Health Sciences, Exponent, Inc., 149 Commonwealth Drive, Menlo Park, California, 94025, USA.
Scand J Work Environ Health. 2021 Jan 1;47(1):85-86. doi: 10.5271/sjweh.3909. Epub 2020 Jul 6.
As the first case-control study of malignant mesothelioma of the pericardium and the tunica vaginalis testis (mTVT), the paper by Marinaccio et al (1) is potentially an important epidemiologic contribution. A careful review of the paper, however, raises a number of methodological issues. Any case-control study can be viewed as being nested within a conceptual cohort, with controls being sampled from the at-risk cohort as cases arise over time. This view of case-control studies leads to the concept of incidence-density sampling of controls (eg, 2, 3). For Marinaccio et al (1) this would mean that, as cases were registered over the study period, each would be matched to an individual control or set of controls of the same gender, age, and region of the country (since asbestos exposure varies by time and region [4]). For example, if a case were 50 years old in 1995, then any matched control should be close to age 50 in 1995 and of the same gender and from the same region as the case. Matching for age in this fashion automatically results in matching for year of birth, which is essential in this context because birth-cohort effects are determinants of asbestos exposure and mesothelioma incidence (eg, 5-8). If Marinaccio et al (1) used this scheme for age-matching, one would expect to see similar distributions of cases (table 1) and controls (table S3 in the supplemental material) by period of birth. Among males, however, the distributions of mesothelioma cases (whether pericardial or mTVT) and controls by period of birth are clearly different (P<0.001). Among females, the distributions of cases of pericardial mesothelioma and controls by birth year are less dissimilar (P≈0.05). Thus, the female cases of pericardial mesothelioma are better matched to controls on year of birth than are male cases of either mTVT or pericardial mesothelioma. We note also that the distributions of male and female controls by year of birth are distinctly different (P<0.002), whereas the birth-year distributions of cases of mesothelioma by site and gender are not (P≈0.8). In the Marinaccio et al (1) sensitivity analysis restricted to subjects born before 1950, the distributions of cases and controls by period of birth remain significantly different. Therefore, based on the reported evidence, cases and controls were not matched on birth cohort, thereby possibly biasing the results. Similarly, bias may result from the lack of matching on geographic region; while cases were registered from across Italy, controls were selected from only six regions. Although a sensitivity analysis restricted cases and controls to those from only the six regions, a comparison of tables S1 and S3 indicates that the regional distribution of controls is different from that of person-time observed; that is, the controls do not appear to be representative of the underlying population at risk by region. The second major issue of concern has to do with ascertainment of asbestos exposure. Information on exposure for the cases was presumably obtained at the time of registration. The two sets of controls, obtained from previously unpublished case-control studies, were interviewed during 2014-2015 and 2014-2016; that is, many years after the exposure for most cases was ascertained (1993-2015). Few other details of the control groups are provided, except that participation by one set of controls was <50%, raising additional concerns about selection bias. For details on the second set of controls, Marinaccio et al (1) reference a paper by Brandi et al (9). On review of that paper, however, we found no description of the control group, only references to three earlier papers. Marinaccio et al (1) present analyses only with both sets of controls combined; to evaluate potential sources of bias from the use of different sets of controls, they should also report results using each set of controls separately. The authors also did not detail their methods of exposure classification. For example, what does probable or possible exposure mean? The authors should at least present separate analyses of definite occupational exposure. Eighty cases of mTVT were registered, but only 68 were included in the analyses. Information on the 12 omitted cases (eg, age, year of birth, and region) would be helpful. Marinaccio et al (1) did not provide clear information on what occupations and/or industries they considered as exposed to asbestos. In an earlier study, Marinaccio et al (10) remarked on the absence of pericardial mesothelioma and mTVT in industries with the highest exposures to asbestos, saying, "[t]he absence of exposures in the shipbuilding, railway and asbestos-cement industries … for all the 67 pericardial and testicular cases is noteworthy but not easy to interpret." By contrast, Marinaccio et al (1) stated, "[t]he economic sectors more frequently associated with asbestos exposure were construction, steel mills, metal-working industry, textile industry and agriculture." The possibility of exposure in the "agriculture economic sector" was not mentioned in Marinaccio et al (10) and appears not to have been considered in previous epidemiologic studies in Italy. In general, epidemiologic studies indicate that farmers and agricultural workers are not at increased risk of developing mesothelioma (eg, 11-17). The fact that few, if any, cases of mTVT and pericardial mesothelioma occurred in industries traditionally associated with high asbestos exposure raises the possibility that the results of Marinaccio et al (1) are attributable to deficiencies in study design, very possibly bias in the selection of controls, and deficiencies in exposure assessment and classification as described above, leading to a spurious association of occupational exposure with mTVT and male pericardial mesothelioma. Conflict of interest This research has received no outside funding. All authors are employees of Exponent, Inc., an international scientific and engineering consulting company. All authors have worked as both consulting and testifying experts in litigation matters related to asbestos exposure and asbestos-related disease. References 1. Marinaccio A, Consonni D, Mensi C, Mirabelli D, Migliore E, Magnani C et al.; ReNaM Working Group. Association between asbestos exposure and pericardial and tunica vaginalis testis malignant mesothelioma: a case-control study and epidemiological remarks. Scand J Work Environ Health. 2020;46(6):609-617. https://doi.org/10.5271/sjweh.3895. 2. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. 2008; Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins. 3. Richardson DB. An incidence density sampling program for nested case-control analyses. Occup Environ Med 2004 Dec;61(12):e59. https://doi.org/10.1136/oem.2004.014472. 4. Marinaccio A, Binazzi A, Marzio DD, Scarselli A, Verardo M, Mirabelli D et al.; ReNaM Working Group. Pleural malignant mesothelioma epidemic: incidence, modalities of asbestos exposure and occupations involved from the Italian National Register. Int J Cancer 2012 May;130(9):2146-54. https://doi.org/10.1002/ijc.26229. 5. La Vecchia C, Decarli A, Peto J, Levi F, Tomei F, Negri E. An age, period and cohort analysis of pleural cancer mortality in Europe. Eur J Cancer Prev 2000 Jun;9(3):179-84. https://doi.org/10.1097/00008469-200006000-00005. 6. Price B, Ware A. Mesothelioma trends in the United States: an update based on Surveillance, Epidemiology, and End Results Program data for 1973 through 2003. Am J Epidemiol 2004 Jan;159(2):107-12. https://doi.org/10.1093/aje/kwh025. 7. Moolgavkar SH, Meza R, Turim J. Pleural and peritoneal mesotheliomas in SEER: age effects and temporal trends, 1973-2005. Cancer Causes Control 2009 Aug;20(6):935-44. https://doi.org/10.1007/s10552-009-9328-9. 8. Moolgavkar SH, Chang ET, Mezei G, Mowat FS. Chapter 3. Epidemiology of mesothelioma. In Testa JR. Asbestos and mesothelioma; 2017. pp. 43-72. Cham, Switzerland: Springer International Publishing. 9. Brandi G, Di Girolamo S, Farioli A, de Rosa F, Curti S, Pinna AD et al. Asbestos: a hidden player behind the cholangiocarcinoma increase? Findings from a case-control analysis. Cancer Causes Control 2013 May;24(5):911-8. https://doi.org/10.1007/s10552-013-0167-3. 10. Marinaccio A, Binazzi A, Di Marzio D, Scarselli A, Verardo M, Mirabelli D et al. Incidence of extrapleural malignant mesothelioma and asbestos exposure, from the Italian national register. Occup Environ Med 2010 Nov;67(11):760-5. https://doi.org/10.1136/oem.2009.051466. 11. Teschke K, Morgan MS, Checkoway H, Franklin G, Spinelli JJ, van Belle G et al. Mesothelioma surveillance to locate sources of exposure to asbestos. Can J Public Health 1997 May-Jun;88(3):163-8. https://doi.org/10.1007/BF03403881. 12. Bouchardy C, Schüler G, Minder C, Hotz P, Bousquet A, Levi F et al. Cancer risk by occupation and socioeconomic group among men--a study by the Association of Swiss Cancer Registries. Scand J Work Environ Health 2002;28(1 Suppl 1):1-88. 13. Hemminki K, Li X. Time trends and occupational risk factors for pleural mesothelioma in Sweden. J Occup Environ Med 2003a Apr;45(4):456-61. https://doi.org/10.1097/01.jom.0000058341.05741.7e. 14. Hemminki K, Li X. Time trends and occupational risk factors for peritoneal mesothelioma in Sweden. J Occup Environ Med 2003b Apr;45(4):451-5. https://doi.org/10.1097/01.jom.0000052960.59271.d4. 15. Pukkala E, Martinsen JI, Lynge E, Gunnarsdottir HK, Sparén P, Tryggvadottir L et al. Occupation and cancer - follow-up of 15 million people in five Nordic countries. Acta Oncol 2009;48(5):646-790. https://doi.org/10.1080/02841860902913546. 16. Rolland P, Gramond C, Berron H, Ducamp S, Imbernon E, Goldberg M et al. Mesotheliome pleural: Professions et secteurs d'activite a risque chez les hommes [Pleural mesothelioma: Professions and occupational areas at risk among humans]. 2005; Institut de Veille Sanitaire, Departement Sante Travai, Saint-Maurice, France. 17. Rolland P, Gramond C, Lacourt A, Astoul P, Chamming's S, Ducamp S et al. PNSM Study Group. Occupations and industries in France at high risk for pleural mesothelioma: A population-based case-control study (1998-2002). Am J Ind Med 2010 Dec;53(12):1207-19. https://doi.org/10.1002/ajim.20895.
作为首例心包膜和睾丸鞘膜间皮瘤的病例对照研究（mTVT），[作者]的论文具有潜在的重要流行病学贡献。然而，仔细审查该论文会提出许多方法学问题。任何病例对照研究都可以被视为一个概念性队列的嵌套，随着时间的推移，随着病例的出现，对个体进行病例对照抽样。这种病例对照研究的观点导致了对对照的发病率密度抽样的概念（例如，2、3）。对于[作者]来说，这意味着，随着研究期间病例的登记，每个病例都将与同一性别、相同年龄和国家（由于石棉暴露随时间和地区而变化[4]）的相同性别、相同年龄和同一地区的个体对照相匹配。例如，如果一个病例在 1995 年为 50 岁，那么任何匹配的对照应该接近 1995 年的 50 岁，并且来自病例的同一性别和相同地区。以这种方式按年龄匹配会自动导致按出生年份匹配，这在这种情况下是必不可少的，因为出生队列效应是石棉暴露和间皮瘤发病率的决定因素（例如，5-8）。如果[作者]使用这种年龄匹配方案，人们预计会看到病例（表 1）和对照（补充材料表 S3）在出生时期的相似分布。然而，男性间皮瘤病例（无论是心包膜还是 mTVT）和对照的出生时期分布显然不同（P<0.001）。在女性中，心包膜间皮瘤病例和对照的出生年份分布通过出生年份的差异较小（P≈0.05）。因此，与男性 mTVT 或心包膜间皮瘤病例相比，女性心包膜间皮瘤病例与对照的出生年份匹配更好。我们还注意到，男性和女性对照的出生年份分布明显不同（P<0.002），而男性和女性间皮瘤病例的出生年份分布则不同（P≈0.8）。在[作者]的敏感性分析中，将病例限制在出生于 1950 年之前的人群中，病例和对照的出生时期分布仍然存在显著差异。因此，根据报告的证据，病例和对照不是按出生队列匹配的，从而可能导致结果偏倚。同样，由于缺乏地理区域的匹配，也可能导致偏倚；虽然病例是在意大利各地登记的，但对照仅来自六个地区。尽管对病例和对照进行了限制，仅来自六个地区的敏感性分析，但比较表 S1 和表 S3 表明，对照的分布与观察到的基础人群的地理区域分布不同；也就是说，对照似乎不能代表整个风险人群的区域分布。关注的第二个主要问题与石棉暴露的确定有关。关于病例的暴露信息可能是在登记时获得的。来自两个以前未发表的病例对照研究的两组对照，在 2014-2015 年和 2014-2016 年期间接受了访谈；也就是说，许多年之后大部分病例的暴露情况才被确定（1993-2015 年）。关于对照组的其他细节很少提供，除了一组对照组的参与率<50%，这进一步增加了选择偏倚的担忧。关于第二组对照的详细信息，[作者]参考了 Brandi 等人（9）的一篇论文。然而，审查该论文时，我们没有发现对照组的描述，只提到了之前的三篇论文。[作者]仅使用两组对照进行了分析，为了评估使用不同对照组合的潜在偏差来源，他们还应该报告使用每组对照单独进行的分析结果。作者也没有详细说明他们的暴露分类方法。例如，什么是“可能”或“可能”暴露？作者至少应该报告明确的职业暴露分析。共登记了 80 例 mTVT，但仅纳入了 68 例进行分析。关于被排除的 12 例病例（例如，年龄、出生年份和地区）的信息将很有帮助。[作者]没有提供关于他们考虑了哪些职业和/或行业作为暴露于石棉的信息。在早期的一项研究中，[作者]指出，在石棉暴露最高的行业（例如造船、铁路和石棉水泥行业）中没有发现心包膜间皮瘤和 mTVT，“这一发现引人注目，但不易解释”。相比之下，[作者]指出，“经济部门中与石棉暴露相关的更频繁的行业是建筑、钢厂、金属加工业、纺织业和农业。”在 Brandi 等人（10）的研究中没有提到农业经济部门，在意大利之前的流行病学研究中也没有提到农业部门与间皮瘤发病率有关（11-17）。一般来说，流行病学研究表明，农民和农业工人患间皮瘤的风险并不高（例如，11-17）。很少（如果有的话）发生 mTVT 和心包膜间皮瘤的事实表明，[作者]的研究结果可能归因于研究设计的缺陷，很可能是对照选择偏倚，以及之前描述的暴露评估和分类方法存在缺陷，这些都导致职业暴露与 mTVT 和男性心包膜间皮瘤之间的关联具有误导性。
