Background
Older adults are an increasing population with complex health issues, such as cancer, which disproportionately affect these individuals.1 Notably, caring for older adults with cancer is often challenging due to their complex constellation of medical and psychosocial issues.2 When caring for these patients, clinicians must address many competing factors, including functional impairments, psychosocial issues, and comorbidities. Consequently, an urgent need exists to identify older adults with cancer who may experience poor outcomes. Although older patients with cancer represent an increasing and heterogeneous population with diverse needs, little research has sought to identify those at risk of experiencing high symptom burden or greater use of healthcare services.
To date, most cancer centers have not integrated assessments or screening tools into routine practice to identify older adults at risk of experiencing poor outcomes. Notably, geriatricians have developed geriatric assessment tools to evaluate a variety of domains pertinent to older patients, including functional status, comorbidities, and social support.3–5 In addition, scoring tools exist to help predict risk of chemotherapy toxicity in older adults.6 Despite their benefits, many of these tools require considerable time and resources to be integrated into practice, limiting their widespread use.7,8 Furthermore, a long-standing shortage of geriatric and palliative care clinicians complicates efforts to integrate these specialists into the care of older adults.9–11 Therefore, to deliver high-quality care to older patients with cancer, those at risk for experiencing poor outcomes must be identified, ideally with simple and reliable screening tools.
We sought to determine whether a brief, patient-reported screening tool that categorizes patients as vulnerable could identify those with higher symptom burden and worse health outcomes. The Vulnerable Elders Survey (VES-13) has been validated in the medical literature as a tool that identifies older adults at risk for functional decline and death.12 We prospectively collected patients’ self-reported quality of life (QoL), symptom burden, and functional impairments, and our primary objective was to compare these outcomes between patients who screened positive as vulnerable versus those who did not. We also explored relationships between vulnerability and risk of unplanned hospital visits and overall survival as secondary objectives. By demonstrating that a simple screening tool can identify older patients at risk for poor outcomes, this study will provide additional evidence supporting the integration of such tools into oncology practice and promote the development of interventions targeting these patients.
Methods
Study Procedures
Approval for this study was obtained from the Dana-Farber/Harvard Cancer Center Institutional Review Board. Between October 7, 2015, through June 28, 2018, patients aged ≥70 years with newly diagnosed advanced gastrointestinal cancer receiving care at Massachusetts General Hospital were prospectively enrolled in a cross-sectional study. Patients with gastrointestinal cancers were included because these cancers are highly prevalent in the geriatric oncology population.13–15 We used an age cutoff of ≥70 years because many studies use this cutoff when examining an older population.16–18 Consecutive patients were recruited during the study period by screening outpatient oncology schedules and contacting the oncology team before appointments to ensure patients were appropriate for participation. Study staff obtained written informed consent from eligible patients, after which participants completed self-reported surveys.
Participants
Eligible patients included those aged ≥70 years who had been diagnosed with advanced gastrointestinal cancer within the previous 8 weeks. Patients with advanced cancer were defined as those receiving treatment with palliative intent. We determined whether patients were receiving treatment with palliative intent based on the treatment intent designation (palliative vs curative) specified in the chemotherapy order entry or using documentation in oncology clinic notes for those not receiving chemotherapy. Participants also had to be able to read and respond to study questionnaires in English or with minimal assistance from an interpreter. We excluded patients with significant psychiatric or other comorbid diseases, such as cognitive or mental issues, which the treating clinician believed prohibited informed consent or study participation.
Study Measures
Sociodemographic and Clinical Characteristics
Participants completed a demographic questionnaire to report their race, relationship status, work status, education level, annual income, insurance status, and comorbid conditions. Electronic health records were reviewed to obtain information on age, sex, cancer diagnosis, and treatment.
Patient Vulnerability
The VES-13 was used to screen patients for vulnerability. The self-reported VES-13 is a validated survey that contains 13 items, including age, self-rated health status, limitations in physical function, and functional disabilities.12,17–19 VES-13 scores range from 0 to 10, with higher scores representing greater vulnerability. The VES-13 can be interpreted both continuously and categorically, with scores ≥3 indicating a positive screen result for vulnerability.12,18,19
Quality of Life
To assess patients’ QoL, we used the EORTC Quality of Life of Cancer Patients questionnaire (QLQ-C30) and the EORTC Quality of Life Questionnaire–Elderly Cancer Patients module (QLQ-ELD14), both of which have been validated for use in this population.20,21 The QLQ-C30 evaluates global QoL and 5 functional domains (physical, role, emotional, cognitive, and social),20 whereas the QLQ-ELD14 consists of 5 scales (mobility, worries about others, future worries, maintaining purpose, and burden of illness) and 2 single items (joint stiffness and family support).21 Scores are linearly transformed to a 0 to 100 scale, with higher scores for the global QoL and functional scales indicating better QoL or functioning. For the symptom scales and single items, higher scores indicate worse symptoms or problems.
Physical and Psychological Symptom Burden
We used the self-administered revised Edmonton Symptom Assessment System (ESAS-r) to assess patients’ symptoms.22 The ESAS-r assesses pain, fatigue, drowsiness, nausea, appetite, shortness of breath, depression, anxiety, and well-being. We also included diarrhea and constipation because these symptoms are highly prevalent among patients with cancer.23–25 Each individual symptom is scored on a scale of 0 to 10 (with 0 reflecting absence of the symptom and 10 reflecting the worst possible severity). We categorized the severity of ESAS-r scores as none (0), mild (1–3), moderate (4–6), and severe (7–10), consistent with prior research.24–26 Also consistent with prior work, we computed composite ESAS-r physical and ESAS-r total symptom variables, which included summed scores of patients’ physical and total symptoms.22–26
We used the Geriatric Depression Scale (GDS-15) to assess depression symptoms. The 15-item GDS (scored 0–15) measures depression symptoms in older adults, with higher scores indicating greater depression symptoms.27
Functional Impairments
We assessed patients’ physical function by asking about activities of daily living (ADLs), instrumental ADLs (IADLs), and number of falls in the past 6 months. For ADLs, we used a subscale of the Medical Outcomes Study to determine the number of independent ADLs (from 0 to 10).28 For IADLs, we used a subscale of the Multidimensional Functional Assessment Questionnaire from the Older Americans Resources and Services Program to determine the number of independent IADLs (from 0 to 7).29 In addition, patients were asked to report the number of falls they experienced in the past 6 months, consistent with prior work.30
To assess cognitive function, we used the Blessed Orientation-Memory-Concentration test (BOMC).31,32 The BOMC consists of 6 questions designed to screen for cognitive impairment; scores range from 0 to 28, with higher scores reflecting worse cognitive function.
Healthcare Use and Overall Survival
We explored the relationship between patients categorized as vulnerable and their healthcare use and survival using data from the electronic health record. Consistent with prior work, we investigated time to first unplanned hospitalization within 90 days and time to first unplanned emergency department (ED) visit within 90 days.23–25 We used the 90-day time frame to account for mortality, because patients who die may have less time at risk for hospitalizations and ED visits. We defined time to first unplanned hospitalization as the number of days from study enrollment to first unplanned hospitalization within 90 days. We censored patients without a hospitalization at their 90-day postenrollment date and those who died within 90 days at their death date. We used the same methods when investigating time to first ED visit within 90 days. We also investigated the proportion of days in the hospital within 90 days for all patients by calculating the number of unplanned hospital days and dividing by the number of days patients were alive within 90 days after enrollment, which allowed us to use data from all patients even if they died within 90 days. Last, we explored overall survival by investigating time from study enrollment to death, censoring patients who had not died at last follow-up.
Statistical Analysis
Results
Participant Sample
Of 132 eligible patients that were approached, 102 (77.3%) were enrolled and provided VES-13 data (Figure 1). Participants (mean ± SD age, 77.25 ± 5.75 years) were primarily white (96.1%), married (62.7%), and retired (72.5%) (Table 1). Participants had a mean time from cancer diagnosis of 3.75 weeks (SD, 2.28), and most (88.2%) received some form of anticancer treatment. Rates of hospitalizations, ED visits, and death within 90 days of enrollment were 32.4%, 9.8%, and 19.6%, respectively.
Flow of patients through the study.
Abbreviation: VES-13, Vulnerable Elders Survey.
Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 18, 3; 10.6004/jnccn.2019.7355
Flow of patients through the study.
Abbreviation: VES-13, Vulnerable Elders Survey.
Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 18, 3; 10.6004/jnccn.2019.7355
Flow of patients through the study.
Abbreviation: VES-13, Vulnerable Elders Survey.
Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 18, 3; 10.6004/jnccn.2019.7355
Patient Characteristics
Patient Vulnerability
Participants had a mean (M) VES-13 score of 3.25 (SD, 3.07), and 45.1% screened positive for vulnerability. Compared with nonvulnerable patients, those who were vulnerable were older (M, 79.45 vs 75.44 years; P=.001), had more comorbid conditions (M, 2.13 vs 1.34; P=.017), had longer time since diagnosis (M, 4.33 vs 3.28 weeks; P=.022), and were less likely to receive anticancer treatment (80.4% vs 94.6%; P=.031).
Relationship Between Vulnerability and QoL
Table 2 depicts the relationship between vulnerability and patient-reported outcomes with P values from adjusted multivariable models; unadjusted and adjusted results are presented in supplemental eTable 1 (available with this article at JNCCN.org). Vulnerable patients had significantly worse global QoL than nonvulnerable patients (mean [M], 53.26 vs 66.82; P=.041). In addition, vulnerable patients reported worse QoL across all EORTC QLQ-C30 function domains (physical: M, 58.95 vs 88.24; P<.001; role: M, 53.99 vs 82.12; P=.001; emotional: M, 73.19 vs 85.76; P=.007; cognitive: M, 79.35 vs 92.73; P=.011; social: M, 59.42 vs 82.42; P<.001). Using the EORTC QLQ-ELD14, we found that vulnerable patients had significantly higher scores for poor mobility (M, 45.93 vs 9.49; P<.001), future worries (M, 54.35 vs 40.00; P=.009), and high burden of illness (M, 51.09 vs 38.48; P=.009).
Patient-Reported Outcomes
Relationship Between Vulnerability and Symptom Burden
Vulnerable patients had higher ESAS-r physical (M, 22.78 vs 10.17; P<.001) and ESAS-r total (M, 31.05 vs 15.00; P<.001) scores than nonvulnerable patients (see Table 2). As shown in Figure 2, patients who screened positive for vulnerability had higher rates of moderate/severe symptom burden.
Proportion of patients with moderate-to-severe symptoms according to VES-13.
Abbreviation: VES-13, Vulnerable Elders Survey.
aDifferences are significant.
Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 18, 3; 10.6004/jnccn.2019.7355
Proportion of patients with moderate-to-severe symptoms according to VES-13.
Abbreviation: VES-13, Vulnerable Elders Survey.
aDifferences are significant.
Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 18, 3; 10.6004/jnccn.2019.7355
Proportion of patients with moderate-to-severe symptoms according to VES-13.
Abbreviation: VES-13, Vulnerable Elders Survey.
aDifferences are significant.
Citation: Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw 18, 3; 10.6004/jnccn.2019.7355
Relationship Between Vulnerability and Functional Impairments
Vulnerable patients had significantly worse physical function, with fewer independent ADLs (M, 2.25 vs 6.40; P<.001) and IADLs (M, 3.83 vs 6.50; P<.001) than nonvulnerable patients (see Table 2). Vulnerable patients also had higher cognitive impairment scores (M, 5.60 vs 2.66; P=.057). Notably, using an acceptable FDR of 10% to correct for multiple tests, all significant P values remained significant for all outcomes.
Relationship Between Vulnerability, Healthcare Use, and Overall Survival
Vulnerable patients experienced a greater proportion of days in the hospital within 90 days (rate ratio, 3.56; 95% CI, 1.44–8.81; P=.006) (Table 3). Vulnerable patients had a higher risk of unplanned hospitalizations within 90 days of enrollment than nonvulnerable patients (hazard ratio, 2.38; 95% CI, 1.08–5.27; P=.032), but no significant difference was observed in time to first ED visit. In addition, vulnerable patients had worse survival than nonvulnerable patients (hazard ratio, 2.26; 95% CI, 1.14–4.48; P=.020).
Relationship Between Vulnerable Elders Survey, Healthcare Use, and Survival
Discussion
In this prospective study of older adults with advanced cancer, a substantial proportion of patients screened positive for vulnerability, and we demonstrated that these patients are at risk for experiencing high symptom burden and poor health outcomes. Specifically, vulnerable patients experienced worse QoL, physical and psychological symptoms, and functional impairments compared with nonvulnerable patients. We also found that vulnerable patients had greater healthcare use and inferior survival. Collectively, these findings provide valuable evidence that a brief, patient-reported screening tool has potential to identify older patients with cancer who are particularly vulnerable for experiencing worse outcomes.
Our work underscores the need for simple and scalable screening tools to identify older patients with significant supportive care concerns, such as poor QoL, high symptom burden, increased healthcare use, and impaired survival. Nearly half of the patients in our cohort met the criteria for vulnerability, consistent with prior work,17–19,35 thereby supporting the use of this brief and easily administered tool to identify individuals at risk for worse health outcomes. Currently, standard of care for the geriatric oncology population often lacks screening of patients, despite guideline recommendations.5,7,8 Integration of the VES-13 into routine care can be instrumental in (1) identifying patients who might benefit from additional services, such as comprehensive geriatric assessment and palliative care; (2) understanding how patients’ supportive care needs influence other important outcomes, such as treatment tolerability, healthcare use, end-of-life care, and survival; and (3) developing targeted interventions or geriatric oncology programs tailored to the unique needs of these patients. Thus, our findings provide evidence supporting the use of the VES-13, a simple screening tool with potential for widespread dissemination, to identify older patients at risk for experiencing adverse clinical outcomes and for whom supportive care interventions may be particularly beneficial.
Our study describes the supportive care needs of older adults with advanced cancer and identifies a vulnerable subgroup of patients at risk for poor outcomes. Although prior studies have highlighted that older patients categorized as vulnerable may experience worse chemotherapy tolerability, greater physical and cognitive functional decline, and inferior survival,17–19,35,36 information was lacking on the relationship between vulnerability and QoL, symptoms, and healthcare use among patients with cancer. In our study, vulnerable patients reported worse physical function, which may contribute to their poor QoL, high symptom burden, greater healthcare use, and worse survival.37,38 Alternatively, vulnerable patients’ high symptom burden may influence their functional decline and need for healthcare services.24,26 Ultimately, with higher rates of hospitalizations and a greater proportion of days in the hospital, vulnerable patients likely incur increased healthcare costs, which can lead to financial distress and poor QoL.39–41 By highlighting novel findings that vulnerable patients experience worse health outcomes, these data underscore the need to develop supportive care interventions targeting this population.
We also identified patient characteristics associated with vulnerability. Specifically, older patients and those with greater comorbidity were at risk for being categorized as vulnerable, consistent with prior work.17–19 We also identified an association between vulnerability and longer time since diagnosis with advanced cancer. We enrolled patients within 8 weeks of their diagnosis with advanced cancer, and yet, even at this early time point, we identified a cohort at risk for vulnerability. In addition, we demonstrated a relationship between vulnerability and initial treatment received. Specifically, we found that vulnerable patients were less likely than nonvulnerable patients to receive anticancer treatment, likely reflecting clinicians’ tendency to avoid use of anticancer treatment among frail, older patients.35,36 Ultimately, our findings help identify vulnerable patients at risk for poor outcomes and should inform future efforts to target these patients with interventions addressing their distinct geriatric and supportive care concerns.
Several limitations merit discussion. First, we performed the study at a single academic center in a cohort with limited sociodemographic diversity. Second, we may be underestimating the risk of hospitalizations and ED visits for the minority of patients who seek care outside our health system. Also, we lack data about healthcare costs, which are often largely influenced by hospitalizations,40,41 and we did not ask about patients’ financial burden, an important issue that could impact their QoL.39 In addition, we lack information regarding patients who felt too ill to participate in this study, and these patients may have been particularly vulnerable. Third, although we report on associations, we cannot determine the mechanisms of these associations or comment on causality. In addition, our study’s cross-sectional design prohibits us from exploring how these relationships change over time. Future research should include longitudinal assessments to understand better how patients’ care needs vary over time and in response to other factors, such as the receipt of certain cancer treatments or supportive care services, including geriatrics and palliative care.42,43
Conclusions
Our study provides evidence regarding the utility of a brief screening tool that effectively identifies patients vulnerable to experiencing higher symptom burden and worse clinical outcomes. We showed associations between vulnerability and patients’ QoL, physical and psychological symptoms, and functional impairments, and thus identified a population with substantial supportive care needs. We also discovered that vulnerable patients experienced greater healthcare use and worse survival, underscoring the need to target this group with supportive care interventions to enhance care delivery and outcomes. Future research should focus on developing and testing interventions tailored to the geriatric and supportive care issues unique to vulnerable older adults with cancer while understanding that such efforts must comprehensively address these patients’ QoL, symptom burden, and functional impairments.
References
- 2.↑
Hamaker ME, Vos AG, Smorenburg CH, et al.. The value of geriatric assessments in predicting treatment tolerance and all-cause mortality in older patients with cancer. Oncologist 2012;17:1439–1449.
- 3.↑
Wildiers H, Heeren P, Puts M, et al.. International Society of Geriatric Oncology consensus on geriatric assessment in older patients with cancer. J Clin Oncol 2014;32:2595–2603.
- 4.↑
Stuck AE, Siu AL, Wieland GD, et al.. Comprehensive geriatric assessment: a meta-analysis of controlled trials. Lancet 1993;342:1032–1036.
- 6.↑
Hurria A, Togawa K, Mohile SG, et al.. Predicting chemotherapy toxicity in older adults with cancer: a prospective multicenter study. J Clin Oncol 2011;29:3457–3465.
- 7.↑
Puts MT, Santos B, Hardt J, et al.. An update on a systematic review of the use of geriatric assessment for older adults in oncology. Ann Oncol 2014;25:307–315.
- 8.↑
Sattar S, Alibhai SM, Wildiers H, et al.. How to implement a geriatric assessment in your clinical practice. Oncologist 2014;19:1056–1068.
- 9.↑
Kane R, Solomon D, Beck J, et al.. The future need for geriatric manpower in the United States. N Engl J Med 1980;302:1327–1332.
- 10.↑
Spetz J, Dudley N, Trupin L, et al.. Few hospital palliative care programs meet national staffing recommendations. Health Aff (Millwood) 2016;35:1690–1697.
- 11.↑
Lupu D. Estimate of current hospice and palliative medicine physician workforce shortage. J Pain Symptom Manage 2010;40:899–911.
- 12.↑
Saliba D, Elliott M, Rubenstein LZ, et al.. The Vulnerable Elders Survey: a tool for identifying vulnerable older people in the community. J Am Geriatr Soc 2001;49:1691–1699.
- 13.↑
Bluethmann SM, Mariotto AB, Rowland JH. Anticipating the “silver tsunami”: prevalence trajectories and comorbidity burden among older cancer survivors in the United States. Cancer Epidemiol Biomarkers Prev 2016;25:1029–1036.
- 14.↑
Mariotto AB, Yabroff KR, Feuer EJ, et al.. Projecting the number of patients with colorectal carcinoma by phases of care in the US: 2000-2020. Cancer Causes Control 2006;17:1215–1226.
- 15.↑
Manzano JG, Luo R, Elting LS, et al.. Patterns and predictors of unplanned hospitalization in a population-based cohort of elderly patients with GI cancer. J Clin Oncol 2014;32:3527–3533.
- 16.↑
Caillet P, Canoui-Poitrine F, Vouriot J, et al.. Comprehensive geriatric assessment in the decision-making process in elderly patients with cancer: ELCAPA study. J Clin Oncol 2011;29:3636–3642.
- 17.↑
Mohile SG, Bylow K, Dale W, et al.. A pilot study of the Vulnerable Elders Survey-13 compared with the Comprehensive Geriatric Assessment for identifying disability in older patients with prostate cancer who receive androgen ablation. Cancer 2007;109:802–810.
- 18.↑
Luciani A, Ascione G, Bertuzzi C, et al.. Detecting disabilities in older patients with cancer: comparison between Comprehensive Geriatric Assessment and Vulnerable Elders Survey-13. J Clin Oncol 2010;28:2046–2050.
- 19.↑
Mohile SG, Xian Y, Dale W, et al.. Association of a cancer diagnosis with vulnerability and frailty in older Medicare beneficiaries. J Natl Cancer Inst 2009;101:1206–1215.
- 20.↑
Aaronson NK, Ahmedzai S, Bergman B, et al.. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993;85:365–376.
- 21.↑
Wheelwright S, Darlington AS, Fitzsimmons D, et al.. International validation of the EORTC QLQ-ELD14 questionnaire for assessment of health-related quality of life elderly patients with cancer. Br J Cancer 2013;109:852–858.
- 22.↑
Bruera E, Kuehn N, Miller MJ, et al.. The Edmonton Symptom Assessment System (ESAS): a simple method for the assessment of palliative care patients. J Palliat Care 1991;7:6–9.
- 23.↑
Nipp RD, El-Jawahri A, Ruddy M, et al.. Pilot randomized trial of an electronic symptom monitoring intervention for hospitalized patients with cancer. Ann Oncol 2019;30:274–280.
- 24.↑
Nipp RD, El-Jawahri A, Moran SM, et al.. The relationship between physical and psychological symptoms and health care utilization in hospitalized patients with advanced cancer. Cancer 2017;123:4720–4727.
- 25.↑
Nipp RD, El-Jawahri A, D’Arpino SM, et al.. Symptoms of posttraumatic stress disorder among hospitalized patients with cancer. Cancer 2018;124:3445–3453.
- 26.↑
Lage DE, Nipp RD, D’Arpino SM, et al.. Predictors of posthospital transitions of care in patients with advanced cancer. J Clin Oncol 2018;36:76–82.
- 27.↑
Sheikh JI, Yesavage JA. Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. In: Brink TL, ed. Clinical Gerontology: A Guide to Assessment and Intervention. New York, NY: Haworth Press; 1986:165–173.
- 28.↑
Stewart AL, Kamberg CJ. Physical functioning measures. In: Stewart AL, Ware JE Jr, eds. Measuring Functioning and Well-Being: The Medical Outcomes Study Approach. Durham, NC: Duke University Press; 1992:86–101.
- 29.↑
Fillenbaum GG, Smyer MA. The development, validity, and reliability of the OARS multidimensional functional assessment questionnaire. J Gerontol 1981;36:428–434.
- 30.↑
Hurria A, Gupta S, Zauderer M, et al.. Developing a cancer-specific geriatric assessment: a feasibility study. Cancer 2005;104:1998–2005.
- 31.↑
Kawas C, Karagiozis H, Resau L, et al.. Reliability of the Blessed Telephone Information-Memory-Concentration test. J Geriatr Psychiatry Neurol 1995;8:238–242.
- 32.↑
Blessed G, Tomlinson BE, Roth M. The association between quantitative measures of dementia and of senile change in the cerebral grey matter of elderly subjects. Br J Psychiatry 1968;114:797–811.
- 33.↑
Kansagara D, Englander H, Salanitro A, et al.. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306:1688–1698.
- 34.↑
Glickman ME, Rao SR, Schultz MR. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. J Clin Epidemiol 2014;67:850–857.
- 35.↑
Luciani A, Biganzoli L, Colloca G, et al.. Estimating the risk of chemotherapy toxicity in older patients with cancer: the role of the Vulnerable Elders Survey-13 (VES-13). J Geriatr Oncol 2015;6:272–279.
- 36.↑
Antonio M, Saldaña J, Linares J, et al.. Geriatric assessment may help decision-making in elderly patients with inoperable, locally advanced non-small-cell lung cancer. Br J Cancer 2018;118:639–647.
- 37.↑
Lunney JR, Lynn J, Foley DJ, et al.. Patterns of functional decline at the end of life. JAMA 2003;289:2387–2392.
- 38.↑
Hoppe S, Rainfray M, Fonck M, et al.. Functional decline in older patients with cancer receiving first-line chemotherapy. J Clin Oncol 2013;31:3877–3882.
- 39.↑
Kale HP, Carroll NV. Self-reported financial burden of cancer care and its effect on physical and mental health-related quality of life among US cancer survivors. Cancer 2016;122:283–289.
- 40.↑
Adrion ER, Ryan AM, Seltzer AC, et al.. Out-of-pocket spending for hospitalizations among nonelderly adults. JAMA Intern Med 2016;176:1325–1332.
- 41.↑
Yabroff KR, Lamont EB, Mariotto A, et al.. Cost of care for elderly cancer patients in the United States. J Natl Cancer Inst 2008;100:630–641.
- 42.↑
Nipp RD, El-Jawahri A, Traeger L, et al.. Differential effects of early palliative care based on the age and sex of patients with advanced cancer from a randomized controlled trial. Palliat Med 2018;32:757–766.
- 43.↑
Nipp RD, Greer JA, El-Jawahri A, et al.. Age and gender moderate the impact of early palliative care in metastatic non-small cell lung cancer. Oncologist 2016;21:119–126.
