (0.43) 1.77% 0.11 (0.32) 0.74 (0.24) a OR = random odds ratio. b RR = random relative risk. c Omitting Safaee et al. [27]. d Omitting Khaw et al. [36]. e Omitting Safaee et al. and Khaw et al. [27, 36]. f Restriction to studies which adjusted for age, BMI and physical activity. E U R O P E A N J O U R N A L O F CA N C E R48 (2012)

12 1280 E U RO P E A N J O U R NA L O F CA N C E R48 (2012) Table 4 Geographical differences including all studies. Study type Exclusions Sex Pooled RR a (95% CI) Heterogeneity/inconsistency Publication bias Egger s t value (p-value) Q (p-value) I 2 Kendall s tau (p-value) USA None (main analysis) Men 1.21 ( ) 4.80 (0.57) 0% 0.29 (0.18) 2.15 (0.04) Women 1.32 ( ) (0.14) 33.84% 0.22 (0.19) 1.07 (0.16) Europe (including Israel) None (main analysis) Men 1.30 ( ) (0.14) 31.58% 0.05 (0.42) 0.45 (0.33) Women 1.34 ( ) 7.33 (0.60) 0% 0.18 (0.24) 0.88 (0.20) Outlier b Men 1.29 ( ) (0.23) 22.66% (0.32) 0.18 (0.43) Women 1.34 ( ) 7.28 (0.51) 0% 0.19 (0.23) 0.82 (0.22) Asia None (main analysis) Men 1.44 ( ) (0.001) 79.18% 0.50 (0.11) 2.15 (0.06) Women 1.56 ( ) (0.001) 79.13% 0.50 (0.11) 1.22 (0.15) Outlier c Men 1.22 ( ) 4.83 (0.18) 37.94% 0.17 (0.37) 1.13 (0.19) Women 1.24 ( ) 1.02 (0.80) 0% 0.17 (0.37) 0.51 (0.33) a RR = random relative risk. b Omitting Khaw et al. [36]. Omitting Safaee et al. [27]. c Residual or unknown confounding is still possible after adjusting for most relevant confounding factors. Second, our results might be affected by some degree of misclassification of exposure in the original studies. The majority of the studies (17 out of 29) collected the information on diabetes only via responses in self-administered questionnaires without information of the age at onset of diabetes. This might be crucial since it is known that diabetes is often diagnosed by chance and diabetes patients who are not yet treated by oral medication or insulin often do not report their disease although a physician diagnosis was given. 51 Underreporting of exposure which would be expected to be non-differential with respect to CRC risk in cohort studies (and possibly also in case-control studies) might have led to underestimation of the diabetes-crc association. However, results were rather similar in additional subgroup analyses amongst studies with self-reported diabetes and studies with physician reported diabetes (data not shown). Third, as in any other meta-analysis there is the possibility of publication bias, because small studies with null results tend not to be published, as well as outcome reporting biases and language bias. In this meta-analysis, we did not find evidence of substantial publication bias. However, tests for publication bias are known to lack statistical power, and publication bias might be still a concern. Furthermore, there may be other factors influencing and confounding CRC risk since T2DM and CRC share common risk factors. The association between T2DM and CRC is strongly influenced by shared risk factors such as sex, age, overweight and lack of physical activity. The risk for CRC is generally higher in men independent of age. 52 Such sexattributable differences are not known for T2DM. However, due to the longer life expectancy of compared to men the lifetime prevalence of T2DM is higher in than in men. 53 Furthermore, there are number of explanations for gender differences in CRC mechanisms that might have a different impact on the T2DM-CRC association amongst and men. In particular, endogenous oestrogen which plays a role especially in obese postmenopausal with hormone replacement therapy has been suggested to be related to CRC risk in an independent biological pathway. 24 As far as overweight is considered, visceral body fat is of concern which was found to be associated with CRC incidence and CRC-related mortality. 54 Recently, a stronger correlation between waist circumference and glucose was found for but not for men. 55 However, it is still in question whether the T2DM-CRC association is largely due to the aforementioned risk factors or whether T2DM itself with its influence on the human metabolism increases the risk for CRC. 5. Conclusion In conclusion, despite its limitations, our review and metaanalyses provide the most comprehensive and updated summary of epidemiological evidence to date on the sex-specific association between T2DM and CRC risk. Both case-control studies and cohort studies support the hypothesis that T2DM is associated with a moderately increased risk for CRC in men and in. Estimates of relative risk were

13 E U R O P E A N J O U R N A L O F CA N C E R48 (2012) almost identical amongst men and, a finding that was very robust in a number of sensitivity analyses. Because available data on validated and verified information on T2DM either by physician diagnosis or by medical records are still sparse, further studies with carefully validated exposure definition would be desirable. Further studies should also aim for a more comprehensive consideration of covariates in order to allow far more comprehensive control for confounding and to elucidate hypothesised causal pathways. Our findings furthermore underline the importance to limit the emerging worldwide T2DM epidemic also in the context of efforts for enhanced cancer prevention and control. Conflict of interest statement The authors report no conflicts of interest. We disclose any financial and personal relationships with other people or organisations that could inappropriately influence this work. The authors alone are responsible for the content and writing of the paper. REFERENCES 1. Giovannucci E, Harlan DM, Archer MC, et al. Diabetes and cancer: a consensus report. Diabetes Care 2010;33(7): Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for Diabetes Care 2004;27(5): Wee CC, Hamel MB, Huang A, et al. Obesity and undiagnosed diabetes in the US. Diabetes Care 2008;31(9): IDF. Global Burden: Prevalence and Projections, 2010 and 2030 [updated updated /07/2010]; Available from: < International Diabetes Federation (IDF). Europe at a glance [updated /27/2011]; Available from: < Dawson SI, Willis J, Florkowski CM, Scott RS. Cause-specific mortality in insulin-treated diabetic patients: a 20-year follow-up. Diabetes Res Clin Pract 2008;80(1): Romon I, Jougla E, Balkau B, Fagot-Campagna A. The burden of diabetes-related mortality in France in 2002: an analysis using both underlying and multiple causes of death. Eur J Epidemiol 2008;23(5): Boyle P, Levin B, editors. Introduction: needs and prospects for cancer control. Lyon, France: IARC Press; Jemal A, Thomas A, Murray T, Thun M. Cancer statistics, CA Cancer Journal for Clinicians 2002;52(1): Screening for colorectal cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2008; 149(9): Gao RN, Neutel CI, Wai E. Gender differences in colorectal cancer incidence, mortality, hospitalizations and surgical procedures in Canada. J Public Health (Oxf) 2008;30(2): McKeown-Eyssen G. Epidemiology of colorectal cancer revisited: are serum triglycerides and/or plasma glucose associated with risk? Cancer Epidemiol Biomarkers Prev 1994;3(8): Giovannucci E. Insulin and colon cancer. Cancer Causes Control 1995;6(2): Vigneri P, Frasca F, Sciacca L, Pandini G, Vigneri R. Diabetes and cancer. Endocr Relat Cancer 2009;16(4): La Vecchia C, Negri E, Decarli A, Franceschi S. Diabetes mellitus and colorectal cancer risk. Cancer Epidemiol Biomarkers Prev 1997;6(12): Rapp K, Schroeder J, Klenk J, et al. Fasting blood glucose and cancer risk in a cohort of more than 140, 000 adults in Austria. Diabetologia 2006;49(5): Kuriki K, Hirose K, Tajima K. Diabetes and cancer risk for all and specific sites among Japanese men and. Eur J Cancer Prev 2007;16(1): Campbell PT, Deka A, Jacobs EJ, et al. Prospective study reveals associations between colorectal cancer and type 2 diabetes mellitus or insulin use in men. Gastroenterology 2010;139(4): Le Marchand L, Wilkens LR, Kolonel LN, Hankin JH, Lyu LC. Associations of sedentary lifestyle, obesity, smoking, alcohol use, and diabetes with the risk of colorectal cancer. Cancer Res 1997;57(21): Levi F, Pasche C, Lucchini F, La Vecchia C. Diabetes mellitus, family history, and colorectal cancer. J Epidemiol Community Health 2002;56(6): Yang YX, Hennessy S, Lewis JD. Type 2 diabetes mellitus and the risk of colorectal cancer. Clin Gastroenterol Hepatol 2005;3(6): Chodick G, Heymann AD, Rosenmann L, et al. Diabetes and risk of incident cancer: a large population-based cohort study in Israel. Cancer Causes Control 2010;21(6): He J, Stram DO, Kolonel LN, et al. The association of diabetes with colorectal cancer risk: the Multiethnic Cohort. Br J Cancer 2010;103(1): Gunter MJ, Hoover DR, Yu H, et al. Insulin, insulin-like growth factor-i, endogenous estradiol, and risk of colorectal cancer in postmenopausal. Cancer Res 2008;68(1): Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000;283(15): DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7(3): Normand SL. Meta-analysis: formulating, evaluating, combining, and reporting. Stat Med 1999;18(3): Rothstein HR, Sutton AJ, Borenstein M. Publication bias in metaanalysis: prevention, assessment and adjustments. Chichester, England: Wiley; Kune GA, Kune S, Watson LF. Colorectal cancer risk, chronic illnesses, operations, and medications: case control results from the Melbourne Colorectal Cancer Study. Cancer Res 1988;48(15): Safaee A, Fatemi R, Pourhoseingholi MA, et al. Positive association between diabetes mellitus and risk of colorectal cancer. Iranian Journal of Cancer Prevention 2009;2(4): Pelucchi C, Negri E, Talamini R, et al. Metabolic syndrome is associated with colorectal cancer in men. Eur J Cancer 2010;46(10): Steenland K, Nowlin S, Palu S. Cancer incidence in the National Health, Nutrition Survey I. Follow-up data: diabetes, cholesterol, pulse and physical activity. Cancer Epidemiol Biomarkers Prev 1995;4(8): Will JC, Galuska DA, Vinicor F, Calle EE. Colorectal cancer: another complication of diabetes mellitus? Am J Epidemiol 1998;147(9): Hu FB, Manson JE, Liu S, et al. Prospective study of adult onset diabetes mellitus (type 2) and risk of colorectal cancer in. J Natl Cancer Inst 1999;91(6): Schoen RE, Tangen CM, Kuller LH, et al. Increased blood glucose and insulin, body size, and incident colorectal cancer. J Natl Cancer Inst 1999;91(13): Sandhu MS, Luben R, Khaw KT. Self reported non-insulin dependent diabetes, family history, and risk of prevalent

14 1282 E U RO P E A N J O U R NA L O F CA N C E R48 (2012) colorectal cancer: population based, cross sectional study. J Epidemiol Community Health 2001;55(11): Lund Nilsen TI, Vatten LJ. Prospective study of colorectal cancer risk and physical activity, diabetes, blood glucose and BMI: exploring the hyperinsulinaemia hypothesis. Br J Cancer 2001;84(3): Ferrara A, Van Den Eeden SK, Karter AJ, Shan J, Hedderson MM. Women with diabetes are at increased risk of colorectal cancer and endometrial cancer. Diabetologia. [Meeting]. 2003;46:A78 (Supplement 2). 39. Khaw KT, Wareham N, Bingham S, et al. Preliminary communication: glycated hemoglobin, diabetes, and incident colorectal cancer in men and : a prospective analysis from the European prospective investigation into cancer- Norfolk study. Cancer Epidemiol Biomarkers Prev 2004;13(6): Limburg PJ, Anderson KE, Johnson TW, et al. Diabetes mellitus and subsite-specific colorectal cancer risks in the Iowa Women s Health Study. Cancer Epidemiol Biomarkers Prev 2005;14(1): Jee SH, Ohrr H, Sull JW, et al. Fasting serum glucose level and cancer risk in Korean men and. JAMA 2005;293(2): Larsson SC, Giovannucci E, Wolk A. Diabetes and colorectal cancer incidence in the cohort of Swedish men. Diabetes Care 2005;28(7): Seow A, Yuan JM, Koh WP, Lee HP, Yu MC. Diabetes mellitus and risk of colorectal cancer in the Singapore Chinese Health Study. J Natl Cancer Inst 2006;98(2): Inoue M, Iwasaki M, Otani T, et al. Diabetes mellitus and the risk of cancer - Results from a large-scale population-based cohort study in Japan. Arch Intern Med 2006;166(17): Stürmer T, Buring JE, Lee IM, Gaziano JM, Glynn RJ. Metabolic abnormalities and risk for colorectal cancer in the physicians health study. Cancer Epidemiol Biomarkers Prev 2006;15(12): Bowers K, Albanes D, Limburg P, et al. A prospective study of anthropometric and clinical measurements associated with insulin resistance syndrome and colorectal cancer in male smokers. Am J Epidemiol 2006;164(7): Rinaldi S, Rohrmann S, Jenab M, et al. Glycosylated hemoglobin and risk of colorectal cancer in men and, the European prospective investigation into cancer and nutrition. Cancer Epidemiol Biomarkers Prev 2008;17(11): Flood A, Strayer L, Schairer C, Schatzkin A. Diabetes and risk of incident colorectal cancer in a prospective cohort of. Cancer Causes Control Norris CM, Murray JW, Triplett LS, Hegadoren KM. Gender Roles in Persistent Sex Differences in Health-Related Qualityof-Life Outcomes of Patients With Coronary Artery Disease. Gender Medicine 2010;7(4): Larsson SC, Orsini N, Wolk A. Diabetes mellitus and risk of colorectal cancer: a meta-analysis. J Natl Cancer Inst 2005;97(22): Sinclair AJ, Gadsby R, Penfold S, Croxson SC, Bayer AJ. Prevalence of diabetes in care home residents. Diabetes Care 2001;24(6): Center MM, Jemal A, Smith RA, Ward E. Worldwide variations in colorectal cancer. CA Cancer J Clin 2009;59(6): Arias E. United States life tables, Natl Vital Stat Rep 2010;58(21): Larsson SC, Wolk A. Obesity and colon and rectal cancer risk: a meta-analysis of prospective studies. Am J Clin Nutr 2007;86(3): Ashbeck EL, Jacobs ET, Martinez ME, et al. Components of metabolic syndrome and metachronous colorectal neoplasia. Cancer Epidemiol Biomarkers Prev 2009;18(4):