Abstract
Introduction:
Outcomes of oncologic resection are related to tumor biology and patient-reported health factors. However, data regarding changes in functional status and health-related quality of life (HRQOL) before and after lung surgery for older adults are lacking.
Methods:
We identified lung cancer patients from the SEER-Medicare Health Outcomes Survey (MHOS) linked database. HRQOL surveys captured physical/mental health, activities of daily living (ADLs), and medical comorbidities. Patients who underwent surgery with baseline pre-diagnosis HRQOL survey and post-diagnosis follow-up survey were selected. Patient, disease, and HRQOL measures were analyzed using Cox proportional hazards regression for overall survival (OS) and disease-specific survival (DSS).
Results:
Overall, 138 patients were evaluated. Disease extent was localized for 75 (54%), and regional for 58 (42%). The cohort experienced an increase in the number of major comorbidities and declines in physical HRQOL, mental HRQOL, and ADLs. Median OS was 74 months. Decreased OS was independently associated with male sex (HR 1.7, p=0.03), more advanced disease (regional vs. localized: HR 1.8, p=0.01; distant vs. localized: HR 2.1, p=0.22), and decline in ADLs (HR 1.8, p=0.02). Decreased DSS was independently associated with male sex (HR 2.2, p=0.03), more advanced disease (regional vs. localized: HR 2.9, p=0.002; distant vs. localized: HR 3.1, p=0.22), and decline in mental HRQOL (OR 2.1, p=0.02).
Conclusions:
The potential survival benefit of lung resection for malignancy is diminished by declines in physical and mental health. Among older surgical patients at risk for functional and HRQOL deterioration, identification and mitigation of such deterioration may optimize oncologic outcomes.
Keywords: Quality of life, functional status, clinical outcomes, geriatric oncology, lung cancer
INTRODUCTION
In the United States, lung cancer currently is the second most common malignancy diagnosed each year and is the leading cause of cancer-related mortality.1 Lung cancer is primarily a malignancy of the elderly; the median age of diagnosis is 70 years.2 In the United States, the population has been steadily ageing, and the proportion of people over the age of 65 years is projected to be nearly 20% by the year 2030.3 As the population ages, it is expected that the incidence of cancer will also increase.4
Surgery is frequently the sole therapy or a component of the treatment plan for patients with early stage lung cancer.5 Evaluation of a patient’s fitness for surgery is made more complex by the need to consider the patient’s baseline pre-operative and projected post-operative lung function, as surgery for lung cancer frequently involves resection of an entire lobe.6 This consideration is further compounded by the changes in lung function with ageing, including decreased functional reserve capacity and decreased lung compliance.7,8 Pulmonary function testing provides a good assessment of such measures but provides an incomplete picture of a patient’s appropriateness for lung resection.9,10
Patient-centered outcomes, such as health-related quality of life (HRQOL), provide a more complete characterization of a patient’s overall fitness. Pre-operative assessments of these factors are facilitated by validated scoring systems that measure patient comorbidities, frailty, functional status, and HRQOL.11–14 These scoring systems are complementary, evaluating various aspects of a patient’s well-being. Despite the existence of patient-centered outcomes assessments and the overall high incidence of lung cancer, patients over 65 years of age with lung cancer remain an understudied population. Furthermore, most baseline assessments of HRQOL in this population occur after the diagnosis of lung cancer. Thus, baseline measures are affected by both the underlying cancer and the patient’s response to the cancer, such as stress and anxiety. We hypothesized that comparing patient-centered outcomes among older adults with lung cancer before cancer diagnosis and after lung surgery would provide more insight into the relative impact of such factors on survival.
METHODS
We applied for and obtained data from a linked resource of the Surveillance, Epidemiology, and End Results (SEER) program and the Medicare Health Outcomes Survey (MHOS) database. The SEER-MHOS linked data resource is jointly managed by the National Cancer Institute (NCI) and the Centers for Medicare and Medicaid (CMS). The data set links SEER cancer registry data and patient-reported outcomes (PROs) from the MHOS obtained from a nationwide sample of Medicare Advantage Organization enrollees aged 65 years and older. The MHOS has been continuously recruiting yearly cohorts since 1998. The study randomly samples Medicare Advantage enrollees with survey administration by mail or telephone, with follow-up surveys at two years.15,16 Combined, the SEER-MHOS dataset describes HRQOL outcomes for older cancer patients.
Sample
We identified patients with a first diagnosis of lung cancer from fifteen yearly cohorts (1998–2014) of the SEER-MHOS data resource. A subset of survivors who had completed HRQOL surveys both before diagnosis (i.e. baseline) and at least one year after diagnosis (i.e. follow-up) were selected for longitudinal analysis. We chose one year post-diagnosis as sufficient elapsed time to account for treatment around the time of surgery and post-operative recovery, since exact timing of treatment was not available from the dataset. Survivors who had more than one missing ADL response were excluded.
Under the Health Insurance Portability and Accountability Act (HIPAA) of 1996, SEER-MHOS data are exempt from additional informed consent and are considered a limited dataset. All survivors who participated in the MHOS provided informed consent at initial survey. In accordance with HIPAA policies, investigators for this analysis completed signed user agreement forms prior to receiving the data.
The selection criteria for this analysis began with a cohort of 15,863 participants who were age 65 or older. Overall, 673 patients who did not have cancer before the survey and had only lung malignancy during the follow-up were identified from the SEER-MHOS dataset, of whom 276 received lung cancer directed surgery. We further refined our cohort pool with the following inclusion criteria: 1) participants who had survey data that was collected at least 1-year post-diagnosis; 2) participants without missing stage or not staged; 3) participants with at least 5 non-missing answers for the 6 ADL questions at baseline and follow-up. With the inclusion criteria, our final cohort for the analysis was 138 (21%) participants who had completed surveys prior to and following their cancer diagnosis.
Measures
Demographic characteristics obtained through the SEER cancer registry linked cases included age, sex, marital status, race/ethnicity, education level, and income. Comorbidities considered included heart conditions (angina, myocardial infarction, or congestive heart failure), stroke, chronic obstructive pulmonary disease, diabetes, and inflammatory or irritable bowel conditions. Disease stage was delineated as localized, regional, or distant.
The MHOS evaluates HRQOL using the Medical Outcomes Study 36-item Short Form (SF-36) from 1998–2005, and the VR-12 from 2006 onward.17 The SF-36 and VR-12 contain items that measure physical functioning, bodily pain, general health, vitality, mental health, role limitations due to emotional problems, and social functioning. The measures yield two summary scores: physical component summary (PCS) and mental component summary (MCS).18
The adapted Katz activities of daily living (ADL) index was used to assess functional limitations. The index ranks adequacy of performance by level of difficulty (no difficulty; a little difficulty; a lot of difficulty) in the following six functions: bathing, dressing, toileting, transferring, continence, and feeding. An aggregate score of 6 indicates full function, 3–4 indicates moderate impairment, and 2 or less indicates severe functional impairment.19,20
Beginning in 2003, questions from the Centers for Disease Control and Prevention (CDC) Healthy Days Module on the number of physically and mentally unhealthy days in the past month were added to the MHOS. Prior research demonstrated that responses to the number of unhealthy days questions have been linked to greater hospitalization and mortality.16
The date of death variable (missing if alive at last follow-up) from the original dataset was used to code participant survival as alive or deceased. For the deceased, the SEER cause-specific death classification variables were utilized to classify cause of death as death from lung cancer or from other causes.
Statistical Analysis
SAS 9.4 (SAS Institute, Cary, NC) was used for analysis. A two-sided p-value <0.05 was considered significant. Patient demographics and disease characteristics were presented as summary statistics. Categorical variables were reported as percentages and continuous variables as medians with interquartile range (IQR). The six ADLs were reported as the composite Katz score, dichotomized to moderate/severe or minor/no impairment. Comorbidities were summed. Mental and physical HRQOL scores were dichotomized using the United States population mean as the cut-point.
Baseline and follow-up data were compared to evaluate changes in the Katz score, total comorbidities, and mental and physical HRQOL. All variables measuring changes between baseline and follow-up were dichotomized into the stable or improved group or the declined group. Changes in Katz composite score was dichotomized as stable/improved or worsened at follow-up compared to the baseline. Changes in HRQOL between the baseline and follow-up was dichotomized into stable or improved (PCS/MCS score changed less than 2 points or increased 2 or more points) or declined (PCS/MCS score decreased two or more points). As described by others, a 2-point difference in PCS and MCS scores represent minimal clinically important differences.21 Patients whose number of major comorbidities did not change between the baseline and follow-up were categorized as stable, while patients who had more major comorbidities were classified in the increased group. McNemar’s test was used to compare frequencies between the baseline and follow-up, and the Generalized Estimation Equations were used for comparison, adjusting for covariates.
Kaplan-Meier method was used to estimate the overall survival functions, and groups were compared by the log-rank test. For overall survival, univariate analysis using Cox regression was first performed to assess each risk factor. A forward step-wise multivariate regression analysis was performed by successively including the most significant variable (p<0.05) given those significant variables already in the model until no further significant variables could be included. Non-significant variables were then successively removed in a backward step-wise manner starting from the least significant (p>0.05), followed by further testing individually the significance of the non-included variables to obtain a parsimonious multivariate model. The risk factors for disease-specific and non-disease-specific survival were assessed similarly using Fine and Gray proportional sub-distribution hazards models accounting for competing risks.
RESULTS
Of the 138 patients included in analysis (Table 1), median age at diagnosis was 74 years, 51% were female, 81% were Caucasian, 63% were married, and 17% completed four years of college. Among 115 patients with income data, 12% reported annual income greater than $50,000. Overall, 55% had localized disease, whereas 42% had regional and 4% had distant disease involvement.
Table 1:
Patient demographic and clinicopathologic features
| Variable | N=138 (%) | |
|---|---|---|
| Age at diagnosis, years, median [IQR] | 74.0 [8] | |
| Sex | Female | 71 (51) |
| Male | 67 (49) | |
| Race | Caucasian | 112 (81) |
| Other | 26 (19) | |
| Marital status | Married | 87 (63) |
| Not Married | 49 (36) | |
| Education level | Up to some high school | 34 (24) |
| High school degree / some college | 80 (58) | |
| 4+ years of college | 23 (17) | |
| Income | < $30,000 | 71 (51) |
| $30,000–$49,999 | 28 (20) | |
| ≥ $50,000 | 16 (12) | |
| Missing | 23 (17) | |
| Katz ADL Scores, mean [SD] | Before diagnosis | 5.4 [1.1] |
| 1 year after diagnosis | 4.6 [1.8] | |
| Comorbidities | 0 | 72 (52) |
| 1 | 48 (35) | |
| >1 | 17 (12) | |
| Physical HRQOL, mean [SD] | Before diagnosis | 39.7 [11.7] |
| 1 year after diagnosis | 33.9 [11.3] | |
| Mental HRQOL, mean [SD] | Before diagnosis | 53.3 [8.8] |
| 1 year after diagnosis | 50.2 [11.4] | |
| Stage of disease | Localized | 75 (54) |
| Regional | 58 (42) | |
IQR = interquartile range; ADL = activity of daily living; SD = standard deviation; HRQOL = health-related quality of life
Comparison of baseline to follow-up PROs
The median time from baseline survey to diagnosis was 6 months, and the median time from baseline survey to follow-up survey was 20 months. Katz ADL composite score was 5.4 (SD ±1.1) at baseline and declined for 27% of patients at follow-up (p<0.0001, adjusted for education). Of 126 patients with complete comorbidity survey data, 20% reported an increase in number of comorbidities (p=0.16, no significant covariates). Physical HRQOL was at or above the population mean for 27% of patients at baseline and declined for 57% between baseline and follow-up (p<0.0001, adjusted for gender). Mental HRQOL was at or above the population mean for 67% of patients at baseline, with 45% of patient reporting a decline on follow-up survey (p=0.07, adjusted for education) (Table 2). There was no association between declining MCS and declining PCS (Chi-squared p=0.19)
Table 2:
Change in health-related quality of life, activities of daily living, and comorbidity scores between survey time points
| Variable | Change from baseline to follow-up | Number (%) | p Value |
|---|---|---|---|
| Katz ADL Score | Stable or improved | 101 (73) | <0.0001 |
| Declined | 37 (27) | ||
| Comorbidities* | Stable | 101 (80) | 0.16 |
| Increased | 25 (20) | ||
| Physical HRQOL | Stable or improved | 59 (43) | <0.0001 |
| Declined | 79 (57) | ||
| Mental HRQOL# | Stable or improved | 75 (55) | 0.07 |
| Declined | 62 (45) | ||
ADL = activity of daily living; HRQOL = health-related quality of life
= 12 patients did not have appropriate comorbidity-related data on the follow-up survey and were excluded from this analysis
= 1 patient did not have follow-up information for mental HRQOL and was excluded from this analysis
Subset analyses showed a significant increase in the number of days of poor physical health between baseline (5.1±8.7) and follow-up (10.2±13.8; p<0.0001, no significant covariates) and no significance difference in the number of days of poor mental health between baseline (3.3±10.6) and follow-up (5.6±8.1; p=0.19, no significant covariates).
Overall survival
Median OS from diagnosis was 73.5 months. On univariate analyses, decreased OS was significantly associated with male sex, more advanced disease stage, and decline in Katz score. Increasing patient age, comorbidities, and physical or mental HRQOL were not associated with OS. Multivariate analysis showed that male sex, advanced disease stage, and a decline in Katz score were independently significantly associated with decreased overall survival (Table 3). Survival curves for the population stratified by change in Katz score are provided (Figure 1).
Table 3.
Univariate and multivariate analyses with overall survival as outcome measure
| Variable | N (%) | Univariate Analysis | Multivariate Analysis | |||||
|---|---|---|---|---|---|---|---|---|
| HR | 95% CI | p Value | HR | 95% CI | p Value | |||
| Age at diagnosis, per year | 138 (100) | 1.04 | 0.99–1.09 | 0.17 | - | - | - | |
| Sex | Female | 71 (51) | Ref | - | - | Ref | - | - |
| Male | 67 (49) | 1.68 | 1.08–2.62 | 0.02 | 1.67 | 1.07–2.60 | 0.03 | |
| Race | Caucasian | 112 (81) | Ref | - | - | - | - | - |
| Other | 26 (19) | 0.99 | 0.54–1.80 | 0.96 | ||||
| Marital Status | Married | 87 (63) | Ref | - | - | - | - | - |
| Not Married | 49 (36) | 1.01 | 0.64–1.59 | 0.98 | ||||
| Education | Some HS | 34 (24) | Ref | - | 0.56* | - | - | - |
| HS degree | 80 (58) | 0.53 | 0.31–0.89 | 0.02 | ||||
| 4+ years college | 23 (17) | 0.65 | 0.33–1.29 | 0.22 | ||||
| Income | ≥ $50,000 | 71 (51) | Ref | - | 0.24* | - | - | - |
| $30,000–49,999 | 28 (20) | 2.19 | 0.81–5.92 | 0.12 | ||||
| < $30,000 | 16 (12) | 2.20 | 0.87–5.55 | 0.09 | ||||
| Stage | Localized | 75 (54) | Ref | - | 0.02* | Ref | - | 0.04* |
| Regional | 58 (42) | 1.84 | 1.18–2.87 | 0.01 | 1.76 | 1.12–2.76 | 0.01 | |
| Distant | -- | 1.85 | 0.57–6.04 | 0.31 | 2.10 | 0.64–6.89 | 0.22 | |
| Katz ADL Score | Stable/improved | 101 (73) | Ref | - | - | Ref | - | - |
| Declined | 37 (27) | 1.84 | 1.13–3.00 | 0.01 | 1.78 | 1.09–2.91 | 0.02 | |
| Comorbidities | Stable | 101 (80) | Ref | - | - | - | - | - |
| Increased | 25 (20) | 0.84 | 0.46–1.54 | 0.57 | ||||
| Physical HRQOL | Stable/improved | 59 (43) | Ref | - | - | - | - | - |
| Declined | 79 (57) | 1.28 | 0.82–1.99 | 0.28 | ||||
| Mental HRQOL | Stable/improved | 75 (55) | Ref | - | - | - | - | - |
| Declined | 62 (45) | 1.47 | 0.95–2.29 | 0.09 | ||||
HS = high school; ADL = activity of daily living; HRQOL = health-related quality of life
= overall p value
Figure 1.
Kaplan-Meier survival curve for overall mortality stratified by change in Katz score.
Disease-specific and non-disease-specific survival
Competing-risks analyses were performed to determine factors associated with disease-specific versus non-disease-specific survival. The only factor significantly associated with non-disease-specific survival on multivariate analysis was increasing patient age. Thus, only the results of multivariate analyses for disease-specific survival are presented (Table 4). On univariate analysis, factors associated with decreased disease-specific survival included male sex, more advanced disease stage, decline in Katz score, and decline in mental HRQOL, whereas improved disease-specific survival was associated with increasing education level. On multivariate analysis, male sex, education level, disease stage, and mental HRQOL were independently associated with survival whereas Katz score was not. Cumulative incidence function curves for disease-specific mortality for the population stratified by change in mental HRQOL are provided (Figure 2).
Table 4.
Univariate and multivariate analyses with disease-specific survival as outcome measure
| Variable | N (%) | Univariate Analysis | Multivariate Analysis | |||||
|---|---|---|---|---|---|---|---|---|
| HR | 95% CI | p Value | HR | 95% CI | p Value | |||
| Age at diagnosis, per year | 138 (100) | 0.99 | 0.93–1.05 | 0.68 | - | - | - | |
| Sex | Female | 71 (51) | Ref | - | - | Ref | - | - |
| Male | 67 (49) | 2.28 | 1.22–4.25 | 0.009 | 2.21 | 1.07–4.59 | 0.03 | |
| Race | Caucasian | 112 (81) | Ref | - | - | - | - | - |
| Other | 26 (19) | 1.32 | 0.60–2.88 | 0.49 | ||||
| Marital Status | Married | 87 (63) | Ref | - | - | - | - | - |
| Not Married | 49 (36) | 1.12 | 0.60–2.07 | 0.72 | ||||
| Education | Some HS | 34 (24) | Ref | - | 0.02* | Ref | - | 0.04* |
| HS degree | 80 (58) | 0.39 | 0.20–0.78 | 0.008 | 0.37 | 0.18–0.79 | 0.01 | |
| 4+ years college | 23 (17) | 0.75 | 0.34–1.66 | 0.47 | 0.53 | 0.22–1.31 | 0.17 | |
| Income | ≥ $50,000 | 71 (51) | Ref | - | 0.57* | - | - | - |
| $30,000–49,999 | 28 (20) | 1.83 | 0.57–5.82 | 0.31 | ||||
| < $30,000 | 16 (12) | 1.53 | 0.43–5.45 | 0.51 | ||||
| Stage | Localized | 75 (54) | Ref | - | 0.007* | Ref | - | 0.008* |
| Regional | 58 (42) | 2.71 | 1.45–5.04 | 0.002 | 2.85 | 1.46–5.59 | 0.002 | |
| Distant | -- | 2.67 | 0.58–12.2 | 0.21 | 3.06 | 0.52–18.0 | 0.22 | |
| Katz ADL Score | Stable/improved | 101 (73) | Ref | - | - | - | - | - |
| Declined | 37 (27) | 1.93 | 1.02–3.64 | 0.04 | ||||
| Comorbidities | Stable | 101 (80) | Ref | - | - | - | - | - |
| Increased | 25 (20) | 1.63 | 0.80–3.34 | 0.18 | ||||
| Physical HRQOL | Stable/improved | 59 (43) | Ref | - | - | - | - | - |
| Declined | 79 (57) | 1.34 | 0.73–2.46 | 0.35 | ||||
| Mental HRQOL | Stable/improved | 75 (55) | Ref | - | - | Ref | - | - |
| Declined | 62 (45) | 2.15 | 1.17–3.92 | 0.01 | 2.11 | 1.15–3.89 | 0.02 | |
HS = high school; ADL = activity of daily living; HRQOL = health-related quality of life
= overall p value
Figure 2.
Cumulative incidences of disease-related mortality stratified by change in mental HRQOL.
DISCUSSION
This study demonstrates that PROs were significant prognostic factors for mortality among older adults who underwent lung resection for cancer. Patients in this cohort experienced significant worsening of PROs over time, namely those of Katz ADL scores, physical HRQOL, and number of comorbidities. A decline in Katz ADL composite scores was independently associated with decreased overall survival. Although mental HRQOL for the cohort did not significantly change during the time between surveys, those patients who reported a decline in mental HRQOL experienced decreased disease-specific survival. Despite a significant decline in physical HRQOL and an increase in comorbidities, neither PRO was associated with overall or disease-specific survival.
It is widely accepted that surgery for lung cancer has a negative impact on multiple aspects of QOL. The reciprocal relationship between surgical recovery and QOL is increasingly recognized. Indeed, such patient-centered outcomes may influence surgical outcomes as much as technical aspects of the operation or biology of the disease.22 Pre-operative identification of patients actively experiencing or at potential risk for significant declines in functional status or HRQOL may provide an opportunity to enroll the patient in an appropriate pre-habilitation or rehabilitation programs.23 However, the accurate identification of patients who would most benefit from such a program remains unclear.24 Our study showed that patients who experience declines in functional status and mental HRQOL were at risk of decreased survival. Therefore, efforts integrating pre-operative geriatric assessment, physical and occupational therapy programs, and interventions to prevent or lessen post-operative neurocognitive decline may address concerns related to functional status and mental HRQOL.
Despite significant changes in Katz ADL composite scores, comorbidities, and physical HRQOL, only Katz scores were associated with decreased survival. Part of this may be due to the relatively small patient cohort and multiple PRO assessments included. However, this may also have been related to the factors included in the Katz score, which are activities that are critical for daily independent functioning. While not specifically captured in the SEER-MHOS database, patients experiencing declines in ADLs are more likely to be discharged to skilled nursing facilities following surgery, and some may never regain their pre-operative functional status in order to return home.25
Although mental HRQOL did not change significantly across the entire study cohort over time, those who experienced a decline in mental HRQOL were at greater risk for disease-related death. This association exemplifies the potential impact of a significant decline in PROs on survival following cancer surgery.26 We were unable to tell if declines in mental HRQOL were related to post-operative delirium episodes, sudden exacerbation of baseline dementia, or changes in social functioning related to a different living situation following surgery. Regardless, it is interesting to note that a decline in mental HRQOL was associated with decreased disease-specific survival on multivariate analysis whereas a decline in Katz score was associated on univariate but not multivariate analysis. This finding highlights the need to better elucidate which older patients are at risk for mental health deterioration following lung surgery, as alternative treatments may need to be considered if appropriate.
Limitations of the SEER-MHOS dataset pertinent to this analysis include the lack of data on timing of surgical resection in relation to the PRO surveys or specifics of administration and sequence of chemotherapy and/or radiation therapy. Although the receipt of surgical intervention is available from the dataset, more granular data on timing and receipt of other therapies would have enhanced the survival analyses in terms of survival from operation. Likewise, due to the retrospective nature of the study, our data demonstrate associations rather than causality. Indeed, some declines in PROs may have been a result of cancer recurrence, which was not captured in the dataset. In addition, our inclusion criterion of a completed PRO survey at least a year following the diagnosis of lung cancer potentially skewed our study population to more favorable disease biology and/or better initial functional status than excluded patients.
In summary, patient-centered outcomes such as Katz ADL composite scores and PROs such as mental HRQOL are associated with survival following lung resection for malignancy. Pre-operative identification of older patients at risk for declines in functional status or mental HRQOL paired with post-operative interventions to prevent and mitigate such declines are important in order to optimize outcomes of resection for lung cancer.
Acknowledgments
Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Footnotes
Conflict of interest: None to declare
Disclosures: None to declare
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