Abstract
Objective:
Smoking cessation improves quality of life (QOL) in the general population. However, there is limited information on the role of smoking status on QOL among cancer patients. Moreover, previous studies tended to analyze smoking status dichotomously and at a single point in time, potentially reducing the strength of the relation between smoking cessation and QOL. This study examined the association of smoking abstinence and QOL over time, including depression, pain, and fatigue in patients with a wide variety of cancers.
Methods:
Participants were 332 cancer patients (e.g., gynecologic, breast, thoracic, HN, genitourinary) who had been abstinent for at least 24 hours. Days abstinent and QOL were assessed at baseline and 2, 6, and 12 months later. Latent growth curve models examined if days abstinent was associated with QOL at each assessment. Baseline demographics (e.g., sex, income) and smoking history variables (e.g., nicotine dependence) were used as time-invariant covariates.
Results:
The final model for each QOL component had good-to-excellent fit. More days abstinent was associated with lower depression at all follow-ups and with lower fatigue at 12 months, but was not associated with pain.
Conclusions:
QOL was better among patients who quit smoking for longer periods. Findings suggest different timelines, with smoking abstinence most immediately associated with lower depression, followed by lower fatigue. Although pain decreased over time, it was not associated with length of smoking abstinence. Results reinforce the relationship between sustained smoking cessation and QOL, which should be communicated to patients.
Keywords: Cancer, Oncology, Quality of Life, Smoking, Smoking Abstinence
BACKGROUND
Over 16 million Americans suffer a disease caused by smoking, with cancer among the major health consequences. To date, smoking has been associated with at least 12 different types of cancer including lung, head and neck (HN), acute myeloid leukemia, bladder, cervix, colorectal, esophagus, kidneys, larynx, liver, pancreas, and stomach.1
Although a diagnosis of cancer is often associated with increased motivation to quit smoking, over one-third of cancer patients continue to smoke after diagnosis.2 Cancer patients, independent of cancer type, who continue smoking have an increased risk of developing second primary tumors, poorer cancer treatment efficacy, increased cancer recurrence rates, and greater mortality.1,3
Smoking after cancer has also been associated with poorer quality of life (QOL) in terms of physical (e.g., pain and fatigue), functional, social, and emotional well-being.4–7 Similar to the general population,8 patients with smoking-related cancers experience an improvement on some indices of QOL (e.g., pain, fatigue, cough, sleep, social functioning) when they quit smoking.5,9,10 However, previous studies tended to analyze smoking status dichotomously and at a single point in time, potentially reducing the strength of associations between smoking cessation and QOL. Thus, we sought to extend findings from previous research by analyzing changes of QOL over time as a function of days of smoking abstinence in a large sample of patients with a variety of cancer types. We used structural equation modeling to examine three of the most common domains of QOL in cancer patients that have also been associated with smoking status in patients with lung or HN cancers: depression,10 pain,11–13 and fatigue.13,14 We expected that greater number of days of smoking abstinence would be associated with lower depression, pain, and fatigue levels at each assessment point when controlling for the latent growth curve and other covariates. Furthermore, we expected that greater number of days abstinent would be associated with lower levels of depression, pain, and fatigue over time (i.e., more negative slope).
METHODS
This is a secondary analysis of data collected from a randomized control trial testing the efficacy of a targeted, multimodal, empirically-based smoking relapse prevention intervention for cancer patients who had recently quit smoking (i.e., within 3 months).15 All participants received standard of care. Those randomized to the intervention condition also received an educational DVD with smoking relapse-prevention information designed for cancer patients16 and 8 relapse-prevention booklets17,18 that were mailed over 3 months. Assessments were completed at baseline and at 2, 6, and 12 months post-baseline.
Participants
Participants were 412 cancer patients who: (1) received a diagnosis of cancer within the previous 90 days; (2) were ≥18 years; (3) smoked ≥10 cigarettes per day for ≥1 year prior to diagnosis; (4) were able to read/write English; (5) were able to give informed consent; (6) quit smoking for ≥24 hours after diagnosis; (7) were abstinent from smoking ≤3 months. All participants were receiving the first round of cancer treatment at a large NCI-designated Comprehensive Cancer Center. From the parent study, 80 participants were excluded because they died during the course of the study (Deceased, n=56) or did not complete any of the follow-ups (Non-completers, n=24). The final sample comprised 332 patients who completed baseline and at least one follow-up (Completers). Most participants completed three assessments (n=254), 49 completed two, and 29 completed one.
Procedure
Study procedures have been described previously.15 Briefly, potential participants were identified through an electronic capture and trigger system and informed about the study during a medical visit. Those interested were screened and, if eligible, were consented and enrolled. Follow-ups were conducted in person or by phone. The protocol was approved by the University of South Florida’s institutional review board (Pro00002292).
Measures
Demographics, clinical variables, and smoking history.
The baseline questionnaire included items assessing age, sex, race, ethnicity, education, marital status, income, cancer-related finances (“Do you have financial concerns related to your cancer?”), and employment status. Clinical data regarding cancer type, stage, treatment and comorbidity were obtained from medical records. Participants’ smoking history included number of years smoking and number of cigarettes per day. Items from the Fagerström Test for Nicotine Dependence (FTND)19 were reworded to measure nicotine dependence retrospectively to when they were regular smokers.
Smoking.
At baseline participants were asked about their smoking status for the prior 90 days. At each follow-up, we calculated cumulative days abstinent from pre-baseline up until each specific assessment by using the time-line follow-back (TLFB) procedure.20
Quality of life.
Participants completed the eight-item version of the Center for Epidemiologic Studies Depression Scale (CES-D)21 assessing the frequency of symptoms of depression (e.g., feeling sad, fearful, crying spells) over the past week. The Brief Pain Inventory22 was used to measure pain severity (worst and least pain in last 24 hours, pain right now and on average) and interference in daily life (e.g., general activity, social relations, sleep).23 The Brief Fatigue Inventory24 was used to measure fatigue severity (worst, usual, and current levels) and interference in general activity (e.g., ability to walk, normal work).
Analyses
Descriptive statistics using SPSS version 24 summarized demographic, smoking, and clinical characteristics. Latent Growth Curve models examined the relationship between days of smoking abstinence and QOL measures at each assessment. Latent growth curve intercept and linear slope were included in the model to account for individual trajectories. Number of days abstinent was used as a predictor of QOL through its association with depression, pain, and fatigue at each assessment point and/or with the slope.
Partial gaps in the TLFB data of ≤12 continuous missing days within a follow-up period were replaced based on consistent self-reported smoking status of the surrounding days (smoking/abstinent). At baseline, missing number of days abstinent (n=60) was estimated using the item “in the past week, how many days have you smoked at least 1 cigarette?” A value of 0 was imputed for those patients who indicated that they smoked within the previous week (n=52), and for the 8 patients who reported not smoking in the past week, we imputed the mean number of days abstinent at baseline for the total sample (M=30). Missing data for all other variables was managed using Full Information Maximum Likelihood in Amos 24.0.0.25 This approach estimates parameters using all variables included in the model.
Three models, one for depression, pain, and fatigue, assessed the relationship between days abstinent and QOL. For pain and fatigue, a latent variable was created at each time point to combine measures of severity and interference. Because the follow-ups were not spaced equally, the loadings for the indicators of linear slope were fixed at 0, 0.167, 0.5, and 1 from baseline to 12-month assessment. Number of days abstinent was a time-varying predictor at each assessment. Age, sex, marital status, education, employment status, income, financial situation and nicotine dependence were included as time-invariant covariates for each QOL assessment, but are not shown in the model. Study condition was not included because there were no significant differences between the two interventions in number of days abstinent or any QOL variable. Model fit was considered good when the comparative fit index (CFI)26 and the Tucker-Lewis Index (TLI),27 were over .9526,28 and the root mean square error of approximation (RMSEA)29 was under .06.
RESULTS
Participant characteristics
Table 1 presents characteristics of study participants (Completers) and the two groups of excluded participants from the parent study (Non-completers and Deceased). Compared to study participants, Non-completers reported fewer days of smoking abstinence and higher pain severity at baseline and Deceased were more likely to be male, have a late stage cancer, have hematological cancer, have received chemotherapy or surgery, and have smoked more cigarettes per day.
TABLE 1.
Descriptive Statistics and Group Comparisons
Completers1 (n=332) | Non-completers (n=24) | Deceased (n=56) | |
---|---|---|---|
Demographics | n (%)/M (SD) | n (%)/M (SD) | n (%)/M (SD) |
Sex: Female | 173 (52.1%) | 14 (58.3%) | 20 (35.7%)* |
Age | 54.8 (10.8) | 56.4 (11.5) | 56.0 (10.5) |
Race: non-Hispanic White | 291 (87.7%) | 23 (95.8%) | 47 (83.9%) |
Marital status: Married/life partner | 177 (53.3%) | 11 (45.8%) | 35 (62.5%) |
Education: >High school | 173 (53.6%) | 12 (50.0%) | 28 (50.0%) |
Employed: Yes | 186 (57.8%) | 14 (58.3%) | 29 (53.7%) |
Difficult/very difficult financial situation | 87 (26.8%) | 9 (37.5%) | 19 (33.9%) |
Financial concerns related to cancer: Yes | 194 (60.6) | 18 (75.0%) | 36 (66.7%) |
Annual income: ≤ $30K | 131 (42.4%) | 13 (54.2%) | 25 (47.2%) |
Clinical Variables | |||
Cancer type | |||
Thoracic | 71 (21.4%) | 6 (25.0%) | 11 (19.6%) |
Head and Neck | 61 (18.4%) | 4 (16.7%) | 10 (17.9%) |
Bone Marrow | 2 (0.6%) | 0 (0.0%) | 1 (1.8%) |
Breast | 46 (13.9%) | 1 (4.2%) | 1 (1.8%)* |
Cutaneous | 36 (10.8%) | 1 (4.2%) | 2 (3.6%) |
Gastrointestinal | 36 (10.8%) | 7 (29.2%) | 8 (14.3%) |
Genitourinary | 36 (10.8%) | 2 (8.3%) | 5 (8.9%) |
Gynecological | 31 (9.3%) | 1 (4.2%) | 3 (5.4%) |
Hematological | 27 (8.1%) | 1 (4.2%) | 13 (23.2%)* |
Neurological | 1 (0.3%) | 0 (0.0%) | 1 (1.8%) |
Sarcoma | 4 (1.2%) | 1 (4.2%) | 1 (1.8%) |
Early stage cancer | 187 (63.4%) | 15 (65.2%) | 8 (21.1%)*** |
≥1 comorbidities | 117 (35.2%) | 12 (50.0%) | 25 (44.6%) |
Chemotherapy | 202 (61.0%) | 15 (62.5%) | 43 (76.8%)* |
Radiation Therapy | 137 (41.6%) | 12 (50.0%) | 22 (40.7%) |
Surgery | 273 (82.2%) | 19 (79.2%) | 34 (60.7%)*** |
Smoking Variables | |||
Years smoking | 34.8 (12.0) | 32.1 (12.4) | 34.8 (12.3) |
CPD average | 20.7 (9.5) | 21.4 (7.7) | 21.9 (11.1)* |
Fagerström dependence | 5.2 (2.1) | 5.3 (2.1) | 5.3 (2.4) |
Number of Days Abstinent | |||
Baseline | 26.4 (26.0) | 16.4 (20.9)* | 31.3 (27.8) |
2 Months | 80.4 (34.2) | -- | -- |
6 Months | 171.7 (72.0) | -- | -- |
12 Months | 313.3 (135.2) | -- | -- |
Quality of Life Variables | M (SD) | M (SD) | M (SD) |
Depression | |||
Baseline | 16.4 (5.9) | 15.4 (6.4) | 16.2 (5.6) |
2 Months | 14.9 (6.5) | -- | -- |
6 Months | 13.6 (5.8) | -- | -- |
12 Months | 14.0 (6.1) | -- | -- |
Pain Severity | |||
Baseline | 15.3 (10.5) | 16.4 (8.4)* | 15.7 (10.4) |
2 Months | 12.7 (10.1) | -- | -- |
6 Months | 13.0 (10.6) | -- | -- |
12 Months | 12.8 (10.8) | -- | -- |
Pain Interference | |||
Baseline | 29.7 (22.0) | 33.3 (20.4) | 28.6 (22.9) |
2 Months | 23.9 (21.0) | -- | -- |
6 Months | 23.7 (21.2) | -- | -- |
12 Months | 23.5 (21.7) | -- | -- |
Fatigue Severity | |||
Baseline | 15.8 (8.7) | 17.2 (9.2) | 16.7 (7.9) |
2 Months | 13.6 (8.9) | -- | -- |
6 Months | 12.4 (8.5) | -- | -- |
12 Months | 12.0 (8.9) | -- | -- |
Fatigue Interference | |||
Baseline | 26.6 (18.5) | 29.9 (17.3) | 25.9 (18.3) |
2 Months | 22.5 (17.8) | -- | -- |
6 Months | 19.7 (17.9) | -- | -- |
12 Months | 18.9 (18.1) | -- | -- |
Notes: M=mean; SD=standard deviation; CPD=cigarettes per day
p<.05;
p<.001
Number of surveys returned was 315, 302, & 273 at 2, 6, and 12 months, respectively.
To ensure the results were not driven from the sample of patients with thoracic and HN cancers (40% of the sample), we compared them with all other cancer types across all model variables. There were no significant differences in number of days abstinent or in any of the QOL measures. However, these patients differed (p’s<.05) from other cancer types on several demographic (more likely to be male, older, and with fewer financial problems), and smoking variables (more years smoking, more cigarettes per day, greater nicotine dependence).
Quality of life models
Correlations between observed variables are displayed in Table 2. A simplified version of the final model for each QOL component is presented in Figure 1.
TABLE 2.
Correlation Matrix among Observed Variables
TABLE 2.
Continued
NOTE: BL=baseline; Pain Sev.=Pain Severity; Pain Int =Pain Interference; Fatigue Sev.=Fatigue Severity; Fatigue Int.=Fatigue Interference
p<.05;
p<.01;
p<.001;
Figure 1.
Latent Growth Curve models for (a) Depression, (b) Pain, and (c) Fatigue
Depression.
The model (Figure 1a) showed a good fit to the data (CFI=.992; TLI=.982; RMSEA=.033). Non-significant paths were removed for parsimony and the fit remained good (CFI=.990; TLI=.985; RMSEA=.038). Across participants, there was a decline in average depression levels (Table 1). In addition, more days of smoking abstinence were associated with lower levels of depression at each follow-up beyond the overall decline in depression over time. At baseline, higher levels of depression were associated with being female, financial concerns related to cancer, income <$30K, and higher nicotine dependence.
Pain.
The model (Figure 1b) showed a good fit to the data (CFI=.991; TLI=.984; RMSEA=.031). After removing non-significant paths, the model achieved a good fit (CFI=.996; TLI=.994; RMSEA=.020). At baseline, higher levels of pain were associated with younger age, financial concerns related to cancer, being unemployed and higher nicotine dependence. Although levels of pain decreased over time (Table 1), number of days of smoking abstinence was not associated with pain at any follow-up.
Fatigue.
The model (Figure 1c) showed a good fit to the data before (CFI=.988; TLI=.978; RMSEA=.037) and after removing non-significant paths (CFI=.997; TLI=.996; RMSEA=.020). Average levels of fatigue decreased over time (Table 1). There was a direct effect of days abstinent on fatigue at 12 months and an indirect effect through the slope, with an overall effect of lower fatigue at 12 months. At baseline, nicotine dependence was associated with higher fatigue and there was an interaction with time and nicotine dependence. More specifically, fatigue significantly declined over time for most participants, but the decline was smaller among those with higher initial nicotine dependence. Financial concerns related to cancer and being unemployed were associated with higher fatigue at baseline.
DISCUSSION
This study extends previous research by analyzing QOL over a year as a function of days of smoking abstinence in a large sample of patients with a wide range of cancer types. Overall, QOL was better among cancer patients who remained abstinent. The nature of this association was different for the three QOL indices.
Depression and negative affect are barriers for smoking cessation in cancer patients30 because patients may use smoking as a coping strategy after diagnosis. In addition, providers may fear encouraging cessation due to a potential negative impact on mood. However, our longitudinal data showed that the association between days abstinent and lower depression was observed at the first follow-up (2 months) and continued throughout the study. Given that patients and clinicians may believe that smoking is a useful strategy to cope with cancer-related stress and clinicians may be hesitant to proscribe smoking, these findings may offer assurance that smoking cessation is generally associated with less, rather than greater, depression.
Studies with lung31 and HN13 cancer patients indicated that smoking after diagnosis was associated with greater fatigue. In this study, we found a relationship between days abstinent and a lower fatigue, but only after a long period of abstinence (>6 months). Thus, unlike depression, patients may need more sustained smoking abstinence to perceive benefits in their level of fatigue. Alternatively, it is possible that higher levels of fatigue earlier in treatment may reduce the ability to sustain smoking abstinence. Whatever the nature of the relationship, providers and patients may benefit from understanding that long-term abstinence from smoking is associated with lower levels of fatigue. Thus, promoting continued smoking abstinence may have long term benefits in QOL for cancer patients.
Regarding pain, prior studies with lung and HN cancer patients found that smokers were more likely to have higher pain levels compared to former or never smokers.11,13,32 We found that pain decreased on average over time, but it was not associated with days abstinent. Pain levels in our study may have been lower compared to other studies because patients with high levels of pain who did not manage to quit smoking would have been excluded from the parent study.
Finally, cancer-related financial concerns were associated with poorer QOL. Other indicators of economic status (income and employment) were also significant for one or more QOL measures. Previous studies found that financial burden caused by cancer was associated with poorer QOL.33,34 Thus, patients’ cancer-related financial stress is an issue that warrants clinical and research attention.
Study limitations
This study has several limitations. First, this secondary analysis evaluated only three indicators of QOL in cancer patients.35,36 QOL is a multi-dimensional construct and future research should include other validated measures (e.g., 36-Item Short-Form Health Survey questionnaire).37,38 Second, although cancer patients are typically heavily nicotine dependent,39 light or intermittent smokers were not included in the sample. In addition, participants had recently quit smoking and were enrolled in a smoking relapse prevention intervention. Therefore, we were unable to compare these recent quitters with never or long-term former smokers. Thus, it is not clear that the associations found between QOL and length of abstinence would continue for shorter or longer periods of abstinence. Third, generalizability is limited because most participants were non-Hispanic White. Fourth, although the sample comprised patients with a wide variety of cancer types, there was insufficient statistical power for analyses by cancer type. Fifth, although the TLFB procedure is widely used and valid for assessing smoking behavior,20 it is a self-report measure of smoking that does not include bioverification.39 Finally, we cannot rule out a reciprocal relationship between QOL and smoking.
Despite these limitations, this study contributes to the literature in several ways. QOL has gained attention as a key outcome variable above and beyond cancer survivorship. Prior research had shown relationships between QOL and smoking status in smoking-related cancers. The longitudinal nature of the study allowed for analyses of QOL and smoking abstinence over time, while using a continuous measure of smoking behavior that better reflects the dynamic nature of the smoking cessation process.39,40 Also, this study extends findings to a sample with a wide range of cancer types.
Clinical implications
Our results indicate that QOL improves over time in cancer patients in association with smoking abstinence and showed different trajectories in symptom improvement among specific QOL components. This highlights the importance of encouraging cancer patients to quit smoking and to maintain abstinence in support of cancer-related health benefits and aspects of their QOL in both the short and long term.
Acknowledgments
FUNDING SOURCE
This research was supported by grant R01 CA154596 from the National Cancer Institute and in part by the Biostatistics and Bioinformatics Shared Resource at the H. Lee Moffitt Cancer Center & Research Institute, an NCI-designated Comprehensive Cancer Center (P30CA76292). The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH.
Footnotes
Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.
CONFLIC OF INTEREST
Dr. Thomas Brandon has received research support from Pfizer, Inc.
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