Article:Diabetes mellitus and the risk of gastric cancer: a meta-analysis of cohort studies (5546528)

From ScienceSource
Jump to: navigation, search

This page is the ScienceSource HTML version of the scholarly article described at https://www.wikidata.org/wiki/Q36348876. Its title is Diabetes mellitus and the risk of gastric cancer: a meta-analysis of cohort studies and the publication date was 2017-07-04. The initial author is Zhi-Feng Miao.

Fuller metadata can be found in the Wikidata link, which lists all authors, and may have detailed items for some or all of them. There is further information on the article in the footer below. This page is a reference version, and is protected against editing.



Converted JATS paper:

Journal Information

Title: Oncotarget

Diabetes mellitus and the risk of gastric cancer: a meta-analysis of cohort studies

  • Zhi-Feng Miao
  • Hao Xu
  • Ying-Ying Xu
  • Zhen-Ning Wang
  • Ting-Ting Zhao
  • Yong-Xi Song
  • Hui-Mian Xu

1 Department of Surgical Oncology, First Hospital of China Medical University, Shenyang, Liaoning Province, China

2 Department of Breast Surgery, First Hospital of China Medical University, Shenyang, Liaoning Province, China

Publication date (collection): 7/2017

Publication date (epub): 3/2017

Abstract

Studies examining the relationship between diabetes mellitus (DM) and the risk of gastric cancer incidence or gastric cancer mortality have produced inconsistent results. The purpose of this study was to evaluate the evidence regarding the relationship between DM and subsequent gastric cancer incidence or gastric cancer mortality risk on the basis of cohort studies. A systematic search of articles in PubMed, EmBase, the Cochrane Library, and reference lists was conducted to identify relevant literature. Twenty-two cohort studies reporting data on 8,559,861 participants were included in the study. Overall, participants with DM had little or no change in the risk of gastric cancer, or gastric cancer mortality. There was no evidence of difference in the RR for gastric cancer between men and women. Participants with DM had a non-significant trend towards an increased risk of gastric cancer mortality in men. There was no significant difference between men and women for this relationship. Finally, although subgroup analysis suggested DM was associated with a significant impact on gastric cancer incidence and gastric cancer mortality risk in several specific populations, a significance based on gender difference was not observed. In conclusion, DM might increase the risk of gastric cancer in men when the study used standard incidence/mortality ratio as effect estimate. Further, DM were associated with higher risk of gastric cancer mortality in men if the mean age at baseline less than 55.0 years, used RR or HR as effect estimate, the study adjusted smoking or not, and the study not adjusted alcohol drinking.

Paper

INTRODUCTION

Diabetes mellitus (DM) is a growing global pandemic afflicting approximately three to four percent of adults worldwide. An estimated 366 million people worldwide will development in DM by 2030 [[1][4]]. DM may predispose patients to premature illness and death due to the relevant risk of cardiovascular diseases [[5][6]]. In addition, the relationship between DM and cancer risk has been examined in numerous meta-analyses [[7][14]]. Epidemiologic studies examining the association between DM and gastric cancer risk have largely been inconclusive and provide conflicting results [[15][21]], including two meta-analyses of the relationship between DM and the risk of gastric cancer [[22][23]]. Furthermore, whether these relationships differ according to gender in specific subpopulations remains controversial.

In 2012 alone, there were approximately 952,000 gastric cancer cases and 723,000 deaths from gastric cancer worldwide, accounting for 6.8% of the total cancer cases and 8.8% of all cancer deaths [[24]]. Several meta-analyses have indicated that numerous lifestyle factors might play beneficial or harmful impacts on the risk of gastric cancer [[25][27]]. Yang et al suggested that being overweight or obese associates with an increased risk of gastric cancer and the strength of this relationship increases with increasing body mass index (BMI) [[28]]. It is also worth noting that increased BMI is associated with an increased risk of DM [[29]]. Clarifying the potential role that DM plays on the risk of gastric cancer is particularly important in the DM populations, as it has not been definitively determined. Hence, the role of DM on the risk of gastric cancer incidence or mortality still needs further evaluation and discussion. Here we attempted a large-scale examination of the available cohort studies to determine the association between DM and the incidence of gastric cancer or gastric cancer mortality. Furthermore, we also evaluated gender differences in this relationship in patients with different baseline characteristics.

RESULTS

The process of study selection is presented as a flow chart in Figure 1. A total of 2,130 articles from the initial search were identified and screened, of which 2096 were excluded due to being irrelevant, reviews, letters to the editor, having a case control design, producing no desirable outcomes, or including participants with other diseases. A total of 34 studies were reviewed in detail, and 4 without gastric cancer incidence or mortality outcomes were ruled out and another 8 studies were excluded as being different publications of the same sample of participants, thereby including main results that had already been reviewed [[30][37]]. Ultimately, 22 studies were eligible for the final pooled analysis [[15][21], [49][63]]. A manual search of the reference lists of these studies did not yield any new eligible studies. The general characteristics of the included studies are presented in Table 1.

Figure 1

Flow diagram of the literature search and trials selection process

Table 1

Baseline characteristics of studies included in the systematic review and meta-analysis

Study Place Assessment of exposure Sample size Age at baseline Gender (M/F) Percentage of overweight (%) Gastric cancer cases Death due to gastric cancer cases Effect estimate Follow-up (year) Adjusted factors NOS score
Wideroff L 1997 [[15]] Denmark Danish Cancer Registry 109581 64.0 for men and 69.0 for women 54571/55010 NA 319 NA SIR 17.0 Age, sex, calendar year 6
CPS II 2004 [[49]] USA Self administered questionnaire 1056243 57.0 467922/588321 48.9 NA 109 RR 12.5 Age, sex, race, education, family history, BMI, PA, smoking, alcohol, diet 8
NHIC 2005 [[16]] Korea Self-report and blood glucose levels 1298385 47.0 829770/468615 NA 1120 511 HR 10.0 Age, smoking, alcohol 9
JPHC 2006 [[50]] Japan Self-report 97771 51.4 for men and 51.8 for women 46548/51223 27.3 1339 NA HR 14.0 Age, study area, VD,smoking, alcohol, BMI, PA, vegetable and coffee intake 8
MHS 2010 [[51]] Israel Self-report or bloodglucose level 100595 61.6 52913/47682 79.4 307 NA HR 8.0 Age, region, SES level, use of healthcare services, BMI, and history of VD 7
Hemminki K 2010 [[17]] Sweden Medical records 125126 >39.0 NA NA 469 NA SIR 15.0 NA 5
NIH-AARP Diet and Health Study 2011 [[18]] USA Self-report 469448 62.0 280883/188565 64.6 631 NA HR 10.0 Age, sex, calories, alcohol, smoking, fruit consumption, ethnicity, education, and PA 8
Tseng CH 2011 [[52]] Taiwan Self-report 88694 >25.0 40799/47895 NA NA 1049 SMR 12.0 Age and sex 6
Verona DiabetesStudy 2003 [[53]] Italy Medical records 7148 67.0 3366/3782 70.7 NA 48 SMR 10.0 Age, smoking, BMI 7
Swerdlow AJ 2005 [[54]] UK Self-report 5066 30-49 2944/2122 NA 12 9 SIR 18.0 Age, sex, calendar year,residence 6
Kessler II 1970 [[55]] USA Blood glucose test 218313 40-59 96010/122313 NA NA 98 SMR 10.0 Age, sex 6
HIC 2009 [[56]] Scotland Self-report 28731 62.0 15227/13504 NA NA 62 RR 3.9 Deprivation decile 7
U.S. Veterans 2010 [[57]] USA Discharge diagnosis 4501578 59.1 4501578/0 5.7 7515 NA RR 10.5 Age, time, latency, race, number of visits,alcohol, obesity and COPD 8
Zendehdel K 2003 [[19]] Sweden Medical records 29187 38.7 14864/14323 NA 10 NA SIR 14.4 Excluding the 1 st -year of follow-up 7
Koskinen SV 1998 [[58]] Finland Census records 58000 30-74 24000/34000 NA NA 73 RR 5.0 Age 6
JACC 2006 [[20]] Japan Self administeredquestionnaire 56881 40-79 23378/33503 19.8 631 NA RR 18.0-20.0 Age, BMI, smoking, and drinking 8
Ragozzino M 1982 [[59]] USA Blood glucose levels 1135 61.0 602/533 NA 8 NA SIR 8.6 Age, sex 7
Adami HO 1991 [[21]] Sweden Medical records 51008 NA 23146/27862 NA 159 NA RR 5.2 Age, sex 6
Whitehall study 2004 [[60]] UK Oral glucose tolerance test 18006 51.5 18006/0 NA NA 162 HR 25.0 Age, employment, smoking, SBP, PA, disease history 7
NHIRD 2013 [[61]] Taiwan Medical records 98125 56.0 54675/43450 NA 263 NA HR 5.5 Age, sex, CGD, pneumoconiosis 8
Strong Heart Study 2015 [[62]] USA Self administeredquestionnaire 4419 55.1 1794/2625 50.9 NA 19 HR 20.0 Age, sex, center, BMI, education, drinking status and smoking 8
Xu HL 2015 [[63]] China Self administeredquestionnaire 136421 53.4 61480/74941 NA 755 NA HR 7.5 for men and 13.2 for women Age, sex, education, income, BMI, CGD, family history of stomach cancer, PA, EI, smoking, tea, alcohol, vegetable, red meat, and fruit intake 8

Abbreviations: BMI: body mass index; PA: physical activity; VD: vascular disease; EI: energy intake; CGD: chronic gastric disease; NA: not available.

Study characteristics

The 22 included studies covered a total of 8,559,861 individuals and reported 13,538 new gastric cancer cases and 2,140 deaths due to gastric cancer. The sample size for each individual study was 1,135-4,501,578 participants, while the follow-up period for participants was 3.9-25.0 years. Seven studies were conducted in Asia [[16],[20], [50][52], [61], [63]], 9 in Europe [[15], [17], [19], [21], [53], [54], [56], [58], [60]], and 6 in the USA [[18], [49], [55], [57], [59], [62]]. 4 studies used self-administered questionnaires [[20], [49], [62], [63]], 7 studies used self-reporting [[16], [18], [50][52], [54], [56]], 7 studies used medical records [[15], [17], [19], [21], [53], [58], [61]], and the remaining 4 studies used blood glucose tests [[55], [57], [59], [60]] to assess exposure. Eight studies used SIR/SMR to evaluate the relationship between DM and gastric cancer incidence or mortality [[15],[1][7], [19], [52][55], [59]], and the remaining 14 studies used OR, RR or HR to calculate this association [[16], [18], [20], [21], [49]-[51], [56]-[58], [60]-[63]]. Fourteen studies evaluated the relationship between DM and the incidence of gastric cancer [[15]-[21], [50], [51], [54], [57], [59], [61], [63]], and ten studies evaluated the relationship between DM and the risk of gastric cancer mortality [[16], [49], [52]-[56], [58], [60], [62]]. Study quality was evaluated using the NOS score (Table 1) [[39]]. Overall, 1 study had a score of 9 [[16]], 8 studies had a score of 8 [[18], [20], [49], [50], [57], [61]-[63]], 6 studies had a score of 7 [[19], [51], [53], [56], [59], [60]], 6 studies had a score of 6 [[15], [21], [52], [54], [55], [58]], and the remaining 1 study had a score of 5 [[17]].

DM and the risk of gastric cancer incidence or mortality

A total of 15 studies reported an association between DM and the incidence of gastric cancer [[15]-[21], [50], [51], [54], [56], [57], [59], [61], [63]]. The summary RR showed that participants with DM were not associated with a change in gastric cancer risk (RR: 1.10; 95%CI: 0.94-1.29; P = 0.229; Figure 2A), but substantial heterogeneity was detected (P < 0.001). Furthermore, a total of 9 studies reported an association between DM and the risk of gastric cancer mortality [[16], [49], [52]-[55], [58], [60], [62]]. There was no significant association between DM patients and participants without DM for gastric cancer mortality across all studies (RR: 1.28; 95%CI: 0.93-1.76; P = 0.123; Figure 2B). Substantial heterogeneity was observed in the magnitude of the effect across the studies (P < 0.001).

Figure 2

Association of diabetes mellitus with the risk of gastric cancer incidence (A) and mortality (B).

DM and the risk of gastric cancer incidence in men and women

There were 11 studies with data available for men [[15], [16], [18], [20], [21], [50], [51], [57], [59], [61], [63]] and 10 studies for women [[15], [16], [18], [20], [21], [50], [51], [59], [61], [63]]. The summary analysis results for men and women with or without DM showed that DM was not associated with the risk of gastric cancer incidence in men (RR: 1.00; 95%CI: 0.90-1.11; P = 0.972; Figure 3A) or in women (RR: 1.07; 95%CI: 0.93-1.22; P = 0.368; Figure 3B). Gender difference was not significantly associated with the relationship between DM and gastric cancer incidence (RRR: 0.93; 95%CI: 0.77-1.14; P = 0.495). Furthermore, we noted potential evidence of heterogeneity for gastric cancer in men (I-square: 67.0%; P = 0.001), and mild heterogeneity for gastric cancer in women (I-square: 35.1%; P = 0.127). Once sensitivity analyses were conducted for men and women, we noted that the conclusion was not affected by the systematic exclusion of any one specific study from the pool (Supplemental 2: Tables S1 and S2). However, women were found to have increased risk for gastric cancer when excluding the JACC study [[20]] (RR: 1.09; 95%CI: 0.99-1.20; P P = 0.066; I-square: 0.9%; P value for heterogeneity: 0.426), which illustrated the incidence of gastric cancer is gradually decreasing in Japan recently.

Figure 3

Association of diabetes mellitus with the risk of gastric cancer incidence in men (A) and women (B).

DM and the risk of gastric cancer mortality in men and women

The breakdown for the number of studies available for mortality associations with men and women was 6 [[16], [49], [52], [53], [58], [60]] and 5 studies [[16], [49], [52], [53], [58]], respectively. The summary analysis results for men and women with or without DM indicated that DM was not associated with the risk of gastric cancer mortality in men (RR: 1.33; 95%CI: 0.93-1.89; P = 0.114; Figure 4A) or women (RR: 1.40; 95%CI: 0.95-2.06; P = 0.085; Figure 4B). The RRR indicated that no gender difference existed for this relationship (RRR: 0.95; 95%CI: 0.56-1.61; P = 0.848). Substantial heterogeneity was detected for gastric cancer mortality in men and women (men: I-square: 96.0%, P < 0.001; women: 93.1%, P < 0.001). According to sensitivity analyses, DM was associated with an increased risk of gastric cancer mortality in men when excluding the Tseng study, the study specific reported SMR at different age stages, and the effect estimate was inconceivable higher in DM patients aged 25-64 years [[52]] (RR: 1.17; 95%CI: 1.07-1.28; P < 0.001; I-square: 1.2%; P value for heterogeneity: 0.400; Supplemental 2: Table S3), which specifically included a wide range of participants and had a mean age greater than 25.0 years. Similarly, after excluding the Tseng study [[52]], we noted participants with DM may have an increased risk of gastric cancer mortality in women (RR: 1.21; 95%CI: 1.06-1.40; P = 0.006; I-square: 0.0%; P value for heterogeneity: 0.533; Supplemental 2: Table S4).

Figure 4

Association of diabetes mellitus with the risk of gastric cancer mortality in men (A) and women (B).

Subgroup analysis

Substantial heterogeneity was detected for gastric cancer incidence and mortality in men and women. We therefore performed subgroup analyses to minimize heterogeneity and evaluate the potential role of DM on the progression of gastric cancer among the included studies. First, DM was associated with an increased risk of gastric cancer incidence in men if the study used SIR/SMR as an effect estimate index (Table 2). Second, participants with DM showed an increased risk of gastric cancer mortality if the study was conducted on women in Western countries, the study used OR, RR, or HR as an effect estimate index, and the study was not adjusted for smoking or alcohol consumption (Table 3). Third, DM significantly increased the risk of gastric cancer mortality in men if the mean age was less than 55 years, the study used OR, RR, or HR as an effect estimate index, and the study was not adjusted for alcohol consumption (Table 3). There were no gender differences for gastric cancer incidence and gastric cancer mortality in specific subsets.

Table 2

Subgroup analysis of relative risk (ratios) for gastric cancer in men and women

Subgroup Stratified analyses Sex RR and 95%CI P value I-square and P value for heterogeneity RRR and 95%CI P value for interaction test
Country Western countries Men 0.98 (0.84-1.15) 0.817 73.3% (0.005) 0.92 (0.75-1.14) 0.466
Women 1.06 (0.92-1.22) 0.400 0.0% (0.456)
Eastern countries Men 1.02 (0.86-1.20) 0.817 46.3% (0.097) 0.97 (0.72-1.32) 0.851
Women 1.05 (0.82-1.36) 0.690 55.0% (0.049)
Age at baseline ≥55 Men 1.06 (0.90-1.25) 0.481 64.4% (0.015) 0.95 (0.77-1.19) 0.679
Women 1.11 (0.96-1.28) 0.175 0.0% (0.922)
<55 Men 1.06 (0.93-1.22) 0.373 26.5% (0.257) 0.91 (0.67-1.24) 0.566
Women 1.16 (0.88-1.53) 0.306 59.0 (0.087)
Effect estimate SIR/SMR Men 1.20 (1.05-1.36) 0.007 0.0% (0.666) 1.09 (0.88-1.35) 0.420
Women 1.10 (0.93-1.30) 0.264 0.0% (0.933)
OR, RR, or HR Men 0.97 (0.87-1.09) 0.598 66.5% (0.002) 0.92 (0.74-1.16) 0.487
Women 1.05 (0.87-1.28) 0.594 49.4% (0.054)
Follow-up duration (yr) ≥15 Men 0.99 (0.61-1.61) 0.957 73.2% (0.053) 1.65 (0.38-7.21) 0.506
Women 0.60 (0.15-2.43) 0.477 82.7% (0.016)
<15 Men 0.98 (0.88-1.10) 0.756 64.0 (0.005) 0.91 (0.76-1.08) 0.273
Women 1.08 (0.95-1.24) 0.248 13.2% (0.327)
Adjusted BMI Yes Men 0.98 (0.83-1.16) 0.826 42.5% (0.138) 1.02 (0.58-1.79) 0.942
Women 0.96 (0.56-1.63) 0.870 70.3% (0.018)
No Men 1.01 (0.87-1.18) 0.889 68.5% (0.007) 0.92 (0.77-1.10) 0.359
Women 1.10 (0.99-1.21) 0.067 0.0% (0.660)
Adjusted smoking Yes Men 1.03 (0.90-1.18) 0.690 27.0 (0.241) 0.93 (0.66-1.30) 0.666
Women 1.11 (0.81-1.51) 0.509 65.4% (0.021)
No Men 1.00 (0.85-1.18) 0.995 74.5% (0.001) 0.96 (0.78-1.19) 0.713
Women 1.04 (0.91-1.18) 0.592 0.0% (0.816)
Adjusted alcohol drinking Yes Men 1.00 (0.89-1.12) 0.952 61.5% (0.024) 0.90 (0.65-1.26) 0.538
Women 1.11 (0.81-1.51) 0.509 65.4% (0.021)
No Men 1.02 (0.78-1.33) 0.879 76.5% (0.002) 0.98 (0.73-1.32) 0.898
Women 1.04 (0.91-1.18) 0.592 0.0% (0.816)
Adjusted physical activity Yes Men 0.98 (0.80-1.19) 0.802 0.0% (0.498) 0.77 (0.48-1.25) 0.291
Women 1.27 (0.82-1.97) 0.284 63.0% (0.067)
No Men 1.01 (0.89-1.14) 0.913 75.6% (<0.001) 0.97 (0.81-1.17) 0.757
Women 1.04 (0.91-1.20) 0.556 27.8% (0.216)
Table 3

Subgroup analysis of relative risk (ratios) for gastric cancer mortality in men and women

Subgroup Stratified analyses Sex RR and 95%CI P value I-square and P value for heterogeneity RRR and 95%CI P value for interaction test
Country Western countries Men 1.19 (0.99-1.43) 0.070 24.5% (0.264) 0.91 (0.70-1.18) 0.467
Women 1.31 (1.09-1.57) 0.004 0.0% (0.739)
Eastern countries Men 1.61 (0.85-3.03) 0.144 99.0% (<0.001) 1.01 (0.38-2.66) 0.980
Women 1.59 (0.77-3.31) 0.212 97.4% (<0.001)
Age at baseline ≥55 Men 1.04 (0.84-1.28) 0.737 0.0% (0.503) 0.85 (0.61-1.20) 0.359
Women 1.22 (0.93-1.59) 0.151 0.0% (0.773)
<55 Men 1.16 (1.05-1.29) 0.004 0.0% (0.834) 1.06 (0.84-1.35) 0.612
Women 1.09 (0.88-1.36) 0.438 -
Effect estimate SIR/SMR Men 1.65 (0.88-3.11) 0.120 90.2% (0.001) 0.98 (0.39-2.46) 0.959
Women 1.69 (0.86-3.32) 0.127 87.9% (0.004)
OR, RR, or HR Men 1.17 (1.04-1.33) 0.012 25.9% (0.257) 0.96 (0.79-1.17) 0.674
Women 1.22 (1.05-1.42) 0.009 6.4% (0.343)
Follow-up duration (yr) ≥15 Men 1.24 (0.67-2.29) 0.493 - - -
Women - - -
<15 Men 1.34 (0.92-1.96) 0.129 96.7% (<0.001) 0.96 (0.56-1.64) 0.874
Women 1.40 (0.95-2.06) 0.085 97.1% (<0.001)
Adjusted BMI Yes Men 1.04 (0.84-1.28) 0.737 0.0% (0.503) 0.85 (0.61-1.20) 0.359
Women 1.22 (0.93-1.59) 0.151 0.0% (0.773)
No Men 1.48 (0.96-2.28) 0.075 97.1% (<0.001) 0.97 (0.50-1.88) 0.922
Women 1.53 (0.92-2.53) 0.100 95.7% (<0.001)
Adjusted smoking Yes Men 1.14 (1.03-1.25) 0.008 0.0% (0.498) 1.00 (0.82-1.23) 1.00
Women 1.14 (0.95-1.36) 0.165 0.0% (0.494)
No Men 1.58 (1.04-2.39) 0.032 91.1% (<0.001) 0.99 (0.54-1.82) 0.968
Women 1.60 (1.02-2.50) 0.039 90.5% (<0.001)
Adjusted alcohol drinking Yes Men 1.12 (0.98-1.27) 0.095 23.9% (0.252) 0.98 (0.79-1.23) 0.875
Women 1.14 (0.95-1.36) 0.165 0.0% (0.494)
No Men 1.51 (1.04-2.21) 0.031 88.1% (<0.001) 0.94 (0.53-1.70) 0.846
Women 1.60 (1.02-2.50) 0.039 90.5% (<0.001)
Adjusted physical activity Yes Men 1.02 (0.81-1.29) 0.853 0.0% (0.506) 0.82 (0.55-1.22) 0.320
Women 1.25 (0.90-1.73) 0.181 -
No Men 1.45 (0.95-2.20) 0.085 97.1% (<0.001) 1.01 (0.55-1.86) 0.982
Women 1.44 (0.92-2.24) 0.108 94.2% (<0.001)

Publication bias

Review of the funnel plots could not rule out the potential for publication bias for gastric cancer incidence and gastric cancer mortality (Figure 5). The Egger [[47]] and Begg tests [[48]] results showed no evidence of publication bias for gastric cancer incidence (P value for Egger: 0.892; P value for Begg: 0.621) or gastric cancer mortality (P value for Egger: 0.148; P value for Begg: 0.348).

Figure 5

Funnel plots for gastric cancer incidence (A) and gastric cancer mortality (B).

DISCUSSION

Our current study was based on cohort studies and explored all possible correlations between DM and the outcomes of gastric cancer incidence and gastric cancer mortality. This large quantitative study included 8,559,861 participants from 22 cohort studies with a broad range of populations. The findings from our study indicate that DM has no overall significant impact on the risk of gastric cancer incidence and gastric cancer mortality. Subgroup analyses suggested mean age at baseline, effect estimate, adjusted smoking, alcohol drinking or not might affect the incidence of gastric cancer mortality in men, and Country, effect estimate, adjusted smoking, alcohol drinking or not were affect gastric cancer mortality in women. However, there were no gender differences between men and women for any correlations of DM and gastric cancer.

The methodological evaluation of each included study was limited by the representativeness of the exposed cohort, selection of the non-exposed cohort, ascertainment of DM, demonstration that outcomes were not present at the start of study, comparability on the basis of the design or analysis, assessment of outcome, adequate follow-up duration, and adequate follow-up rate. Our meta-analysis of cohort studies provides unclear results for the selection of the non-exposed cohort if the study reported SIR/SMR as the effect estimate, which contributed to heterogeneity in overall analysis. Therefore, the summary results might be biased due to different effect estimate indexes.

A previous meta-analysis suggested that DM patients had a similar risk of gastric cancer incidence and substantial heterogeneity was observed. Furthermore, subgroup analyses indicated DM significantly increased the risk of gastric cancer in men, whereas it had no effect in women [[23]]. However, another meta-analysis suggested that total participants with DM have an increased risk of gastric cancer, and are positively associated with gastric cancer mortality [[22]]. The inherent limitation of those previous meta-analyses is that case control studies were included and various confounding factors might be biasing the results, as several important confounders cannot be adjusted. We therefore conducted this study to evaluate the relationship between DM and the risk of gastric cancer incidence or mortality on the basis of gender.

Most of our findings were in agreement with a recently published large cohort study conducted in the UK [[54]]. This prospective study included 28,900 patients with insulin-treated diabetes and found that DM was not associated with gastric cancer incidence or mortality risk. The reason for this could be that the study design used total cancer events as primary outcomes, and the sample size might not have been sufficient to evaluate the relationship between DM and gastric cancer risk. Event rates were lower than expected, which always requires broad confidence intervals, resulting in no statistically significant difference. Chodick et al [[51]] conducted a cohort study and, after an 8 year follow-up, concluded that there was no significant increase in overall risk of gastric cancer incidence between DM and non-DM participants. Xu et al [[63]] did not find any evidence that type 2 DM was associated with an increased risk of gastric cancer either in men or in women. Our current study also indicated that DM has no significant effect on the overall risk of gastric cancer. Yet symptoms of gastric cancer can be hidden and diagnosis might come late in DM patients with gastric cancer, which could incorrectly lend toward this conclusion of non-significant correlations.

There was no significant difference between DM and non-DM participants and the risk of gastric cancer incidence or mortality. However, several studies included in our study reported inconsistent results. Jee et al [[16]] indicated that elevated fasting serum glucose and DM are independent risk factors for gastric cancer, and the relative risk tends to increase accompanying an increased fasting serum glucose level. Similarly, Lin et al [[18]] found a significant association between DM and the higher risk of gastric cancer. They explained this relationship saying that DM patients with hyperglycemia may cause dysregulation of energy balance, which could affect intracellular metabolism and impair immune system and might play an important role in the progression of gastric cancer [[64]]. Conversely, a significantly reduced risk for gastric cancer following DM was detected in Khan et al and Adami et al [[20], [21]]. These could be due to time effects in certain cases, with an early decrease followed by an increased risk.

Subgroup analysis suggested that males with DM were associated with an increased risk of gastric cancer if the study used SIR/SMR as an effect estimate index. Furthermore, participants with DM might have an increased risk of gastric cancer mortality in multiple subsets. It is possible that longer diabetes duration could be associated with insulin resistance and hyperinsulinemia, which might has an effect on promoting cell growth and proliferation. Although an important population-based study compared the incidence of gastric cancer in insulin users and nonusers and showed a lack of association between insulin use and gastric cancer, which might due to DM patients received insulin or not with different DM status [[65]]. Furthermore, most confounders cannot be adjusted in several studies, which might bias the summary result. Finally, several conclusions may be variable since smaller cohorts were included. Therefore, relative results with a comprehensive review were provided in our study.

We noted higher heterogeneity for the summary results, the reason for this could be the baseline characteristics might affect the relationship between DM and gastric cancer incidence or mortality. Tseng et al indicated hyperglycemia, Helicobacter pylori (HP) infection, high salt intake, medications and comorbidities might play an important role on the risk of gastric cancer. They stated DM patients was associated with higher infection rate, lower eradication rate and higher reinfection rate of HP. Further, salt intake might affect HP infection [[66]]. However, salt intake and HP infection status were not reported in the studies included in our meta-analysis. In addition, patients in different ethnicities and geographical regions with different levels of salt intake and HP infection, which may affect the relationship between DM and gastric cancer and contribute to the potential heterogeneity. Furthermore, Tseng et al resulted DM patients received metformin might affect the incidence of gastric cancer [[67]]. Finally, they indicated DM was contributed a harmful effect on gastric cancer, whereas insulin use has no significant effect on the gastric cancer risk [[65]]. In this study, mostly studies included could not adjusted antidiabetic drugs, which may introduce potential heterogeneity.

Three strengths of our study should be highlighted. First, only cohort studies were included, which should eliminate uncontrolled biases. Second, the large sample size allowed us to quantitatively assess the association of DM with the risk of gastric cancer and mortality, potentially making our findings more robust than those of any individual study. Third, the summary RRR was employed to evaluate gender differences for this relationship.

The limitations of our study are as follows: (1) the adjusted models are different across the included studies, and these factors might play an important role in the development of gastric cancer; (2) the incidence of gastric cancer and mortality was difference, which might introduce uncontrol biases; (3) postmenopausal status in women might affect the incidence of gastric cancer or mortality, whereas the results of stratified analysis in individual study was not available; (4) in a meta-analysis of published studies, publication bias is an inevitable problem; and (5) the analysis used pooled data (individual data were not available), which restricted us from performing a more detailed relevant analysis and obtaining more comprehensive results.

The findings of this study suggest that DM is not associated with overall changes in gastric cancer or mortality risk. Furthermore, subgroup analyses suggested that certain participants (mean age at baseline less than 55.0, used RR or HR as effect estimate, the study adjusted smoking or not, and the study not adjusted alcohol drinking in men, and the study conducted in Western Countries, used RR or HR as effect estimate, not adjusted smoking or alcohol drinking in women.) with DM may see a higher risk of gastric cancer mortality. Future studies are needed to focus on specific populations and evaluate potential interactions of other important confounders.

MATERIALS AND METHODS

We followed Preferred Reporting Items for Systematic reviews and Meta-analysis guideline in reporting this systematic review and meta-analysis [[38]].

Data Sources, Search Strategy, and Selection Criteria

Literature research was carried out by searching relevant publications via the electronic databases PubMed, EmBase and the Cochrane Library. Any cohort study that examined the relationship between DM and the risk of gastric cancer incidence or mortality was eligible for inclusion in our study, and no restrictions were placed on language or publication status (published, in press, or in progress). The following search terms (“gastric” OR “stomach”) AND (“carcinoma” OR “cancer” OR “neoplasm” OR “adenocarcinoma”) AND (“diabetes” OR “diabetes mellitus”) were searched (from inception to June 2016). The details of the search strategy are listed in Supplemental 1. Manual searches of the reference lists from all the relevant studies and review articles were conducted as well. The medical subject heading, methods, population status, design, exposure, and outcome variables of these articles were used to identify the relevant studies.

The literature search was independently undertaken by 2 authors using a standardized approach. Any inconsistencies between these 2 authors were settled by the primary author until a consensus was reached. The criteria for eligibility of the studies were as follows: (1) the study had to have a cohort design (prospective or retrospective); (2) the study investigated the association between DM and the risk of gastric cancer incidence or mortality; and (3) the study should report effect estimates (risk ratio [RR], hazard ratio [HR], standard incidence/mortality ratio [SIR/SMR]) and 95% confidence intervals (CIs) for comparisons of participants with DM and those without DM. We used the following exclusion criteria: (1) the type of study was non-cohort design; (2) the studies evaluated other factors such that the relationship between DM and gastric cancer was not available; and (3) the publications were duplicated studies, abstracts, reviews, or the reported data from an abstract or from a meeting.

Data collection and quality assessment

Studies were reviewed and data extracted independently by two authors using a pre-designed standard form. The following data were extracted from each study: the study group or first author's name, publication year, country, assessment of exposure, sample size, age at baseline, gender, percentage of participants overweight, gastric cancer cases, gastric cancer mortality cases, effect estimate, follow-up duration, and adjusted factors. For studies that reported several multivariable adjusted RRs, we selected the effect estimate that was maximally adjusted for potential confounders. Attempts were made to contact the authors for missing data.

The Newcastle-Ottawa Scale (NOS), which is quite comprehensive and has been partially validated for evaluating the quality of observational studies in meta-analysis, was used to evaluate methodological quality [[39]]. The NOS is based on the following 3 subscales: selection (4 items), comparability (1 item), and outcome (3 items). A “star system” (range, 0-9) has been developed for assessment (Table 1). The data extraction and quality assessment were conducted independently by 2 authors. Information was examined and adjudicated independently by an additional author referring to the original studies.

Statistical analysis

We examined the relationship between DM and risk of gastric cancer incidence or mortality on the basis of the effect estimate (RR, HR, SIR/SMR) and its 95% CI published in each study. If more than one, subsets were pooled by using a fixed effect model to calculate their RRs and 95%CIs for effect estimates of each study [[40]]. We used the random-effects model to calculate summary RRs and 95%CIs for participants with DM versus participants without DM [[41]]. We probed the association between DM and gastric cancer in men and women separately. Finally, the ratios of relative risk (RRRs) and the corresponding 95%CIs were used to calculate gender difference for the relationship between DM and gastric cancer incidence or mortality [[42]].

Heterogeneity between studies was investigated by using I-square and Q statistic, and were regarded as significant heterogeneity if the P value was less than 0.10 [[43], [44]]. Sensitivity analyses were also conducted to evaluate the impact of individual studies by systematically removing each individual study from the meta-analysis [[45]]. Subgroup analyses were conducted for gastric cancer incidence and mortality in men and women on the basis of country, age at baseline, effect estimate, follow-up duration, adjusted BMI, smoking, alcohol consumption, and physical activity or lack thereof. Interaction tests for differences between men and women in subsets were also calculated [[46]]. Several methods were employed to check for potential publication bias, including visual inspections of funnel plots for gastric cancer incidence and gastric cancer mortality and the Egger [[47]] and Begg [[48]] tests. All reported P values are 2-sided, and P values less than 0.05 were regarded as statistically significant. Statistical analyses were performed using STATA software (version 12.0; Stata Corporation, College Station, TX, USA).

SUPPLEMENTARY MATERIALS TABLES

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 81272718, 81302125 and 81372550). The sponsors played no role in the study design, data collection, or analysis, or decision to submit the article for publication.

References

  1. S WildG RoglicA GreenR SicreeH KingGlobal prevalence of diabetes: estimates for the year 2000 and projections for 2030Diabetes Care20042710475315111519
  2. Centers for Disease Control and Prevention2011National Diabetes Fact Sheet: National Estimates and General Information on Diabetes and Pre-diabetes in the United StatesAtlantaU.S. Department of Health and Human Services, Centers for Disease Control and Prevention2011
  3. International Diabetes FederationDiabetes atlasInternational Diabetes Federation2013
  4. SC PalmerD MavridisE NavareseJC CraigM TonelliG SalantiN WiebeM RuospoDC WheelerGF StrippoliComparative efficacy and safety of blood pressure-lowering agents in adults with diabetes and kidney disease: a network meta-analysisLancet201538520475626009228
  5. T MazzoneIntensive glucose lowering and cardiovascular disease prevention in diabetes: reconciling the recent clinical trial dataCirculation201012222011121098460
  6. N SarwarP GaoSR SeshasaiR GobinS KaptogeE Di AngelantonioE IngelssonDA LawlorE SelvinM StampferCD StehouwerS LewingtonL PennellsEmerging Risk Factors CollaborationDiabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studiesLancet201037522152220609967
  7. S SongB WangX ZhangL HaoX HuZ LiS SunLong-Term Diabetes Mellitus Is Associated with an Increased Risk of Pancreatic Cancer: A Meta-AnalysisPLoS One201510e013432126222906
  8. L ChenH LiL GuX MaX LiY GaoY ZhangD ShenY FanB WangX BaoX ZhangThe Impact of Diabetes Mellitus on Renal Cell Carcinoma Prognosis: A Meta-Analysis of Cohort StudiesMedicine (Baltimore)201594e105526131819
  9. SY GurayaAssociation of type 2 diabetes mellitus and the risk of colorectal cancer: A meta-analysis and systematic reviewWorld J Gastroenterol20152160263126019469
  10. Y ZhouX ZhangC GuJ XiaDiabetes mellitus is associated with breast cancer: systematic review, meta-analysis, and in silico reproductionPanminerva Med2015571010825971328
  11. Y GongB WeiL YuW PanType 2 diabetes mellitus and risk of oral cancer and precancerous lesions: a meta-analysis of observational studiesOral Oncol2015513324025650271
  12. KK TsilidisJC KasimisDS LopezEE NtzaniJP IoannidisType 2 diabetes and cancer: umbrella review of meta-analyses of observational studiesBMJ2015350g760725555821
  13. P Jian GangL MoY LuL RunqiZ XingDiabetes mellitus and the risk of prostate cancer: an update and cumulative meta-analysisEndocr Res201540546125105463
  14. C LiaoD ZhangC MungoDA TompkinsAM ZeidanIs diabetes mellitus associated with increased incidence and disease-specific mortality in endometrial cancer? A systematic review and meta-analysis of cohort studiesGynecol Oncol20141351637125072931
  15. L WideroffG GridleyL MellemkjaerWH ChowM LinetS KeehnK Borch-JohnsenJH OlsenCancer incidence in a population-based cohort of patients hospitalized with diabetes mellitus in DenmarkJ Natl Cancer Inst1997891360659308706
  16. SH JeeH OhrrJW SullJE YunM JiJM SametFasting serum glucose level and cancer risk in Korean men and womenJAMA200529319420215644546
  17. K HemminkiX LiJ SundquistK SundquistRisk of cancer following hospitalization for type 2 diabetesOncologist2010155485520479278
  18. SW LinND FreedmanAR HollenbeckA SchatzkinCC AbnetProspective study of self-reported diabetes and risk of upper gastrointestinal cancersCancer Epidemiol Biomarkers Prev2011209546121415356
  19. K ZendehdelO NyrénCG OstensonHO AdamiA EkbomW YeCancer incidence in patients with type 1 diabetes mellitus: a population-based cohort study in SwedenJ Natl Cancer Inst200395179780014652242
  20. M KhanM MoriY FujinoA ShibataF SakauchiM WashioA TamakoshiJapan Collaborative Cohort Study GroupSite-specific cancer risk due to diabetes mellitus history: evidence from the Japan Collaborative Cohort (JACC) StudyAsian Pac J Cancer Prev200672535916839219
  21. HO AdamiJ McLaughlinA EkbomC BerneD SilvermanD HackerI PerssonCancer risk in patients with diabetes mellitusCancer Causes Control19912307141932543
  22. T TianLQ ZhangXH MaJN ZhouJ ShenDiabetes mellitus and incidence and mortality of gastric cancer: a meta-analysisExp Clin Endocrinol Diabetes20121202172322187293
  23. Z GeQ BenJ QianY WangY LiDiabetes mellitus and risk of gastric cancer: a systematic review and meta-analysis of observational studiesEur J Gastroenterol Hepatol20112311273521934509
  24. J FerlayI SoerjomataramR DikshitS EserC MathersM RebeloDM ParkinD FormanF BrayCancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012Int J Cancer2015136E35986
  25. L LiY GanC WuX QuG SunZ LuCoffee consumption and the risk of gastric cancer: a meta-analysis of prospective cohort studiesBMC Cancer20151573326481317
  26. J HanY JiangX LiuQ MengQ XiQ ZhuangY HanY GaoQ DingG WuDietary Fat Intake and Risk of Gastric Cancer: A Meta-Analysis of Observational StudiesPLoS One201510e013858026402223
  27. Y GuoZ ShanH RenW ChenDairy consumption and gastric cancer risk: a meta-analysis of epidemiological studiesNutr Cancer2015675556825923921
  28. P YangY ZhouB ChenHW WanGQ JiaHL BaiXT WuOverweight, obesity and gastric cancer risk: results from a meta-analysis of cohort studiesEur J Cancer20094528677319427197
  29. National Task Force on the Prevention and Treatment of ObesityOverweight, obesity, and health riskArch Intern Med200016089890410761953
  30. JM YoonKY SonCS EomD DurranceSM ParkPre-existing diabetes mellitus increases the risk of gastric cancer: a meta-analysisWorld J Gastroenterol2013199364523429469
  31. A HidakaS SasazukiA GotoN SawadaT ShimazuT YamajiM IwasakiM InoueM NodaH TajiriS TsuganeJPHC Study GroupPlasma insulin, C-peptide and blood glucose and the risk of gastric cancer: the Japan Public Health Center-based prospective studyInt J Cancer201513614021025066446
  32. A TamakoshiK OzasaY FujinoK SuzukiK SakataM MoriS KikuchiH IsoF SakauchiY MotohashiI TsujiY NakamuraH MikamiJACC Study GroupCohort profile of the Japan Collaborative Cohort Study at final follow-upJ Epidemiol2013232273223583921
  33. TM PhamY FujinoK NakachiK SuzukiY ItoY WatanabeY InabaK TajimaA TamakoshiT YoshimuraJACC Study GroupRelationship between serum levels of superoxide dismutase activity and subsequent risk of cancer mortality: findings from a nested case-control study within the Japan Collaborative Cohort StudyAsian Pac J Cancer Prev200910Suppl697320553085
  34. TM PhamY FujinoK NakachiK SuzukiY ItoY WatanabeY InabaK TajimaA TamakoshiT YoshimuraJACC Study GroupRelationship between serum levels of insulin-like growth factors and subsequent risk of cancer mortality: findings from a nested case-control study within the Japan Collaborative Cohort StudyCancer Epidemiol2010342798420427254
  35. TM PhamY FujinoS KikuchiA TamakoshiS MatsudaT YoshimuraDietary patterns and risk of stomach cancer mortality: the Japan collaborative cohort studyAnn Epidemiol2010203566320382336
  36. JL DixonLA CopelandJE ZeberAA MacCarthySI ReznikWR SmythePA RascoeAssociation between diabetes and esophageal cancer, independent of obesity, in the United States Veterans Affairs populationDis Esophagus2016297475126455587
  37. MC CamargoND FreedmanAR HollenbeckCC AbnetCS RabkinHeight, weight, and body mass index associations with gastric cancer subsitesGastric Cancer2014174636824174008
  38. D MoherA LiberatiJ TetzlaffDG AltmanPRISMA GroupPreferred reporting items for systematic reviews and meta-analyses: the PRISMA statementPLoS Med20096e100009719621072
  39. G WellsB SheaD O’ConnellThe Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analysesOttawa (ON)Ottawa Hospital Research Institute2009Available: http://www.ohri.ca/programs/clinical_epidemiology/oxford.htm
  40. R DerSimonianN LairdMeta-analysis in clinical trialsControl Clin Trials19867177883802833
  41. AE AdesG LuJP HigginsThe interpretation of random-effects meta-analysis in decision modelsMed Decis Making2005256465416282215
  42. RR HuxleyM WoodwardCigarette smoking as a risk factor for coronary heart disease in women compared with men: a systematic review and meta-analysis of prospective cohort studiesLancet2011378129730521839503
  43. JJ DeeksJP HigginsDG AltmanAnalysing Data and Undertaking Meta-AnalysesCochrane Handbook for Systematic Reviews of Interventions2008Chapter 9
  44. JP HigginsSG ThompsonJJ DeeksDG AltmanMeasuring inconsistency in meta-analysesBMJ20033275576012958120
  45. A TobiasAssessing the influence of a single study in meta-analysisStata Tech Bull1999471517
  46. DG AltmanJM BlandInteraction revisited: the difference between two estimatesBMJ200332621912543843
  47. M EggerG Davey SmithM SchneiderC MinderBias in meta-analysis detected by a simple, graphical testBMJ1997315629349310563
  48. CB BeggM MazumdarOperating characteristics of a rank correlation test for publication biasBiometrics19945010881017786990
  49. SS CoughlinEE CalleLR TerasJ PetrelliMJ ThunDiabetes mellitus as a predictor of cancer mortality in a large cohort of US adultsAm J Epidemiol200415911606715191933
  50. M InoueM IwasakiT OtaniS SasazukiM NodaS TsuganeDiabetes mellitus and the risk of cancer: results from a large-scale population-based cohort study in JapanArch Intern Med200616618717717000944
  51. G ChodickAD HeymannL RosenmannMS GreenS FlashA PorathE KokiaV ShalevDiabetes and risk of incident cancer: a large population-based cohort study in IsraelCancer Causes Control2010218798720148361
  52. CH TsengDiabetes conveys a higher risk of gastric cancer mortality despite an age-standardised decreasing trend in the general population in TaiwanGut201160774e77921193459
  53. G VerlatoG ZoppiniE BonoraM MuggeoMortality from site-specific malignancies in type 2 diabetic patients from VeronaDiabetes Care20032610475112663571
  54. AJ SwerdlowSP LaingZ QiaoSD SlaterAC BurdenJL BothaNR WaughAD MorrisW GatlingEA GaleCC PattersonH KeenCancer incidence and mortality in patients with insulin-treated diabetes: a UK cohort studyBr J Cancer20059220707515886700
  55. II KesslerCancer mortality among diabeticsJ Natl Cancer Inst1970446738611515436
  56. AA OgunleyeSA OgstonAD MorrisJM EvansA cohort study of the risk of cancer associated with type 2 diabetesBr J Cancer2009101119920119690547
  57. EA AtchisonG GridleyJD CarreonMF LeitzmannKA McGlynnRisk of cancer in a large cohort of U.S. veterans with diabetesInt J Cancer20111286354320473855
  58. SV KoskinenAR ReunanenTP MartelinT ValkonenMortality in a large population-based cohort of patients with drug-treated diabetes mellitusAm J Public Health199888765709585742
  59. M RagozzinoLJ Melton 3rdCP ChuPJ PalumboSubsequent cancer risk in the incidence cohort of Rochester, Minnesota, residents with diabetes mellitusJ Chronic Dis19823513197068798
  60. GD BattyMJ ShipleyM MarmotGD SmithDiabetes status and post-load plasma glucose concentration in relation to site-specific cancer mortality: findings from the original Whitehall studyCancer Causes Control2004158738115577289
  61. YL ChenKC ChengSW LaiIJ TsaiCC LinFC SungCC LinPC ChenDiabetes and risk of subsequent gastric cancer: a population-based cohort study in TaiwanGastric Cancer2013163899623053824
  62. LG BestE García-EsquinasJL YehF YehY ZhangET LeeBV HowardJH FarleyTK WeltyDA RhoadesER RhoadesJG UmansA Navas-AcienAssociation of diabetes and cancer mortality in American Indians: the Strong Heart StudyCancer Causes Control20152615516026250516
  63. HL XuYT TanM EppleinHL LiJ GaoYT GaoW ZhengXO ShuYB XiangPopulation-based cohort studies of type 2 diabetes and stomach cancer risk in Chinese men and womenCancer Sci20151062949825557005
  64. P VigneriF FrascaL SciaccaG PandiniR VigneriDiabetes and cancerEndocr Relat Cancer20091611032319620249
  65. CH TsengDiabetes, insulin use, and gastric cancer: a population-based analysis of the TaiwaneseJ Clin Gastroenterol201347e606423269314
  66. CH TsengFH TsengDiabetes and gastric cancer: the potential linksWorld J Gastroenterol20142017011124587649
  67. CH TsengMetformin reduces gastric cancer risk in patients with type 2 diabetes mellitusAging (Albany NY)2016816364910.18632/aging.10101927587088
The underlying source XML for this text is taken from https://www.ebi.ac.uk/europepmc/webservices/rest/PMC5546528/fullTextXML. The license for the article is Creative Commons Attribution 3.0 Unported. The main subject has been identified as complications of diabetes mellitus.