Literature DB >> 25928706

Stomach cancer and occupational exposure to asbestos: a meta-analysis of occupational cohort studies.

L Fortunato1, L Rushton1.   

Abstract

BACKGROUND: A recent Monographs Working Group of the International Agency for Research on Cancer concluded that there is limited evidence for a causal association between exposure to asbestos and stomach cancer.
METHODS: We performed a meta-analysis to quantitatively evaluate this association. Random effects models were used to summarise the relative risks across studies. Sources of heterogeneity were explored through subgroup analyses and meta-regression.
RESULTS: We identified 40 mortality cohort studies from 37 separate papers, and cancer incidence data were extracted for 15 separate cohorts from 14 papers. The overall meta-SMR for stomach cancer for total cohort was 1.15 (95% confidence interval 1.03-1.27), with heterogeneous results across studies. Statistically significant excesses were observed in North America and Australia but not in Europe, and for generic asbestos workers and insulators. Meta-SMRs were larger for cohorts reporting a SMR for lung cancer above 2 and cohort sizes below 1000.
CONCLUSIONS: Our results support the conclusion by IARC that exposure to asbestos is associated with a moderate increased risk of stomach cancer.

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Year:  2015        PMID: 25928706      PMCID: PMC4647249          DOI: 10.1038/bjc.2014.599

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


The most recent IARC monograph on asbestos (Straif ; IARC, 2011) concluded that all forms of asbestos (chrysotile, crocidolite, amosite, tremolite, actinolite and anthophyllite) are carcinogenic to humans (Group 1). They concluded that asbestos causes mesothelioma and cancer of the lung, larynx and ovary (Group1), and note that positive associations have been observed between asbestos and cancer of the pharynx, stomach and colorectum (group 2A). However, no quantitative estimates of these associations were carried out, except for ovarian cancer (Camargo ). We conducted a meta-analysis of the results on stomach cancer of cohort studies of workers exposed to asbestos, as part of our work estimating the burden of occupational cancer in the United Kingdom (Rushton ). The present analysis was built on the US IOM report published in 2006 (IOM, 2006); we have updated their results and extended the analyses by gender and subcategory (geography, industry and type of asbestos).

Materials and methods

Literature search

A search of the literature was performed to find all published reports of asbestos-exposed cohorts according to the MOOSE guideline (Stroup ). As stomach cancer was not generally the primary disease of concern in those studies, each paper was read and those reporting mortality from or incidence of cancer of the stomach were selected. Searches of Medline and Embase were conducted for papers published worldwide in English between 1964 and 2010. Only cohorts of workers with predominant exposure to asbestos were included. For example, although workers in the rubber industry are exposed to asbestos, the causal role of this specific carcinogen cannot be established (IARC, 1998). When several publications relating to the same cohort were available, we used the most recent report. References of identified papers were examined for additional relevant publications, and a check was made with previous reviews to ensure all cohorts were identified. For each study, we extracted the following data (when the information was available): observed and expected numbers of cases due to stomach cancer and/or the SMR/SIR and its associated confidence interval (CI), the total number of cases, the lung cancer SMR/SIR, the dates when the study was carried out, inclusion and exclusion criteria, the comparison population, the percentage of men, the average duration of employment, the geographical area, the industry sector, the type of asbestos. For the studies that reported results based on latency period, latency periods were defined as the time since the first exposure or employment. We extracted both sets of results with and without latency.

Methods for quantitative syntheses

Overall pooled estimates of the SMR/SIR (meta-SMR/SIR) with associated 95% CI were obtained using random- and fixed-effects methods (Sutton ). When not provided, 95% CI of SMR/SIR were obtained via Byar's approximation (Breslow and Day, 1987). For studies in which there were zero observed cases, 1 was added to both observed and expected cases. Sensitivity analyses to this approach were undertaken in which either studies with zero observed case were excluded from the analysis or the observed number of cases was set to equal to the expected number of cases (Alder ). A test for heterogeneity between study results was performed as a χ2-test with degrees of freedom equal to the number of studies minus one and associated P-value was reported. As this test is susceptible to the number of studies included in the meta-analysis, Higgins and Thompson (2002) developed an alternative approach that quantifies the effect of heterogeneity, providing a measure of the degree of inconsistency in the studies' results. This quantity I2 describes the proportion of total variation in study estimates that is due to heterogeneity. Negative values of I2 are put equal to zero so that I2 lies between 0 and 100%. A value of 0% indicates no observed heterogeneity and larger values show increasing heterogeneity. This quantity was also reported with its associated 95% CI; a value >50% was considered to indicate substantial heterogeneity (Higgins ). The influence of individual studies on the overall meta-SMR was assessed visually via radial plots, by re-estimating the overall effect omitting each study in turn. In addition, we used common influence diagnostics to highlight outlying influential studies (Viechtbauer and Cheung, 2010). Meta-regression techniques and stratified analyses were used to explore the influence of cohort and study characteristics. Publication bias was also assessed graphically with a funnel plot and by using Egger's test (Egger ). Analyses were performed separately for men and women, and for both genders combined. We also analysed the data according to the latency, that is, the time since the first exposure: studies were categorised as to whether they had carried out a lagged analysis or not, with the definition of a lagged category being an exposure lag of at least 10 years after the first exposure/employment. Separate subgroup analyses were carried out by geography (Europe, North America and Australia, China and Russia together) and by occupation/industry. The latter contained six categories as defined in the IOM reports (IOM, 2006): insulators, generic asbestos workers (where no occupation or industry was specified), textile asbestos workers, cement asbestos workers, miners and other occupations with substantial exposure to asbestos (such as shipyard workers). We also provided a pooled estimated by type of asbestos, sample size and publication year. To analyse the dose–response effect of asbestos exposure, we used two different methods. The first one was based on the RR for the highest category of exposure, as the categories for the dose–response relationships were not comparable. In the second approach, studies were divided according to the magnitude of the lung cancer SMR (below or above 2), corresponding to low and high occupational exposure to asbestos. Lung cancer mortality/incidence was used as a substitute for the exposure measurements, because of the clear relationship between asbestos exposure and lung cancer (IARC, 2011). All the analyses described above were carried out using the Metafor package (Viechtbauer, 2010) for R software.

Results

Characteristics of the studies

The literature search identified 70 references that contained potentially relevant information for the meta-analysis. Mortality was the outcome in most of the cohort studies reviewed. Data on mortality were extracted for 40 cohorts from 37 separate papers, and data on cancer incidence were extracted for 15 separate cohorts from 14 papers. Table 1 summarises the study characteristics. Unique cohorts are numbered 1–55.
Table 1

Study characteristics–mortality and incidence studies

IDReference (related papers)OYearCountryIndustryAsbestos typeGenderEmploymentEnd of follow-upNo of subjects
1Selikoff 1979 (Selikoff et al, 1979) (Selikoff et al, 1964; Selikoff and Seidman, 1991; Selikoff et al, 1980)M1979USAInsulation workers (union)Ch, AmMenUnion before 19431976632
2Acheson 1982. I (Acheson et al, 1982)M1982UKManufacture of gas masksChWomenFrom 19391980570
3Acheson 1982.I (Acheson et al, 1982)M1982UKManufacture of gas masksCrWomenFrom 19391980757
4Acheson 1984 (Acheson et al, 1984)M1984UKManufacture of insulation boardAmMen1947–197819805969
5Olshon 1984 (Ohlson et al, 1984)M1984SwedenRailroad shopMixedMen1939–198019803442
6Peto 1985.I (Peto et al, 1985)M1985UKAsbestos textile workersCh, CrMen1916–19831983145
7Peto 1985.II (Peto et al, 1985)M1985UKAsbestos textile workersCh, CrWomen1916–19831983283
8Peto 1985.III (Peto et al, 1985)M1985UKAsbestos textile workersCh, CrMen1916–198319833211
9Gardner 1986 (Gardner et al, 1986)M1986UKasbestos cement factoryChMen and women1941–198319842167
10Seidman 1986 (Seidman et al, 1986)M1986USAInsulation workersAmMen1941–19451985820
11Amandus 1987 (Amandus and Wheeler, 1987)M1987USAVermiculite miners and millersTr-AcMenUntil 19701981575
12Enterline 1987 (Enterline et al, 1987)M1987USAAsbestos products companyCh, Cr, AmMen1941–196719801074
13Hughes 1987 (Hughes et al, 1987)M1987USAAsbestos cement factoryCh, Cr, AmMenUntil 197019826931
14Sanden 1987 (Sandén and Järvholm, 1987)I1987SwedenShipyard workersChMen1977–197919833787
15Tola 1988 (Tola et al, 1988)I1988FinlandShipyard workersMixedMen1945–196019817775
16Melkild 1989 (Melkild et al, 1989)I1989NorwayShipyard workersChMen1946–197719864778
17Raffn 1989 (Raffn et al, 1989)I1989DenmarkAsbestos cement factoryMixedMen1928–198419847996
18Neuberger 1990 (Neuberger and Kundi, 1990)M1990AustriaAsbestos cement factoryCh, CrMen and women1950–198119872816
19Botta 1991 (Botta et al, 1991)M1991ItalyAsbestos cement factoryCh, CrMen and women1950–198019863367
20Selikoff 1991 (Selikoff and Seidman, 1991) (Selikoff et al, 1964; Selikoff et al, 1979; Selikoff et al, 1980)M1991USA/CanadaInsulation workers (union)Ch, AmMenIn union 1967198717 800
21Cheng 1992 (Cheng and Kong, 1992)M1992ChinaChrysolite asbestos products workersChMen and womenPresent in 197219871172
22Sanden 1992 (Sandén et al, 1992)M1992SwedenShipyard workersChMen1977–197919873893
23Danielsen 1993 (Danielsen et al, 1993)I1993NorwayShipyard production workersChMen1940–19794571
24Kogan 1993 (Kogan et al, 1993)M1993RussiaFriction productsChMen and women19882834
25Zhu 1993 (Zhu and Wang, 1993)M1993ChinaAsbestos factoryChMen and women19865893
26Meurman 1994 (Meurman et al, 1994)I1994FinlandAsbestos minersAnMen and women1953–19671991903
27Liddell 1997 (Liddell et al, 1997) (McDonald et al, 1993; McDonald et al, 1980)M1997CanadaMiners and millersChMen19929780
28Pang 1997 (Pang et al, 1997)M1997ChinaAsbestos factoryChMen and womenUntil 19721994530
29Levin 1998 (Levin et al, 1998)M1998USAManufacture of asbestos pipe insulationAmMenAlive in 196419931121
30Battista 1999 (Battista et al, 1999)M1999ItalyRail carriage construction and repairCh, CrMen1945–19691997734
31Germani 1999 (Germani et al, 1999)M1999ItalyWomen compensated for asbestosisCh, CrWomenAlive in 19791997631
32Karjalainen 1999.I (Karjalainen et al, 1999)I1999FinlandPatients with asbestos-related pulmonaryMixedMen and women1964–199519951376
33Karjalainen 1999.II (Karjalainen et al, 1999)I1999FinlandPatients with pleural fibrosisMixedMen and women1964–199519954887
34Berry 2000 (Newhouse et al, 1985; Berry et al, 2000)M2000UKAsbestos factoryCh, Cr, AmMen and women1933–1964 1936–194219805100
35Szeszenia 2000 (Szeszenia-Dabrowska et al, 2000)M2000PolandAsbestos cement factoryCh, CrMenUntil 198019912525
36Puntoni 2001 (Puntoni et al, 2001)M2001ItalyShipyard workersMixedMen1960–198119963984
37LaProvote 2002 (de La Provôté et al, 2002)I2002FranceManufacture fireproof textiles and friction materialsMixedMen and womenUntil 197819951820
38Ulvestad 2002 (Ulvestad et al, 2002)I2002NorwayAsbestos cement factoryMixedMen1942–19761999541
39Szeszenia 2002 (Szeszenia-Dabrowska et al, 2002)M2002PolandWorkers compensated for asbestosisMixedMen1970–19971999907
40Koskinen 2003 (Koskinen et al, 2003)I2003FinlandAsbestos workers (screening campaign)MixedMen and women199224 215
41Finkelstein 2004 (Finkelstein and Verma, 2004)M2004CanadaPipe trades workers (union)MixedMenFrom 1949199925 285
42Reid 2004 (Armstrong et al, 1988; Reid et al, 2004)I2004AustraliaCrocidolite miners and millersCrMen1943–196619995685
43Smailyte 2004 (Smailyte et al, 2004)I2004LithuaniaAsbestos cement factoryChMen and womenUntil 197820001887
44Ulvestad 2004 (Ulvestad et al, 2004)I2004Norwayinsulation workers (union)Ch, AmMen1930–197519991116
45Wilczynska 2005 (Wilczynska et al, 2005) (Szeszenia-Dabrowska et al, 1991; Szeszenia-Dabrowska et al, 1988a; Szeszenia-Dabrowska et al, 1988b)M2005PolandAsbestos processing plantMixedMen and women1945–198019994187
46Hein 2007 (Hein et al, 2007) (Brown et al, 1994; Dement et al, 1994; Dement et al, 1983)M2007USAAsbestos textile workersChMen and women1940–196520013072
47Krstev 2007 (Krstev et al, 2007)M2007USAShipyard production workersMixedMen and women1950–196420014702
48Pira 2007 (Pira et al, 2005, 2007)M2007ItalyAsbestos textile workersMixedMen and women1946–198420041966
49Frost 2008 (Frost et al, 2008)M2008GBAsbestos removal workers (campaign)MixedMen and womenFrom 1971200552 387
50Musk2008 (Musk et al, 2008) (Armstrong et al, 1988; Reid et al, 2004)M2008Australiacrocidolite miners and millersCrMen1943–196620006943
51Clin 2009 (Clin et al, 2009)I2009FranceAsbestos reprocessing plant (textile, friction)MixedMen and womenBefore 197820042024
52Harding 2009 (Hutchings et al, 1995; Harding et al, 2009)M2009UKAsbestos surveyMixedMen and women 20059811
53Loomis 2009 (Loomis et al, 2009)M2009USAAsbestos textile workersChMen and women1950–197320035770
54Pira 2009 (Pira et al, 2009) (Piolatto et al, 1990; Rubino et al, 1979)M2009ItalyChrysotile asbestos minersChMen1930–197519462003
55Pesch 2010 (Pesch et al, 2010)M2010GermanyAsbestos surveyMixedMen1993–19952007576

Abbreviations: -=not applicable; Am=Amosite; An=Anthophyllite; Ch=Chrysotile; Cr=Crocidolite; I=Incidence; M=Mortality; O=Outcome.

Mortality cohort studies have been carried out mainly in Europe (23 studies, 58%) and North America (12 studies, 30%). Three mortality cohorts were Chinese, one was Russian and one was Australian. Study mortality cohorts ranged in size between 145 and 52 387 workers. Thirteen (33%) of the mortality cohorts included women, although in most women were a small proportion of the total. Four studies involved only women (Acheson ; Peto ; Germani ), and four reported results for the total cohort (Gardner ; Zhu and Wang, 1993; Frost ; Harding ). The most common occupations were insulators (20%), generic asbestos workers (20%), textile asbestos workers (15%), cement asbestos workers (13%) and miners (10%). The latency (exposure lag) ranged between 10 and 20 years. The earliest follow-up period started in 1941 and the latest ended in 2007. The average length of follow-up was 29.9 years (range=9–49). The largest overall cohort RRs were among the earliest insulation workers (Selikoff ) with a RR of 3.52 (Figure 1), and among two sets of workers in Chinese asbestos factories (Zhu and Wang, 1993; Pang ): RRs were 4.4 and 2.2, respectively. Two studies carried out in Canada (Liddell ) and the United Kingdom (Harding ), involving 183 and 322 deaths from stomach cancer, showed consistent RR estimates with narrow 95% CI (1.24 and 1.66, respectively).
Figure 1

Meta-analysis of stomach cancer mortality and incidence for total cohort, all exposure lags.

Incidence studies have been carried out in Northern Europe (11 studies, 73%), in France (2 studies), in Lithuania (1 study) and in Australia (1 study) and included fewer than 900 subjects to over 24 200. Half of the studies included women, in a small proportion of the total cohort. The largest overall cohort RR was among Danish asbestos cement workers (Raffn ) with a RR of 1.43 (95% CI 1.03–1.93). All the other studies reported RRs close to one.

Quantitative synthesis

Table 2 summarises all the meta-SMRs and meta-SIRs obtained for men and women separately, and by consideration of an exposure lag or not. The meta-SIR for stomach cancer incidence was 1.09 (95% CI 0.94–1.26; 14 studies) and 1.10 (95% CI 0.52–2.33; 6 studies) for men and women, respectively, with homogenous results (P=0.16 and 0.99, respectively).
Table 2

Pooled analysis for stomach cancer mortality and incidence by exposure lag (latency) and type of outcome using random effects model

 OutcomenaSMR95% CIτ2 bPQcI2 (%)d
Men
All exposure lagsI141.09(0.94–1.26)0.0190.1628.0
 M301.16(1.00–1.34)0.085<0.00163.5
 M+I441.13(1.02–1.26)0.057<0.00154.7
At least 10 yr exposure lagI2
 M91.16(0.79–1.69)0.213<0.00175.3
 M+I111.09(0.77–1.53)0.197<0.00171.8
No exposure lagI141.09(0.94–1.26)0.0190.1628.0
 M261.18(0.99–1.40)0.111<0.00169.6
 M+I401.14(1.01–1.28)0.069<0.00159.7
Women
All exposure lagsI61.1(0.52–2.33)00.99
 M130.93(0.67–1.30)00.900
 M+I190.96(0.71–1.30)00.99
No exposure lagI61.1(0.52–2.33)00.99
 M120.89(0.62–1.26)00.900
 M+I180.92(0.67–1.27)00.99
Total cohort
All exposure lagsI151.07(0.91–1.25)0.0220.2625.5
 M401.17(1.03–1.33)0.087<0.00169.1
 M+I551.15(1.03–1.27)0.069<0.00161.9
At least 10 yr exposure lagI0
 M101.12(0.80–1.56)0.182<0.00181.6
 M+I121.07(0.79–1.44)0.169<0.00178.5
No exposure lagI151.07(0.91–1.25)0.0220.2625.5
 M361.18(1.03–1.36)0.102<0.00172.7
 M+I511.15(1.03–1.28)0.078<0.00164.8

Abbreviations: – = not applicable; CI=confidence interval; I=incidence, M=mortality.

No results for women for at least 10 year exposure lag as only one mortality study reported a SMR.

Number of cohorts included.

Variance (amount of heterogeneity).

P-value for the heterogeneity test.

Percentage of total variability due to heterogeneity.

The pooled analysis for stomach cancer mortality yielded a meta-SMR of 1.16 (95% CI 1.00–1.34; 30 studies) for men, with large heterogeneity of results (P<0.001, I2=63.5%); a meta-SMR of 0.93 (95% CI 0.67–1.30, 13 studies) was found for women, with homogeneous results across studies (P=0.90). For the total cohort, the meta-SMR was similar to that found for men only (meta-SMR=1.17, 95% CI 1.03–1.33, 40 studies). Because mortality is a relatively accurate measure of disease incidence as stomach cancer has a low survival rate, and because of the very limited numbers of primary studies in which incidence data were reported, pooled analyses are also reported using mortality and incidence combined. In this situation, the meta-SMRs were similar to those found using only mortality data, with a slight reduction in heterogeneity (I2=54.7%). Figure 1 presents the individual study results and the overall meta-SMR for total cohort. As the meta-SMRs from studies reporting results with exposure lag did not differ substantially from the overall results, the meta-SMRs below are reported for all exposure lag group and for mortality and incidence combined, unless specified otherwise.

Between study heterogeneity and influence of individual studies

Table 2 also shows the heterogeneity (P-value) for each analysis. There was no evidence of heterogeneity in women but some in men. A few specific studies contributed to this heterogeneity, as illustrated by outlying points in the radial plot for stomach cancer for men (Figure 2): cohort 1 (Selikoff ) was conducted in the earliest period, cohort 5 (Ohlson ) was the only study to find a significant decrease in risk, cohort 28 (Pang ) was carried out in China. For the total cohort, another cohort in China, cohort 25 (Zhu and Wang, 1993) also contributed to the heterogeneity.
Figure 2

Radial plot for SMRs in a meta- analysis of stomach cancer mortality and incidence for total cohort, all exposure lags.

The covariates listed in the Methods section were explored as potential sources of heterogeneity using meta-regression methods. Table 3 gives the meta-SMR by subgroup for men and women. No significant predictor of the meta-SMR for women was found. Apart for type of asbestos and publication year, all the variables were a significant predicator for men, with some heterogeneity. The meta-SMRs for men showed elevated risks in the United States and Australia (meta-SMR=1.30, 95% CI 1.10–1.55), and China and Russia (meta-SMR=1.91, 95% CI 1.03–3.56). The pooled analysis within occupational strata demonstrated the highest meta-SMR for stomach cancer among generic asbestos workers (meta-SMR=1.41, 95% CI 1.10–1.82), followed by insulators (meta-SMR= 1.27, 95% CI 1.05–1.53). Meta-regression also showed positive associations for stomach cancer for the cohort sizes below 1000 compared with cohort size above 1000. Similar results were found for the total cohort (Supplementary Table 1).
Table 3

Stratification of cohort studies by subgroups, for men and women, mortality and incidence combined, all exposure lags (random effects model)

 Men
Women
 naSMR95% CIτ2 bPQEcPQMdnaSMR95% CIτ2 bPQEcPQMd
Geography
Europe281.03(0.91–1.16)0.042<0.001<0.001141.1(0.77–1.57)010.48
North America + Australia131.3(1.10–1.55)   20.37(0.04–3.13)   
China+Russia31.91(1.03–3.56)   30.69(0.38–1.28)   
Occupation
Cement asbestos workers61.12(0.88–1.42)0.028<0.001<0.00121.27(0.59–2.72)00.950.97
Generic asbestos workers71.41(1.10–1.82)   50.87(0.44–1.73)   
Insulators101.27(1.05–1.53)   10.63(0.03–12.89)   
Miners61.18(0.95–1.47)   10.67(0.05–9.13)   
Textile asbestos workers41.15(0.83–1.61)   31.22(0.53–2.79)   
Other occupation110.87(0.73–1.04)   70.87(0.56–1.34)   
SMR for lung cancer
⩽2251.02(0.91–1.15)0.039<0.001<0.00150.88(0.54–1.42)00.980.86
>2171.46(1.22–1.77)   131.02(0.69–1.52)   
Type of asbestos
Amosite31.25(0.64–2.44)0.058<0.0010.3200.970.95
Chrysotile111.09(0.87–1.37)   60.84(0.52–1.35)   
Crocidolite21.14(0.75–1.74)   11.14(0.42–3.06)   
Mixed271.13(0.99–1.29)   111.05(0.68–1.64)   
Sample size
<1000121.68(1.32–2.15)0.0340.001<0.001151.15(0.77–1.71)010.56
1000–150061.19(0.88–1.61)   30.79(0.38–1.62)   
>1500261.04(0.93–1.16)   10.7(0.37–1.33)   
Publication year
Before 1999261.16(1.00–1.34)0.057<0.0010.07110.94(0.63–1.40)00.980.95
After 1999181.1(0.94–1.29)   80.99(0.62–1.59)   

Abbreviations: – = not applicable; CI=confidence interval.

Number of cohorts included.

residual variance (residual amount of heterogeneity).

P-value for the residual heterogeneity test.

P-value for the test of moderators (if the SMRs are different or not within the subgroup).

Figure 3 shows, for men, the investigation of the influence of individual studies via systematic ‘leave one out' exclusion. The studies appearing to contribute to heterogeneity also influence the meta-SMR. Using the other diagnostics, only Selikoff and Ohlson were influential (Supplementary Figure 1). The meta-SMR for stomach cancer excluding these 2 studies were 1.13 (95% CI 1.05–1.22), relatively similar to the one found with all the studies for men. The exclusion of the 3 influential studies (Selikoff ; Ohlson ; Pang ) led to a meta-SMR of 1.12 (95% CI 1.04–1.20) and eliminated completely the heterogeneity (P=0.59, I2=7.3%) as well as the residual heterogeneity in the meta-regressions (P>0.44). The associations were generally attenuated (Supplementary Table 2), except for the miners (meta-SMR=1.21, 95% CI 1.07–1.36) compared with the other occupations.
Figure 3

Influence of excluding each individual cohort for men, mortality and incidence combined, all exposure lags. Meta-SMRs and associated 95% CI (random-effects model). Dotted and dash lines represent the overall meta-SMR and its 95% CI.

Dose–response associations

Estimates of cumulative or duration of exposure among asbestos-exposed workers were reported for only 11 studies (Supplementary Table 3). The pooled SMR estimate of stomach cancer for men was 1.40 (95% CI 0.81–2.40), with a large degree of heterogeneity (I2= 67.7%). Using a low/high exposure categorisation based on the lung cancer SMR, cohorts that reported a lung cancer SMR above 2.0 had higher meta-SMRs (SMR=1.46; 95% CI 1.22–1.77) compared with other cohorts (SMR=1.02; 95% CI 0.91–1.15).

Assessment of publication bias

For men and women, there was no evidence of publication bias from plots and statistical tests. However, for the total cohort, there is an evidence of publication bias (funnel plot in Supplementary Figure 2), with a suggestive lack of studies in the top right-hand corner of the plot, that is, large cohorts with large associations.

Zero cases

Four studies reported no deaths from stomach cancer for women; (Cheng and Kong, 1992; Pang ; Hein ; Krstev ); only one study with men was concerned with this issue (Levin ) Therefore, the investigation of the influence of approaches to handling zero cases was carried out only for women. Both excluding studies for which observed cases are zero and setting observed equal to expected values resulted in an increase in meta-SMRs and a slight widening of the confidence intervals compared with the default method of adding 1 to both observed and expected values. Whatever the latency, the meta-SMRs were 1.00 (95% CI 0.73–1.36) and 1.03 (95% CI 0.77–1.39) with the exclusion approach and imputation approach, respectively, compared with a meta-SMR of 0.96 (95% CI 0.71–1.30) with the default method.

Discussion

The association between asbestos and stomach cancer has been estimated in a meta-analysis of studies of workers in which a major portion of the cohort is presumed to have been exposed to asbestos. Our results demonstrated an increase in the pooled estimate in men (meta-SMR=1.13, 95% CI 1.02–1.26) for stomach cancer in relation to exposure to asbestos. Our meta-analysis provided an update of studies, compared with previous reviews and quantitative estimates and also thoroughly explored heterogeneity and publication bias. The magnitude of the association in our meta-analysis was similar to that reported in the IOM report that included 42 cohorts (meta-SMR=1.17, 95% CI 1.07–1.28). More recently, Gamble (2008) reported that point estimates for cancer of the stomach mortality tended towards 1, with an overall RR estimate of 1.01 (95% CI 0.94–1.08), results more similar to those obtained by Goodman . Our analysis addressed heterogeneity and was based on studies included in the published meta-analyses and more recent publications. The observed overall heterogeneity among studies seemed to be explained by four cohorts. The cohort by Selikoff considered an early exposure period (up to 1962). Ohlson were the only ones to find a significant decrease in risk (SMR=0.57, 95% CI 0.42–0.79). Two studies (Zhu and Wang, 1993; Pang ) were conducted in China, where asbestos production and exposure can be very high (LaDou, 2004). We carried out meta-regression to investigate the influence of several variables. Positive and statistically significant associations were observed for non-European cohorts, generic asbestos workers, cohorts reporting a SMR for lung cancer above 2, and cohort size below 1000. Our meta-analysis mainly represented studies conducted in developed geographical areas, particularly among European populations. It is possible that studies conducted in other geographic regions (e.g., developing countries) may be available through other biomedical literature databases. The meta-analysis (da Sun ) published in Chinese with an abstract in English, which searched Chinese literature as well, found a meta-SMR of 1.20 (P<0.01) among workers exposed to chrysotile alone or mixed asbestos. The stomach cancer SMR was significantly increased in the asbestos cement workers, the screening mine workers and the insulators, (1.27, 1.21 and 2.13, respectively, P<0.05). These results seem consistent with the ones we observed. Another source of publication bias can arise from the lack of publications in parts of Asia, South America and the former Soviet Union where asbestos use is increasing (LaDou, 2004). Some studies may have failed to take account of co-exposures that have been to be associated with excess risk of stomach cancer. The reported SMRs were not adjusted for known risk factors such as chronic infection with Helicobacter pylori, smoking and diet habits. Liddell , for example, report that their finding of no trend of lung cancer with exposure up to 300 mpcf.y suggests that the 21% excess was due to some other factor, probably smoking, and that the effect of smoking on stomach cancer was twice as high as the effect of >300 mpcf.y. A recent study found statistically significant increased hazard ratios for gastric cancer and several asbestos exposure variables, adjusted for age and family history of gastric cancer, although, with the exception of long duration at high exposure, these associations tended to disappear after adjusting for smoking (Offermans ). Increases in stomach cancer have also been associated with work in a variety of dusty industries and from exposure to fumes and metal particles, for example, in foundry, steel and mining work (Cocco ; Ji and Hemminki, 2006). A study in Swedish construction workers found exposure to silica exposure, but not asbestos, was significantly related to stomach cancer (Sjodhal ). However, in our meta-analysis we restricted our studies to only those where the dominant exposure was asbestos. We found a suggestive but nonsignificant association between asbestos type and the stomach cancer meta-SMR. Cohorts exposed to mixed asbestos showed larger SMRs than those exposed only to chrysotile asbestos. A meta-analysis by Li of 15 studies published before 2003 of workers exposed only to chrysotile found also a nonsignificant association (meta-SMR=1.24; 95% CI 0.95–1.62). Our risk estimate was slightly smaller as we did not include four cohorts, as they were published in Chinese. There has been a considerable controversy over the potency of asbestos fibre types with the risks of lung cancer and mesothelioma. As discussed in the review by Hodgson and Darnton (2000) some studies showed no difference in risk between these cancers and asbestos fibre types, while others have claimed a reduced potency for chrysotile, leading to a substantial heterogeneity in the findings. Our results tend to support a reduced risk for chrysotile and stomach cancer compared with the risk associated with other asbestos types. In summary our results support the conclusion by IARC that exposure to asbestos is associated with a moderate increased risk of stomach cancer. Given the large number of workers exposed to asbestos worldwide, this may contribute to a substantial burden of mortality and morbidity.
  86 in total

1.  Mortality from all cancers of asbestos factory workers in east London 1933-80.

Authors:  G Berry; M L Newhouse; J C Wagner
Journal:  Occup Environ Med       Date:  2000-11       Impact factor: 4.402

2.  Quantifying heterogeneity in a meta-analysis.

Authors:  Julian P T Higgins; Simon G Thompson
Journal:  Stat Med       Date:  2002-06-15       Impact factor: 2.373

3.  Incidence of cancer among welders and other workers in a Norwegian shipyard.

Authors:  A Melkild; S Langård; A Andersen; J N Tønnessen
Journal:  Scand J Work Environ Health       Date:  1989-12       Impact factor: 5.024

4.  Mortality experience of insulation workers in the United States and Canada, 1943--1976.

Authors:  I J Selikoff; E C Hammond; H Seidman
Journal:  Ann N Y Acad Sci       Date:  1979       Impact factor: 5.691

5.  Incidence of cancer among welders, platers, machinists, and pipe fitters in shipyards and machine shops.

Authors:  S Tola; P L Kalliomäki; E Pukkala; S Asp; M L Korkala
Journal:  Br J Ind Med       Date:  1988-04

6.  Cancer mortality in a surveillance cohort of German males formerly exposed to asbestos.

Authors:  Beate Pesch; Dirk Taeger; Georg Johnen; Isabelle M Gross; Daniel G Weber; Monika Gube; Alice Müller-Lux; Evelyn Heinze; Thorsten Wiethege; Volker Neumann; Andrea Tannapfel; Hans-Jürgen Raithel; Thomas Brüning; Thomas Kraus
Journal:  Int J Hyg Environ Health       Date:  2009-09-26       Impact factor: 5.840

7.  [Cohort studies on cancer mortality of digestive system among workers exposed to asbestos: a meta-analysis].

Authors:  Tong-da Sun; Jian-Er Chen; Xiu-Juan Zhang; Xiu-Yang Li
Journal:  Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi       Date:  2008-10

8.  Cancer morbidity in Swedish shipyard workers 1978-1983.

Authors:  A Sandén; B Järvholm
Journal:  Int Arch Occup Environ Health       Date:  1987       Impact factor: 3.015

9.  Follow-up study of chrysotile asbestos textile workers: cohort mortality and case-control analyses.

Authors:  J M Dement; D P Brown; A Okun
Journal:  Am J Ind Med       Date:  1994-10       Impact factor: 2.214

10.  Cancer mortality in a cohort of asbestos textile workers.

Authors:  E Pira; C Pelucchi; L Buffoni; A Palmas; M Turbiglio; E Negri; P G Piolatto; C La Vecchia
Journal:  Br J Cancer       Date:  2005-02-14       Impact factor: 7.640

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  12 in total

1.  Post-9/11 cancer incidence in World Trade Center-exposed New York City firefighters as compared to a pooled cohort of firefighters from San Francisco, Chicago and Philadelphia (9/11/2001-2009).

Authors:  William Moir; Rachel Zeig-Owens; Robert D Daniels; Charles B Hall; Mayris P Webber; Nadia Jaber; James H Yiin; Theresa Schwartz; Xiaoxue Liu; Madeline Vossbrinck; Kerry Kelly; David J Prezant
Journal:  Am J Ind Med       Date:  2016-09       Impact factor: 2.214

2.  Associations of BNIP3 and DAPK1 gene polymorphisms with disease susceptibility, clinicopathologic features, anxiety, and depression in gastric cancer patients.

Authors:  Xiaoqi Lou; Dingtao Hu; Zhen Li; Ying Teng; Qiuyue Lou; Shunwei Huang; Yanfeng Zou; Fang Wang
Journal:  Int J Clin Exp Pathol       Date:  2021-05-15

3.  Framework for assessment and phytoremediation of asbestos-contaminated sites.

Authors:  Cédric Gonneau; Kinsey Miller; Sanjay K Mohanty; Rengyi Xu; Wei-Ting Hwang; Jane K Willenbring; Brenda B Casper
Journal:  Environ Sci Pollut Res Int       Date:  2017-09-22       Impact factor: 4.223

4.  A Quantitative Retrospective Exposure Assessment for Former Chrysotile Asbestos Miners and Millers from Baie Verte, NL, Canada.

Authors:  Tina Giles Murphy; Stephen Bornstein; John Oudyk; Paul A Demers
Journal:  Ann Work Expo Health       Date:  2021-01-14       Impact factor: 2.179

5.  Asbestos Fiber Preparation Methods Affect Fiber Toxicity.

Authors:  Ashkan Salamatipour; Sanjay K Mohanty; Ralph A Pietrofesa; David R Vann; Melpo Christofidou-Solomidou; Jane K Willenbring
Journal:  Environ Sci Technol Lett       Date:  2016-06-14

6.  Cancer incidence in a cohort of asbestos-exposed workers undergoing health surveillance.

Authors:  Fabiano Barbiero; Tina Zanin; Federica E Pisa; Anica Casetta; Valentina Rosolen; Manuela Giangreco; Corrado Negro; Massimo Bovenzi; Fabio Barbone
Journal:  Int Arch Occup Environ Health       Date:  2018-06-05       Impact factor: 3.015

Review 7.  Occupational Exposure to Talc Increases the Risk of Lung Cancer: A Meta-Analysis of Occupational Cohort Studies.

Authors:  Che-Jui Chang; Yu-Kang Tu; Pau-Chung Chen; Hsiao-Yu Yang
Journal:  Can Respir J       Date:  2017-08-31       Impact factor: 2.409

8.  Does exposure to asbestos cause prostate cancer? A systematic literature review and meta-analysis.

Authors:  Rui Peng; Fang Fang; Zhijun Chen; Shuai Yang; Changyuan Dai; Chengyong Wang; Han Guan; Qingwen Li
Journal:  Medicine (Baltimore)       Date:  2019-01       Impact factor: 1.817

9.  Colorectal cancer and asbestos exposure-an overview.

Authors:  Qian Huang; Ya-Jia Lan
Journal:  Ind Health       Date:  2019-09-12       Impact factor: 2.179

10.  Gastric and rectal cancers in workers exposed to asbestos: a case series.

Authors:  Byeong Ju Choi; Saerom Lee; Iu Jin Lee; Soon Woo Park; Sanggil Lee
Journal:  Ann Occup Environ Med       Date:  2020-01-02
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