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(Chest. 2004;125:27-37.)
© 2004 American College of Chest Physicians

Smoking and Lung Cancer Survival*

The Role of Comorbidity and Treatment

C. Martin Tammemagi, PhD; Christine Neslund-Dudas, MA; Michael Simoff, MD, FCCP and Paul Kvale, MD, FCCP

* From the Josephine Ford Cancer Center (Dr. Tammemagi and Ms. Neslund-Dudas); and Pulmonary Critical Care Medicine (Drs. Simoff and Kvale), Henry Ford Health System, Detroit, MI.

Correspondence to: C. Martin Tammemagi, PhD, Josephine Ford Cancer Center, 1 Ford Place, 5C, Detroit, MI 48202-3450; e-mail: mtammem1{at}hfhs.org


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Study objectives: Numerous studies indicate that smoking is associated with poorer outcomes in patients with cancer. The aim of this study was to determine whether smoking independently predicts survival in patients with lung cancer or whether an existent effect is mediated through comorbidity and/or treatment.

Design and setting: Cox proportional hazards analysis was used to study a cohort of 1,155 patients with lung cancer diagnosed at the Henry Ford Health System between 1995 and 1998, inclusive.

Results: Adjusted for the baseline covariates, age, gender, illicit drug use, adverse symptoms, histology, and stage, the hazard ratio (HR) for smoking (current vs former/never) was 1.37 (95% confidence interval [CI], 1.18 to 1.59; p < 0.001). Adjusted for the baseline covariates and for 18 deleterious comorbidities, the HR for smoking was 1.38 (95% CI, 1.18 to 1.60; p < 0.001), indicating that the hazardous effect of smoking was not mediated through comorbidity. Current smoking was inversely associated with treatment (any surgery and/or chemotherapy and/or radiation therapy vs none) [odds ratio, 0.73; 95% CI, 0.55 to 0.98 (p = 0.03)]. Adjusted for baseline covariates, comorbidities and treatment, the HR for current smoker vs former/never was 1.26 (95% CI, 1.08 to 1.47; p = 0.003), a decline of 30.7% explained by treatment (HR for any treatment vs none, 0.40; 95% CI, 0.33 to 0.48; p < 0.001).

Conclusions: Current smoking at diagnosis is an important independent predictor of shortened lung cancer survival. That this effect was not explained by sociodemographic/exposure factors, adverse symptoms, histology, stage, comorbidity, and treatment suggests that it may be mediated through direct biological effects.

Key Words: comorbidity • lung neoplasm • smoking • survival • symptoms • treatment


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Smoking has been associated with decreased survival following diagnosis with a variety of cancers, including head and neck,1 2 kidney,3 4 5 prostate,6 7 8 9 10 colorectal,11 breast,8 12 13 14 15 16 and vulvar17 cancers, and leukemia18 and malignant melanoma.19 20 Studies have found that in patients with lung cancer, smoking is associated with cancer recurrence, lung cancer-specific and all-causes mortality, as well as with strong predictors of survival, such as weight loss.21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 An association between smoking and lung cancer survival was not observed in all studies.40 41 42 43 44 45 46 47

Smoking is associated with many factors that may contribute to poorer cancer survival: lower socioeconomic status (SES),48 49 poorer nutrition,50 51 52 comorbidity,53 impaired immune function,54 55 56 57 58 and an increased mutation burden that could lead to accelerated carcinogenesis and progression.38 59 60 61 62 Of these, comorbidity may be one of the most important determinants, as smoking is strongly associated with numerous serious diseases, in addition to lung cancer. The US Surgeon General concluded that cigarette smoking accounts for 82% of COPD deaths, 21% of coronary heart disease deaths, and 18% of deaths from stroke.63 Cigarette smoking is also associated with hypertension, atherosclerosis, aortic aneurysm, peripheral vascular diseases, pulmonary tuberculosis, pneumonia, and asthma,64 and with cancers of the larynx, mouth, esophagus, bladder, pancreas, kidney, cervix, and possibly cancers of the colon and liver, and acute myeloid leukemia.65 Thus, patients with lung cancer and a history of heavy smoking or ongoing smoking are at risk of death from a spectrum of smoking-associated diseases. Although it is a common perception that almost all patients with lung cancer die specifically from lung cancer, this is not necessarily the case. Several studies25 38 44 66 have found that approximately 20 to 40% of patients with nonmetastatic lung cancer died without evidence of cancer progression. Thus, the association between smoking and shortened survival, at least in nonmetastatic lung cancer, may be caused by smoking-related comorbidities.

In addition, smokers may have shorter survivals because they receive less aggressive or complete treatment, possibly because smoking is associated with lower SES,67 which might impede smokers from seeking out and/or obtaining optimal treatment, or because smoking has led to impaired pulmonary function or comorbidity that precludes preferred therapies. The aim of the current study is to determine whether tobacco smoking predicts survival independently of important prognostic factors and to determine whether survival effects are mediated through comorbidity and/or treatment.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
A historical cohort study was carried out in the Henry Ford Health System to evaluate the impact of comorbidity, smoking, and other factors on the survival of patients with lung cancer. Study subjects, identified through the Josephine Ford Cancer Center Tumor Registry, had primary bronchogenic lung cancer diagnosed between January 1, 1995, and December 31, 1998, and received their principal care at the Henry Ford Health System. The study was limited to black and white patients because all other race/ethnic groups combined accounted for only 1% of patients. The study received Institutional Review Board approval.

Sociodemographic, exposure, clinicopathologic, treatment, and survival data were collected by abstraction of electronic medical records and from the Josephine Ford Cancer Center Tumor Registry. Sociodemographic data included age, gender, race/ethnicity, SES, and marital status. SES was estimated using block group median household income (BGMHI) derived from patient address at diagnosis and 1990 US census data.

Smoking data included pack-years smoked (PY) [the average number of packages of cigarettes smoked per day multiplied by the number of years smoked]; smoking status was defined as never smoker, former smoker, current smoker, and quit time in former smokers. Smokers who claimed to have quit in the 4 weeks prior to diagnosis were classified as current smokers, as their ability to sustain a prolonged abstinence from smoking was in question.

Clinicopathologic data included comorbidity, tumor histopathology, and stage. Data on 56 categories of comorbidity were collected from all available computerized medical records from the period of first suspicion or symptom/sign of lung cancer until patient assessments in all relevant departments were complete, which usually occurred within 2 to 3 months of diagnosis. The total number of comorbid conditions per individual was evaluated and is referred to as comorbidity count.

In a previous analysis of the 56 comorbidities in this study population, it was found that 18 comorbidities were independent, important predictors of reduced survival: HIV/AIDS, tuberculosis, previous metastatic cancer, thyroid/glandular (nondiabetic) disorders, electrolyte/mineral imbalance, anemia (pretreatment), blood disorders (other than primary anemia), dementia, neurologic disease, congestive heart failure (CHF), COPD, asthma, pulmonary fibrosis, liver disease, GI hemorrhage, renal disease, musculoskeletal/connective tissue disorders, and osteoporosis.68 In addition, hoarseness, dyspnea, chest pain (nonangina), extrathoracic pain, neurologic symptoms, weight loss, fatigue/weakness, and hemoptysis were symptoms that were associated with relatively higher/advanced stage and/or reduced survival (manuscript submitted for publication). The label adverse in the text will identify these comorbidities and symptoms, respectively.

In modeling, American Joint Committee on Cancer TNM stage groups69 were generally treated as categorical variables with five levels (I, II, III, IV, and unstaged). Six lung cancer histotypes based on the World Health Organization histologic classification system70 were coded by indicator variables into the following categories: squamous cell carcinoma (SqCC), adenocarcinoma, bronchioloalveolar carcinoma (BAC), small cell lung cancer (SCLC), other defined histotypes pooled (including large cell and mixed types), and bronchogenic carcinoma not otherwise specified (NOS). Treatment data were analyzed as four dichotomous variables: surgery, chemotherapy, radiation therapy, and treatment (any vs none).

Statistical Methods
Descriptive analyses comparing categorical variables were carried out using Fisher exact tests, between continuous and two-level categorical variables using t tests, and between categorical and ordinal variables using Mantel-Haenszel {chi}2 tests for trend. Because of the skewed nature of quit-time data, it was studied using quantile (median) regression.71 Multivariate logistic regression modeling was used to estimate the strength of association between variables using odds ratios (ORs) and 95% confidence intervals (CIs).72 Survival effects were evaluated at the univariate level using the product-limit life-table method and associated Kaplan-Meier survival plots73 and log-rank tests,74 and at univariate and multivariate levels using Cox proportional hazards regression modeling.75 SAS 8.0 (SAS Institute; Cary, NC), S-Plus 6 (Insightful Corporation; Seattle, WA), and Stata 7.0 (Stata Corporation; College Station, TX) softwares were used to prepare the figure and statistics. All reported p values are two sided.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
The sample consisted of 470 women (41%), 685 men (59%), 462 blacks (40%), and 693 whites (60%). The distribution of selected sociodemographic, smoking, clinicopathologic, and treatment variables, stratified by gender and race/ethnicity, are presented in Table 1 . The mean age of subjects was 67.2 years, and age did not differ significantly by gender and race/ethnicity. SES was considerably lower in blacks than in whites (BGMHI, $19,903 vs $38,812; p = 0.0001). Being without a spouse was significantly more common in women compared to men (52.7% vs 35.4%, p = 0.001) and in blacks compared to whites (50.4% vs 37.1%, p = 0.001). The histopathologic groups considered in analysis included 299 SqCC (25.9%), 382 adenocarcinoma (33.0%), 19 BAC (1.7%), 42 other defined types pooled (3.6%), 138 SCLC (11.9%), and 275 bronchogenic carcinoma NOS (23.8%). Stage distribution did not differ appreciably by gender, but did by race/ethnicity, with blacks having significantly more advanced stage at diagnosis (p trend = 0.01) and unstaged disease (p = 0.006) [Table 1 ].


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  		Table 1. Distributions of Sociodemographic, Smoking, Clinicopathologic, and Treatment Variables by Gender and Race*

 
Smoking status data were available for 1,116 of 1,155 patients (96.6%). Overall, 8.3% were classified as never smokers, 43.8% were former smokers, and 47.9% were current smokers. The mean PY in former smokers was 54.7, and in current smokers was 59.5. PY was significantly greater in male smokers compared to female smokers (61.4 PY vs 50.7 PY in ever smokers, p = 0.0001), and in white smokers compared to black smokers (62.6 PY vs 48.8 PY in ever smokers, p < 0.0001), and these patterns were present in both former and current smokers (Table 1) . The median quit time in former smokers was 8.0 years, and did not differ significantly by gender or race/ethnicity (Table 1) .

The hazard ratio (HR) for former smokers was more similar to the HR for never smokers than it was for current smokers: HR for former vs current, 0.75; HR for never vs current, 0.72. For this reason and because the size of the never-smoking group was small, in analysis the hazard for current smokers was compared to former and never smokers pooled. In analysis, the smoking variable that was the strongest, most robust predictor of survival was current smoking status at diagnosis. Adjusted for stage, PY appeared to have a modest impact on survival (HR per 40 PY, 1.10; 95% CI, 1.02 to 1.19; p = 0.02). However, this effect diminished with adjustment for other covariates. In the model adjusted for relevant baseline covariates (age, gender, illicit drug use, adverse symptoms, histology, and stage) and including both smoking status and PY, the hazard associated with smoking status endured (HR for current vs former/never, 1.30; 95% CI, 1.10 to 1.53; p = 0.002), while the effect of PY approached the null (HR per 40 PY, 1.00; 95% CI, 0.90 to 1.10; p = 0.93). The following report focuses on associations between current smoking and survival.

The median survival for current smokers was 0.76 years (95% CI, 0.67 to 0.89), and for former/never smokers was 1.01 years (95% CI, 0.89 to 1.15) [Fig 1 ]. The univariate HR for current smoking at diagnosis was 1.29 (95% CI, 1.12 to 1.48; p < 0.001). In addition, in univariate Cox analysis, shortened survival was associated with older age, male gender, African-American race/ethnicity, lower SES, marital status (being spouseless), illicit drug use, having adverse histologic types (SCLC or carcinoma NOS), adverse symptoms, adverse comorbidities, advanced stage and unstaged disease, and nonreceipt of treatment (Table 2 ). In multivariate analysis, race/ethnicity, SES, and marital status were not independent predictors of survival. Current smoking was associated with deleterious levels of 9 of the 12 aforementioned prognostic factors, all except for adverse comorbidity, unstaged disease, and advanced age. Current smokers were significantly younger than former/never smokers, and this was the only protective association that current smokers had. Considering specific adverse comorbidities, CHF was associated with not being a current smoker (OR, 0.59; 95% CI, 0.37 to 0.93; p = 0.02), and COPD was associated with being a current smoker (OR, 1.36; 95% CI, 1.05 to 1.76; p = 0.02). In multivariate analysis, current smoking was associated with younger age (OR per 10 years, 0.72; 95% CI, 0.63 to 0.82; p < 0.001), male gender (OR for male vs female, 1.45; 95% CI, 1.11 to 1.89; p = 0.007), lower SES (OR per $10,000, 0.87; 95% CI, 0.81 to 0.94; p = 0.001), being without a spouse (OR for spouseless vs not, 1.32; 95% CI, 1.01 to 1.74; p = 0.05), having an adverse tumor histology (OR for SCLC/carcinoma NOS vs other, 1.53; 95% CI, 1.17 to 2.02; p = 0.002), having COPD (OR, 1.55; 95% CI, 1.16 to 2.08; p = 0.003), and not having CHF (OR, 0.48; 95% CI, 0.28 to 0.81; p = 0.006). These observations suggest the possibility that the observed crude hazard associated with current smoking may in large part be mediated by other important prognostic factors.



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  		Figure 1. Kaplan-Meier survival plot describing the survival experience of 1,155 patients with lung cancer stratified by smoking status.

 

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  		Table 2. Prognostic Factors: HRs, Distributions, and Associations With Smoking Status

 
Cox proportional hazard models were prepared evaluating the independent hazard associated with smoking adjusted for baseline covariates (Table 3 , model A), and additionally adjusted for 18 specific adverse comorbidities (model B), and then additionally adjusted for receipt of treatment (model C). Adjusted for the baseline covariates age, gender, illicit drug use, adverse symptoms, histology, and stage, the HR for current smoking was 1.37 (95% CI, 1.18 to 1.59; p < 0.001) [Table 3 , model A]. In the Cox model that was additionally adjusted for 18 deleterious comorbidities, the HR for smoking was 1.38 (95% CI, 1.18 to 1.60; p < 0.001) [Table 3 , model B]. These findings indicate that the hazardous effect of smoking is independent of the 18 specific prognostic comorbidities. Indeed, when the model was adjusted for baseline covariates and all 56 comorbidities under study, the HR for current smoking was 1.37 (95% CI, 1.17 to 1.60; p < 0.001). Adjusted for the effects of the baseline covariates, 18 adverse comorbidities, and treatment, the HR for current smoking was 1.26 (95% CI, 1.08 to 1.47; p = 0.003); in this model, the HR for treatment was 0.40 (95% CI, 0.33 to 0.48; p < 0.001) [Table 3 , model C]. The multivariate HR for current smoking declined by 30.7% (HR, 1.378 vs 1.262) following adjustment for treatment. However, an important, independent effect of smoking remained after adjustment for important baseline covariates, comorbidity, and treatment. When the complete multivariate Cox model was adjusted for the effects of surgery, chemotherapy, and radiation therapy as three dichotomous variables in place of the single variable treatment, the HR for smoking was 1.30 (95% CI, 1.11 to 1.52; p = 0.001), confirming the important independent effect of current smoking. Adjusted for baseline covariates, comorbidity, and treatment, and additionally adjusted for race/ethnicity and SES, the HR for smoking was 1.27 (95% CI, 1.08 to 1.49; p = 0.005).


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  		Table 3. HRs (95% CI, p Values) for Variables in Multivariate Cox Models Excluding and Including Comorbidity and Treatment Variables

 
Subset analysis was carried out with stratified models adjusted for available baseline covariates and comorbidity count. The adjusted hazard associated with current smoking was observed in younger and older patients (HR for < 65 years, 1.34; HR for >= 65 years, 1.42), in both genders (HR for female patients, 1.38; HR for male patients, 1.38), and in both race groups (HR for blacks, 1.48; HR for whites, 1.31). The effect of current smoking was evident in both localized and advanced stage: HR in stage I, II, and IIIA, 1.35; HR in stage IIIB and IV and unstaged, 1.36. The median survival for the study population was 315 days. Current smoking was hazardous in short-term survivors (HR for follow-up < 315 days, 1.20) and in long-term survivors (HR for follow-up >= 315 days, 1.44). The HRs for smoking in histologic types were as follows: HR in SqCC, 1.29; HR in adenocarcinoma, 1.13; HR in SCLC, 1.32; and HR in carcinoma NOS, 2.04. These findings indicate that the hazard associated with smoking applies broadly to most subgroups of patients with lung cancer.


   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Current smoking at diagnosis increased the hazard of dying by approximately one third compared to former/never smokers, and this effect was observed in different age, gender, race/ethnic, histologic, and stage groups. Patients with lung cancer who were current smokers at diagnosis were more likely to have numerous negative prognostic factors. However, adjusted for important sociodemographic, exposure, clinicopathologic, comorbidity, and treatment factors, current smoking remained a significant independent predictor of reduced survival. By elimination, this suggests that the injurious effect of smoking on survival may be mediated by direct biological pathways acting on cancer progression, possibly through late mutational effects, smoking-associated oxidative tissue damage, or immune suppressive effects leading to cancer advancement. It is also possible that shorter survival in current smokers resulted from the postdiagnosis development of lethal comorbidities, which were not measured in this study.

That PY and former smoking were not as strongly related to survival as current smoking was suggests that the adverse effect of smoking on patients with lung cancer occurs relatively late. Indeed, the hazard associated with current smoking at diagnosis may in part be due to ongoing smoking that occurs after diagnosis, as has been suggested in SCLC.21 28 34 Manjer and colleagues14 similarly found in patients with breast cancer that the strongest hazard associated with smoking was with current smoking at diagnosis rather than with former smoking. Yancik et al16 studied the effect of age and comorbidity in patients with postmenopausal breast cancer. They found in Cox models that were adjusted for age, stage, and 10 comorbidities that the HR for current smoking was 1.54 (95% CI, 1.07 to 2.23).

Patients who were current smokers at diagnosis were at 1.39-fold greater risk of not receiving treatment than former/never smokers (OR for treatment vs no treatment, 0.72; 95% CI, 0.51 to 1.03; p = 0.07), after adjustment for the relevant covariates, age, marital status, adverse comorbidities (>= 1 vs 0), adverse symptoms (>= 1 vs 0), histology, and stage. The reasons for this finding are not clear and need investigation, as known predictors of treatment failed to explain the association between current smoking and nonreceipt of treatment.

The outcome in the current study was death from all causes. It might be expected that studying cause-specific mortality would help clarify whether the impact of smoking on survival is due to comorbidity (leading to competing causes of death) or cancer progression (leading to lung cancer-specific death). However, in the case of lung cancer this is not a straightforward matter, as a good deal of misclassification of cause of death can be expected.23 This is a consequence of lung cancer deaths being prone to "assignment bias"76 : individuals who have died with a history of lung cancer have lung cancer listed as the cause of death even if there was no evidence of recurrence or progression in carefully monitored patients. In the situation in which smoking is truly only associated with competing causes of death, ie, death directly from comorbidity, such misclassification would lead to a spurious association between comorbidity and lung cancer-specific death. This could be erroneously interpreted to indicate that comorbidity is associated with cancer progression. In addition, studying the effect of smoking exclusively on competing causes of death, putatively mediated by comorbidity, could lead to a biased underestimate of the impact of smoking. There are no compelling reasons to think that death in patients with lung cancer results from cancer or competing causes in a mutual exclusive manner. Smoking may lead to death through comorbidity and cancer progression or an interaction of the two pathways. For example, smoking can lead to comorbidities, such as COPD, which can directly lead to shortened survival (competing-causes death), and can lead to suboptimal cancer treatment, which in turn shortens survival due to cancer progression (cancer-specific death). Thus, evaluation of all-causes death as the outcome assesses the overall impact of smoking on survival better than analyzing either cancer-specific death or competing-causes death alone.

Demonstration of an association between smoking and recurrence/progression/metastasis might appear to support the hypothesis of a direct biological cause for the smoking/survival association. However, this approach may have a serious drawback, one that may lead to a null finding or reverse conclusion, even if a smoking-> carcinogenesis-> recurrence/progression/metastasis association exists. Compared to date-of-death data that have relatively minimal error, the date of detection of recurrence/progression/metastasis can be imprecisely measured, and data suggest that to an important extent this may depend on patient factors. African-American race/ethnicity, lower SES, and marital status (being spouseless) are associated with current smoking and as well with advanced stage at diagnosis, and the latter associations are thought to be mediated through disparities in resources, access to care, knowledge base, belief system, and social support. The ORs for the associations between race/ethnicity, SES (BGMHI per $10,000), and marital status and advanced stage (IIIB and IV vs I-IIIA) were as follows: OR for black race vs stage, 1.34 (95% CI, 1.02 to 1.77; p = 0.04), OR for SES vs stage, 0.93 (95% CI, 0.86 to 1.00; p = 0.04), and OR for spouseless vs stage, 1.56 (95% CI, 1.18 to 2.06; p = 0.002). The ORs between current smoking and race/ethnicity, SES, and marital status were as follows: OR for smoker vs blacks, 1.46 (95% CI, 1.14 to 1.85; p = 0.002), OR for smoker vs SES, 0.86 (95% CI, 0.80 to 0.93; p < 0.001), and OR for smoker vs spouseless, 1.41 (95% CI, 1.11 to 1.79; p = 0.005). Current smoking at diagnosis was associated with advanced stage at diagnosis in univariate analysis (OR for smoker vs stage, 1.35; 95% CI, 1.03 to 1.77; p = 0.03), but was much less so following adjustment for race/ethnicity, SES, and marital status (OR for adjusted smoke vs stage, 1.23; 95% CI, 0.92 to 1.63; p = 0.16). It is likely that disparities in sociodemographic factors that are associated with smoking status and advanced stage will also influence the intensity of patient follow-up and lead to delayed diagnosis of recurrence/progression/metastasis. Thus, shorter time to recurrence/progression/metastasis caused by smoking-induced biological effects may be masked by smoking-associated patient factors that lead to delayed diagnosis. It should be noted that unlike the smoking/stage association, the smoking/survival association endured adjustment for sociodemographic factors.

The current study findings need confirmation; if found to be real, these findings have public health, clinical, and research implications. The study findings reinforce the urgent need to convert smokers into former smokers. The hazardous effect of current smoking was independent of age at diagnosis and PY. Thus, efforts to convert elderly patients or individuals with a long or heavy smoking history should not be evaded, as has been the practice by some.77 Effective smoking cessation programs are available,78 and there is little reason to think that such programs conflict with cancer treatment or create excessive stress.79 80 Induction of smoking cessation in patients with lung cancer is not a futile undertaking and can be successfully achieved.81 82 In response to the report by Murin and Inciardi15 that smoking increased the risk of pulmonary metastases in patients with breast cancer, it has been suggested that vigorous treatment for achieving smoking cessation become part of standard therapy for patients with breast cancer who are smokers.83 This edict appears to apply to patients with lung cancer as well.

Lung cancer clinical trials should consider sampling stratified by smoking status or should measure smoking status and adjust for it in analysis. Clinicians may want to consider more intensive treatment and/or surveillance for those individuals with lung cancer who are recent or ongoing smokers. Future research should attempt to confirm the findings of the current study, to identify pathways involved, and to identify the role of postdiagnosis smoking in explaining the observed effect, as well as the impact of recidivism in former smokers. The effect of smoking on survival may be mediated through smoking-associated genetic alterations that promote cancer progression, smoking-associated tissue damage fostering metastatic spread, or immune depression inhibiting immune surveillance. Developing a better understanding of the underlying mechanism(s) may provide insight into lung carcinogenesis and uncover novel therapeutic approaches.


   Acknowledgements
 
We thank Drs. Joseph L. Lewis and Mei Lu for their reviews of the manuscript, and medical students Ginja B. Massey and Mandira Ray for assistance in abstracting data.


   Footnotes
 
Abbreviations: BAC = bronchioloalveolar carcinoma; BGMHI = block group median household income; CHF = congestive heart failure; CI = confidence interval; HR = hazard ratio; NOS = not otherwise specified; OR = odds ratio; PY = pack-years smoked; SCLC = small cell lung cancer; SES = socioeconomic status; SqCC = squamous cell carcinoma

This study was internally funded by the Henry Ford Health System.

Received for publication May 5, 2003. Accepted for publication July 22, 2003.


   References
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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