染发与癌症

Case–control study of risk factors of myelodysplastic syndromes according to World Health Organization classification in a Chinese population Ling Lv,1 Guowei Lin,2 Xiang Gao,1 Cuie Wu,3 Junmin Dai,3 Yongchen Yang,4 Hejian Zou,1 Hengjuan Sun,4 Minghua Gu,1 Xi Chen,5 Hua Fu,3 and Liming Bao4,6 Risk factors of mydelodysplastic syndromes (MDS) remain largely unknown. We conducted a hospital-based case–control study consisting of 403 newly diagnosed MDS patients according to World Health Organization classification and 806 individually gender and age-matched patient controls from 27 major hospitals in Shanghai, China, to examine relation of lifestyle, environmental, and occupational factors to risk of MDS. The study showed that all MDS (all subtypes combined) risk factors included anti tuberculosis drugs [odds ratio (OR)adj 5 3.15; 95% confidence interval (CI) 5 1.22–8.12] as an independent risk factor, benzene (ORadj 5 3.73; 95% CI 5 1.32–10.51), hair dye use (OR 5 1.46; 95% CI 5 1.03–2.07), new building and renovations (OR 5 1.69; 95% CI 5 1.11–2.00), pesticides (OR 5 2.16; 95% CI 5 1.22–3.82), and herbicides (OR 5 5.33; 95% CI 5 1.41– 20.10) as relative risk factors. Risk factors of MDS subtype refractory cytopenia with multiple dysplasia (RCMD) were benzene (ORadj 5 5.99; 95% CI 5 1.19–30.16) and gasoline (ORadj 5 11.44; 95% CI 5 1.31–100.03) as independent risk factors, and traditional Chinese medicines (OR 5 2.17; 95% CI 5 1.15–4.07), pesticides (OR 5 2.92; 95% CI 5 1.37–6.25), and herbicides (OR 5 12.00; 95% CI 5 1.44–99.67) as relative risk factors. Smoking tobacco was significantly associated with refractory anemia with excess of blasts (RAEB) (ORadj 5 2.43; 95% CI 5 1.02–5.77). Education is shown as an independent protective factor against all MDS (ORadj 5 0.90; 95% CI 5 0.83–0.99) and RCMD (ORadj 5 0.89; 95% CI 5 0.79–0.99). These findings suggest that multiple modifiable behavioral, environmental, and occupational factors play a role in MDS etiology, and various MDS subtypes may have different susceptibility. Am. J. Hematol. 86:163–169, 2011. VVC 2010 Wiley-Liss, Inc. Introduction Myelodysplastic syndromes (MDS) represent a heteroge- neous group of neoplastic clonal stem cell disorders characterized by clinical presentations of anemia, thrombo- cytopenia, and leucopenia. MDS may be categorized into subtypes according to histological, immunological, and genetic characteristics. MDS was usually diagnosed by French–American–British (FAB) classification with subtypes including refractory anemia (RA), RA with ringed sidero- blasts (RARS), RA with excess of blasts (RAEB), RAEB in transformation (RAEB-T), and chronic myelomonocytic leukemia (CMML) [1]. Since its publication in 2001, World Health Organization (WHO) classification for MDS has become widely adopted [2]. In the WHO MDS system, blast cutoff is less than 20% compared to 30% in FAB system. Additional WHO MDS subtypes include refractory cytopenia with multiple dysplasia (RCMD), MDS with isolated del(5q), and MDS unclassifiable (MDS-u) and the WHO MDS system does not include CMML [3]. Secondary MDS is usually resulted from radiation and chemotherapy. Little is known about the etiology of primary or de novo MDS. Most previous studies on MDS risk fac- tors focused on FAB MDS [4–6]. Here, we report a large hospital-based case–control study of 403 WHO MDS cases and 806 age and sex-matched controls in a Chinese popu- lation to assess effects of lifestyle, environmental, and occupational factors on MDS development. Patients and Methods Patients and controls. A total of 403 adult de novo MDS patients were enrolled to the Shanghai Hematology Collaboration Study at 27 major hospitals in Shanghai, China, between June 2003 and November 2006. The patients were at least 18 years old, and MDS diagnoses were made according to WHO classification [2]. Each MDS case was matched with two controls on age (±5 years) and gender. The controls were recruited during the same period at the hospital where the case was enrolled. The controls were hospitalized patients for conditions not related to hematological diseases. The most common diseases in the control group were respiratory infections, acute gastrointestinal infections, genitourinary diseases, cardiovascular diseases, and trauma. Those with current or a history of any malignant or nonmalignant hematological dis- eases were excluded from the control group. Diagnosis of tuberculosis (TB), were based on medical history, physical examination, chest X-ray, tuberculin skin test and confirmed by positive for Mycobacterium tubercu- losis. The cases and controls were from the same regions and had simi- lar occupations (Tables I and II). An informed consent was obtained from each study participant before data collection. This study was reviewed and approved by the Ethic Committee of Fudan University. Data. The study participants (cases and controls) were face-to-face interviewed by trained study coordinators using a standard question- naire. To minimize recall bias, neither cases and controls nor inter- *Correspondence to: Liming Bao or Hua Fu, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA or School of Public Health, Fudan University, 130 Dong An Road, Shanghai 200032, China. E-mail: liming.bao@cchmc.org or hfu@shmu.edu.cn Conflict of interest: Nothing to report. 1Departments of Occupational Medicine and Clinical Epidemiology, Huashan Hospital, Fudan University, Shanghai, China; 2Departments of Hematology and Clinical Epidemiology, Huashan Hospital, Fudan University, Shanghai, China; 3Department of Occupational Health, School of Public Health, Fudan University, Shanghai, China; 4Shanghai Children’s Hospital, Shanghai Jiaotong University Affiliated Children’s Hospital, Shanghai, China; 5Center for Clinical Molecular Medicine, Children’s Hospital of Chongqing Medical University, Chongqing, China and 6Division of Human Genetics, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA Ling Lv and Guowei Lin contributed equally to this work. Contract grant sponsors: Shanghai Shen Kang Hospital Development Center; (SHDC12007201); Shanghai Bureau of Public Health; (200702); Chongqing Science and Technology Commission; (CSTC2009AB5217). Received for publication 15 October 2010; Revised 10 November 2010; Accepted 15 November 2010 Am. J. Hematol. 86:163–169, 2011. Published online 29 November 2010 in Wiley Online Library (wileyonlinelibrary. com). DOI: 10.1002/ajh.21941 Research Article VVC 2010 Wiley-Liss, Inc. American Journal of Hematology 163 http://wileyonlinelibrary.com/cgi-bin/jhome/35105 viewers were informed of the study hypothesis. The interviewers were not informed of study participant’s case/control status. Medication his- tory (at least one month) in the past 5 years prior to at the time of MDS diagnosis in cases or the time of interview in controls was sought. The surveyed medications included anti-TB drugs, N-(4-methylben- zene-sulfonyl)-N-butyl urea (D860) for diabetes, chloramphenicol, sulfo- namides, diazepam, phenobarbital, colchicine, cyclophosphamide (CTX), antihyperthyroidism drugs, antimalarial drugs, and traditional Chinese medicines (angelica root, bezoar of ox, arsenic trioxide, and tripterygium wilfordii hook). Information on hair dye use (frequency and accumulative uses) was collected. Alcohol consumption was classified as never and ever (former and current) drinkers. The amount of alcohol intake was measured as 10 g of alcohol equivalent to either one bottle of beer (5802600 ml), 25 ml wine, or 150 ml rice wine. The quantity of alcohol consumption per week and estimated drinking duration (number of years) were documented. For tobacco smoking, the study partici- pants were classified as ever (current and former) smokers and never smokers. Additional information on number of cigarettes smoked per day, number of years smoked, and accumulative quantity of tobacco consumption over lifetime estimated in pack-years (number of cigarette packs per day 3 number of years) were collected from the smokers. Other personal information collected included years of education, living within 100 m of high-voltage power lines in the past year, living in new buildings and/or newly renovated home/workplaces in the past year, and a family history of malignancies. Regarding occupational exposure, the hazards surveyed were ben- zene, heavy metals, pesticides, herbicides, gasoline, diesel, glue/adhe- sives, dyes, ionizing radiation, eproxy resin, and formaldehyde. The work history queried jobs were held over each study participant’s entire career. Assessment of occupational hazard exposure was performed by a panel of experts who were familiar with workplace exposure in Shanghai and its sounding regions using at least one, but often several of the following sources: information recorded in the database at the Shanghai Institute of Public Health (SIPH), which had historical expo- sure measurements taken at factories since 1950s; records for surro- gate factories, industries or jobs in the SIPH database; and Chinese literature for relevant industries. All occupational hazard exposures except benzene were recorded in a dichotomous classification of ‘‘ever’’ or ‘‘never.’’ Additional data sources used in benzene exposure assess- ment included exposure measurements records in the SIPH database for the jobs and locations where study participants worked; measure- ment records and facility histories maintained at the factories where study participants worked; onsite investigations including ad hoc walk- through surveys and measurements conducted by a exposure assess- ment team; records for surrogate factories industries or jobs in the SIPH database; and reports on technology changes over time in key industrial sectors. The committee members were blinded to case/con- trol status of study participants. Exposure to benzene was categorized into five exposure groups (EG): EG0 (nonexposure), EG1 (<1 mg/m3), EG2 (1–10 mg/m3), EG3 (10–100 mg/m3), and EG4 (>100 mg/m3). The ranges of these EGs were intended as approximate estimates of exposure and not meant to imply any numerical precision of the esti- mates. EG scores (EGS) with values of 0–4 were used to correspond- ing EG. Statistics analysis. Descriptive analyses were conducted using X2 tests. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess relation of the parameters to risk of MDS. Parameters with P � 0.2 in the univariate analyses (anti-TB drugs, D860, Chinese medi- cines, exposed to high-voltage power lines, new building/renovation, benzene, pesticides, herbicides, gasoline, gules, tobacco smoking, alcohol intake, hair dye use (�2 times a year), and education) were subjected to multivariate conditional logistic regression analysis to adjust for potential confounding factors. For variables with more than two categories, a trend test was performed. The statistical tests were two-sided. Probability values equal or less than 0.05 were considered as statistically significant. All analyses were performed using STATA software version 7.0 (StataCorp, College Station, TX). Results The median ages of cases and controls were 59 and 61 years, respectively, and MDS patients were male domi- nance (Table I). Basic characteristics of cases and controls including age, sex, regions, and occupations were compa- rable (Tables I and II). Of 403 MDS cases, 211 (52.36%) were 60 or younger and 192 (47.64%) over 60. Significant difference in education was noted between cases and con- trols (P < 0.01). The subtype distribution was 263 RCMD (65.26%), including 17 RCMD-ringed sideroblast (RCMD- RS), 99 RAEB (24.57%) (40 RAEB-1 and 59 RAEB-2), 25 MDS-u (6.20%), 8 RA (1.99%), 5 RARS (1.24%), and 3 MDS 5q- (0.74%) (Table III). RCMD and RAEB subtypes had large numbers, and they were subjected for subse- quent analyses. Anti-TB regimens usually contain isoniazid, rifampicin, ethambutol, or pyrazinamide. Our analysis revealed that study participants who used anti-TB drugs before MDS were more likely to develop all MDS (OR 5 2.11, 95% CI 5 1.11–4.02) and RCMD (OR 5 3.43; 95% CI 5 1.35– 8.71) (Table IV). Elevated risk of RAEB (OR 5 1.33; 95% CI 5 0.47–3.75) was also noted among those who took anti-TB drugs although the difference was not of statistical significance. RCMD patients were more likely to have a his- tory of taking Chinese medicines (OR 5 2.17; 95% CI 5 1.15–4.07). The numbers of study participants who used other medications were too small for statistics analysis. For instance, the numbers of study participants who used chlor- amphenicol were 3 and 0 in case and control groups, respectively, sulfonamides: 0 and 2, respectively, and CTX: 0 and 2, respectively. None of study participants reported a TABLE III. Distribution of WHO Subtypes Subtypes No. of cases (%) Male (%) Female (%) Median age (years) RA 8 (1.99) 3 (1.32) 5 (2.84) 62 RARS 5 (1.24) 1 (0.44)) 4 (2.27) 79 RCMD 263 (65.26) 148 (65.20) 115 (65.34) 57 RAEB 99 (24.57) 65 (28.63) 34 (19.32) 63 RAEB-1 40 (9.26) 25 (11.01) 16 (8.52) 63 RAEB-2 59 (14.64) 38 (16.74) 21 (11.93) 60 MDS-u 25 (6.20) 9 (3.96) 16 (9.09) 61 5q- syndrome 3 (0.74) 1 (0.44) 2 (1.14) 74 All-MDS (total) 403 227 176 59 TABLE I. Characteristics of Cases and Controls Cases (%) Controls (%) (n 5 403) (n 5 806) X2 P Median age (years) 59 (20–86) 61 (24–88) �60 211 (52.36) 388 (48.14) >60 192 (47.64) 418 (51.86) 1.91 0.17 Sex Female 176 (43.67) 352 (43.67) Male 227 (56.33) 454 (56.33) 0.01 0.94 Places of residence Metropolitan Shanghai 263 (65.26) 564 (69.98) 3.62 0.31 Suburb Shanghai 27 (6.70) 54 (6.70) Cities in neighboring provinces 69 (17.12) 121 (15.01) Rural areas in neighboring provinces 44 (10.92) 67 (8.31) Education (years) None 48 (11.91) 44 (5.46) �5 88 (21.84) 122 (15.14) 6–9 119 (29.53) 240 (29.78) 0–12 81 (20.10) 219 (27.17) >12 59 (14.64) 167 (20.72) 32.4 <0.01 Missing data 8 (1.99) 14 (1.74) TABLE II. Occupations of Cases and Controls Cases [n 5 403 (%)] Controls [n 5 806 (%)] Clerks 46 (11.41) 122 (15.14) Armed forces 20 (4.96) 50 (6.20) Plant and mechine operators 73 (18.11) 170 (21.09) Technicans 26 (6.45) 33 (4.09) Service and sales workers 33 (8.19) 84 (10.42) Elementary occupations 31 (7.69) 61 (7.57) Skilled/agricultural 72 (17.87) 87 (10.79) Craft workers 24 (5.96) 43 (5.33) Managers 12 (2.98) 8 (0.90) 164 American Journal of Hematology research article history of taking diazepam, phenobarbital, colchicine, anti- hyperthyroidism drugs, and antimalarial drugs. Hair dye users at frequency of twice a year or more showed an elevated risk of MDS (OR 5 1.46; 95% CI 5 1.03–2.07) (Table IV). The trend test for number of hair dye users per year was statistically significant (Ptrend 5 0.02). But the trend test for lifetime hair dye users did not attain statistically signifi- cant. The data also revealed significantly increased risk of all MDS (OR 5 1.69, 95% CI 5 1.11–2.00) and marginal ele- vated risks of RAEB (OR 5 1.65, 95% CI 5 0.67–4.07) and RCMD (OR 5 1.60, 95% CI 5 0.96–2.68) among those who lived in new buildings and/or newly renovated homes/work- places in the past year. Finally, a family history of malignan- cies did not appear to have effects on MDS risk (Table IV). Positive association was observed between smoking and development of all MDS (OR 5 1.44; 95% CI 5 1.04–2.01) and RAEB (OR 5 2.32; 95% CI 5 1.12–4.77) (Table V). The trend for accumulative smoking and risk of RAEB was significant (Ptrend < 0.001), suggesting dose-dependent relationship. With regard to alcohol intake, although increases in risk of MDS were not statistically significant, the P values of the trend tests for weekly alcohol consump- tion and years of drinking attained statistically significant, indicating a dose-response pattern between alcohol intake and RARB risk (Table V). We did not obtain information on types of liquor from our study participants and therefore, possible effects of different liquors such as beer, wine, and hard liquor on MDS susceptibility were not ascertained. Table VI shows that study participants with none or ele- mentary school education (�5 years) were more suscepti- ble to all MDS (OR 5 20.67; 95% CI 5 2.74–156.1 and OR 5 1.65; 95% CI 5 1.00–2.72, respectively). Moreover, TABLE V. Relationship Between Smoking Tobacco and Alcohol Consumption and Susceptible to MDS Variables All MDS RAEB RCMD OR (95% CI) Cases/controls OR (95% CI) Cases/controls OR (95% CI) Cases/controls Smoking Never 1 262/563 1 62/144 1 174/355 Ever (former and current) 1.44 (1.04–2.01) 141/243 2.32 (1.12–4.77) 37/54 1.10 (0.73–1.65) 89/171 Current 1.37 (0.89–2.12) 71/118 2.33 (0.95–5.73) 17/23 1.01 (0.59–1.72) 44/89 Former 1.48 (0.94–2.33) 70/125 2.28 (0.83–6.27) 20/31 1.20 (0.69–2.01) 45/82 Duration (years) 1–19 1.32 (0.67–2.61) 22/37 3.29 (0.82–13.15) 8/14 1.39 (0.58–3.32) 13/28 �20 1.22 (0.91–1.63) 108/96 2.35 (0.97–5.68) 27/36 0.96 (0.61–1.53) 68/134 Trend test P-trend 5 0.44 P-trend 5 0.02 P-trend 5 0.85 No. of cigarettes per day 1–19 1.21 (0.82–1.78) 62/99 3.95 (1.41–11.05) 18/22 1.05 (0.61–1.80) 34/70 �20 1.06 (0.75–1.50) 73/138 1.08 (0.42–276) 19/31 1.09 (0.64–1.88) 50/94 Trend test P-trend 5 0.52 P-trend 5 0.07 P-trend 5 0.53 Pack-years 1–19 1.11 (0.76–1.61) 68/119 1.43 (0.45–4.61) 7/27 0.96 (0.57–1.63) 39/85 �20 1.06 (0.73–1.55) 61/116 2.66 (1.06–6.69) 27/22 1.08 (0.60–1.92) 46/80 Trend test P-trend 5 0.20 P-trend 5 <0.001 P-trend 5 0.55 Alcohol consumption Never 1 331/684 1 80/175 1 216/435 Ever 1.26 (0.89–1.78) 72/122 1.86 (0.94–3.69) 19/23 1.05 (0.69–1.60) 47/91 Current 1.40 (0.82–2.38) 30/51 2.39 (0.88–6.49) 9 /8 0.80 (0.40–1.60) 16/42 Former 1.26 (0.80–1.99) 42/64 1.33 (0.54–3.34) 10/15 1.36 (0.79–2.35) 31/44 Alcohol drinking per week <70 g 1.00 (0.67–1.49) 49/98 1.34 (0.59–3.02) 12/18 0.99 (0.64–1.54) 41/82 �70 g 1.68 (0.87–3.24) 20/24 3.31 (0.96–11.35) 7/4 1.00 (0.16–6.14) 3/6 Trend test P-trend 5 0.28 P-trend 5 0.03 P-trend 5 0.95 Duration (years) 1–19 1.60 (0.90–2.84) 25/38 1.55 (0.43–5.57) 5/9 1.51 (0.72–3.17) 15/26 �20 1.07 (0.70–1.64) 46/83 2.09 (093–4.69) 14/14 0.90 (0.53–1.52) 31/63 Trend test P-trend 5 0.34 P-trend 5 0.05 P-trend 5 1.00 10 g alcohol 5 a can of beer (580/620 ml) or 25 ml of red wine or 150 ml of rice wine. Values of statistical significance are indicated in bold. TABLE IV. Relationship Between Nonoccupational Exposures and Risk of MDS Variables All MDS RAEB RCMD OR (95% CI) Cases Controls OR (95% CI) Cases Controls OR (95% CI) Cases Controls Anti-TB drugs 2.11 (1.11–4.02) 19 18 1.33 (0.47–3.75) 6 9 3.43 (1.35–8.71) 12 7 D860 0.44 (0.15–1.31) 4 18 1.33 (0.22–7.98) 2 3 0.18 (0.02–1.41) 1 11 Traditional Chinese medicines 1.54 (0.93–2.55) 32 45 0.56 (0.20–1.54) 6 19 2.17 (1.15–4.07) 18 22 Hair dyes 1.24 (0.96–1.62) 170 303 1.00 (0.59–1.70) 37 74 1.19 (0.86–1.65) 113 207 <2 time per year 1.05 (0.68–1.63) 49 106 1.00 (0.39–2.53) 10 18 1.17 (0.69–1.99) 36 79 �2 times per year 1.46 (1.03–2.07) 97 146 0.92 (0.47–1.82) 20 43 1.20 (0.77–1.87) 61 95 Trend test P-trend 5 0.02 P-trend 5 0.93 P-trend 5 0.15 Total lifetime uses <70 1.28 (0.97–1.68) 160 283 1.00 (0.56–1.78) 31 64 1.27 (0.91–1.77) 111 197 �70 0.92 (0.34–2.51) 7 19 1.00 (0.24–4.25) 3 10 0.26 (0.03–2.22) 2 9 Trend test P-trend 5 0.22 P-trend 5 0.68 P-trend 5 0.47 Living within 100 m of high-voltage power lines 1.30 (0.97–1.75) 96 159 1.34 (0.70–2.56) 19 31 1.25 (0.87–1.79) 64 107 New building/renovation 1.69 (1.11–2.00) 47 60 1.65 (0.67–4.07) 10 13 1.60 (0.96–2.68) 30 40 Family history of malignancy 1.00 (0.74–1.36) 91 185 0.81 (0.45–1.47) 21 51 0.89 (0.61–1.32) 56 121 Values of statistical significance are indicated in bold. American Journal of Hematology 165 research article an elevated risk of RCMD was noted among those with either none (OR 5 2.30; 95% CI 5 1.20–4.44) or primary education (OR 5 1.62; 95% CI 5 0.88–3.