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Evaluation of the key geriatric assessment constructs in primary brain tumor population - a descriptive study

Open AccessPublished:August 27, 2022DOI:https://doi.org/10.1016/j.jgo.2022.08.013

      Abstract

      Introduction

      Despite an increasing aging population, older adults (≥ 65 years) with primary brain tumors (PBTs) are not routinely assessed for geriatric vulnerabilities. Recent reports of geriatric assessment (GA) in patients with glioblastomas demonstrated that GA may serve as a sensitive prognosticator of overall survival. Yet, current practice does not include routine evaluation of geriatric vulnerabilities and the relevance of GA has not been previously evaluated in broader cohorts of PBT patients. The objective of this descriptive study was to assess key GA constructs in adults with PBT dichotomized into older versus younger groups.

      Materials and Methods

      A cross-sectional analysis of data collected from 579 participants with PBT recruited between 2016 and 2020, dichotomized into older (≥ 65 years, n = 92) and younger (≤ 64 years, n = 487) from an ongoing observational trial. GA constructs were evaluated using socio-demographic characteristics, Charlson Comorbidity Index (CCI), polypharmacy (>5 daily medications), Karnofsky Performance Status (KPS), Neurologic Function Score (NFS), and patient-reported outcome assessments including general health, functional status, symptom burden and interference, and mood. Descriptive statistics, t-tests, chi-square tests, and Pearson correlations were used to evaluate differences between age groups.

      Results

      Older participants were more likely to have problems with mobility (58% vs. 44%), usual activities (64% vs 50%) and self-care (38% vs 26%) compared to the younger participants (odds ratios [ORs] = 1.3–1.4, ps < 0.05), while older participants were less likely to report feeling distressed (OR = 0.4, p < 0.05). Older participants also had higher CCI and were more likely to have polypharmacy (OR = 1.7, ps < 0.05). Increasing age strongly correlated with worse KPS score (r = −0.232, OR = 1.4, p < 0.001) and worse NFS (r = 0.210, OR = 1.5, p < 0.001). No differences were observed in overall symptom burden, symptom interference, and anxiety/depression scores.

      Discussion

      While commonly used GA tools were not available, the study employed patient- and clinician-reported outcomes to identify potential future research directions for the use of GA in the broader neuro-oncology population. Findings illustrate missed opportunities in neuro-oncology practice and underscore the need for incorporation of GA into routine care of this population. Future studies are warranted to further evaluate the prognostic utility of GA and to better understand functional aging outcomes in this patient population.

      Keywords

      1. Introduction

      The incidence of primary brain tumors (PBT) is higher in adults older than 40 years, with a median age of 60 years for all PBTs and 65 years for glioblastomas and meningiomas [
      • Ostrom Q.T.
      • Patil N.
      • Cioffi G.
      • Waite K.
      • Kruchko C.
      • Barnholtz-Sloan J.S.
      CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2013–2017.
      ,
      • Ostrom Q.T.
      • Adel Fahmideh M.
      • Cote D.J.
      • et al.
      Risk factors for childhood and adult primary brain tumors.
      ,
      • Barnholtz-Sloan J.S.
      • Ostrom Q.T.
      • Cote D.
      Epidemiology of brain tumors.
      ]. Cancer and cancer treatments accelerate functional aging phenotypes compounded with normal aging processes, leading to increased morbidity and mortality [
      • Hurria A.
      • Jones L.
      • Muss H.B.
      Cancer treatment as an accelerated aging process: assessment, biomarkers, and interventions.
      ,
      • Guida J.L.
      • Ahles T.A.
      • Belsky D.
      • et al.
      Measuring aging and identifying aging phenotypes in cancer survivors.
      ]. Efforts to date in neuro-oncology have focused on evaluating tumor response and tolerance of standard treatment and its modifications based on chronological age and performance status scores alone [
      • Chahal M.
      • Thiessen B.
      • Mariano C.
      Treatment of older adult patients with glioblastoma: moving towards the inclusion of a comprehensive geriatric assessment for guiding management.
      ]. While past studies demonstrated that older adults (≥ 65 years) diagnosed with glioblastoma may benefit from temozolomide monotherapy, hypofractionated radiotherapy with concurrent temozolomide [
      • Malmström A.
      • Grønberg B.H.
      • Marosi C.
      • et al.
      Temozolomide versus standard 6-week radiotherapy versus hypofractionated radiotherapy in patients older than 60 years with glioblastoma: the Nordic randomised, phase 3 trial.
      ,
      • Wick W.
      • Platten M.
      • Meisner C.
      • et al.
      Temozolomide chemotherapy alone versus radiotherapy alone for malignant astrocytoma in the elderly: the NOA-08 randomised, phase 3 trial.
      ,
      • Perry J.R.
      • Laperriere N.
      • O’Callaghan C.J.
      • et al.
      Short-course radiation plus temozolomide in elderly patients with glioblastoma.
      ], or hypofractionated radiotherapy alone [
      • Roa W.
      • Kepka L.
      • Kumar N.
      • et al.
      International atomic energy agency randomized phase III study of radiation therapy in elderly and/or frail patients with newly diagnosed glioblastoma multiforme.
      ,
      • Roa W.
      • Brasher P.
      • Bauman G.
      • et al.
      Abbreviated course of radiation therapy in older patients with glioblastoma multiforme: a prospective randomized clinical trial.
      ], there is currently no standard approach to guide treatment in older adults with PBTs.
      Extant literature demonstrates that some older patients with PBTs may be at higher risk of toxicity due to overtreatment, whereas others eligible for treatment may receive less aggressive treatments or remain untreated, which may further contribute to earlier mortality [
      • Chahal M.
      • Thiessen B.
      • Mariano C.
      Treatment of older adult patients with glioblastoma: moving towards the inclusion of a comprehensive geriatric assessment for guiding management.
      ,
      • Braun K.
      • Ahluwalia M.S.
      Treatment of glioblastoma in older adults.
      ]. Moreover, a recent study demonstrated that older patients with malignant gliomas experience geriatric vulnerabilities, such as falls, polypharmacy, and comorbidities, not captured by performance status scales [
      • Wasilewski A.
      • Alam A.
      • Mohile N.
      Chemotherapy toxicities and geriatric syndromes in older patients with malignant gliomas.
      ].
      In recent years, geriatric assessment (GA) has been increasingly used as set forth by the International Society of Geriatric Oncology and American Society for Clinical Oncology, aimed at identifying older adults at greatest risk for mortality and adverse events [
      • Wildiers H.
      • Heeren P.
      • Puts M.
      • et al.
      International society of geriatric oncology consensus on geriatric assessment in older patients with cancer.
      ,
      • Mohile S.G.
      • Dale W.
      • Somerfield M.R.
      • et al.
      Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology.
      ]. Several recent studies demonstrated that GA or specific GA domains may serve as significant prognosticator of overall survival in patients with glioblastoma [
      • Lorimer C.F.
      • Walsh G.
      • MacKinnon M.
      • et al.
      Geriatric assessment of glioblastoma patients is feasible and may provide useful prognostic information.
      ,
      • Lombardi G.
      • Bergo E.
      • Caccese M.
      • et al.
      Validation of the comprehensive geriatric assessment as a predictor of mortality in elderly glioblastoma patients.
      ,
      • Deluche E.
      • Leobon S.
      • Lamarche F.
      • Tubiana-Mathieu N.
      First validation of the G-8 geriatric screening tool in older patients with glioblastoma.
      ]. However, these studies excluded patients with non-glioblastoma tumors and did not capture the impact of treatment on patient-centered outcomes, such as symptom burden and overall health status. Greater symptom burden is associated with functional impairment in older patients with cancer [
      • Pandya C.
      • Magnuson A.
      • Flannery M.
      • et al.
      Association between symptom burden and physical function in older patients with cancer.
      ] and both symptom burden and poor performance status were previously shown to be associated with functional limitations in patients with glioblastoma [
      • Vera E.
      • Acquaye A.A.
      • Mendoza T.R.
      • Gilbert M.R.
      • Armstrong T.S.
      Relationship between symptom burden and health status: analysis of the MDASI-BT and EQ-5D.
      ].
      To our knowledge, no studies have evaluated age-related differences using GA in adults across multiple PBT other than glioblastoma. To fill this gap and assess the relevance within the broader neuro-oncology population, we evaluated GA constructs in a large cohort of adults with diverse PBT types. Leveraging patient- and clinician-reported outcomes, the constructs assessed encompassed comorbidities, polypharmacy, functional status, neurologic function, patient-reported health status, mood, symptom burden, and symptom interference. We hypothesized that older adults will have higher comorbidities, polypharmacy, greater functional impairment, lower neurologic function score, and higher mood disturbances, symptom burden, and interference compared to younger adults.

      2. Materials and Methods

      2.1 Study Design and Setting

      This is a cross-sectional analysis of an ongoing observational IRB-approved Natural History Study conducted at the Neuro-Oncology Branch, National Cancer Institute (NCI), National Institutes of Health (NIH) (NCT02851706, PI: TS Armstrong). Details of the study procedures have been previously described [
      • Rogers J.L.
      • Vera E.
      • Acquaye A.
      • et al.
      Living with a central nervous system (CNS) tumor: findings on long-term survivorship from the NIH natural history study.
      ]. Briefly, participants diagnosed with PBT who completed patient-reported outcomes (PROs) measures and enrolled between September 21, 2016 and January 31, 2020 were included in analyses. Clinician-reported outcomes (CROs) and demographic data were collected using standardized forms by the clinicians evaluating the patient. Tumor diagnoses and grading were based on the 2016 World Health Organization Classification of Tumors of the Central Nervous System. Older age was defined as ≥65 years, consistent with prior neuro-oncology studies [
      • Lorimer C.F.
      • Walsh G.
      • MacKinnon M.
      • et al.
      Geriatric assessment of glioblastoma patients is feasible and may provide useful prognostic information.
      ,
      • Lombardi G.
      • Bergo E.
      • Caccese M.
      • et al.
      Validation of the comprehensive geriatric assessment as a predictor of mortality in elderly glioblastoma patients.
      ,
      • Deluche E.
      • Leobon S.
      • Lamarche F.
      • Tubiana-Mathieu N.
      First validation of the G-8 geriatric screening tool in older patients with glioblastoma.
      ]. The cohort was dichotomized into older (≥ 65 years) and younger groups (≤ 64 years) using the age recorded at the last clinic visit prior to analysis. Informed consent was obtained prior to data collection.

      2.2 Clinician-Reported Outcomes Instruments

      Karnofsky Performance Status (KPS) scale was used to evaluate functional status [
      • Karnofsky D.
      Performance scale.
      ]. This non-linear scale includes eleven categories with scores ranging from 0 (dead) to 100 (normal, no complaints; no evidence of disease). The scores were dichotomized as good (KPS ≥ 90) and poor (KPS ≤ 80) [
      • Armstrong T.S.
      • Vera-Bolanos E.
      • Acquaye A.A.
      • Gilbert M.R.
      • Ladha H.
      • Mendoza T.
      The symptom burden of primary brain tumors: evidence for a core set of tumor-and treatment-related symptoms.
      ].
      Comorbidities were assessed using the Charlson Comorbidity Index (CCI), which consists of nineteen items of different medical comorbid conditions [
      • Charlson M.E.
      • Pompei P.
      • Ales K.L.
      • MacKenzie C.R.
      A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.
      ] and both unadjusted and age-adjusted CCI were included. Age-adjusted CCI was weighed to adjust for age with 40 years considered as lowest with each subsequent decade adding 1 point [
      • Charlson M.
      • Szatrowski T.P.
      • Peterson J.
      • Gold J.
      Validation of a combined comorbidity index.
      ]. Seizure incidence (“at least one seizure”) was collected in addition to CCI. Self-reported medication lists were collected during clinic visits and polypharmacy was calculated as more than five daily medications [
      • Masnoon N.
      • Shakib S.
      • Kalisch-Ellett L.
      • Caughey G.E.
      What is polypharmacy? A systematic review of definitions.
      ].
      Lastly, neurological function was assessed using the Neurologic Function Score (NFS), which has five distinct categories ranging from zero(no neurologic symptoms; fully active at home/work without assistance) to four (severe neurologic symptoms; totally inactive requiring complete assistance; unable to work). Scores were dichotomized as good (0–1) and poor (2–4), as previously established [
      • Maranzano E.
      • Terenzi S.
      • Anselmo P.
      • et al.
      A prospective phase II trial on reirradiation of brain metastases with radiosurgery.
      ,
      • Brown P.D.
      • Buckner J.C.
      • O’Fallon J.R.
      • et al.
      Importance of baseline mini-mental state examination as a prognostic factor for patients with low-grade glioma.
      ].

      2.3 Patient-Reported Outcome Instruments

      The EQ-5D-3L instrument was used to measure self-reported general health status along the five dimensions of mobility, self-care, usual activities, pain/discomfort, and anxiety/depression [
      • Group TE
      EuroQol-a new facility for the measurement of health-related quality of life.
      ]. Each dimension consists of three levels: “no problems,” “some problems,” and “extreme problems.” We dichotomized each dimension into (i) “reporting impairment,” which included “some problems,” “unable to perform,” “confined to bed,” and “extreme problems” and (ii) “no impairment,” which included only “no problems.” An EQ-5D-3L global index score was calculated using population-based preference weights with final scores ranging from 0 (health described death-like) to 1 (perfect health) [
      • Shaw J.W.
      • Johnson J.A.
      • Coons S.J.
      US valuation of the EQ-5D health states: development and testing of the D1 valuation model.
      ].
      Patient-Reported Outcomes Measurement Information System (PROMIS)-Anxiety Short Form 8a and -Emotional Distress-Depression Short Form 8a were used to assess anxiety and depressive symptoms over the past seven days, respectively [
      • Pilkonis P.A.
      • Choi S.W.
      • Reise S.P.
      • et al.
      Item banks for measuring emotional distress from the patient-reported outcomes measurement information system (PROMIS®): depression, anxiety, and anger.
      ]. PROMIS-Anxiety and -Depression use an 8-item Likert scale ranging from “never” to “always” with established validity and reliability (r > 0.80). Mean t-scores centered on the general US population are 50 ± standard deviation (SD) of 10 for both measures [
      • Cella D.
      • Riley W.
      • Stone A.
      • et al.
      The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008.
      ].
      The MD Anderson Symptom Inventory-Brain Tumor (MDASI-BT), a self-reported measure of symptom burden and interference with established validity and reliability, was used to capture symptom experiences within the last 24 h [
      • Armstrong T.
      • Mendoza T.
      • Gring I.
      • et al.
      Validation of the MD Anderson symptom inventory brain tumor module (MDASI-BT).
      ]. The questionnaire includes 22 symptom burden items and uses a Likert scale ranging from 0 (“not present”) to 10 (“as bad as you can imagine”) and six symptom interference items rated from 0 (“did not interfere”) to 10 (“interfered completely”). The symptom burden items were categorized into six primary factors (affective, cognitive, neurologic, treatment-related, general disease, and gastrointestinal) and interference items were categorized into two interference subscales (activity-related and mood-related) [
      • Armstrong T.
      • Mendoza T.
      • Gring I.
      • et al.
      Validation of the MD Anderson symptom inventory brain tumor module (MDASI-BT).
      ]. Symptoms rated as ≥5 were considered moderate-severe while interference mean scores of ≥2 were considered moderate-severe.

      2.4 Statistical Analyses

      Descriptive statistics, together with frequency distributions, were used to characterize clinical and demographic variables. All statistical analyses were conducted using IBM SPSS Statistics Version 28.0 (IBM Corporation, Armonk, NY) and figures were created using GraphPad Prism version 8.4.3 for Windows (GraphPad Software, San Diego, California USA, www.graphpad.com). Pearson bivariate correlation analysis was run between the continuous variable of age and measures of functional status (i.e., KPS) and neurologic function (i.e., NFS). Differences between older (≥ 65 years) and younger (≤ 64 years) patient groups in demographic, clinical, patient-reported, and clinician-reported variables were analyzed by running 2 × 2 contingency tables with Pearson chi-square tests, Fisher's tests for categorical variables, and independent samples t-tests for continuous variables. A value of p < 0.05 was considered statistically significant and False Discovery Rate (FDR) was applied for multiple comparison corrections using the RStudio version 1.4.1717 statistical package version 4.1.1. (RStudio, Boston, MA, https://www.rstudio.com). Odds ratios (ORs) were calculated for variables with two categories. Several CROs and demographic variables had missing data with exact numbers outlined in Supplementary Table 1.

      3. Results

      3.1 Sociodemographic and Clinical Characteristics

      A total of 579 PBT participants were included in this cohort, dichotomized into the older group (n = 92, 16%) and the younger group (n = 487, 84%) (Table 1). Participants were predominately White/Non-Hispanic (75%) males (58%). Importantly, no significant differences were identified in the sex, education, race, ethnicity, marital status, or “lives alone” variables. Older participants were more likely to be retired and have an annual income of ≥ $150,000. Astrocytomas were the most common tumor diagnosis (61% older and 63% younger) with the majority having a high grade (III-IV) lesion. Additionally, there was no difference in the percentage of patients undergoing a gross total resection; however, older participants were less likely to have had upfront chemotherapy (p = 0.005) or radiation therapy (p = 0.098) after surgery.
      Table 1Clinical and demographic characteristics.
      Total sample N = 579Older adults n = 92Younger adults n = 487p
      AgeMean [SD]50 [14]70 [4]46 [11]NA
      Median [min, max]50 [18, 85]70 [65, 85]47 [18, 64]
      BMI (kg/m2)Mean [SD]28 [10]29 [15]28 [9]0.507
      Median [min, max]26 [16, 64]26 [18, 51]26 [16,64]
      Time since diagnosis (months)Mean [SD]68 [72]73 [89]67 [69]0.494
      Median [min, max]35 [403]29 [376]36 [403]
      n (%)
      SexFemale243 (42)35 (38)208 (43)0.422
      Male336 (58)57 (62)279 (57)
      Race/EthnicityWhite433 (75)71 (77)362 (74)0.191
      Black/African American38 (7)9 (10)29 (6)
      Asian/Native Hawaiian/Pacific Islander30 (5)6 (7)24 (5)
      Missing/Other25 (4)2 (2)23 (5)
      Hispanic/Latino53 (9)4 (4)49 (10)
      Marital status^Single113 (21)6 (7)107 (23)0.349
      Married375 (69)69 (81)306 (67)
      Divorced/Separated/Widowed57 (10)10 (12)47 (10)
      Lives alone^^No282 (92)41 (89)241 (93)0.379
      Yes24 (8)5 (11)19 (7)
      Education^High school or below77 (14)14 (16)63 (13)0.705
      Some college88 (16)12 (14)76 (16)
      Bachelor's degree192 (34)25 (29)167 (36)
      Professional/Graduate degree201 (36)35 (41)166 (35)
      Annual Household Income^^< $25,00032 (11)3 (7)29 (11)0.046
      Atypical Teratoid Rhabdoid Tumor, atypical meningioma, central neurocytoma, diffuse midline glioma, dysembryoplastic neuroepithelial tumor, ganglioglioma, glial neoplasm, hemangiopericytoma, high grade glioma, high grade neuroepithelial tumor, low grade glioma, medulloblastoma, meningioma, multinodular and vacuolating neuronal tumors, papillary glioneuronal tumor, papillary tumor of pineal region, pineal parenchymal tumor (intermediate differentiation), pineoblastoma, pituitary carcinoma, rosette-forming glioneuronal tumor, rhabdoid meningioma, undifferentiated pleomorphic sarcoma.
      $25,000-$49,99934 (11)2 (5)32 (13)
      $50,000–$149,999125 (42)19 (44)106 (42)
      ≥$150,00059 (20)15 (35)44 (17)
      Missing46 (16)4 (9)42 (17)
      Work status^Employed/Homemaker/Student284 (51)17 (20)267 (57)<0.001
      Atypical Teratoid Rhabdoid Tumor, atypical meningioma, central neurocytoma, diffuse midline glioma, dysembryoplastic neuroepithelial tumor, ganglioglioma, glial neoplasm, hemangiopericytoma, high grade glioma, high grade neuroepithelial tumor, low grade glioma, medulloblastoma, meningioma, multinodular and vacuolating neuronal tumors, papillary glioneuronal tumor, papillary tumor of pineal region, pineal parenchymal tumor (intermediate differentiation), pineoblastoma, pituitary carcinoma, rosette-forming glioneuronal tumor, rhabdoid meningioma, undifferentiated pleomorphic sarcoma.
      Retired99 (18)60 (71)39 (8)
      Disabled/Medical leave/Unemployed due to tumor126 (23)7 (8)119 (25)
      Unemployed47 (9)1 (1)46 (10)
      Tumor DiagnosisAstrocytoma361 (62)56 (61)305 (63)0.706
      Oligodendroglioma76 (13)8 (9)68 (14)
      Ependymoma39 (7)7 (8)32 (7)
      Other
      Atypical Teratoid Rhabdoid Tumor, atypical meningioma, central neurocytoma, diffuse midline glioma, dysembryoplastic neuroepithelial tumor, ganglioglioma, glial neoplasm, hemangiopericytoma, high grade glioma, high grade neuroepithelial tumor, low grade glioma, medulloblastoma, meningioma, multinodular and vacuolating neuronal tumors, papillary glioneuronal tumor, papillary tumor of pineal region, pineal parenchymal tumor (intermediate differentiation), pineoblastoma, pituitary carcinoma, rosette-forming glioneuronal tumor, rhabdoid meningioma, undifferentiated pleomorphic sarcoma.
      88 (15)18 (19)70 (14)
      No tissue diagnosis15 (3)3 (3)12 (2)
      Tumor GradeWHO grade I-II130 (22)23 (25)107 (22)0.795
      WHO grade III-IV427 (74)66 (72)361 (74)
      No tissue/none assigned22 (4)3 (3)19 (4)
      Surgery⁎⁎Gross total resection191 (33)30 (33)161 (33)0.692
      Subtotal resection186 (32)25 (28)161 (33)
      Biopsy124 (21)20 (22)104 (21)
      Resection NOS62 (11)13 (14)49 (10)
      No surgery15 (3)3 (3)12 (3)
      Prior radiation⁎⁎Yes477 (82)70 (76)407 (84)0.098
      No101 (18)22 (24)79 (16)
      Prior chemotherapy⁎⁎Yes417 (72)55 (60)362 (74)0.005
      Atypical Teratoid Rhabdoid Tumor, atypical meningioma, central neurocytoma, diffuse midline glioma, dysembryoplastic neuroepithelial tumor, ganglioglioma, glial neoplasm, hemangiopericytoma, high grade glioma, high grade neuroepithelial tumor, low grade glioma, medulloblastoma, meningioma, multinodular and vacuolating neuronal tumors, papillary glioneuronal tumor, papillary tumor of pineal region, pineal parenchymal tumor (intermediate differentiation), pineoblastoma, pituitary carcinoma, rosette-forming glioneuronal tumor, rhabdoid meningioma, undifferentiated pleomorphic sarcoma.
      No161 (28)37 (40)124 (26)
      Recurrence0235 (41)37 (40)198 (41)0.091
      1142 (24)30 (33)112 (23)
      ≥2202 (35)25 (27)177 (36)
      Polypharmacy^ (> 5 medications)Yes246 (44)61 (68)185 (39)<0.001
      Atypical Teratoid Rhabdoid Tumor, atypical meningioma, central neurocytoma, diffuse midline glioma, dysembryoplastic neuroepithelial tumor, ganglioglioma, glial neoplasm, hemangiopericytoma, high grade glioma, high grade neuroepithelial tumor, low grade glioma, medulloblastoma, meningioma, multinodular and vacuolating neuronal tumors, papillary glioneuronal tumor, papillary tumor of pineal region, pineal parenchymal tumor (intermediate differentiation), pineoblastoma, pituitary carcinoma, rosette-forming glioneuronal tumor, rhabdoid meningioma, undifferentiated pleomorphic sarcoma.
      No315 (56)29 (32)286 (61)
      At least 1 seizure⁎⁎Yes210 (37)19 (22)191 (40)0.001
      No357 (63)69 (78)288 (60)
      Abbreviations: BMI = body mass index, SD = standard deviation, WHO = World Health Organization, NOS = not otherwise specified.
      Missing data: variables that had lower sample sizes due to missing data are denoted as following:⁎⁎missing 1–12, ^ missing 18–34, ^^missing 273–283 participants' responses (Supplementary Table 1).
      low asterisk Atypical Teratoid Rhabdoid Tumor, atypical meningioma, central neurocytoma, diffuse midline glioma, dysembryoplastic neuroepithelial tumor, ganglioglioma, glial neoplasm, hemangiopericytoma, high grade glioma, high grade neuroepithelial tumor, low grade glioma, medulloblastoma, meningioma, multinodular and vacuolating neuronal tumors, papillary glioneuronal tumor, papillary tumor of pineal region, pineal parenchymal tumor (intermediate differentiation), pineoblastoma, pituitary carcinoma, rosette-forming glioneuronal tumor, rhabdoid meningioma, undifferentiated pleomorphic sarcoma.

      3.2 Clinician-Reported Outcomes

      3.2.1 Comorbidities

      Experiencing at least one seizure was reported by 22% of older participants compared to 40% of younger participants (X2(1) = 10.66, OR = 0.5, p = 0.001) (Table 1). In addition, older participants had higher CCI (mean = 0.94, range 0–6) compared to their younger counterparts (mean = 0.14, range = 0–2, t (65.7) = −4.596, p < 0.001). Similarly, for age-adjusted CCI, older participants had significantly higher CCI (mean = 3.45, range = 2–9) compared to younger participants (mean = 0.64, range = 0–4, t(72.1) = −14.612, p < 0.001) (Fig. 2A and B).

      3.2.2 Polypharmacy

      Regarding medications, older participants reported taking a mean of eight (range 1–25) medications daily, while younger participants had a mean of five (range 1–21). When categorized into polypharmacy (> 5 daily medications), older participants (68%) were 1.7 times more likely to report taking more than five medications compared to younger participants (39%) (X2(1) = 24.9, OR = 1.7, p < 0.001) (Table 1).

      3.2.3 Body Mass Index (BMI)

      There were no differences in BMI between the two age groups. Both older and younger participants had similar percentages in underweight (1% vs. 1%), normal weight (38% vs. 35%), overweight (35% vs. 36%), and obese (26% vs. 28%) categories, respectively.

      3.2.4 Functional Status

      KPS scores ranged from 40 to 100 in both groups. As age increased, KPS scores significantly decreased (r = −0.232, p < 0.001) (Fig. 1A ). Older patients were 1.4 times more likely to have a poor KPS (≤ 80) than younger patients (X2(1) = 8.7, p = 0.003, OR = 1.4) (59% versus 43%) (Fig. 1C).
      Fig. 1
      Fig. 1Older age associated with worse functional status and neurological function. (A) KPS scores negatively correlated with age (r = −0.232, p < 0.001, n = 573), (B) NFS scores positively correlated with age (r = 0.210, p < 0.001, n = 548); (C) Chi-square test found that older patients were more likely to have a poor KPS (≤80) than younger patients (X2(1) = 8.7, p = 0.003, OR = 1.4), (D) Chi-square test found that older patients were more likely to have a poor NFS (2–4) than younger patients (X2(1) = 7.7, p = 0.006, OR = 1.5).
      p < 0.05.
      Fig. 2
      Fig. 2Charlson Comorbidity Index(CCI)⁎⁎. (A) Higher unadjusted CCI was found in older group (mean = 0.94, SD = 1.36, range = 0–6) compared to younger group (mean = 0.14, SD = 0.45, range = 0–2, t(65.7) = −4.596, p < 0.001). (B) Higher age-adjusted CCI was found in older group (mean = 3.45, SD = 1.5, range = 2–9) compared to younger group (mean = 0.64, SD = 1.9, range = 0–4, t(72.1) = −14.612, p < 0.001).
      ⁎⁎CCI had complete data of 64 older and 334 younger participants.
      Fig. 3
      Fig. 3Mood. No significant differences (p = 0.074) were found in anxiety measured by PROMIS-Anxiety between older (mean = 49.2, SD = 9.02) and younger (mean = 51.2, SD = 10.12) adults. PROMIS-Depression did not differ between older (mean = 50.1, SD = 9.08) and younger adults (mean = 50.3, SD = 9.69, p = 0.083).

      3.2.5 Neurologic Function

      NFS ranged from 0 to 4 in both age groups. As age increased, NFS scores also significantly increased (r = 0.210, p < 0.001) (Fig. 1B). Older patients were 1.5 times more likely to have a poor NFS (2–4) than younger patients (X2(1) = 7.7, p = 0.007, OR = 1.5) (42% versus 27%, respectively) (Fig. 1D).

      3.3 Patient-Reported Outcomes

      3.3.1 General Health Status

      Older participants reported greater functional impairment in the EQ-5D-3L dimensions of mobility, usual activities, and self-care (ORs = 1.3–1.4, p = 0.035), after adjusting the significance for multiple comparisons (Table 2). Specifically, older participants were 1.3 times more likely to have problems with mobility (58% vs. 44%) and usual activities (64% vs 50%), and 1.4 times more likely to have problems with self-care (38% vs 26%) compared to the younger participants. No significant differences were found in the pain/discomfort or anxiety/depression dimensions (Table 2). Notably, there was no significant difference in the perception of overall health status (EQ-5D index score) between older and younger participants' scores (0.73 vs. 0.77, respectively, p = 0.237).
      Table 2EQ-5D-3L dimensions.
      Primary domainsLevels of impairmentOlder patients (n = 92)Younger patients (n = 487)pAdj. pOR
      Older group is the reference for odds ratio.
      n%n%
      MobilityNo problems walking about3942%27556%0.0130.035
      p < 0.05.
      1.3
      Some problems or confined to bed5358%21244%
      Usual activitiesNo problems with usual activities3336%24250%0.0150.035
      p < 0.05.
      1.3
      Some problems or unable to perform5964%24550%
      Self-careNo problems with self-care5762%35974%0.0210.035
      p < 0.05.
      1.4
      Some problems or unbale to perform3538%12826%
      Anxiety/DepressionNot anxious or depressed5560%24350%0.0890.1110.8
      Moderately or severely anxious or depressed3740%24450%
      Pain/DiscomfortNo pain or discomfort5863%30362%0.9070.9071.0
      Moderate or extreme pain or discomfort3437%18438%
      All p-values are calculated using Fisher's Exact test. False Discovery Rate (FDR) was used for multiple comparison corrections.
      Abbreviations: OR = odds ratio, adj. = adjusted.
      low asterisk p < 0.05.
      a Older group is the reference for odds ratio.

      3.3.2 Mood

      Mean anxiety scores were 49.2 (SD = 9.02) for older and 51.2 (SD = 10.12) for younger participants. Mean depression scores were 50.1 (SD = 9.08) for older and 50.3 (SD = 9.69) for younger participants (Fig. 3). No significant differences were found in either PROMIS-Anxiety or -Depression scores.

      3.3.3 Symptom Burden and Interference

      MDASI-BT mean symptom burden scores for older and younger participants ranged from zero to six and zero to eight, respectively. No significant differences were found in symptom burden scores between older (mean = 1.8, SD = 1.5) and younger (mean = 2, SD = 1.7) participants. The top three moderate-severe symptoms in both groups were (1) fatigue (44% older, 41% younger), (2) feeling drowsy (29% older, 30% younger), and (3) difficulty remembering (28% older, 29% younger) (Table 3). Fewer older participants reported feeling distressed compared to younger participants (11% vs. 27%, respectively, OR = 0.4, p = 0.022) after a false discovery rate (FDR) correction was applied (Table 3). Among the six symptom factors, older participants had only a lower affective symptom factor score compared to younger participants (mean = 2.3 vs. 2.9, respectively, p = 0.011); however, after applying a FDR correction, the difference was no longer statistically significant (p = 0.066).
      Table 3Comparison of patients with moderate - severe symptoms (MDASI-BT) between older and younger cohorts.
      SymptomsOlder patients (n = 92)Younger patients (n = 487)pAdj. pORa
      count%count%
      Affective
      Fatigue4044200410.7291.0001.1
      Disturbed sleep1415140290.0070.0770.5
      Feeling distressed1011132270.0010.0220.4
      Feeling sad1415117240.0770.340.6
      Irritability1213106220.0660.3630.6
      Cognitive
      Difficulty understanding182082170.5481.0001.2
      Difficulty remembering2628140291.0001.0001.0
      Difficulty speaking232580160.0540.3961.5
      Difficulty concentrating171992191.0001.0001.0
      Neurologic
      Seizures223160.1420.520.3
      Weakness on one side of body2022116240.7891.0000.9
      Numbness/tingling141576161.0001.0001.0
      Pain121386180.3630.890.7
      Treatment-related
      Dry mouth161771150.5241.0001.2
      Feeling drowsy2729145301.0001.0001.0
      Lack of appetite8951110.7091.0000.8
      General Disease
      Change in appearance121356120.7241.0001.1
      Vision2123100210.6751.0001.1
      Change in bowel pattern91079160.1530.4800.6
      Shortness of breath674390.5461.0000.7
      GI
      Nausea7858120.2820.780.6
      Vomiting552350.791.0001.2
      Note: a Older group is the reference for odds ratio. p < 0.05. A rating of 5 or higher on a 0–10 scale is considered moderate - severe.
      Abbreviations: OR = odds ratio, adj. = adjusted, GI = gastrointestinal.
      Interference scores ranged from 0 to 10, with a mean of 2.9 for both age groups. Although not statistically significant, older participants were 1.2 times (55% vs. 45%, OR = 1.2, p = 0.067) more likely to report moderate-severe interference of their walking compared to younger participants (Table 4). There were no significant differences in the activity-related and mood-related interference subscale scores between groups.
      Table 4Severity of interference items between older and younger groups.
      Interference itemsLevels of impairmentOlder patients (n = 92)Younger patients (n = 487)pOR a
      n%n%
      Activity-Related
      General ActivityNone-Mild3740215440.4861.1
      Moderate-Severe556027256
      WorkNone-Mild4448215440.5150.9
      Moderate-Severe485227256
      WalkingNone-Mild4145266550.0671.2
      Moderate-Severe515521845
      Mood-Related
      MoodNone-Mild4953220450.1540.9
      Moderate-Severe434726755
      EnjoymentNone-Mild4043238490.3421.2
      Moderate-Severe525724951
      RelationsNone-Mild5661272560.3730.8
      Moderate-Severe363921544
      Note: a Older group is the reference for odds ratio. p < 0.05. Interference items 0–1 are coded as none-mild and ≥ 2 are coded as moderate- severe.
      Abbreviations: OR = odds ratio.

      4. Discussion

      The world's aging population is growing at an accelerated rate, with adults aged 65 years and above expected to reach 83.7 million by the year 2050 [
      • Ortman J.M.
      • Velkoff V.A.
      • Hogan H.
      An aging nation: the older population in the United States.
      ]. This, coupled with the fact that cancer, including brain tumors, occurs more commonly in older adults, contributes to a substantial increase in cancer numbers in an aging population. The GA can potentially identify vulnerabilities, guide interventions, assist in clinical treatment decisions, predict toxicity and prognosticate survival in oncology patients [
      • Hamaker M.
      • Lund C.
      • te Molder M.
      • et al.
      Geriatric assessment in the management of older patients with cancer–a systematic review (update).
      ,
      • Loh K.P.
      • Soto-Perez-de-Celis E.
      • Hsu T.
      • et al.
      What every oncologist should know about geriatric assessment for older patients with cancer: young international society of geriatric oncology position paper.
      ]. To our knowledge, this is the first study using patient- and clinician- reported outcomes along with standard clinical assessments and characteristics to assess key GA constructs between age groups in a large PBT cohort. We found that older participants were more likely to be retired, have higher annual income, higher comorbidities, worse performance status and neurological function, and more impairments in mobility, usual activities, and self-care. Older participants also reported significantly less distress; however, both age groups had comparable overall symptom burden, symptom interference, and mood disturbance.
      The GA starts with careful review for demographic and social vulnerabilities of older adults [
      • Wildiers H.
      • Heeren P.
      • Puts M.
      • et al.
      International society of geriatric oncology consensus on geriatric assessment in older patients with cancer.
      ,
      • Loh K.P.
      • Soto-Perez-de-Celis E.
      • Hsu T.
      • et al.
      What every oncologist should know about geriatric assessment for older patients with cancer: young international society of geriatric oncology position paper.
      ]. In our cohort, the majority in both age groups were married and did not live alone, suggesting a lower likelihood of social loneliness and isolation, two critical geriatric vulnerabilities [
      • Soto-Perez-de-Celis E.
      • Li D.
      • Yuan Y.
      • Lau Y.M.
      • Hurria A.
      Functional versus chronological age: geriatric assessments to guide decision making in older patients with cancer.
      ,
      • Steptoe A.
      • Shankar A.
      • Demakakos P.
      • Wardle J.
      Social isolation, loneliness, and all-cause mortality in older men and women.
      ]. Additionally, older participants were more likely to be retired and have higher income than younger participants. This is congruent with other studies showing that increasing age is a risk factor for an early retirement [
      • Carlsen K.
      • Oksbjerg Dalton S.
      • Frederiksen K.
      • Diderichsen F.
      • Johansen C.
      Cancer and the risk for taking early retirement pension: a Danish cohort study.
      ] and younger age is a predictor of higher likelihood of financial hardship [
      • Hastert T.A.
      • Young G.S.
      • Pennell M.L.
      • et al.
      Financial burden among older, long-term cancer survivors: results from the LILAC study.
      ,
      • Yabroff K.R.
      • Dowling E.C.
      • Guy Jr., G.P.
      • et al.
      Financial hardship associated with cancer in the United States: findings from a population-based sample of adult cancer survivors.
      ] among cancer survivors.
      The measurement of comorbidities, aggregation of two or more co-occurring medical diagnoses in the same individual [
      • Fried L.P.
      • Ferrucci L.
      • Darer J.
      • Williamson J.D.
      • Anderson G.
      Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care.
      ], using indices such as the CCI has been demonstrated to have high prognostic value of survival among cancer survivors [
      • Canoui-Poitrine F.
      • Segaux L.
      • Benderra M.-A.
      • et al.
      The prognostic value of eight comorbidity indices in older patients with cancer: the ELCAPA cohort study.
      ]. Consistent with prior oncology reports [
      • Williams G.R.
      • Mackenzie A.
      • Magnuson A.
      • et al.
      Comorbidity in older adults with cancer.
      ], the older group had higher comorbidity index demonstrated by both age-adjusted and unadjusted CCI. The presence of comorbidities diminishes receipt of chemotherapy [
      • Williams G.R.
      • Mackenzie A.
      • Magnuson A.
      • et al.
      Comorbidity in older adults with cancer.
      ,
      • Søgaard M.
      • Thomsen R.W.
      • Bossen K.S.
      • Sørensen H.T.
      • Nørgaard M.
      The impact of comorbidity on cancer survival: a review.
      ], which is on par with our finding that older participants were less likely to receive chemotherapy, a finding not observed in the younger group. Conversely, while seizures are not a factor in CCI, they are prevalent in the PBT population. We, therefore, evaluated the incidence of seizures and, as anticipated, fewer older participants reported seizures compared to younger adults, who tend to have slower-growing tumors [
      • Armstrong T.S.
      • Grant R.
      • Gilbert M.R.
      • Lee J.W.
      • Norden A.D.
      Epilepsy in glioma patients: mechanisms, management, and impact of anticonvulsant therapy.
      ].
      Polypharmacy is common in older patients with cancer and leads to additional toxicities, drug interactions, and increased costs [
      • Lees J.
      • Chan A.
      Polypharmacy in elderly patients with cancer: clinical implications and management.
      ]. Decreased renal and hepatic function alters drug pharmacology, typically decreasing drug clearance, and is associated with biological aging [
      • McLean A.J.
      • Le Couteur D.G.
      Aging biology and geriatric clinical pharmacology.
      ]. Decline in these functions can be further accelerated by cancer and its treatment. In our cohort, polypharmacy was 1.7 times more likely in the older group. Polypharmacy is associated with moderate-to-severe drug-drug interactions and therapeutic duplication [
      • Balducci L.
      • Goetz-Parten D.
      • Steinman M.
      Polypharmacy and the management of the older cancer patient.
      ]. Therefore, inclusion of GA tools, such as Beers criteria, in older PBT patients may help mitigate adverse outcomes.
      Nutritional status represents an additional oncogeriatric parameter related to decreased performance status and worse overall survival [
      • Wildiers H.
      • Heeren P.
      • Puts M.
      • et al.
      International society of geriatric oncology consensus on geriatric assessment in older patients with cancer.
      ,
      • Huisman M.
      • Veronese G.
      • Audisio R.
      • et al.
      Poor nutritional status is associated with other geriatric domain impairments and adverse postoperative outcomes in onco-geriatric surgical patients–a multicentre cohort study.
      ]. Although nutritional status or weight loss were not assessed, comparison of BMI and BMI categories between age groups revealed no significant differences. BMI, albeit a straightforward clinical tool, is limited in its ability to discern between fat versus muscle and a one-time measure does not capture weight loss [
      • Bullock A.F.
      • Greenley S.L.
      • McKenzie G.A.
      • Paton L.W.
      • Johnson M.J.
      Relationship between markers of malnutrition and clinical outcomes in older adults with cancer: systematic review, narrative synthesis and meta-analysis.
      ], making it a poor proxy of malnutrition. However, in a recent review of nutritional measures in all malignancies, BMI was included in 21 studies. No association between BMI and patient outcomes was found in thirteen studies and an association between low BMI and poor cancer-related outcomes was found in eight studies [
      • Bullock A.F.
      • Greenley S.L.
      • McKenzie G.A.
      • Paton L.W.
      • Johnson M.J.
      Relationship between markers of malnutrition and clinical outcomes in older adults with cancer: systematic review, narrative synthesis and meta-analysis.
      ].
      Functional status is the most significant GA domain because it is intended to capture early functional decline, a significant prognosticator of early morbidity and mortality [
      • Guida J.L.
      • Ahles T.A.
      • Belsky D.
      • et al.
      Measuring aging and identifying aging phenotypes in cancer survivors.
      ,
      • Soto-Perez-de-Celis E.
      • Li D.
      • Yuan Y.
      • Lau Y.M.
      • Hurria A.
      Functional versus chronological age: geriatric assessments to guide decision making in older patients with cancer.
      ,
      • Loh K.P.
      • Lam V.
      • Webber K.
      • et al.
      Characteristics associated with functional changes during systemic cancer treatments: a systematic review focused on older adults.
      ]. Consistent with previous studies in PBT patients [
      • Oszvald Á.
      • Güresir E.
      • Setzer M.
      • et al.
      Glioblastoma therapy in the elderly and the importance of the extent of resection regardless of age.
      ,
      • Slot K.M.
      • Peters J.V.
      • Vandertop W.P.
      • Verbaan D.
      • Peerdeman S.M.
      Meningioma surgery in younger and older adults: patient profile and surgical outcomes.
      ], using CROs we found that age significantly correlated with worse functional status scores and older adults were more likely to have poor functional status. While KPS is frequently used in oncology practice, contemporary evidence demonstrates that it does not capture functional deficits that may be revealed by GA and is a poor prognosticator of functional decline [
      • Soto-Perez-de-Celis E.
      • Li D.
      • Yuan Y.
      • Lau Y.M.
      • Hurria A.
      Functional versus chronological age: geriatric assessments to guide decision making in older patients with cancer.
      ,
      • Jolly T.A.
      • Deal A.M.
      • Nyrop K.A.
      • et al.
      Geriatric assessment-identified deficits in older cancer patients with normal performance status.
      ]. In support of this are studies that found 47% of people with glioblastoma and good KPS (70–100) were diagnosed as frail using the comprehensive GA [
      • Lombardi G.
      • Bergo E.
      • Caccese M.
      • et al.
      Validation of the comprehensive geriatric assessment as a predictor of mortality in elderly glioblastoma patients.
      ], and older age was associated with mobility impairment measured by Timed Up and Go test and Times Sit-to-Stand (TSS) in a PBT cohort [
      • Rogers J.L.
      • De La Cruz Minyety J.
      • Vera E.
      • et al.
      Assessing mobility in primary brain tumor patients: a descriptive feasibility study using two established mobility tests.
      ].
      We investigated differences in functional status between age groups using PROs, the EQ-5D-3L and MDASI-BT, and found that older participants had significantly greater impairments in mobility, usual activities, and self-care. In addition, while not statistically significant, older adults were more likely to report greater walking interference. Notably, about half of the participants in both age groups reported activity-related interference, with older participants more frequently reporting moderate-severe interference with walking. Similarly, in a cohort of 903 cancer survivors, older age was associated with greater symptom interference with walking [
      • Mohile S.G.
      • Heckler C.
      • Fan L.
      • et al.
      Age-related differences in symptoms and their interference with quality of life in 903 cancer patients undergoing radiation therapy.
      ]. These findings suggest a relationship between activity-related symptom interference with functional impairment [
      • Vera E.
      • Acquaye A.A.
      • Mendoza T.R.
      • Gilbert M.R.
      • Armstrong T.S.
      Relationship between symptom burden and health status: analysis of the MDASI-BT and EQ-5D.
      ], and, as previously reported by our group, greater activity-related interference may be related to tumor progression in patients with glioblastomas [
      • Armstrong T.S.
      • Vera-Bolanos E.
      • Gning I.
      • et al.
      The impact of symptom interference using the MD Anderson symptom inventory-brain tumor module (MDASI-BT) on prediction of recurrence in primary brain tumor patients.
      ]. These findings highlight the need for gait assessment, fall risk, and potentially rehabilitation and assistance needs in this patient population.
      Although we did not observe differences in cognitive or neurologic factors of the MDASI-BT, increasing age correlated with worsening NFS scores and older participants were more likely to have poor NFS. NFS reflects clinician-assessed impact of neurologic symptoms (e.g., aphasia, seizures, and weakness) of participants in PBTs. Poor NFS indicates greater impairment of function. Notably, there was a lower incidence of seizures found among the older group compared to the younger group, and fewer older participants received chemotherapy with no group differences in tumor diagnoses, tumor grade, or history of tumor recurrence. The observed age differences in NFS may be related to brain aging processes previously reported in glioblastomas (i.e., senescence-associated secretory phenotype (SASP), neuroinflammation, and indoleamine 2,3-dioxygenase [IDO]) [
      • Kim M.
      • Ladomersky E.
      • Mozny A.
      • et al.
      Glioblastoma as an age-related neurological disorder in adults.
      ,
      • Ladomersky E.
      • Zhai L.
      • Lauing K.L.
      • et al.
      Advanced age increases immunosuppression in the brain and decreases immunotherapeutic efficacy in subjects with glioblastoma.
      ]. Moreover, given the higher CCI scores and presence of polypharmacy among older participants, NFS findings may be related to the synergistic effects of comorbidities and polypharmacy together with brain aging and effects of the tumor itself.
      Lastly, we found that older participants were less likely to report feeling distressed or to report disturbed sleep, a finding that is consistent with prior reports [
      • Cataldo J.K.
      • Paul S.
      • Cooper B.
      • et al.
      Differences in the symptom experience of older versus younger oncology outpatients: a cross-sectional study.
      ,
      • Oksholm T.
      • Miaskowski C.
      • Kongerud J.S.
      • et al.
      Does age influence the symptom experience of lung cancer patients prior to surgery?.
      ] of cancer survivors. In contrast, a study by Mohile et al. [
      • Mohile S.G.
      • Heckler C.
      • Fan L.
      • et al.
      Age-related differences in symptoms and their interference with quality of life in 903 cancer patients undergoing radiation therapy.
      ] found that older adults had greater distress and sleep disturbances in the last week of radiation therapy, compared to younger adults. These differences between our studies may be related to the timing of assessments, which were more acute in the Mohile et al. [
      • Mohile S.G.
      • Heckler C.
      • Fan L.
      • et al.
      Age-related differences in symptoms and their interference with quality of life in 903 cancer patients undergoing radiation therapy.
      ] study compared to ours. In addition, Mohile et al. [
      • Mohile S.G.
      • Heckler C.
      • Fan L.
      • et al.
      Age-related differences in symptoms and their interference with quality of life in 903 cancer patients undergoing radiation therapy.
      ] had equal doses of therapy delivered in both age groups in contrast to our cohort, which reported a lower incidence of chemotherapy in older participants. Additionally, anxiety and depression symptom scores were found to be comparable between age groups. In contrast, distress, anxiety, and depression, are frequently reported to be higher among younger cancer survivors across all cancer types [
      • Mohile S.G.
      • Heckler C.
      • Fan L.
      • et al.
      Age-related differences in symptoms and their interference with quality of life in 903 cancer patients undergoing radiation therapy.
      ,
      • Götze H.
      • Friedrich M.
      • Taubenheim S.
      • Dietz A.
      • Lordick F.
      • Mehnert A.
      Depression and anxiety in long-term survivors 5 and 10 years after cancer diagnosis.
      ,
      • Weiss Wiesel T.R.
      • Nelson C.J.
      • Tew W.P.
      • et al.
      The relationship between age, anxiety, and depression in older adults with cancer.
      ]. This generational difference may be related to younger participants viewing cancer as a greater threat to their phase of life and work, greater cancer fatalism, or fear of inevitable death due to cancer [
      • Paige S.R.
      • Alpert J.M.
      • Bylund C.L.
      Fatalistic cancer beliefs across generations and geographic classifications: examining the role of health information seeking challenges and confidence.
      ], while older participants are thought to assess their health status in comparison to their chronological age peers [
      • Götze H.
      • Friedrich M.
      • Taubenheim S.
      • Dietz A.
      • Lordick F.
      • Mehnert A.
      Depression and anxiety in long-term survivors 5 and 10 years after cancer diagnosis.
      ].
      Although this study includes a large cohort of participants with PBT, which were demographically and clinically well-matched, and leveraged concurrent use of PROs and CROs, there are several key limitations worth noting. First, the older participants' sample size was small compared to younger participants, which limited the statistical power of analyses. Second, the study is cross-sectional in nature, thus limiting the ability to evaluate changes in the GA constructs over time. It is important to note our study employed CROs (KPS, NFS) and PROs (EQ-5D-3L, MDASI-BT) to assess functional status rather than commonly used GA tools such as ADLs or iADLs. Further, data on cognition, falls and geriatric syndromes such as frailty and dementia were not collected. Thus, future GA studies in the broader neuro-oncology patient population would benefit from incorporating GA constructs [
      • Wildiers H.
      • Heeren P.
      • Puts M.
      • et al.
      International society of geriatric oncology consensus on geriatric assessment in older patients with cancer.
      ]. Additionally, although the comparison groups are unbalanced, our sample had a mean age of 50 (SD 14), consistent with the higher incidence of PBT in adults older than 40 years of age and represents the diversity of neuro-oncologic diagnoses rather than the high grade gliomas alone. Lastly, we acknowledge a limitation of this study may be a referral bias of patients enrolling into the Natural History Study at the National Institutes of Health and older group (≥ 65 years) may be particularly susceptible to the selection bias as evidenced by the smaller number of participants.
      In summary, our findings highlight that older participants living with a PBT may have more vulnerabilities in functional aging parameters, such as functional and neurological function status, comorbidities, and polypharmacy, compared to younger participants. Functional impairments were more evident in the older group across both PROs and CROs, highlighting this as a vulnerability and an important opportunity for future research. Additionally, both age groups were similar in overall symptom burden, severity of symptom interference, mood and overall health status, suggesting that further assessments encompassing all age groups would be informative in uncovering functional aging impairments related to PBT.
      Findings highlight several important future directions in advancing the science in the PBT population. Specifically, systematic inclusion of geriatric vulnerability assessments, such as frailty, malnutrition, and dementia, using the tools previously outlined by GA researchers [
      • Wildiers H.
      • Heeren P.
      • Puts M.
      • et al.
      International society of geriatric oncology consensus on geriatric assessment in older patients with cancer.
      ]. Future prospective studies should also incorporate longitudinal designs with comprehensive GA across the disease trajectory with measures of emotional and caregiver support, in addition to the items noted above and greater inclusion of gender, racial, and ethnic minorities to fully understand geriatric vulnerabilities across the entire diverse PBT patient population.

      Funding Statement

      This research was supported by the Intramural Research Program of the National Cancer Institute , National Institutes of Health ( 1ZIABC011768-03 , PI: Dr. Terri S. Armstrong).

      Author Contributions

      Conceptualization: DS, EV, TSA, HL, MRG; Supervision: TSA, HL, EV; Data curation: EV, AC, AA, NB, AC, EG, VJ, JL, ML, JR, KR, JR, MT, LB, EB, NL, MP, MPP, VP, LP, BJT, JW, MRG, TSA, HL; Formal analysis: DS, EV, TSA, HL; Writing-original draft: DS, TSA, HL; Writing- editing: DS, EV, AC, AA, NB, AC, EG, VJ, JL, ML, JR, KR, JR, MT, LB, EB, NL, MP, MPP, VP, LP, BJT, JW, MRG, TSA, HL; Writing- review: DS, EV, AC, AA, NB, AC, EG, VJ, JL, ML, JR, KR, JR, MT, LB, EB, NL, MP, MPP, VP, LP, BJT, JW, MRG, TSA, HL.

      Declaration of Competing Interest

      None.

      Acknowledgements

      Our research team would like to thank all of the patients and their families for their generous participation in the Natural History Study.

      Appendix A. Supplementary data

      • The supplementary Table 1 details patient-reported and clinician-reported outcomes with missing data across all groups. BMI = body mass index, CCI = Charlson Comorbidity Index, WHO = World Health Organization.

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