Aggregation of Lung Cancer in Families: Results from a Population-based Case-Control Study in Germany
Katja Bromen1,
Hermann Pohlabeln2,
Ingeborg Jahn2,
Wolfgang Ahrens2 and
Karl-Heinz Jöckel1
1 Institute of Medical Informatics, Biometry, and Epidemiology, University of Essen, Essen, Germany.
2 Bremen Institute for Prevention Research and Social Medicine, Bremen, Germany.
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ABSTRACT
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The authors investigated familial aggregation of lung cancer by means of a population-based case-control study, conducted in Germany between 1988 and 1993. They compared lung cancer prevalence in first degree relatives of 945 patients and 983 controls, accounting for various potential risk factors using logistic regression and generalized estimating equations. Some 83% of the study participants were male, and about 14% were below age 51 (young age group). Overall, lung cancer in parents or siblings was associated with a 1.67-fold (95% confidence interval (CI): 1.11, 2.52) increase in lung cancer risk. For the young participants, this risk was 4.75 (95% CI: 1.20, 18.77). Having multiple affected relatives (two or more) was related to a threefold risk elevation (odds ratio (OR) = 2.99, 95% CI: 0.32, 27.55). Paternal (OR = 1.64, 95% CI: 0.91, 2.96) but not maternal (OR = 0.91, 95% CI: 0.32, 2.61) lung cancer was associated with an increased risk of the disease. Lung cancer risk from smoking was particularly pronounced in the parents of cases (OR = 12.20, 95% CI: 3.34, 44.62 vs. OR = 7.93, 95% CI: 2.43, 25.91 in parents of controls). No risk elevation was detected for other smoking-related and other cancers in general. Results confirm previous findings and support the etiologic role of a genetic predisposition to lung cancer. Am J Epidemiol 2000;152:497505.
case-control studies; environment; family; genetics; lung neoplasms; occupational exposure; smoking
Abbreviations:
CI, confidence interval; ICD-9, international Classification of Diseases, Ninth Revision; OR, odds ratio
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INTRODUCTION
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Lung cancer accounts for the biggest part of cancer incidence and mortality in the world (1
). It is the most frequent cancer in men in many countries and increasingly affects women as a result of changed smoking behavior (1
). While lung cancer mortality among women in the European Union ranked third behind breast and colorectal neoplasms (2
, 3
) as of 1990, this rate among US women has surpassed breast cancer mortality already 11 years ago (4
). For the US population, 171,500 new cases of lung cancer (14 percent of cancer diagnoses) and 160,100 deaths due to it (28 percent of cancer deaths) have been estimated to occur in 1998 (4
).
Cigarette smoking has long been established as the predominant risk factor for lung cancer. From the 1950s onward, this was supported by numerous experimental and epidemiologic studies (5
) that demonstrated a strong dose-response relation (5
, 6
). Other recognized risk factors include exposure (mostly occupational) to various types of radiation and to substances such as asbestos, arsenic, polycyclic aromatic hydrocarbons, chromium, nickel, chloromethyl ethers, and mustard gas (7
).
In the 1960s, it had already been shown that the disease tends to aggregate in families (8
). Since then, scientific evidence has indicated that the effect of exposure to carcinogens such as polycyclic aromatic hydrocarbons and aromatic amines, originating from tobacco smoke and other environmental sources, is modified by host susceptibility factors acting via metabolic polymorphisms (9


,

,16
). The results of previous epidemiologic investigations that focus on the general population indicate a slight increase of risk for relatives of lung cancer cases, with odds ratios ranging between 1.8 and 2.8 (8
, 17
19
). However, many of the case-control studies conducted so far are limited to certain subgroups of the population such as nonsmokers, women, and certain age groups and, therefore, vary somewhat in their risk estimates (20







29
). Furthermore, odds ratios vary because of differences in modeling approaches and adjustments.
In this study, we investigate familial aggregation of lung cancer in a population-based case-control study conducted in West Germany to identify occupational risk factors for lung cancer (30
). We examined the prevalence of lung cancer in the first degree relatives of study participants, aiming to test the hypothesis that lung cancer cases are more likely to have a family member with the same disease. We focused on young lung cancer cases, aiming to test the hypothesis that those potentially susceptible to lung cancer develop the disease early in life.
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MATERIALS AND METHODS
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Study population
Recruitment and interviews of both cases and controls took place between August 1988 and September 1993. A total of 1,004 cases (839 males, 165 females) with histologically or cytologically (based on bronchoscopy) confirmed primary carcinoma of the lung (International Classification of Diseases, Ninth Revision (ICD-9), code 162) served as cases in the study. Only patients of German nationality, born after 1912, who had a recent diagnosis (less than 3 month old) and were in an adequate state to participate in an extensive interview of 1.5 hours in length, were included in the study. Study regions were Bremen and Frankfurt/Main, with the surrounding areas. Most of the participants were from the Bremen area (about 90 percent) and within each study region half the population was living in the city (30
, 31
). Cases were on average 61.2 years old, and those recruited constitute 69 percent of the initial population eligible for participation. Histology of the lung carcinomas was assessed by the hospital pathologist using the classification proposed by the World Health Organization (32
), but additionally allowing for combination of tumors, biopsies without tumor material, and tumors where classification was impossible. However, the last category did not occur in our study. Additionally, for 724 of the cases, tumor material was sent to a reference pathologist for reevaluation. The reference pathology was found to be in good agreement with the first judgment. For the three main histologic types, adeno-, small-cell, and squamous-cell carcinoma, the values for kappa, the measure which was used to quantify this agreement (33
), were 0.54, 0.79, and 0.58, respectively. These values are similar to those obtained in comparable investigations (34
, 35
). The degree of disagreement may be due to the biology of the tumor, where material may consist of several adjacent types of tissue.
Controls were ascertained via random samples drawn from the files of the mandatory registry of residents. The response rate of those eligible (30
) was 68 percent. A total of 1,004 controls were individually matched to the cases according to sex, age (±5 years), and region of residence. They had an average age of 61.6 years.
Some participants did not complete the interview or did not provide any information on familial health status. Therefore, we excluded 21 controls and 59 cases from the analysis on familial health and obtained a final population of 945 cases (786 males, 159 females) and 983 controls (818 males, 165 females). Of these, 131 cases (103 males, 28 females) and 139 controls (109 males, 30 females) were below age 51 or were matched to a case of that age group.
Exposure assessment
Face-to-face interviews were conducted by trained interviewers using a standardized questionnaire to obtain information on occupational exposure, job history, active and passive smoking exposure, nutrition, medical history of the study participants and their families, and sociodemographic characteristics.
Family history of diseases.
Personal and familial health was examined by asking individuals to identify those diseases from a prepared list for which they had been diagnosed until up to 2 years before the interview. Next, they were asked about the number of siblings and offspring, vital status of parents, and cause of and age at death of parents, if applicable. Finally, information on history of cancer, myocardial infarction (heart attack), stroke, tuberculosis, and multiple sclerosis was ascertained for each member of the family, including age at diagnosis. For cancer, information on the particular type was collected by an open question that was subsequently coded according to ICD-9 (36
). For the purpose of this paper, we distinguished three groups of cancers in relatives: 1) lung cancer, 2) cancer in any organ except the lung, and 3) any smoking-related cancer except lung cancer (cancer of lip/mouth/throat, esophagus, pancreas, larynx, bladder, kidney/renal tract, respiratory tract except lung) (5
).
Smoking and occupational exposure.
We considered smoking, by both the participants and the parents, and asbestos exposure as potential confounders in the analysis. They are likely to be related to not only disease development in the participants but also their parents' lung cancer risk because of similarities between the children's and parents' socioeconomic status and therefore smoking habits and professional environment. Assessment of smoking and occupational exposure has been described elsewhere (30
). Briefly, for each smoker, that is, a person having smoked regularly for more than 6 months, detailed information on smoking habits was obtained, including type of tobacco product, amount smoked, brand of cigarette, butt length, intensity of inhalation, age at first cigarette, and age at any major change of smoking habits. For cigarette smokers, pack-years were calculated as a cumulative dose indicator that was categorized into three groups (>020, >2040, >40 pack-years). Persons smoking only pipes and cigars formed a separate group. A cumulative index of lifetime hours of exposure to asbestos was calculated from asbestos-related information derived from job-specific supplementary questionnaires. According to the tertiles of the distribution among exposed individuals, three exposure categories were formed: >0940, >9405,280, and >5,280 lifetime hours. Parental smoking was coded as a dummy variable, indicating whether the parent was a smoker. Information on the number, sex, generation, and age of the relatives was included in some of the analyses. Passive smoking was not being considered in this investigation, since the percentage of nonsmokers for whom this adjustment would matter is small.
Statistical methods
For each relative, that is, father, mother, sibling, and offspring, a dichotomous variable was created to code the history of lung cancer. After calculating the frequencies of lung cancer in the various types of relatives, we determined stratified odds ratios separately for paternal and maternal lung cancer. The potential confounders, age, region of residence, and sex, were considered both in the design, by individual matching of cases and controls, and in the analysis, by applying conditional logistic regression using the PHREG procedure in SAS software (37
). Observations with the same matching criteria were combined into one stratum to improve the efficiency of the risk estimates and to avoid loss of subjects whose matched counterpart had missing data (38
). The odds ratios were adjusted for smoking in the participants, their parents, and for asbestos exposure (males only). These analyses were repeated separately for males and females and for young lung cancer cases only (
50 years of age). Adjustment for asbestos exposure was done solely for men, since among women only three cases and one control had been exposed to asbestos. A total of 944 cases (785 males, 159 females) and 980 controls (816 males, 164 females) were included in the conditional logistic regression. Four persons had to be excluded because of missing values in their counterparts, that is, persons belonging to the same stratum. One female control had to be excluded from the young group. Sensitivity analysis, in which the analyses were repeated including those 80 individuals initially excluded and coding them as unexposed, showed no relevant change in the results.
Data on all first degree relatives were simultaneously evaluated using the following approaches. First, conditional logistic regression was used to assess the risk of lung cancer depending on the number of relatives affected, therefore examining a potential dose-response relation. The odds ratios were adjusted for the study subject's smoking history and the number of relatives. In addition, we tested the mean difference in response levels between cases and controls using the extended Mantel-Haenszel test statistic (39
).
Second, an estimating equations-based technique based on the approach proposed by Zhao and Le Marchand (40
) and by Le Marchand et al. (41
) was applied to account for intrafamilial phenotypic correlations (40
). In this approach, the association between the relatives' and the subject's disease status is described via the logistic regression model
where yij is a variable denoting the phenotype of person j related to study participant i (yij = 1 if diseased; else yij = 0), ci is an indicator variable denoting the case-control status of the ith subject (ci = 1 if study subject i is a case; else ci = 0), xij' = (xij1, ..., xijp) is a vector of p covariates of the subject's relative j, and zi' = (zi1, ..., ziq) is a vector of q covariates describing the participant, such as the matching variables. Subsequently, the regression parameters are estimated by solving a set of estimating equations. The overall familial aggregation can be assessed by calculating the odds ratio through the exponential function exp(ß). The risk estimates were adjusted for the matching variables, smoking and (in males) asbestos exposure of cases and controls, and sex and generation (parent, sibling) of the relative. Some categories of smoking and asbestos exposure were combined because of small numbers when analyzing the data for young lung cancer cases.
Finally, the parental data were analyzed from a different perspective. Since information on parental smoking was available, we investigated its impact on lung and other smoking-related cancers in the parents depending on their relationship to either a case or a control, using unconditional logistic regression. Information on smoking status was available for 1,662 parents of cases (822 fathers, 840 mothers) and 1,738 parents of controls (866 fathers, 872 mothers). Adjustments were made for parental age and sex, the matching variables, that is, age, sex, and region of residence, and smoking of the study subjects. Because of incomplete information on parental age, 782 fathers and 817 mothers of cases and 837 fathers and 858 mothers of controls were included in the calculation of adjusted odds ratios.
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RESULTS
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A general description of cases and controls included in the analysis on familial health is provided in table 1. Data on educational and professional degrees indicate that the controls' socioeconomic status, as measured by the highest educational and professional degree, is somewhat higher than that of the cases.m
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TABLE 1. Distribution of cases and controls according to demographic and educational characteristics, Germany, 19881993
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Parental lung cancer
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Altogether, 70 fathers and 19 mothers of the study population were affected by lung cancer (table 2). Some 4.8 percent of the male and 4.4 percent of the female cases had a father previously diagnosed with the disease. Among controls, the corresponding values are 2.7 percent and 1.8 percent, respectively. For paternal lung cancer, all odds ratios are greater than one with females showing a larger unadjusted odds ratio than males (odds ratio (OR) = 2.42, 95 percent confidence interval (CI): 0.62, 9.35 vs. OR = 1.87, 95 percent CI: 1.09, 3.19). For both males and females, odds ratios decreased after adjustment for occupational asbestos exposure (males only) and the participant's and father's smoking.
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TABLE 2. Odds ratios for lung cancer according to paternal and maternal lung cancer by age group and sex, Germany, 19881993
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The elevation in odds ratios of paternal lung cancer is particularly pronounced in the young age group. Contrary to the results for the whole group, the crude odds ratio of paternal lung cancer increases after adjustment for 1) the participant's and father's smoking and 2) among males for the participant's smoking and asbestos exposure (table 2).
The results for maternal lung cancer yield a different picture. As can be seen in table 2, most odds ratios are below or close to one and, only after adjustment for smoking (active and maternal smoking), the ratio of the female study participants slightly increases. However, there are only 13 cases of maternal lung cancer among males (0.8 percent) and six among females (1.9 percent) without any relevant case-control difference. When focusing the analysis on young study members, we found that the odds ratios increase to values up to 3.0, but these are based on extremely small numbers. Unlike paternal cancer, where the proportions among the sexes are fairly equal, the share of maternal cancer among females is clearly higher than among males and is especially pronounced in young participants where this rate is 5.2 percent in females compared with 0.5 percent in males.
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Lung and other cancers in first degree relatives
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The distribution of lung cancer cases per family and corresponding risk estimates are presented in table 3. While there are few families with multiple occurrences of lung cancer in relatives, families of cases are disproportionately more often affected (five vs. one) and show bigger clusters of affected family members (p value = 0.002).
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TABLE 3. Odds ratios for lung cancer according to the number of first degree relatives (parents, siblings) affected by lung cancer, Germany, 19881993
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For each type of relative, the numbers of family members affected by lung cancer are listed in table 4. Cases had 2,784 siblings of which 27 had a history of lung cancer. The number of controls' siblings was 2,556 and, of these, 11 were affected by the disease. In our data there is no known case of lung cancer in the offspring of the study population. Therefore, the joint evaluation of first degree relatives is limited to data on parents and siblings.
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TABLE 4. Odds ratios for lung cancer in first degree relatives (parents, siblings) according to case-control status of study participants by age group, Germany, 19881993
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Joint analysis based on the generalized estimating equations' technique reveals a constant increase in lung cancer risk of about 70 percent among case families after various adjustments (table 4). As in the analysis of the parental data, this effect is particularly pronounced in young study subjects. When using the generalized estimating equations' approach to examine the associations between case-control status and smoking-related and all cancers, respectively, we found that a similar effect could not be detected (data not shown). Altogether, 430 (9.2 percent) parents and siblings of cases and 417 (9.2 percent) parents and siblings of controls were affected by any type of cancer. In addition, there were six cancers occurring among the offspring of cases and 10 among the offspring of controls.
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Parental lung and other smoking-related cancer and parental smoking
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For the whole parental group, cancer risk from smoking is of a magnitude that is in line with established knowledge (5
). However, when calculating these risk estimates separately for parents of cases and parents of controls, we found that lung cancer risk is especially pronounced in cases' parents while for other smoking-related neoplasms this phenomenon cannot be detected (table 5).
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TABLE 5. Odds ratios for parental cancer according to parental smoking by study subjects' case-control status, Germany, 19881993
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DISCUSSION
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The results of our investigation indicate that lung cancer aggregates in families to some extent. Findings from different analytical approaches support this point: We detected an elevated risk for those persons whose father or siblings were affected by the disease. For those with paternal lung cancer, we found a risk elevation in both male and female participants. In addition, an overall familial aggregation is indicated by the results of the generalized estimating equations' approach, particularly in young subjects. Finally, we found "clusters" of lung cancer for the most part in relatives of cases.
Some of our findings even fit the hypothesis that genetic and not merely any familial mechanisms contribute to this aggregation: 1) familial lung cancer risk is particularly increased in young cases; 2) we detected an increased familial risk for lung cancer only but not for other smoking-related or other cancers in general; 3) familial lung cancer risk remains elevated after the adjustments for various other risk factors; and 4) smoking had a particularly deleterious impact on the parents of cases. Again, this effect was seen for lung cancer only. These results imply that differences in smoking behavior between families of cases and controls do not sufficiently explain differences in familial lung cancer risk.
Our finding that the aggregation seems to be limited to lung cancers and is not reflected in an aggregation of other cancers is in line with some of the results previously reported (22
, 23
). Other investigators found an increased lung cancer risk when relatives were affected by any cancer (17
, 18
, 20
, 25
, 29
, 42
), any smoking-related cancer (
, 24
, 43
), or a cancer at particular sites, that is, the digestive tract and female breast (43
). It should be noted though that some of the results were obtained when limiting the analysis to certain subgroups such as young lung cancer cases with young affected relatives (24
) or nonsmoking study subjects (43
) with several diseased family members (17
, 20
). Sometimes, the category "any cancer" (18
, 20
, 29
) or "any tobacco-related cancer" (24
, 43
) included lung neoplasms, which might explain the risk elevation.
The notion of a genetic contribution to lung cancer development derives support from several types of studies. First, the examination of host susceptibility markers in molecular epidemiologic and other studies has pointed at the role of polymorphisms in genes coding for phase I activating (CYP1A1, CYP2D6, CYP2E1) and phase II detoxifying (GSTM1, GSTT1) enzymes. More recently these studies have begun to evaluate whether germ-line mutations and polymorphisms in oncogenes (ras) and tumor suppressor genes (p53) are potentially useful markers of genetic susceptibility (12
, 44

47
). Despite an increasing body of evidence for the contribution of gene polymorphism in phase I and II enzymes to lung cancer development, the results of such investigations are inconsistent and controversial (48


52
). This is also true for those studies applying quantitative genetic methods, such as examination of heritability (53
, 54
) and segregation analysis (55
57
). In general, the former is being used to assess the relative importance of genetic and environmental factors for disease susceptibility, and the latter is being used to test specific models of inheritance in order to find the one that best describes the data at hand. Finally, classic epidemiologic studies such as ours have detected a familial aggregation of lung cancer (8
, 17










29
). Some of these exclusively recruited non- or exsmokers to eliminate the confounding impact of active smoking (20
22
).
However, results of epidemiologic studies on familial aggregation require careful interpretation. With family members sharing lifestyle and other environmental factors, it is difficult to provide conclusive evidence that accumulation of a disease has a genetic origin. Another limitation of this design when used in genetic studies is that information on the exposure, that is, having a family history of a particular disease, is often provided by the study participants themselves without the possibility to verify the diagnosis through medical sources or health records. We also have to deal with this limitation that potentially results in some misclassification in our study. However, a potential nondifferential misclassification of familial lung cancer would usually lead to an underestimation of the true risk and therefore could not explain the risk elevation.
We examined the frequencies of lung cancer development in relatives as a primary or secondary form of the disease on the basis of the age information available. In only two instances (both among relatives of cases) did the disease occur after a different primary cancer. Additionally, in 12 relatives (five among cases and seven among controls), the order of disease development could not be identified. Exclusion of all 14 relatives would lead to a stronger reduction in lung cancer prevalence among controls' relatives and would therefore increase the risk estimate. Sole exclusion of the two case relatives who developed lung cancer after another neoplasm, however, would lead only to a slight decrease of the odds ratios.
Another, more serious concern raised in this context is that of recall bias causing differential misclassification. We do not believe that recall bias has severely distorted our results for two reasons. First, we think that lung cancer in a first degree relative is a disease severe enough to be remembered by both cases and controls without either of them having to search hard in their memory. Second, we have assessed this issue in our study by asking participants about multiple sclerosis in their relatives, a disease which is also severe but supposedly unrelated to lung cancer development. We found about the same number of relatives with multiple sclerosis in both cases and controls, even slightly more in the families of controls. Moreover, when comparing overall recall of diseases in family members, we found a slightly higher recall of diseases in controls compared with cases.
We also checked the possibility of a selection bias arising from nonresponse. Cases' representativeness in terms of age, sex, and histology had previously been examined and confirmed for the region of Bremen, the place of residence for 92 percent of the original study population (31
). In the comparison of the survival of the cases with mortality statistics, the reference to the eligible study base was assessed for the city of Bremen and confirmed for those up to age 75 who formed about 96 percent of the original study population. For controls, the reasons for nonparticipation were assessed (31
). The reasons relating to health (20 percent) and absence from the region (7 percent) were the two main issues provided. We were concerned that those refusing to participate for health-related reasons had a comparatively low socioeconomic status that would bias the odds ratios. We checked the changes in risk estimates after adjusting the analyses for socioeconomic status, as measured by school and professional education, and did not find a relevant change in estimates; therefore we do not present the data. Overall, there is no indication that refusal to participate could have biased the results presented here.
We had to deal with the issue of missing values that were present for some of the variables considered in our analyses. We conducted complete-case analyses; that is, we excluded participants with missing information, after checking whether dependencies between the missing values in disease and exposure status existed that could lead to biased estimation of the parameters and their variance (58
, 59
). As mentioned earlier, some of the cases and controls had dropped out of the interview or did not provide any information on familial health that was ascertained in the final part of the interview. This happened most frequently when persons had many different occupations during their lives that resulted in particularly lengthy interviews. Although there is some dependency between case-control status and missing data on familial health, a complete-case analysis seems to be adequate for several reasons. First, this dependency is for some part a result of differences in job histories between cases and controls. Second, familial lung cancer is an exposure rare enough to assume that only very few cases of it were missed by excluding these 80 subjects. Third, with familial lung cancer as the main exposure and not merely a covariate, exclusion of subjects who do not provide information is justifiable.
Furthermore, information on parental smoking and parental age was incomplete. We found no relevant dependency between completeness of information on parental smoking and case-control status, parental lung cancer, parental gender, study subjects' smoking status, and matching variables, respectively. The probability of providing information on parental age was independent of parental lung cancer, which is the outcome in the analysis; these results are presented in table 5. Although this probability was dependent on study subjects' smoking status and parents' sex, that is, a bigger share of information was provided by nonsmoking participants and on maternal age, a complete-case analysis should yield unbiased estimates.
Compared with certain previous studies, ours has several advantages. First, the study is population based. Second, the study population is large. Third, we have taken several steps to avoid some of the biases usually arising when summarizing family history of disease in one dummy variable (60
). For instance, we have applied generalized estimating equations to account for intrafamilial phenotypic correlations and for differences in family size. Another strength of our study is that it makes an intensive effort to measure exposure to smoking and asbestos, which are undisputed risk factors for lung cancer (5
) and jointly affect lung cancer risk synergistically (61
, 62
). In addition, we were able to include information on parental smoking in the model. The lower degree of smoking in women in the generations of both the study participants and their parents is reflected in both the low prevalence of lung cancer in mothers compared with fathers and in the different distributions of lung cancer in the male and female study subjects. Though we cannot rule out residual confounding originating from other familial components or from inadequate measurement of the factors considered, we have thus accounted for major potential confounders. However, we were surprised to find that adjustment for these factors did not considerably change the risk estimates. An explanation for this may be that, despite their important role as risk factors, they lack specificity in lung cancer development and show a low level of prediction of this outcome.
Altogether, these findings support the idea that genetic susceptibility might act as both an independent risk factor and an effect modifier of exogenous risk factors, with smoking being the most important one.
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NOTES
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Reprint requests to Katja Bromen, Institute of Medical Informatics, Biometry, and Epidemiology, University of Essen, Hufelandstr. 55, 45122 Essen, Germany (e-mail: katja.bromen{at}uni-essen.de).
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Received for publication June 22, 1999.
Accepted for publication December 16, 1999.