Screening Tool Identifies Older Adults With Cancer at Risk for Poor Outcomes

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  • a Department of Medicine, Division of Hematology and Oncology, Massachusetts General Hospital Cancer Center and Harvard Medical School, Boston, Massachusetts;
  • b University of Maryland School of Medicine, Baltimore, Maryland;
  • c Department of Psychiatry, and
  • d Department of Medicine, Division of Palliative Care, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; and
  • e Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts.

Background: Oncologists often struggle with managing the complex issues unique to older adults with cancer, and research is needed to identify patients at risk for poor outcomes. Methods: This study enrolled patients aged ≥70 years within 8 weeks of a diagnosis of incurable gastrointestinal cancer. Patient-reported surveys were used to assess vulnerability (Vulnerable Elders Survey [scores ≥3 indicate a positive screen for vulnerability]), quality of life (QoL; EORTC Quality of Life of Cancer Patients questionnaire [higher scores indicate better QoL]), and symptoms (Edmonton Symptom Assessment System [ESAS; higher scores indicate greater symptom burden] and Geriatric Depression Scale [higher scores indicate greater depression symptoms]). Unplanned hospital visits within 90 days of enrollment and overall survival were evaluated. We used regression models to examine associations among vulnerability, QoL, symptom burden, hospitalizations, and overall survival. Results: Of 132 patients approached, 102 (77.3%) were enrolled (mean [M] ± SD age, 77.25 ± 5.75 years). Nearly half (45.1%) screened positive for vulnerability, and these patients were older (M, 79.45 vs 75.44 years; P=.001) and had more comorbid conditions (M, 2.13 vs 1.34; P=.017) compared with nonvulnerable patients. Vulnerable patients reported worse QoL across all domains (global QoL: M, 53.26 vs 66.82; P=.041; physical QoL: M, 58.95 vs 88.24; P<.001; role QoL: M, 53.99 vs 82.12; P=.001; emotional QoL: M, 73.19 vs 85.76; P=.007; cognitive QoL: M, 79.35 vs 92.73; P=.011; social QoL: M, 59.42 vs 82.42; P<.001), higher symptom burden (ESAS total: M, 31.05 vs 15.00; P<.001), and worse depression score (M, 4.74 vs 2.25; P<.001). Vulnerable patients had a higher risk of unplanned hospitalizations (hazard ratio, 2.38; 95% CI, 1.08–5.27; P=.032) and worse overall survival (hazard ratio, 2.26; 95% CI, 1.14–4.48; P=.020). Conclusions: Older adults with cancer who screen positive as vulnerable experience a higher symptom burden, greater healthcare use, and worse survival. Screening tools to identify vulnerable patients should be integrated into practice to guide clinical care.

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.35 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.911 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.1315 We used an age cutoff of ≥70 years because many studies use this cutoff when examining an older population.1618 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.12,1719 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.2325 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.2426 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.2226

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.2325 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

We used descriptive statistics to evaluate participants’ demographic and clinical characteristics, patient-reported outcomes, and their healthcare use and survival outcomes. To examine relationships between patients being categorized as vulnerable and their QoL, symptom burden, and functional impairments, we used multivariable linear regression models. We also compared the rates of moderate-to-severe ESAS-r symptoms for patients categorized as vulnerable or not vulnerable using chi-square tests. For the proportion of days in the hospital within 90 days, we used a Poisson model for days of hospitalization, including an offset for the (log-transformed) number of days alive/in follow-up within 90 days and adjusting for overdispersion via a deviance-based scale parameter. Cox proportional hazards regression models were used to investigate the relationship between vulnerability and overall survival. In these regression models, we adjusted for age, sex, employment status, household income, cancer type, time from diagnosis with advanced disease, number of comorbid conditions, and initial treatment received.26,33 To investigate the relationship between vulnerability and time to first hospitalization within 90 days and time to first ED visit within 90 days, we used competing risk regression (with death treated as a competing event) and purposeful selection of covariates to avoid overfitting, given low event rates. As a correction for multiple tests, we used the false discovery rate (FDR) control method,34 in which each P value is compared with the critical value:

equ1
We chose an FDR of 0.10, which represents an acceptable percentage of results as potential false-positive results.34 In the FDR control method, P values are not adjusted or changed, but rather the largest P value that remains less than the critical value (and all P values smaller than this) is considered significant. We included all P values within a single FDR procedure.

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.

Figure 1.
Figure 1.

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

Table 1.

Patient Characteristics

Table 1.

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).

Table 2.

Patient-Reported Outcomes

Table 2.

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.

Figure 2.
Figure 2.

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).

Table 3.

Relationship Between Vulnerable Elders Survey, Healthcare Use, and Survival

Table 3.

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,1719,35 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,1719,35,36 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.3941 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.1719 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.

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Submitted May 5, 2019; accepted for publication September 3, 2019.

Previous presentation: Presented as an abstract at the 2017 ASCO Annual Meeting; June 2–6, 2017; Chicago, Illinois. Abstract 10040.

Author contributions: Study concept and design: All authors. Data acquisition/analysis and interpretation: All authors. Manuscript preparation/critical revision for important intellectual content: All authors. Final approval: All authors.

Disclosures: Dr. Greer has disclosed that he receives grant/research support from and is a scientific advisor for Gaido Health/BCG Digital Ventures. The remaining authors have disclosed that they not received any financial consideration from any person or organization to support the preparation, analysis, results, or discussion of this article.

Funding: Research reported in this publication was supported by NCI of the National Institutes of Health under award number K24 CA181253 (Temel).

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Correspondence: Ryan D. Nipp, MD, MPH, Department of Medicine, Division of Hematology and Oncology, Massachusetts General Hospital Cancer Center, 55 Fruit Street, Yawkey 7B, Boston, MA 02114. Email: rnipp@mgh.harvard.edu
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    Flow of patients through the study.

    Abbreviation: VES-13, Vulnerable Elders Survey.

  • View in gallery

    Proportion of patients with moderate-to-severe symptoms according to VES-13.

    Abbreviation: VES-13, Vulnerable Elders Survey.

    aDifferences are significant.

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