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* From the Divisions of Radiation Oncology (Dr. Garces), Epidemiology (Dr. Yang), and Biostatistics (Ms. Parkinson, Ms. Zhao, Mr. Wampfler, and Dr. Sloan), and Community Internal Medicine (Dr. Ebbert), Mayo Clinic College of Medicine, Rochester, MN.
Correspondence to: Ping Yang, MD, PhD, Mayo Clinic, Charlton 6, 200 First St SW, Rochester, MN 55905; e-mail: yang.ping{at}mayo.edu
| Abstract |
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Design and setting: The LCSS was mailed to eligible patients (1,506 patients) between 1999 and 2002. LCSS scores (total and individual QOL components) were compared among different groups of cigarette smokers via univariate independent group testing and multivariate linear models. The modeling process examined group differences adjusted for age, gender, stage, and time of LCSS assessment. LCSS scores were transformed onto a scale of 0 to 100 points in which higher LCSS scores corresponded to a lower QOL. A 10-point difference between groups was defined a priori as being clinically significant.
Results: At the time of lung cancer diagnosis, 18% of the patients were never-smokers, 58% were former smokers, and 24% were current smokers. Among survey respondents completing the LCSS at follow-up assessment (1,028 respondents), the mean age was 65.2 years (SD, 10.8 years) and 45% were women. Thirty percent of baseline current smokers continued to smoke at the time of the follow-up assessment (ie, persistent smokers). The adjusted mean total LCSS scores for never-smokers and persistent smokers were 17.6 (SD, 4.02) and 28.7 (SD, 5.09), respectively (p < 0.0001). Seven of the individual LCSS QOL components (ie, appetite, fatigue, cough, shortness of breath, lung cancer symptoms, illness affecting normal activities, and overall QOL) were clinically and statistically (p < 0.001) different between never-smokers and persistent smokers. No clinically significant differences were noted for pain or hemoptysis. Former smokers had intermediate LCSS scores. No dose-response trends were observed between the number of packs of cigarettes smoked per day or the total number of pack-years smoked and the adjusted scores.
Conclusion: The hypothesized relationship between smoking status and QOL was supported by this correlational study. Our findings suggest that persistent cigarette smoking after a lung cancer diagnosis negatively impacts QOL scores.
Key Words: lung neoplasms quality of life non-small cell lung carcinoma small cell carcinoma smoking cessation tobacco
| Introduction |
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The available evidence suggests that smoking abstinence at the time of cancer diagnosis improves local control and survival.9101112 QOL measures can guide treatment recommendations13 for interventions with favorable risk/benefit ratios that improve QOL. If smoking cessation after lung cancer diagnosis improves QOL among lung cancer patients, this information could provide physicians with additional motivation to help current smokers quit after they receive a lung cancer diagnosis.
To our knowledge, no studies have attempted to correlate the tobacco history of lung cancer patients with their QOL in a detailed and systematic fashion. The purpose of this study was to determine the impact of the tobacco history of lung cancer survivors on QOL. Our hypothesis was that current smokers would have QOL scores that were indicative of a lower QOL than people who had never smoked. We further hypothesized that former smokers would have QOL scores somewhere between the current and never-smokers. We assessed cigarette-smoking patterns at the time of lung cancer diagnosis and at follow-up to determine the impact of cigarette smoking on patients QOL, as measured by the lung cancer symptom scale (LCSS).
| Materials and Methods |
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Follow-up
At the time of study enrollment, each patient was informed about a six-step follow-up (ie, at 6 months and 1 year, and annually thereafter) in the upcoming 5 years.15 These follow-up assessments were mailed. A total of 1,506 living patients were eligible for follow-up, 1,251 were sent the LCSS questionnaire in the follow-up material, and 1,028 responded to their first requested QOL questionnaire (response rate, 82%). The 1,028 respondents made up the study population in the LCSS analysis. We defined the 478 patients on whom we did not have LCSS data as nonrespondents. The first LCSS follow-up assessments were made with patients at various times from their diagnosis date, as follows: 6 months, 344 of 1,028 patients (33%); 1 year, 308 of 1,028 patients (30%); 2 years, 254 of 1,028 patients (25%); and 3 years, 122 of 1,028 patients (12%). A small number of patients (81) who received their first follow-up with the LCSS at 4 or 5 years from the diagnosis date were excluded. Therefore, the study design is cross-sectional with variable times from diagnosis to the QOL assessment.
QOL Instrument
The QOL assessment for this study utilized the patient portion of the LCSS, version 2. This scale was developed by investigators at Memorial Sloan Kettering Cancer Center and has been shown to be a psychometrically sound index for assessing lung cancer patient QOL.1617 The LCSS consists of nine individual items, and the total score is the average sum of those nine individual items. The first six items of the LCSS represent measures of the specified lung cancer symptoms, including appetite, fatigue, cough, shortness of breath, hemoptysis, and pain. The remaining three items measure general lung cancer symptoms, how the illness affects normal activities, and overall QOL. The items were ranked on a visual analog scale of 0 to 100 mm, in which a check mark at 0 mm would represent no symptoms and a check mark at 100 mm would represent the maximum number of symptoms. The health professional portion of the LCSS was not utilized because the follow-up assessments were mailed to patients.
Tobacco Use History
Definitions of Subcategories of Smokers:
Information on tobacco history is based on self-report. Smoking status was unknown in nine patients who were excluded from the analysis. Never-smokers were those indicating that they had smoked < 100 cigarettes in their lifetime and were not current smokers. Former smokers were those reporting that they had previously smoked > 100 cigarettes in their lifetime and were not currently smoking. Current smokers were those who reported that they were smoking at the time of their cancer diagnosis. In addition to these established definitions, we added descriptors to fully characterize the smoking patterns of patients at baseline and at the first LCSS follow-up assessment. A former smoker is described as a former smoker who was not smoking at diagnosis or at follow-up. A relapsed former smoker is described as someone who was not smoking at diagnosis but had relapsed to smoking cigarettes at the time of follow-up. A persistent smoker describes a current smoker at diagnosis and at follow-up. And, an abstinent smoker describes a patient who was a smoker at diagnosis but became abstinent from smoking at the time of follow-up.
Definitions of Dose-Response Categories
The cigarette dose-response categories were defined as self-reported packs per day (PPDs) as well as the total number of pack-years of smoking history. For the persistent, abstinent, and former smokers, PPD categories were created for those who smoked > 0 to
0.5 PPD, > 0.5 to
1 PPD, and > 1 PPD. We calculated the total number of pack-years by multiplying the self-reported number of PPDs by the number of years of regular cigarette smoking.
Statistical Analysis
Baseline demographics were summarized utilizing mean, SD, and range for continuous variables, and frequency or percent for categoric variables. The association between the LCSS and covariates was determined utilizing the Spearman correlation. A clinically significant correlation was defined as one with an observed coefficient of
0.30.18 A two-sample t test was utilized to look for associations between gender and the LCSS. To compare the differences in the LCSS items for the different groups of cigarette users as well as for the dose-responses (ie, PPDs and total number of pack-years), a multivariate regression model was developed. Although no clinically significant correlations were found among the covariates and the LCSS scores, an adjusted multivariate model was utilized due to the likelihood that the covariates could be associated with the LCSS assessment and because of the uneven distribution of some of these factors among the different groups. The model was adjusted for age at diagnosis, gender, disease stage, and time of follow-up assessment since diagnosis (ie, 6 months, 1, 2, or 3 years).
The total LCSS score and the individual items ranged from 0 (no symptoms) up to 100 (maximal amount of symptoms) with a 10-point difference between groups being considered a clinically significant difference.19 Because multiple comparisons were made, we thought that a conservative approach would be to define statistical significance as two-sided p values of
0.001. We did not adjust or interpolate for missing data or for missing individual items, as the number of missing items was inconsequentially small (fewer than five). A statistical software package (SAS, version 8.0; SAS Institute; Cary, NC) was utilized for the analysis.
| Results |
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80 years of age (respondents, 7%; nonrespondents, 6%). No significant differences were noted between respondents and nonrespondents for SCLC stage, gender, race, number of PPDs or total number of pack-years, and other current or past cigar, pipe, or smokeless tobacco use. Among respondents, the mean age was 65.2 years (SD, 10.8 years), and 45% were women. The majority of respondents had NSCLC (92%), and the remainder had SCLC. Among those patients with NSCLC, 50.8%, 11.8%, 23.6%, and 13.7%, respectively, had stage I, II, III, or IV disease, and 69.2% of the SCLC patients had limited-stage disease (Table 1 ).
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Tobacco Use Status at Baseline and Follow-up
At the time of diagnosis, 18% of the patients (n = 180) were never-smokers, 58% (n = 591) were former smokers, and 24% (n = 248) were current smokers. None of the never-smokers reported smoking at the time of the first follow-up assessment. Among former smokers, 95% (n = 562) remained abstinent at the first follow-up; however, 5% (n = 29) had relapsed to smoking at their first follow-up (ie, relapsed former smokers). Among current smokers, 70% (n = 173) had quit smoking at the time of the follow-up (ie, abstinent smokers). However, 30% (n = 75) continued to smoke at the time of their follow-up (persistent smokers) [Table 2 ].
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Correlations Between Potential Covariates and the Unadjusted LCSS Scores
Age, race, marital status, baseline and follow-up treatment types (ie, surgery, radiation, and chemotherapy), the timing of treatment in relation to follow-up assessment (ie, before, during, or after), the number of pack-years they had smoked, cancer stage, cigar smoking, pipe smoking, smokeless tobacco use, and alcohol use were all assessed for correlations with the LCSS score. We found no clinically significant associations (Spearman correlation coefficients all showed weak correlations). Female gender was associated with better LCSS scores (p < 0.0001 [two-sample t test]). However, the mean difference was 4.4 points on the LCSS. Although this is less than a clinically significant difference (ie, 10 points), we did keep gender in the model along with age at diagnosis, stage, and time of assessment. We chose not to adjust for active treatment during the QOL assessment as determined by a sensitivity analysis (described below).
LCSS
Total Adjusted LCSS Scores:
The adjusted mean total LCSS scores for the never-smokers and persistent smokers were 17.6 (SD, 4.02) and 28.7 (SD, 5.09), respectively (p < 0.0001), while former smokers (abstinent and relapsed) had adjusted mean total LCSS scores that were similar to those of never-smokers (former smokers, 19.8; SD, 4.12; never-smokers, 20.0; SD, 4.9). The abstinent smokers had an adjusted mean total LCSS score of 22.1 (SD, 4.03) [Fig 1
, Table 3
]. The relapsed former smokers were not included in subsequent analyses due to the small number of patients (29 patients) in this category, so the adjusted score for this group should be interpreted with caution. The lower QOL scores correspond to a better QOL among never-smokers compared to persistent smokers who had the highest scores and the worst QOL.
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Sensitivity Analysis for Treatment During Follow-up Assessment
There were 11 patients who completed the follow-up assessment while they were receiving chemotherapy and/or radiation. There were also 167 patients who had reported receiving chemotherapy, but no end date was provided. Therefore, it was possible that these patients were receiving chemotherapy during their assessment and as a result might have higher (worse) LCSS scores. We developed a second multivariate regression model that, in addition to the other covariates (ie, age, gender, stage, and time of assessment), also adjusted for any active treatment received during the follow-up assessment. The model was run under two different scenarios with an estimated minimal length of chemotherapy (3 months) and maximal (7 months) length of chemotherapy (with 1 month of recovery from chemotherapy). We found no differences in the model under either scenario compared to our original model (data not shown).
Dose-Response Data Across All Times
We evaluated the dose-response trend of the LCSS scores and PPDs, as well as of the total number of pack-years of tobacco use among the persistent smokers, abstinent smokers, and former smokers. The hypothesis was that for an increasing number of PPDs smoked per day as well as for an increasing total number of pack-years smoked that the persistent smokers would have a lower QOL. The abstinent smokers and former smokers also were assessed. This portion of the project was viewed as exploratory and hypothesis-generating due to the small number of patients in each category, as described in Table 2. The LCSS scores were adjusted for age, gender, stage, and time of follow-up evaluation.
Among the persistent smokers, we found no clinically or statistically significant dose responses for increasing (worse) LCSS scores and increased amount of tobacco use when they were described as PPDs or total number of pack-years (data not shown). However, a pattern of increasing LCSS scores was noted for increasing PPDs smoked, but not for increasing total number of pack-years. The total number of smokers was small (74 smokers), and the number of smokers using
0.5 PPD (2 smokers) and with a history of 1 to 20 pack-years (3 smokers) was very small, so the results should be interpreted with caution. Similarly, among the abstinent smokers we found no clinically or statistically significant differences for worsening LCSS scores between any of the PPD groups or total pack-year groups. Among the former smokers, there were statistically significant differences; however, no clinically significant differences (the majority were differences of only 2 to 3 points) were found for the PPD groups or for the total pack-year groups (data not shown).
| Discussion |
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Our findings are comparable to those found in the literature regarding how smoking effects QOL in both the general patient population and in specific subgroups (Table 4 ). In general, these selected studies1234568 found that patients who continued to smoke had worse assessments of their own QOL. For example, smokers thought that their general health was worse, and they had lower assessments of vitality and mental health across the different studies. Some reported that these patients also reported more difficulty with physical functioning,45 and correlated the worse QOL findings with respiratory problems5 and trouble walking and climbing stairs.6 Additional studies72021222324 with similar findings were not included in Table 4 for simplicity. Other studies have addressed QOL in lung cancer patients, but smoking history was not a major focus of these reports. One report25 found that smoking status was not predictive of QOL; however, this study was performed only in long-term survivors and had a small number of subjects, and the authors suggested that further study in this area is needed. On the other hand, current smokers undergoing surgery for lung cancer had lower mental health dimension and vitality scores than did former smokers and never-smokers.
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There are limitations to this study. First, selection bias due to self-referral or physician-referral and survival bias for being able to answer LCSS questions may have influenced the strength of our results. These potential biases are reflected by the differences between the respondents and nonrespondents to our study follow-up (eg, age at diagnosis, disease stage, and smoking status). To correct for this, our models were adjusted for age and stage of disease at diagnosis, and were stratified by smoking status. Second, the race and ethnicity of the study sample was predominantly white, so the generalizability of the study might be compromised by the limited sample of underrepresented minorities. Third, the patients smoking status may have fluctuated between diagnosis and follow-up, and biochemical confirmation of tobacco use status was not performed. It is known that a small percentage of subjects intentionally report incorrect smoking status, especially among adults.26 The Society for Research on Nicotine and Tobacco Subcommittee on Biochemical Verification27 has reported that biochemical verification might affect outcome among pregnant women with a history of alcohol use or depression as well as among patients in Veterans Affairs hospitals after surgery. However, verification did not affect the outcome among cancer patients, drug dependent patients, or primary care patients, thus supporting our contention that it is likely that a small percentage of patients falsely reported their smoking status.28 Finally, the numbers of patients in the dose-response categories are relatively small, so the data for them should be interpreted with caution.
Despite these limitations, the study has several strengths. To our knowledge, our study is among the first published reports to specifically address how cigarette smoking affects QOL among lung cancer survivors. The large number of patients who completed the assessments and provided smoking status enabled us to model the LCSS scores, and to adjust for age, gender, disease stage, and time of assessment. Changes over time or time trends will be forthcoming as we gather additional data from the patients. We hope to be able to provide data on the relapsed former smokers in the future. Survival-related outcomes and treatment-related outcomes, as they relate to smoking status, will be assessed as future aims with the entire cohort.
| Acknowledgements |
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| Footnotes |
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Dr. Garces was supported by National Institutes of Health grant CA90628 and by the Fraternal Order of the Eagles Cancer Grant Fund. Dr. Yang was supported by National Institutes of Health grants CA80127 and CA84354.
Received for publication March 4, 2004. Accepted for publication June 7, 2004.
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