Document Detail

Pesticide Exposure as a Risk Factor for Myelodysplastic Syndromes: A Meta-Analysis Based on 1,942 Cases and 5,359 Controls.
Jump to Full Text
MedLine Citation:
PMID:  25335083     Owner:  NLM     Status:  Publisher    
OBJECTIVE: Pesticide exposure has been linked to increased risk of cancer at several sites, but its association with risk of myelodysplastic syndromes (MDS) is still unclear. A meta-analysis of studies published through April, 2014 was performed to investigate the association of pesticide exposure with the risk of MDS.
METHODS: Studies were identified by searching the Web of Science, Cochrane Library and PubMed databases. Summary odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated using random- or fixed-effect models.
RESULTS: This meta-analysis included 11 case-control studies, all of which demonstrated a correlation between pesticide exposure and a statistically significant increased risk of MDS (OR = 1.95, 95% CI 1.23-3.09). In subgroup analyses, patients with pesticide exposure had increased risk of developing MDS if they were living in the Europe or Asia and had refractory anemia (RA) or RA with ringed sideroblasts (RARS). Moreover, in the analysis by specific pesticides, increased risk was associated with exposure to insecticides (OR = 1.71, 95% CI 1.22-2.40) but not exposure to herbicides or fungicides.
CONCLUSION: This meta-analysis supports the hypothesis that exposure to pesticides increases the risk of developing MDS. Further prospective cohort studies are warranted to verify the association and guide clinical practice in MDS prevention.
Jie Jin; Mengxia Yu; Chao Hu; Li Ye; Lili Xie; Jin Jin; Feifei Chen; Hongyan Tong
Related Documents :
19068133 - Risk factors for developing a cutaneous injection-related infection among injection dru...
24799313 - Premenstrual spotting of two or more days is strongly associated with histologically co...
11758043 - Sex-linked carrying styles and the attribution of homosexuality.
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-10-21
Journal Detail:
Title:  PloS one     Volume:  9     ISSN:  1932-6203     ISO Abbreviation:  PLoS ONE     Publication Date:  2014  
Date Detail:
Created Date:  2014-10-21     Completed Date:  -     Revised Date:  2014-10-22    
Medline Journal Info:
Nlm Unique ID:  101285081     Medline TA:  PLoS One     Country:  -    
Other Details:
Languages:  ENG     Pagination:  e110850     Citation Subset:  -    
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Full Text
Journal Information
Journal ID (nlm-ta): PLoS One
Journal ID (iso-abbrev): PLoS ONE
Journal ID (publisher-id): plos
Journal ID (pmc): plosone
ISSN: 1932-6203
Publisher: Public Library of Science, San Francisco, USA
Article Information
Download PDF
Copyright: 2014 Jin et al
Received Day: 1 Month: 6 Year: 2014
Accepted Day: 19 Month: 9 Year: 2014
collection publication date: Year: 2014
Electronic publication date: Day: 21 Month: 10 Year: 2014
Volume: 9 Issue: 10
E-location ID: e110850
PubMed Id: 25335083
ID: 4204937
Publisher Id: PONE-D-14-24403
DOI: 10.1371/journal.pone.0110850

Pesticide Exposure as a Risk Factor for Myelodysplastic Syndromes: A Meta-Analysis Based on 1,942 Cases and 5,359 Controls Alternate Title:A Meta-Analysis of MDS
Jie Jin12
Mengxia Yu12
Chao Hu12
Li Ye12
Lili Xie12
Jin Jin12
Feifei Chen12
Hongyan Tong123*
Shawn Hayleyedit1 Role: Editor
1Department of Hematology, the First Affiliated Hospital of Zhejiang University, Hangzhou, People’s Republic of China
2Institute of Hematology, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
3Myelodysplastic syndromes diagnosis and therapy center, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
Carleton University, Canada
Correspondence: * E-mail:
[conflict] Competing Interests: The authors have declared that no competing interests exist.
Contributed by footnote: Conceived and designed the experiments: Jie Jin HT. Performed the experiments: CH MY. Analyzed the data: LY LX Jin Jin FC. Contributed reagents/materials/analysis tools: CH. Contributed to the writing of the manuscript: CH MY.
[other] ¶ These authors are joint first authors on this work


Myelodysplastic syndromes (MDS) are a heterogeneous group of stem cell malignancies, characterized by ineffective hematopoiesis, and peripheral blood cytopenias. With disease progression, the risk of transformation into acute myeloid leukemia (AML) increased [1], [2]. Despite development of new therapeutic methods in recent years, treatment of MDS is still limited and MDS remains incurable except in the case of the younger patients with good performance status, allogeneic stem cell transplantation eligibility, and adequate donor access [3]. As the whole population ages, MDS will become one of the most common myeloid malignancies. The societal impact and burden of the disease, measured in terms of the number of people affected yearly with a new diagnosis or who are living with the disease, is enormous and will continue to increase in the future. Therefore, a better comprehension of the etiology and further investigation of risk factors may significantly improve MDS prevention measures and reduce MDS incidence.

Since 1950, pesticide use has risen over 50% and pesticide toxicity has increased ten-fold [4]. Pesticide exposure is thought to increase cancer risk by promoting oxidative stress, chromosomal aberrations, cell signaling disturbances or gene mutations [5], [6], [7].

Over the past few decades, some epidemiological studies have analyzed the association between pesticide exposure and risk of MDS, but the findings are controversial. Five studies showed a positive association between incidence of MDS and pesticide exposure [8], [9], [10], [11], [12], and six studies illustrated no association [13], [14], [15], [16], [17], [18]. Hence, the present meta-analysis was undertaken to further examine the potential involvement of pesticide exposure in MDS etiology.

Materials and Methods
Literature research

A systematic literature search of the Web of Science, Cochrane Library and PubMed was executed by two independent reviewers (Chao Hu and Mengxia Yu). The following search strategy was used: (myelodysplastic syndrome OR MDS OR myelodysplastic OR myelodysplasia OR preleukemia) AND (pesticides OR herbicides OR fungicides OR insecticides). All relevant titles or abstracts were screened (see Study selection) to determine the suitability of each publication, and full-text articles were retrieved. We also checked the references from retrieved articles for additional studies not identified by database search.

Study selection

Studies included in this meta-analysis had to meet all the following criteria: (a) one of the exposures of interest was pesticide exposure; (b) one of the outcomes of interest was incidence of MDS; (c) a cohort design or case-control design; (d) providing the risk and corresponding 95% confidence intervals (CIs) or data to calculate these; (e) written in the English language. If there were multiple publications from the same study or overlapping study populations, the most recent and detailed study was eligible for inclusion in the meta-analysis.

Data extraction

Data were collected independently by two reviewers using a predefined data collection form. The following data were extracted from each study and included in the final analysis: the study name (together with the first author’s name and year of publication), country of origin, gender, age, study design, source of patients, number of cases/controls, risk factor assessment, matching covariates, and adjusted covariates. We contacted the corresponding authors of the primary studies to acquire missing or insufficient data (when necessary), used group consensus and consulted a third reviewer to resolve discrepancies, and assigned scores of <7 and ≥7 for low- and high-quality studies, respectively, on the nine-score Newcastle-Ottawa Scale (NOS) [19], [20].

Statistical analysis

To determine whether to use the fixed- or random-effects model, we measured statistical heterogeneity [21]. A fixed-effects model was used to calculate a pooled odds ratio (OR) with 95% CI when there was no heterogeneity. Otherwise, we calculated pooled ORs and confidence intervals assuming a random-effects model. The homogeneity of ORs across individual studies was quantified by the Q statistic and the I2 score. P>0.05 for the Q-test was considered as a lack of heterogeneity among the studies. The I2 values of 25%, 50%, and 75% represented mild, moderate, and severe heterogeneity, respectively [22]. Potential publication bias was assessed by using Begg’s funnel plots (rank correlation method where an asymmetrical plot suggested possible publication bias) [23] and Egger’s bias test (linear regression method where P<0.05 indicated the presence of statistically significant publication bias) [24]. Sensitivity analysis was conducted, in which the meta-analysis estimates were calculated by sequential omission of every study in turn, so as to reflect the influence of the data from individual studies on the pooled ORs and evaluate the stability of the results. Cumulative meta-analysis was also conducted by sorting the studies based on publication time. Subset analyses were performed by source of patients, disease subtype, geographic region, study quality, and type of pesticide. All of the statistical analyses were performed with STATA 11.0 (Stata Corporation, College Station, TX) using two-sided P-values, where P<0.05 was considered statistically significant.

Literature search and study characteristics

The results of our literature search strategy and study selection process were detailed in Figure 1. We identified 11 case-control studies on the association of pesticide exposure with risk of MDS published between 1990 and 2011 [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18]. A total of 1,942 MDS patients and 5,359 controls were included in the present meta-analysis. Among the 5,359 controls, 3853 persons were hospitalized patients without conditions related to hematological diseases and the remaining 1506 were recruited from healthy people. A total of 1456 participants have exposed to pesticide, of whom 323 suffered from MDS. Among the chosen studies, seven were conducted in Europe, three in United States, and one in Asia. Pesticide exposure was ascertained by interview or questionnaire or both. The study quality was graded by the Newcastle-Ottawa Quality Assessment Scale, ranged from 5 to 8 (with a mean of 6). The main characteristics of the included articles were listed in Table 1.

Risk estimation

Our analysis demonstrated a significant adverse association between pesticide exposure (exposed vs. non-exposed status) and incidence of MDS (OR = 1.95, 95%CI 1.23–3.09) (Figure 2). Due to a statistically significant heterogeneity across studies (I2 = 80.8%, P<0.001), the summary OR were estimated using the DerSimonian and Laird random effects model [25]. A Galbraith plot identified four studies as major sources of heterogeneity (Figure 3A). After excluding these four studies [8], [9], [15], [17], there was no study heterogeneity existed (P = 0.999, I2 = 0.0%) and the overall association became stronger (OR = 2.04, 95% CI 1.57–2.66).

Stratified analysis

Next, we pooled the OR estimates by patient source (population-based or hospital-based), MDS subtypes (refractory anemia (RA) and RA with ringed sideroblasts (RARS) or RA with excess blasts (RAEB) and RAEB in transformation (RAEBt)), geographic region (United States, Europe, or Asia), study quality (low or high), and type of pesticide (insecticide, herbicide or fungicide) (Table 2). When separated by patient source, the ORs (95% CI) were 2.26 (1.49–3.42) for hospital-based studies and 0.95 (0.15–6.06) for population-based studies. When stratified by MDS subtype, the associations were more positive for the RA/RARS sbutype (OR = 1.63, 95%CI 1.06–2.51) than the RAEB/RAEBt subtype (OR = 1.49, 95%CI 0.78–2.84). In the subset analyses stratified by geographic region, a statistically significant adverse effect of pesticide exposure on MDS was observed in Europe (OR = 2.13, 95%CI 1.35–3.36) and Asia (OR = 2.00, 95%CI 1.17–3.41), but not in United States (OR = 1.52, 95%CI 0.30–7.73). Furthermore, when stratified by study quality, the relationship was more significant in high quality studies (OR = 2.19, 95%CI 1.40–3.42) than in low quality studies (OR = 1.90, 95%CI 1.09–3.33). In addition, when analyzed by type of pesticide, the ORs (95% CI) for insecticides, herbicides, and fungicides were 1.71 (1.22–2.40), 1.16 (0.55–2.43) and 0.70 (0.20–3.20), respectively.

Sensitivity analysis

We also carried out sensitivity analysis by sequentially excluding one study at a time to detect the influence of a single study on the overall estimate. The results displayed that no study disproportionately affected the summary risk estimates in this meta-analysis (Figure 3B). The eleven study-specific ORs ranged from a low of 1.72 (95%CI 1.11–2.68) to 2.27 (95%CI 1.58–3.27) via the omission of the study by Pekmezovic et al. [8] and the study by Brown et al. [17], respectively.

Cumulative meta-analysis

Cumulative meta-analysis of the relationship between pesticide exposure and risk of MDS was also implemented by sorting the studies based on publication time. Figure 4 showed the results from the cumulative meta-analysis of this connection in chronologic order. The 95% CIs became increasingly narrower with each addition of more data, suggesting the precision of each estimate was progressively increasing with the addition of more cases.

Publication bias

As reflected by the funnel plot (Begg’s test, P = 0.350) and the Egger’s test (P = 0.113), there was no publication bias being discovered. The data witnessed our result was statistically robust.


The first myelodysplastic syndromes (MDS) case series was reported about 40 years ago [26]. Thus, the recognition of MDS is approximately 100 years behind the recognition of other hematologic malignancies. Similarly, the level of epidemiologic knowledge of MDS is far below that of other cancers. Therefore, further investigation of risk factors in MDS patients is needed to improve MDS prevention.

Pesticides are widely applied in agriculture all over the world. Three million cases of acute severe pesticide poisoning and over 200,000 deaths are reported annually [4]. Pesticides are thus considered a risk factor for some cancers. Moreover, two previous meta-analyses have been performed in hematological malignancies, which indicated that pesticide exposure could increase risk of non-Hodgkin lymphoma, leukemia and multiple myeloma [27], [28]. However, the result about MDS and pesticide exposure was limited. Recent epidemiological studies have examined the potential association between pesticide exposure and the risk of MDS, but none of the results has been conclusive. We attempted to clarify this possible relationship through a meta-analysis of eleven case-control studies.

To the best of our knowledge, this is the first meta-analysis assessing the relationship between pesticide exposure and MDS. Several interesting points raised by our analysis are worth discussing. Firstly, our research demonstrated a significantly positive correlation between pesticide exposure and MDS, which indicated pesticide exposure was associated with a 95% increased risk of MDS. Sensitivity analysis and cumulative analysis confirmed the robustness of our outcomes. In addition, subgroup analyses showed a stronger effect of pesticide exposure on RA/RARS than on RAEB/RAEBt (i.e., exposed MDS patients had 63% increased risk of RA/RARS and 49% increased risk of RAEB/RAEBt, respectively). Our study also illustrated that exposure to insecticides can the increase risk of MDS by 71%, while exposure to herbicides (OR = 1.16, 95%CI 0.55–2.43) and fungicides (OR = 0.70, 95%CI 0.20–3.20), respectively, add no risk. Our subset analysis according to geographical region noted higher risk of MDS in Europe (113%) than in Asia (100%) and the United States (52%).

The biological mechanism underlying the linkage of pesticide exposure to the pathogenesis of MDS remains largely unknown. However, several mechanisms are conceivable. Exposure to pesticides might cause overexpression of reactive oxygen species (ROS) sufficient to overwhelm antioxidant defense mechanisms and thereby lead to extensive DNA damage, protein damage, and hematopoietic irregularities [29]. On the other hand, pesticides might bind to and displace endogenous ligands of steroid nuclear receptors, including estrogen and androgen receptors, thus aberrantly activating receptor function and inducing changes in gene expression networks [30]. Recent in vitro mechanistic studies offer novel insight. For example, Boros and Williams reported that exposure of leukemic cell lines (K562) to increasing doses of an organophosphate pesticide (isofenphos) resulted in dose-dependent leukemic cell proliferation [31]. In addition, some previous studies demonstrating that pesticide exposure could induce chromosomal defects [32], [33], might also suggest that pesticides could increase the risk of developing MDS. Further research is warranted to elucidate the likely biological mechanisms.

As a meta-analysis of previously published observational studies, our research has some limitations that influence interpretation of the results. First, although the present results seemed to suggest the absence of publication bias, our meta-analysis was vulnerable to publication bias, because only studies published in English were included. Limited resources prevented us from including articles published in other languages and databases. Second, no prospective studies of the association between pesticide exposure and MDS risk were available, and all included studies had a retrospective case-control design. Thus, owing to the limitations of case-control design, the possibility of undetected bias could not be excluded. Third, it is known farmers in China use large amounts of pesticides and this is an ideal population to study their effect on health. However, only one study from China was included in this meta-analysis. Fourth, too few original studies have separated biocides into insecticides, herbicides or fungicides to justify concluding the potential existence of a relationship between exposure to one or several categories of biocides and MDS. Significantly increased risks were observed, with an apparently higher increase when the exposure was to insecticides.

In summary, our findings support that pesticide exposure is associated with the increased risk of MDS, and this association varies widely across disease subtype, geographic region and specific biocide category. Larger and more rigorous analytical studies will be warranted to generate more robust conclusion to guide clinical practice in MDS prevention in the future.

Supporting Information Checklist S1

PRISMA checklist.


Click here for additional data file (pone.0110850.s001.doc)

1. Kasner MT,, Luger SM, (Year: 2009) Update on the therapy for myelodysplastic syndrome. Am J Hematol84: 177–18619195035
2. Newman K,, Maness-Harris L,, El-Hemaidi I,, Akhtari M, (Year: 2012) Revisiting use of growth factors in myelodysplastic syndromes. Asian Pac J Cancer Prev13: 1081–109122799286
3. Warlick ED,, Smith BD, (Year: 2007) Myelodysplastic syndromes: review of pathophysiology and current novel treatment approaches. Curr Cancer Drug Targets7: 541–55817896920
4. Malek AM,, Barchowsky A,, Bowser R,, Youk A,, Talbott EO, (Year: 2012) Pesticide exposure as a risk factor for amyotrophic lateral sclerosis: a meta-analysis of epidemiological studies: pesticide exposure as a risk factor for ALS. Environ Res117: 112–11922819005
5. Infante-Rivard C,, Weichenthal S, (Year: 2007) Pesticides and childhood cancer: an update of Zahm and Ward's 1998 review. J Toxicol Environ Health B Crit Rev10: 81–9918074305
6. Lafiura KM,, Bielawski DM,, Posecion NC Jr,, Ostrea EM Jr,, Matherly LH,, et al. . (Year: 2007) Association between prenatal pesticide exposures and the generation of leukemia-associated T(8;21). Pediatr Blood Cancer49: 624–62817610268
7. Agopian J,, Navarro JM,, Gac AC,, Lecluse Y,, Briand M,, et al. . (Year: 2009) Agricultural pesticide exposure and the molecular connection to lymphomagenesis. J Exp Med206: 1473–148319506050
8. Pekmezovic T,, Suvajdzic Vukovic N,, Kisic D,, Grgurevic A,, Bogdanovic A,, et al. . (Year: 2006) A case-control study of myelodysplastic syndromes in Belgrade (Serbia Montenegro). Ann Hematol85: 514–51916691397
9. Strom SS,, Gu Y,, Gruschkus SK,, Pierce SA,, Estey EH, (Year: 2005) Risk factors of myelodysplastic syndromes: a case-control study. Leukemia19: 1912–191816167059
10. Nisse C,, Haguenoer JM,, Grandbastien B,, Preudhomme C,, Fontaine B,, et al. . (Year: 2001) Occupational and environmental risk factors of the myelodysplastic syndromes in the North of France. Br J Haematol112: 927–93511298587
11. Rigolin GM,, Cuneo A,, Roberti MG,, Bardi A,, Bigoni R,, et al. . (Year: 1998) Exposure to myelotoxic agents and myelodysplasia: case-control study and correlation with clinicobiological findings. Br J Haematol103: 189–1979792307
12. Ciccone G,, Mirabelli D,, Levis A,, Gavarotti P,, Rege-Cambrin G,, et al. . (Year: 1993) Myeloid leukemias and myelodysplastic syndromes: chemical exposure, histologic subtype and cytogenetics in a case-control study. Cancer Genet Cytogenet68: 135–1398353805
13. Kokouva M,, Bitsolas N,, Hadjigeorgiou GM,, Rachiotis G,, Papadoulis N,, et al. . (Year: 2011) Pesticide exposure and lymphohaematopoietic cancers: a case-control study in an agricultural region (Larissa, Thessaly, Greece). BMC Public Health11: 521205298
14. Lv L,, Lin G,, Gao X,, Wu C,, Dai J,, et al. . (Year: 2011) Case-control study of risk factors of myelodysplastic syndromes according to World Health Organization classification in a Chinese population. Am J Hematol86: 163–16921264898
15. West RR,, Stafford DA,, Farrow A,, Jacobs A, (Year: 1995) Occupational and environmental exposures and myelodysplasia: a case-control study. Leuk Res19: 127–1397869741
16. Mele A,, Szklo M,, Visani G,, Stazi MA,, Castelli G,, et al. . (Year: 1994) Hair dye use and other risk factors for leukemia and pre-leukemia: a case-control study. Italian Leukemia Study Group. Am J Epidemiol139: 609–6198172172
17. Brown LM,, Blair A,, Gibson R,, Everett GD,, Cantor KP,, et al. . (Year: 1990) Pesticide exposures and other agricultural risk factors for leukemia among men in Iowa and Minnesota. Cancer Res50: 6585–65912208120
18. Goldberg H,, Lusk E,, Moore J,, Nowell PC,, Besa EC, (Year: 1990) Survey of exposure to genotoxic agents in primary myelodysplastic syndrome: correlation with chromosome patterns and data on patients without hematological disease. Cancer Res50: 6876–68812208156
19. Xu X, Cheng Y, Li S, Zhu Y, Zheng X, et al. (2014) Dietary carrot consumption and the risk of prostate cancer. Eur J Nutr.
20. Wells G, Shea B, O'Connell D (2009) Ottawa Hospital Research Institute: The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses. Available: epidemiology/oxford.asp.
21. Hu ZH,, Lin YW,, Xu X,, Chen H,, Mao YQ,, et al. . (Year: 2013) Genetic polymorphisms of glutathione S-transferase M1 and prostate cancer risk in Asians: a meta-analysis of 18 studies. Asian Pac J Cancer Prev14: 393–39823534760
22. Castillo JJ,, Dalia S,, Shum H, (Year: 2011) Meta-analysis of the association between cigarette smoking and incidence of Hodgkin's Lymphoma. J Clin Oncol29: 3900–390621911724
23. Begg CB,, Mazumdar M, (Year: 1994) Operating characteristics of a rank correlation test for publication bias. Biometrics50: 1088–11017786990
24. Egger M,, Davey Smith G,, Schneider M,, Minder C, (Year: 1997) Bias in meta-analysis detected by a simple, graphical test. BMJ315: 629–6349310563
25. DerSimonian R,, Laird N, (Year: 1986) Meta-analysis in clinical trials. Control Clin Trials7: 177–1883802833
26. Saarni MI,, Linman JW, (Year: 1973) Preleukemia. The hematologic syndrome preceding acute leukemia. Am J Med55: 38–484515079
27. Van Maele-Fabry G,, Duhayon S,, Lison D, (Year: 2007) A systematic review of myeloid leukemias and occupational pesticide exposure. Cancer Causes Control18: 457–47817443416
28. Merhi M,, Raynal H,, Cahuzac E,, Vinson F,, Cravedi JP,, et al. . (Year: 2007) Occupational exposure to pesticides and risk of hematopoietic cancers: meta-analysis of case-control studies. Cancer Causes Control18: 1209–122617874193
29. Alavanja MC,, Ross MK,, Bonner MR, (Year: 2013) Increased cancer burden among pesticide applicators and others due to pesticide exposure. CA Cancer J Clin63: 120–14223322675
30. Schug TT,, Janesick A,, Blumberg B,, Heindel JJ, (Year: 2011) Endocrine disrupting chemicals and disease susceptibility. J Steroid Biochem Mol Biol127: 204–21521899826
31. Boros LG,, Williams RD, (Year: 2001) Isofenphos induced metabolic changes in K562 myeloid blast cells. Leuk Res25: 883–89011532522
32. Smith MT,, McHale CM,, Wiemels JL,, Zhang L,, Wiencke JK,, et al. . (Year: 2005) Molecular biomarkers for the study of childhood leukemia. Toxicol Appl Pharmacol206: 237–24515967214
33. Chiu BC,, Blair A, (Year: 2009) Pesticides, chromosomal aberrations, and non-Hodgkin's lymphoma. J Agromedicine14: 250–25519437285


[Figure ID: pone-0110850-g001]
doi: 10.1371/journal.pone.0110850.g001.
Figure 1  Process of study selection.

[Figure ID: pone-0110850-g002]
doi: 10.1371/journal.pone.0110850.g002.
Figure 2  A forest plot illustrating risk estimates from included studies on the relationship between pesticide exposure and MDS risk.

[Figure ID: pone-0110850-g003]
doi: 10.1371/journal.pone.0110850.g003.
Figure 3  Evaluating the heterogeneity and the stability of the results.

(A) Galbraith plot evaluating the heterogeneity; (B) Sensitivity analyses by sequential omission of individual studies in our study.

[Figure ID: pone-0110850-g004]
doi: 10.1371/journal.pone.0110850.g004.
Figure 4  Forest plots showing the result of the cumulative meta-analysis.

[TableWrap ID: pone-0110850-t001] doi: 10.1371/journal.pone.0110850.t001.
Table 1  Main characteristics of studies evaluating the association between pesticides exposure and MDS.
Study Country Gender Age StudyDesign Sourceof patients Numberof cases Numberof controls Risk factorAssessment StudyQuality Matching and Adjustments
Kokouva(2011)13 Greece M/F 27–73 Case-control Hospital-based 78 455 Questionnaire 5 Gender, age, smoking, family history
Lv(2011)14 China M/F 20–88 Case-control Hospital-based 403 806 Face-to-faceInterview 6 Age, sex, anti-tb drugs, D860, traditional Chinesemedicine, alcohol intake, benzene, gasoline,glues, hair dye, education, new building
Pekmezovic(2006)8 SerbiaMontenegro M/F 18–85 Case-control Hospital-based 80 160 Interview 6 Age, sex
Strom(2005)9 United States M/F 24–89 Case-control Hospital-based 354 452 Mailedquestionnaire 7 Age, sex, ethnicity, education, family history ofhematopoietic cancer, alcohol intake, benzene,solvent, gasoline
Nisse(2001)10 France M/F NR Case-control Population-based 204 204 Interview 8 Agricultural workers, textile operators, healthprofessionals, living next to an industrial plant,commercial and technical sales representatives,machine operators, oil use, smoking
Rigolin(1998)11 Italy M/F 17–85 Case-control Hospital-based 178 178 Interview andquestionnaire 5 Age, sex
West(1995)15 UK M/F ≥15 Case-control Hospital-based 400 400 Interview andquestionnaire 6 Age, sex, area of residence and hospital,year of diagnosis
Mele(1994)16 Italy M/F ≥15 Case-control Hospital-based 111 1161 Interview 6 Age, sex, education, and residenceoutside study town
Ciccone(1993)12 Italy M/F 15–74 Case-control Hospital-based andpopulation-based 19 246 Interview 5 Sex, area of residence, age
Brown(1990)17 United States M ≥30 Case-control Population-based 63 1245 Interview 6 Vital status, age, state, tobacco use, family historyof lymphopoietic cancer, high-risk occupations andhigh-risk exposure
Goldberg(1990)18 United States NR 28–88 Case-control Hospital-based 52 52 Interview 6 Age and sex

M: male; F: female; NR: not reported; tb: tuberculosis.

[TableWrap ID: pone-0110850-t002] doi: 10.1371/journal.pone.0110850.t002.
Table 2  Stratified pooled odds ratios of the relationship between pesticide exposure and risk of MDS.
Variables Number of studies Pooled OR(95%CI) Q-test for heterogeneityP value (I2 score) Egger’s testP value Begg’s testP value
Total 11 (8, 9, 10, 11, 12, 13, 14,15, 16, 17, 18) 1.95 (1.23–3.09) <0.001 (80.8%) 0.350 0.113
Source of patients
Population based 2 (10, 17) 0.95 (0.15–6.06) <0.001 (92.3%) 1.000
Hospital based 8 (8, 9, 11, 13, 14, 15, 16, 18) 2.26 (1.49–3.42) 0.001 (71.7%) 0.098 0.266
Disease subtype
RA/RARS 3 (9, 11, 18) 1.63 (1.06–2.51) 0.258 (25.6%) 0.413 0.734
RAEB/RAEBt 4 (9, 11, 14, 16) 1.49 (0.78–2.84) 0.005 (70.4%) 0.734 0.452
Geographic region
Europe 7 (8, 10, 11, 12, 13, 15, 16) 2.13 (1.35–3.36) 0.006 (66.8%) 0.133 0.057
Asia 1 (14) 2.00 (1.17–3.41)
United States 3 (9, 17, 18) 1.52 (0.30–7.73) <0.001 (93.4%) 0.407 1.000
Study quality
High 2 (10, 11) 2.19 (1.40–3.42) 0.698 (0.0%) 1.000
Low 9 (8, 9, 12, 13, 14, 15, 16, 17, 18) 1.90 (1.09–3.33) <0.001 (83.9%) 0.155 0.348
Type of pesticides
Insecticides 9 (10, 11, 12, 13, 14, 15, 16, 17, 18) 1.71 (1.22–2.40) 0.009 (60.8%) 0.147 0.348
Herbicides 4 (14, 15, 16, 17) 1.16 (0.55–2.43) 0.056 (60.3%) 0.203 0.089
Fungicides 1 (17) 0.70 (0.20–3.20)

RA: refractory anemia; RARS: RA with ringed sideroblasts; RAEB: RA with excess blasts (RAEB); RAEBt: RAEB in transformation.

Article Categories:
  • Research Article
Article Categories:
  • Medicine and Health Sciences
    • Hematology
      • Hematologic Cancers and Related Disorders
        • Myelodysplastic Syndromes

Previous Document:  Orphan G-Protein Coupled Receptor 22 (Gpr22) Regulates Cilia Length and Structure in the Zebrafish K...
Next Document:  Dietary proteins and IGF I levels in preterm infants: determinants of growth, body composition and n...