Advertisement

Change in four measures of physical function among older adults during lung cancer treatment: A mixed methods cohort study

Open AccessPublished:September 01, 2022DOI:https://doi.org/10.1016/j.jgo.2022.08.015

      Abstract

      Introduction

      Functional outcomes during non-small cell lung cancer (NSCLC) treatment are critically important to older adults. Yet, data on physical function and which measures best capture functional change remain limited.

      Materials and Methods

      This multisite, mixed methods cohort study recruited adults ≥65 years with advanced NSCLC starting systemic treatment (i.e., chemotherapy, immunotherapy, and/or targeted therapy) with non-curative intent. Participants underwent serial geriatric assessments prior to starting treatment and at one, two, four, and six months, which included the Karnofsky Performance Scale (KPS, range: 0–100%), instrumental activities of daily living (IADL, range: 0–14), European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Physical Functioning subscale (EORTC QLQ-C30 PF, range: 0–100), and Life-Space Assessment (LSA, range: 0–120). For all measures, higher scores represent better functioning. In a qualitative substudy, 20 patients completed semi-structured interviews prior to starting treatment and at two and six months to explore how treatment affected their daily functioning. We created joint displays for each interview participant that integrated their longitudinal KPS, IADL, EORTC QLQ-C30 PF, and LSA scores with patient quotes describing their function.

      Results

      Among 87 patients, median age was 73 years (range 65–96). Mean pretreatment KPS score was 79% (standard deviation [SD] 13), EORTC QLQ-C30 PF was 69 (SD 23), and LSA was 67 (SD 28); median IADL was 13 (interquartile range [IQR] 10–14). At two months after treatment initiation, 70% of patients experienced functional decline on at least one measure, with only 13% of these patients recovering at six months. At two and six months, decline in LSA was the most common (48% and 35%, respectively). Joint displays revealed heterogeneity in how well each quantitative measure of physical function captured the qualitative patient experience.

      Discussion

      Functional decline during NSCLC treatment is common among older adults. LSA is a useful measure to detect subtle functional decline that may be missed by other measures. Given heterogeneity in how well each quantitative measure captures changes in physical function, there is value to including more than one functional measure in geriatric oncology research studies.

      Keywords

      1. Background

      Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death in the US with 68% of cases diagnosed in adults age ≥ 65 [
      • Dela Cruz C.S.
      • Tanoue L.T.
      • Matthay R.A.
      Lung cancer: epidemiology, etiology, and prevention.
      ]. Older adults who receive systemic therapy are at risk for impaired physical function from both the cancer and the treatment [
      • Kenis C.
      • Decoster L.
      • Bastin J.
      • et al.
      Functional decline in older patients with cancer receiving chemotherapy: a multicenter prospective study.
      ,
      • Wong M.L.
      • Paul S.M.
      • Mastick J.
      • et al.
      Characteristics associated with physical function trajectories in older adults with Cancer during chemotherapy.
      ,
      • Muhandiramge J.
      • Orchard S.G.
      • Warner E.T.
      • van Londen G.J.
      • Zalcberg J.R.
      Functional decline in the Cancer patient: a review.
      ,
      • Decoster L.
      • Kenis C.
      • Schallier D.
      • et al.
      Geriatric assessment and functional decline in older patients with lung cancer.
      ,
      • Granger C.L.
      • McDonald C.F.
      • Irving L.
      • et al.
      Low physical activity levels and functional decline in individuals with lung cancer.
      ,
      • Presley C.J.
      • Han L.
      • Leo-Summers L.
      • et al.
      Functional trajectories before and after a new cancer diagnosis among community-dwelling older adults.
      ], and functional decline is associated with worse quality of life and survival [
      • Kenis C.
      • Decoster L.
      • Bastin J.
      • et al.
      Functional decline in older patients with cancer receiving chemotherapy: a multicenter prospective study.
      ,
      • Maione P.
      • Perrone F.
      • Gallo C.
      • et al.
      Pretreatment quality of life and functional status assessment significantly predict survival of elderly patients with advanced non-small-cell lung cancer receiving chemotherapy: a prognostic analysis of the multicenter Italian lung cancer in the elderly s.
      ,
      • Wedding U.
      • Röhrig B.
      • Klippstein A.
      • Brix C.
      • Pientka L.
      • Höffken K.
      Co-morbidity and functional deficits independently contribute to quality of life before chemotherapy in elderly cancer patients.
      ]. In a study of older adults, >70% of those with cancer reported that they would not select a treatment that caused severe functional impairment, even if it improved survival [
      • Fried T.R.
      • Bradley E.H.
      • Towle V.R.
      • Allore H.
      Understanding the treatment preferences of seriously ill patients.
      ]. Despite the importance of function to older adults with cancer, data on functional outcomes during NSCLC treatment remain limited [
      • Wong M.L.
      • Shi Y.
      • Smith A.K.
      • et al.
      Changes in older adults’ life space during lung cancer treatment: a mixed methods cohort study.
      ,
      • Presley C.J.
      • Arrato N.A.
      • Shields P.G.
      • et al.
      Functional trajectories & resilience among adults with advanced lung cancer.
      ].
      The American Society of Clinical Oncology and International Society of Geriatric Oncology recognize functional status as a core geriatric assessment domain and recommend its use to guide management of older adults receiving systemic therapy [
      • 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.
      ,
      • Wildiers H.
      • Heeren P.
      • Puts M.
      • et al.
      International Society of Geriatric Oncology consensus on geriatric assessment in older patients with cancer.
      ]. Oncologists traditionally rely on performance status (e.g., Karnofsky Performance Status [KPS]), which evaluates ability to perform normal work and activity [
      • Yates J.W.
      • Chalmer B.
      • McKegney F.P.
      Evaluation of patients with advanced cancer using the Karnofsky performance status.
      ,
      • Crooks V.
      • Waller S.
      • Smith T.
      • Hahn T.J.
      The use of the Karnofsky performance scale in determining outcomes and risk in geriatric outpatients.
      ]. However, KPS is not sensitive to impairments among older adults with cancer. For example, 69% of older adults with a normal KPS have ≥1 impairment identified when a geriatric assessment is conducted [
      • Jolly T.A.
      • Deal A.M.
      • Nyrop K.A.
      • et al.
      Geriatric assessment-identified deficits in older cancer patients with normal performance status.
      ].
      To improve upon the limitations of the KPS, studies of function in older adults with cancer often evaluate activities of daily living (ADL) and instrumental activities of daily living (IADL), which measure difficulty and/or dependence with activities required for self-care and to live independently, respectively [
      • Kenis C.
      • Decoster L.
      • Bastin J.
      • et al.
      Functional decline in older patients with cancer receiving chemotherapy: a multicenter prospective study.
      ,
      • Hoppe S.
      • Rainfray M.
      • Fonck M.
      • et al.
      Functional decline in older patients with cancer receiving first-line chemotherapy.
      ]. Among non-older adult-specific studies of function in oncology, the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) [
      • Aaronson N.K.
      • 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.
      ] is commonly used to assess quality of life and includes a physical function (PF) subscale [
      • 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.
      ]. The EORTC QLQ-C30 PF, which is complementary to a traditional geriatric assessment, assesses the degree of difficulty or assistance patients need to perform various physical activities.
      In addition, life-space mobility [
      • Peel C.
      • Sawyer Baker P.
      • Roth D.L.
      • Brown C.J.
      • Brodner E.
      • Allman R.M.
      Assessing mobility in older adults: the UAB study of aging life-space assessment.
      ,
      • Johnson J.
      • Rodriguez M.A.
      • Al Snih S.
      Life-space mobility in the elderly: current perspectives.
      ] is a widely used measure in the general aging literature that has recently started gaining traction in oncology [
      • Stewart C.M.L.
      • Wheeler T.L.
      • Markland A.D.
      • Straughn J.M.
      • Richter H.E.
      Life-space assessment in urogynecology and gynecological oncology surgery patients: a measure of perioperative mobility and function.
      ,
      • Yee J.
      • Davis G.M.
      • Beith J.M.
      • et al.
      Physical activity and fitness in women with metastatic breast cancer.
      ] and geriatric oncology [
      • Wong M.L.
      • Shi Y.
      • Smith A.K.
      • et al.
      Changes in older adults’ life space during lung cancer treatment: a mixed methods cohort study.
      ,
      • Gattás-Vernaglia I.F.
      • Ramos P.T.
      • Perini M.L.L.
      • et al.
      Impact of the COVID-19 pandemic on the life-space mobility of older adults with cancer.
      ]. Life-space mobility, which can be measured using the patient-reported Life-Space Assessment (LSA) [
      • Peel C.
      • Sawyer Baker P.
      • Roth D.L.
      • Brown C.J.
      • Brodner E.
      • Allman R.M.
      Assessing mobility in older adults: the UAB study of aging life-space assessment.
      ], describes an individual's ability to move within their environment from within their home to outside of town. Among older adults without cancer, LSA predicts quality of life [
      • Iyer A.S.
      • Wells J.M.
      • Bhatt S.P.
      • et al.
      Life-space mobility and clinical outcomes in COPD.
      ], healthcare utilization [
      • Kennedy R.E.
      • Williams C.P.
      • Sawyer P.
      • et al.
      Life-space predicts health care utilization in community-dwelling older adults.
      ], and mortality [
      • Mackey D.C.
      • Lui L.Y.
      • Cawthon P.M.
      • Ensrud K.
      • Yaffe K.
      • Cummings S.R.
      Life-space mobility and mortality in older women: prospective results from the study of osteoporotic fractures.
      ]. Because life-space mobility incorporates physical, social, and cognitive functioning, it represents a broader assessment of function than measures that evaluate performance of individual activities [
      • Wong M.L.
      • Shi Y.
      • Smith A.K.
      • et al.
      Changes in older adults’ life space during lung cancer treatment: a mixed methods cohort study.
      ].
      Given the multiple measures available to assess physical function, each of which captures a different aspect of this domain, we performed a mixed methods cohort study to characterize and compare changes in physical function during systemic NSCLC treatment among older adults using four measures: KPS, IADL, EORTC QLQ-C30 PF, and LSA. To integrate the patient perspective with the quantitative measures, we interviewed a subset of older adults with NSCLC to explore how functional changes impacted their daily lives.

      2. Methods

      2.1 Study Design and Participants

      Details of our “Lung cancer in older adults: Treatment toxicity through the patient's lens” study (Lens Study) have been previously published [
      • Wong M.L.
      • Shi Y.
      • Smith A.K.
      • et al.
      Changes in older adults’ life space during lung cancer treatment: a mixed methods cohort study.
      ]. Briefly, this is an observational cohort study that recruited older adults with advanced NSCLC from three sites within one Comprehensive Cancer Center (academic, Veterans Affairs, and safety-net oncology clinics). Patients were age ≥ 65, diagnosed with stage III-IV or recurrent NSCLC, starting a new systemic treatment (i.e., chemotherapy, immunotherapy, and/or targeted therapy) with non-curative intent, spoke English and/or a Chinese dialect, and able to provide informed consent. Patients undergoing surgery and/or thoracic radiation were excluded. Functional status was assessed pretreatment and at one, two, four, and six months or until treatment discontinuation, whichever occurred earlier. For this analysis, we excluded patients who did not have any follow-up function data and patients who enrolled after February 29, 2020 due to the impact of the COVID-19 pandemic on their life-space mobility. This study was approved by the University of California, San Francisco Institutional Review Board and the San Francisco Veterans Affairs.
      For the qualitative substudy, we conducted semi-structured interviews with 20 English-speaking patients to understand the patient experience of functional change during NSCLC treatment [
      • Wong M.L.
      • Shi Y.
      • Smith A.K.
      • et al.
      Changes in older adults’ life space during lung cancer treatment: a mixed methods cohort study.
      ]. To represent a diverse range of pretreatment function, relatively fit and more frail patients were purposively sampled based on the treating oncologists' clinical impressions of their pretreatment function. Participants were interviewed prior to treatment initiation and at two and six months. Interviews were audio recorded and professionally transcribed. Additional details of our qualitative substudy, including the interview guide, were previously published [
      • Wong M.L.
      • Shi Y.
      • Smith A.K.
      • et al.
      Changes in older adults’ life space during lung cancer treatment: a mixed methods cohort study.
      ].

      2.2 Measurements

      Patients completed a demographic survey and we abstracted clinical characteristics from the medical record. Patients completed a geriatric assessment [
      • Hurria A.
      • Gupta S.
      • Zauderer M.
      • et al.
      Developing a cancer-specific geriatric assessment: a feasibility study.
      ] prior to treatment initiation to assess function (Katz ADL [
      • Katz S.
      • Ford A.B.
      • Moskowitz R.W.
      • Jackson B.A.
      • Jaffe M.W.
      Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function.
      ], Older Americans Resources and Services [OARS] IADL [
      • Fillenbaum G.G.
      • Smyer M.A.
      The development, validity, and reliability of the OARS multidimensional functional assessment questionnaire.
      ], Timed Up and Go [
      • Podsiadlo D.
      • Richardson S.
      The timed “up & go”: a test of basic functional mobility for frail elderly persons.
      ], Short Physical Performance Battery [
      • Guralnik J.M.
      • Simonsick E.M.
      • Ferrucci L.
      • et al.
      A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission.
      ], falls in the last six months [
      • Hurria A.
      • Cirrincione C.T.
      • Muss H.B.
      • et al.
      Implementing a geriatric assessment in cooperative group clinical cancer trials: CALGB 360401.
      ]), comorbidity (OARS Physical Health Subscale [
      • Fillenbaum G.G.
      • Smyer M.A.
      The development, validity, and reliability of the OARS multidimensional functional assessment questionnaire.
      ]), nutrition (body mass index [
      • Hurria A.
      • Cirrincione C.T.
      • Muss H.B.
      • et al.
      Implementing a geriatric assessment in cooperative group clinical cancer trials: CALGB 360401.
      ], involuntary weight loss [
      • Mohile S.G.
      • Epstein R.M.
      • Hurria A.
      • et al.
      Communication with older patients with Cancer using geriatric assessment: a cluster-randomized clinical trial from the National Cancer Institute Community oncology research program.
      ]), cognition (Montreal Cognitive Assessment [
      • Nasreddine Z.S.
      • Phillips N.A.
      • Bédirian V.
      • et al.
      The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment.
      ]), mood (Mental Health Inventory-13 [
      • Pergolotti M.
      • Langer M.M.
      • Deal A.M.
      • Muss H.B.
      • Nyrop K.
      • Williams G.
      Mental status evaluation in older adults with cancer: development of the mental health Index-13.
      ]), and social support (Medical Outcomes Study Social Support Survey [
      • Sherbourne C.D.
      • Stewart A.L.
      The MOS social support survey.
      ]). Symptoms were assessed using the EORTC QLQ-C30 [
      • Aaronson N.K.
      • 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.
      ] and Lee Fatigue Scale [
      • Bischel L.E.
      • Ritchie C.
      • Kober K.M.
      • et al.
      Age differences in fatigue, decrements in energy, and sleep disturbance in oncology patients receiving chemotherapy.
      ,
      • Lee K.A.
      • Hicks G.
      • Nino-Murcia G.
      Validity and reliability of a scale to assess fatigue.
      ].

      2.3 Quantitative Outcome Measures of Function

      Function was quantitatively evaluated prior to treatment initiation and at one, two, four, and six months using four measures: clinician-rated KPS [
      • Yates J.W.
      • Chalmer B.
      • McKegney F.P.
      Evaluation of patients with advanced cancer using the Karnofsky performance status.
      ,
      • Crooks V.
      • Waller S.
      • Smith T.
      • Hahn T.J.
      The use of the Karnofsky performance scale in determining outcomes and risk in geriatric outpatients.
      ], OARS IADL [
      • Fillenbaum G.G.
      • Smyer M.A.
      The development, validity, and reliability of the OARS multidimensional functional assessment questionnaire.
      ], EORTC QLQ-C30 PF subscale [
      • Aaronson N.K.
      • 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.
      ], and LSA [
      • Peel C.
      • Sawyer Baker P.
      • Roth D.L.
      • Brown C.J.
      • Brodner E.
      • Allman R.M.
      Assessing mobility in older adults: the UAB study of aging life-space assessment.
      ]. Higher scores indicate better function for all four measures.
      Clinician-rated KPS classifies patients based on their ability to perform normal activities. KPS scores range from 0 to 100% and we defined functional decline as a decrease of ≥10 points, which is clinically meaningful [
      • Sagberg L.M.
      • Jakola A.S.
      • Solheim O.
      Quality of life assessed with EQ-5D in patients undergoing glioma surgery: what is the responsiveness and minimal clinically important difference?.
      ,
      • Zeng L.
      • Chow E.
      • Zhang L.
      • et al.
      An international prospective study establishing minimal clinically important differences in the EORTC QLQ-BM22 and QLQ-C30 in cancer patients with bone metastases.
      ].
      The OARS IADL assesses dependence in using the telephone, shopping, navigating transportation, preparing meals, doing housework, and managing medicine and money. The OARS IADL scale is scored 0–14 and we defined functional decline as a decrease of ≥1 point, which is clinically meaningful [
      • Abdulaziz K.
      • Perry J.J.
      • Taljaard M.
      • et al.
      National Survey of geriatricians to define functional decline in elderly people with minor trauma.
      ].
      The EORTC QLQ-C30 PF subscale contains five items assessing ADL dependence, need to stay in a bed/chair, and tolerance for different activities. Responses are transformed to a 0–100 scale and we defined functional decline as a decrease of ≥10 points, which is clinically meaningful [
      • Hurria A.
      • Soto-Perez-de-Celis E.
      • Allred J.B.
      • et al.
      Functional decline and resilience in older women receiving adjuvant chemotherapy for breast Cancer.
      ].
      The LSA assesses how often patients move through five life-space levels in their environment (within the home to outside of town) and whether they required assistance. In the general older adult population, decline in LSA score is associated with increased healthcare utilization and mortality [
      • Kennedy R.E.
      • Williams C.P.
      • Sawyer P.
      • et al.
      Life-space predicts health care utilization in community-dwelling older adults.
      ,
      • Kennedy R.E.
      • Sawyer P.
      • Williams C.P.
      • et al.
      Life-space mobility change predicts 6-month mortality.
      ]. Scores range from 0 to 120 and we defined functional decline as a decrease of ≥10 points, which is clinically meaningful [
      • Kennedy R.E.
      • Sawyer P.
      • Williams C.P.
      • et al.
      Life-space mobility change predicts 6-month mortality.
      ,
      • Kennedy R.E.
      • Almutairi M.
      • Williams C.P.
      • Sawyer P.
      • Allman R.M.
      • Brown C.J.
      Determination of the minimal important change in the life-space assessment.
      ].

      2.4 Quantitative Analysis

      All statistical analyses were performed using Stata/SE 17 [

      StataCorp. Published online 2021.

      ]. We summarized pretreatment patient characteristics using descriptive statistics.
      To evaluate changes in functional status during NSCLC treatment, we first evaluated each quantitative measure individually. Mean scores and standard deviations (SD) were calculated for each measure at each time point. Using the definitions of functional decline described above, we categorized each patient's trajectory for each measure as stable/improved or functional decline from (a) prior to treatment initiation to two months and (b) two to six months. We focused on these three time points because they corresponded with the qualitative interviews. Patients who died during follow up were categorized as experiencing functional decline with a KPS, IADL, EORTC QLQ-C30 PF, and LSA score of zero at the next assessment. For cases where one-month quantitative function data were available but two-month data were missing due to patient symptoms, treatment discontinuation, withdrawal of consent, or censoring due to the COVID-19 pandemic, one-month results were carried forward to two months. Similarly, for cases where four-month quantitative function data were available but six-month data were missing, four-month results were carried forward to six months. For LSA scores only, we carried the last assessment obtained on or before February 29, 2020 forward to subsequent assessments because the COVID-19 pandemic shelter-in-place orders likely decreased participant's life space unrelated to their underlying mobility.
      To summarize change in physical function across all four quantitative measures, we evaluated functional decline in any of the quantitative measures (a) prior to treatment initiation to two months and (b) from two to six months. At two months, patients who experienced a decline in any of the four measures were categorized as “decline.” All others were categorized as “stable” at two months. Among patients who had stable function at two months, patients were categorized as (a) still “stable” or (b) “decline” at six months if they experienced a decline in any of the four measures. Among patients who had functional decline at two months, patients were categorized at six months as (a) “recovery” if they demonstrated recovery in all measures that they previously declined in (e.g., KPS returned to within 10 points of the pretreatment score), (b) “no recovery” if they remained stable without recovery or further decline, or (c) “additional decline” if they experienced a decline in any of the four measures between two and six months (e.g., further decline of ≥10 points in KPS).
      To evaluate associations among the four quantitative measures of function at each time point, we calculated Pearson's correlation coefficients between each pair of scores prior to treatment initiation and at two and six months. Patients who died were excluded from the correlation as their functional outcomes were set to zero. To visualize differences in quantitative measures of function at the two-month assessment, we grouped patients who experienced functional decline on any measure in a four-circle Venn diagram with each circle representing the measure(s) that detected the decline.

      2.5 Mixed Methods Analysis

      Interview transcripts were independently reviewed by at least two investigators (SS, SZ, MLW) using thematic analysis [
      • Vaismoradi M.
      • Turunen H.
      • Bondas T.
      Content analysis and thematic analysis: implications for conducting a qualitative descriptive study.
      ] to identify descriptions of functional changes and how these changes impacted patients' daily lives. Functional decline was defined as decline in ability to perform ADLs, IADLs, or other previous activities. Patients who described new symptoms that did not limit their function were coded as having stable function. Disagreements were resolved through consensus (SS, SZ, MLW). Using a convergent mixed methods design, joint displays were created for each patient with complete quantitative and qualitative data. The joint displays integrated the four quantitative measures of function over time with illustrative quotations of the patient experience. We selected exemplar joint displays to represent a range of comparisons between the quantitative and qualitative data.

      3. Results

      3.1 Demographics and Clinical Characteristics

      From August 2017 through February 2020, 87 patients met the inclusion criteria and were included in our two-month analysis (Supplemental Figure). At six months, nineteen patients were off study due to treatment discontinuation (22%), four died prior to the two-month assessment (5%), and two withdrew consent (2%), resulting in 62 patients (71%) for our six-month analysis.
      Pretreatment characteristics are shown in Table 1. Median age was 73 years (interquartile range [IQR] 68–80, range 65–96). Patients were predominantly English-speaking (84%) and received prior lung cancer treatment (72%). During the study, 34% of patients received immunotherapy, 33% targeted therapy, 22% chemoimmunotherapy, and 10% chemotherapy alone.
      Table 1Patient characteristics (N = 87).
      Demographic and clinical characteristicsn (%)
      Age, years
       65–6926 (30)
       70–7425 (29)
       75–7914 (16)
       80+22 (25)
      Female50 (57)
      Race
       Asian26 (30)
       Black4 (5)
       White55 (63)
       More than one race2 (2)
      Primary language
       English73 (84)
       Chinese dialect14 (16)
      Education
       High school or less19 (24)
       College37 (46)
       Graduate level24 (30)
      Partnered50 (60)
      Lives alone18 (21)
      Smoking status
       No history of tobacco use29 (33)
       History of tobacco use54 (62)
       Active tobacco use4 (5)
      Histology
       Adenocarcinoma72 (83)
       Squamous cell11 (13)
       Other4 (5)
      Stage
       IIIA-C6 (7)
       IVA33 (38)
       IVB48 (55)
      Brain metastasis23 (26)
      Any prior lung cancer treatment63 (72)
      Prior lung cancer treatments
       Prior radiation38 (29)
       Prior chemotherapy34 (26)
       Prior targeted therapy26 (20)
       Prior immunotherapy17 (13)
       Prior surgery15 (12)
      Current treatment
       Immunotherapy30 (34)
       Targeted therapy29 (33)
       Chemotherapy and immunotherapy19 (22)
       Chemotherapy9 (10)
      Pretreatment geriatric assessment and symptom characteristicsn (%)
      Dependent in ≥1 ADL16 (18)
      Dependent in ≥1 IADL55 (68)
      Timed Up and Go ≥13.5 s28 (34)
      Short Physical Performance Battery score ≤ 939 (45)
      Fall(s) in last 6 months12 (15)
      ≥3 comorbidities32 (37)
      Low hemoglobin (<10 g/dl for women, <11 g/dl for men)11 (13)
      Creatinine clearance <60 ml/min31 (37)
      Montreal Cognitive Assessment score < 2657 (66)
      Involuntary weight loss in last 6 months47 (59)
      BMI <21 kg/m220 (23)
      MHI-13 depression score ≥ 1229 (40)
      MHI-13 anxiety score ≥ 653 (74)
      Poor tangible social support32 (42)
      High morning fatigue30 (39)
      High evening fatigue23 (30)
      Low morning energy61 (79)
      Low evening energy35 (46)
      Pain (quite a bit or very much)20 (27)
      Shortness of breath (quite a bit or very much)19 (25)
      Abbreviations: ADL, activities of daily living; BMI, body mass index; IADL, instrumental activities of daily living; MHI, Mental Health Inventory.
      Missing data: education n = 7, partnered n = 3, IADL n = 5, timed up and go n = 4, fall(s) n = 7, hemoglobin n = 1, creatinine clearance n = 2, weight loss n = 7, depression n = 14, anxiety n = 14, social support n = 9, morning fatigue/energy n = 9, evening fatigue/energy n = 10, pain n = 12, shortness of breath n = 11.

      3.2 Pretreatment Geriatric Assessment and Symptom Characteristics

      Most patients (68%) were dependent in ≥1 IADL prior to treatment initiation, but only 18% were dependent in ≥1 ADL (Table 1). The mean pretreatment KPS score was 79% (SD 13), EORTC QLQ-C30 PF was 69 (SD 23), and LSA was 67 (SD 28; Table 2). Median IADL was 13 (IQR 10–14).
      Table 2Functional decline by individual quantitative measures.
      Pretreatment2 Months6 Months
      Quantitative MeasurenMean (SD)nMean (SD)% of patients with declinenMean (SD)% of patients with decline
      Karnofsky Performance Status (scale 0–100)8779 (13)8771 (22)41%6177 (20)23%
      IADL (scale 0–14) (median, IQR)8313 (10–14)8313 (10–14)24%5813 (10–14)26%
      EORTC QLQ-C30 PF (scale 0–100)7769 (23)7866 (26)29%5870 (25)22%
      Life-Space Assessment (scale 0–120)8767 (28)8757 (32)48%6062 (31)35%
      Functional decline was defined as clinically meaningful decline in KPS (≥10-point decrease), IADL (≥1-point decrease), EORTC QLQ-C30 Physical Function (≥10-point decrease), or Life-Space Assessment (≥10-point decrease).
      Abbreviations: EORTC QLQ-C30 PF, European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Physical Function; IADL, instrumental activities of daily living; IQR, interquartile range; SD, standard deviation.

      3.3 Change in Physical Function

      Changes in individual measures of function are shown in Table 2. At two months, functional decline ranged from 24% of patients declining in IADL to 48% declining in LSA. From two to six months, 22% of patients declined in EORTC QLQ-C30 PF while 35% declined in LSA. At both time points, decline in LSA was the most common.
      When evaluating functional decline in any of the four quantitative measures, functional decline was common with 70% (61 patients) experiencing decline at two months (Fig. 1). Among these patients, 59% (23 out of 39 patients who declined at two months and had data at six months) experienced additional decline at six months, while 13% (5 out of 39) experienced functional recovery. Among the 30% (26 patients) with stable function at two months, 26% (6 out of 23 who were stable at two months and had data at six months) remained stable at six months while 74% (17 out of 23) developed functional decline. At six months, a total of 82% had declined from their pretreatment baseline function.
      Fig. 1
      Fig. 1Changes in function among older adults with NSCLC from (a) prior to treatment initiation to two months and (b) two to six months. Functional decline was defined as clinically meaningful decline in KPS (≥10-point decrease), IADL (≥1-point decrease), EORTC QLQ-C30 Physical Function (≥10-point decrease), or Life-Space Assessment (≥10-point decrease).
      Abbreviations: EORTC QLQ-C30, European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire; KPS, Karnofsky Performance Status; NSCLC, non-small cell lung cancer; OARS IADL, Older Americans Resources Instrumental Activities of Daily Living.
      a25 patients were not included in the six-month assessment: 19 off treatment, 4 died, and 2 withdrew consent between the two- and six-month assessments
      b61 patients includes 4 patients who died.
      c23 patients includes 2 patients who died.

      3.4 Correlations between Quantitative Measures of Physical Function

      At the pretreatment assessment, IADL and LSA scores were most strongly correlated (correlation coefficient r = 0.75; Table 3) while KPS and LSA were the least (r = 0.48). At two months, IADL and EORTC QLQ-C30 PF scores were most strongly correlated (r = 0.72) while KPS and LSA were the least (r = 0.42). At six months, IADL and EORTC QLQ-C30 PF scores were most strongly correlated (r = 0.80) while KPS and LSA were the least (r = 0.41).
      Table 3Correlations between quantitative measures of physical function decline.
      Pretreatment, n = 872 Months, n = 836 Months, n = 56
      KPSIADLEORTC QLQ-C30 PFKPSIADLEORTC QLQ-C30 PFKPSIADLEORTC QLQ-C30 PF
      IADL0.520.510.61
      EORTC QLQ-C30 PF0.590.690.520.720.620.80
      LSA0.480.750.700.420.710.540.410.700.60
      Pearson's correlation coefficient reported.
      Abbreviations: EORTC QLQ-C30 PF, European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Physical Function; IADL, instrumental activities of daily living; KPS, Karnofsky Performance Status; LSA, Life-Space Assessment.
      Of the 61 patients with functional decline on at least one measure at two months, 53 had complete data with two-month KPS, IADL, EORTC QLQ-C30 PF, and LSA scores. Fig. 2 depicts the number of patients who experienced functional decline at two months and by which quantitative measure. Twenty-five patients (47%) had functional decline in only one measure while four patients (8%) had decline in all four. LSA detected the most patients with decline in only one measure.
      Fig. 2
      Fig. 2Functional decline at two months by quantitative measure (n = 53). Excluded patients missing any quantitative measure at two months or died prior to two-month assessment.
      Abbreviations: EORTC PF, European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Physical Function; IADL, Instrumental Activities of Daily Living; KPS, Karnofsky Performance Status; LSA, Life-Space Assessment.

      3.5 Mixed Methods Results

      Twenty patients participated in the qualitative substudy. Two patients transitioned to hospice care prior to their two-month interview and were not included in this analysis because we lacked patient descriptions of their functional changes. Joint displays representing different patterns of functional change are shown in Fig. 3.
      Fig. 3
      Fig. 3Joint displays. Joint displays integrating quantitative plots of function with qualitative patient descriptions of functional changes. (A) 79-year-old woman receiving chemoimmunotherapy with qualitative and quantitative functional decline in all four measures at two months and recovery in IADL, EORTC PF, and LSA at six months. (B) 74-year-old woman receiving chemotherapy with qualitative and quantitative decline in LSA at two months and qualitative and quantitative decline in KPS, IADL, and EORTC PF from two to six months. (C) 77-year-old woman receiving chemoimmunotherapy with qualitative and quantitative decline in IADL at two and six months. (D) 86-year-old woman receiving immunotherapy with quantitative decline in EORTC PF and LSA at two months (with stable qualitative function) and subsequent qualitative and quantitative decline in IADL and LSA from two to six months.
      Abbreviations: EORTC PF, European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Physical Function; IADL, Older Americans Resources and Services Program Instrumental Activities of Daily Living; KPS, Medical Doctor Karnofsky Performance Status.
      Fig. 3
      Fig. 3Joint displays. Joint displays integrating quantitative plots of function with qualitative patient descriptions of functional changes. (A) 79-year-old woman receiving chemoimmunotherapy with qualitative and quantitative functional decline in all four measures at two months and recovery in IADL, EORTC PF, and LSA at six months. (B) 74-year-old woman receiving chemotherapy with qualitative and quantitative decline in LSA at two months and qualitative and quantitative decline in KPS, IADL, and EORTC PF from two to six months. (C) 77-year-old woman receiving chemoimmunotherapy with qualitative and quantitative decline in IADL at two and six months. (D) 86-year-old woman receiving immunotherapy with quantitative decline in EORTC PF and LSA at two months (with stable qualitative function) and subsequent qualitative and quantitative decline in IADL and LSA from two to six months.
      Abbreviations: EORTC PF, European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Physical Function; IADL, Older Americans Resources and Services Program Instrumental Activities of Daily Living; KPS, Medical Doctor Karnofsky Performance Status.
      Fig. 3A shows function over time for a 79-year-old woman receiving chemoimmunotherapy who experienced decline in all four quantitative measures at two months, which was consisted with her qualitative experience: “The worst is just the feeling like you could just stay in bed all day long because you are just wiped out.” She subsequently had functional recovery at six months as reflected in her IADL, EORTC QLQ-C30 PF, and LSA scores and her qualitative description: “I go to Safeway. I put the groceries in the cart. I unload them.”
      Fig. 3B shows function over time for a 74-year-old woman receiving chemotherapy who experienced functional decline at two months in LSA only, which was confirmed during her interview: “That first week I came home [from the hospital], I was out of it. I was just laying around, had no energy, zip.” She experienced further functional decline at six months with decreased KPS, IADL, and EORTC QLQ-C30 PF scores, which was reflected in her description: “Even just [to] get up and function for the day, it's a struggle.”
      Fig. 3C shows function over time for a 77-year-old woman receiving chemoimmunotherapy who experienced decline at two months in IADL only. Her qualitative description confirmed the quantitative IADL decline: “The tiresome and exhaustion are starting. So today, I was not feeling like eating food.” She experienced further functional decline in IADL at six months, which was also evident during her interview: “Housework also I can't do. Laundry, I can do my laundry.”
      Fig. 3D shows function over time for an 86-year-old woman receiving immunotherapy whose EORTC QLQ-C30 PF and LSA scores declined at two months. However, she described her functional status as stable: “I've been to a dinner several times. I've been to concerts also. It's not much worse than it was.” Her IADL and LSA scores declined at six months, which was consistent with her description: “[I'm doing] not very much I'm afraid. [I'm] at the hospital, and there's not much to do, and I've been a lot in bed.”

      4. Discussion

      In this mixed methods cohort study of older adults with advanced NSCLC receiving systemic treatment, functional decline was.
      common, with 70% of patients experiencing decline in at least one quantitative measure at two months and 82% by six months. Among the patients who experienced functional decline at two months, only 13% recovered by six months. To the best of our knowledge, our study is the first to characterize functional changes among older adults with advanced NSCLC using multiple quantitative measures and the first to integrate qualitative patient descriptions with quantitative trajectories.
      Among the measures we used to quantify function, LSA detected functional decline during NSCLC treatment most frequently, which was sometimes not detected by other measures. For example, the 74-year-old woman receiving chemoimmunotherapy in Fig. 3B experienced decline in only LSA at two months—which was consistent with her qualitative description—while the other measures were stable to improved. In studies of older adults living in the community, lower LSA scores are associated with subsequent development of ADL difficulty/dependence [
      • Portegijs E.
      • Rantakokko M.
      • Viljanen A.
      • Sipilä S.
      • Rantanen T.
      Identification of older people at risk of ADL disability using the life-space assessment: a longitudinal cohort study.
      ,
      • Al Snih S.
      • Peek K.M.
      • Sawyer P.
      • Markides K.S.
      • Allman R.M.
      • Ottenbacher K.J.
      Life-space mobility in Mexican Americans aged 75 and older.
      ]. Compared to more traditional measures of function such as ADL, LSA is a more holistic measure as it evaluates function in the context of a person's actual environment beyond the home, and therefore reflects physical, cognitive, social, and environmental factors [
      • Taylor J.K.
      • Buchan I.E.
      • van der Veer S.N.
      Assessing life-space mobility for a more holistic view on wellbeing in geriatric research and clinical practice.
      ]. Our results suggest that LSA may be able to detect more subtle, early functional changes before the development of decline in other measures such as KPS or IADL. Decline in life-space mobility before decline in other measures of function that focus more on daily activities within the home is consistent with Webber et al.'s hierarchical framework for mobility in older adults [
      • Webber S.C.
      • Porter M.M.
      • Menec V.H.
      Mobility in older adults: a comprehensive framework.
      ].
      In addition to demonstrating that the LSA captured unique aspects of functional decline, we found that the LSA was the least correlated with KPS. KPS is widely used by oncologists to assess performance status but misses impairments identified on more thorough geriatric assessments [
      • Jolly T.A.
      • Deal A.M.
      • Nyrop K.A.
      • et al.
      Geriatric assessment-identified deficits in older cancer patients with normal performance status.
      ,
      • Nightingale G.
      • Battisti N.M.L.
      • Loh K.P.
      • et al.
      Perspectives on functional status in older adults with cancer: an interprofessional report from the International Society of Geriatric Oncology (SIOG) nursing and allied health interest group and young SIOG.
      ,
      • Hamaker M.
      • Lund C.
      • te Molder M.
      • et al.
      Geriatric assessment in the management of older patients with cancer - a systematic review (update).
      ]. In a study of adults age ≥ 18, a minority of whom had cancer, there was a similarly weak correlation between LSA and the Australia-modified KPS [
      • Phillips J.L.
      • Lam L.
      • Luckett T.
      • Agar M.
      • Currow D.
      Is the life space assessment applicable to a palliative care population? Its relationship to measures of performance and quality of life.
      ]. Therefore, we recommend that KPS alone should not be used to evaluate for functional decline during NSCLC treatment in older adults. Furthermore, our findings in combination with the literature suggest that routine assessment of life-space mobility in oncology may help detect functional changes that may otherwise be missed. Clinicians can efficiently assess this by asking patients how far they have gone outside of the room where they sleep (for frail patients) or outside their home (for more fit patients) [
      • Peel C.
      • Sawyer Baker P.
      • Roth D.L.
      • Brown C.J.
      • Brodner E.
      • Allman R.M.
      Assessing mobility in older adults: the UAB study of aging life-space assessment.
      ].
      Through our longitudinal mixed methods design, our joint displays provided a unique lens into how patients experience functional changes during NSCLC treatment and how that compares to quantitative measures. A prior qualitative study that explored how older adults in a primary care setting defined functional decline found that patients described distinct components including loss of strength, mobility, and memory [
      • Viret O.
      • Schwarz J.
      • Senn N.
      • Mueller Y.
      Discussing age-related functional decline in family medicine: a qualitative study that explores both patient and physician perceptions.
      ]. When available, qualitative patient descriptions of functional changes can provide the rich context of their lives and enhance quantitative findings. Our team previously used joint displays to compare life-space mobility with the older patient experience of NSCLC treatment [
      • Wong M.L.
      • Shi Y.
      • Smith A.K.
      • et al.
      Changes in older adults’ life space during lung cancer treatment: a mixed methods cohort study.
      ]. In the present study, we take these joint displays one step further by adding longitudinal data for three additional quantitative measures, which revealed heterogeneity in how well each measure captures the patient perspective. Of note, we did not evaluate patient descriptions of functional decline as the gold standard in our analysis due to the interview substudy's small sample size. Future research asking patients who develop functional decline if treatment harms were “worth it” compared to benefits [
      • Brehaut J.C.
      • O’Connor A.M.
      • Wood T.J.
      • et al.
      Validation of a decision regret scale.
      ,
      • Thanarajasingam G.
      • Basch E.
      • Mead-Harvey C.
      • et al.
      An exploratory analysis of the “was it worth it?” questionnaire as a novel metric to capture patient perceptions of Cancer treatment.
      ] would be valuable in further understanding treatment preferences among older adults.
      Given our findings of wide variation in the prevalence of functional decline based on which quantitative measure is used, we recommend leveraging at least two measures when evaluating functional changes among older adults with cancer in research because no single measure fully captures the patient experience. Selection of the optimal measures to assess functional decline is dependent on the specific patient population and treatment(s) of interest. For example, among a more fit population of older adults with cancer, the LSA may be needed to detect more subtle functional changes. In contrast, IADL may be sufficient to characterize functional changes in a frailer population of older adults with cancer. Understanding if the sensitivity of different functional measures differs based on patient characteristics is an important area for further research.
      This study has several limitations. Our study included a modest sample size and was conducted at three sites within a single institution with a primarily English-speaking population, which may limit the generalizability of our findings. However, 16% spoke a Chinese dialect, which is often excluded in most geriatric oncology studies. While our study did include performance-based measures of function (e.g., Short Physical Performance Battery), ceiling effects limited its ability to detect change over time in this population. Therefore, we did not include performance-based measures in our analysis. Lastly, we did not evaluate pretreatment factors associated with functional decline, which will be the basis for future work as we continue this ongoing cohort study.
      In conclusion, functional decline is common among older adults with advanced NSCLC receiving systemic treatment with only a minority of patients recovering to their pretreatment baseline. When possible in research, function should be assessed with more than one measure to better capture the treatment experience through the patient's lens. Of the quantitative measures we assessed, LSA is a useful measure to detect more subtle, early functional changes, which may facilitate implementation of early interventions to mitigate the risk of further decline and allow for improved shared decision making regarding dose modifications or early treatment discontinuation.

      Funding

      This work was supported by the National Institutes of Health ( P30AG044281 to LCW and MLW, K24AG068312 to AKS, R00CA237744 to KPL, P30AG028716 to HJC, R03AG064374 to CJP, P30CA016058 to CJP, K08CA234225 to GRW, K76AG064394 to AM, K24AG056589 to SGM, R33AG059206 to SGM, R03AG056439 to MLW, KL2TR001870 to MLW, K76AG064431 to MLW); the Wilmot Research Fellowship Award to KPL, the Conquer Cancer American Society of Clinical Oncology Walther Cancer Foundation Career Development Award to KPL, and the University of California, San Francisco Helen Diller Family Comprehensive Cancer Center to MLW. Content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

      Prior Presentation

      This work was presented as an oral presentation at the October 2019 Supportive Care in Oncology Symposium in San Francisco, California.

      Author Contributions

      Conception and Design: Singhal, Walter, Smith, Loh, Cohen, Wong.
      Data Collection: Walter, Smith, Wong.
      Analysis and Interpretation of Data: All authors.
      Manuscript Writing: Singhal, Wong.
      Approval of Final Article: All authors

      Declaration of Competing Interest

      KPL and MLW reported conflicts of interest outside of the submitted work: KPL has served as a consultant for Pfizer and Seattle Genetics and has received speaker fees from Pfizer. MLW reported that an immediate family member is an employee of Genentech with stock ownership. MLW receives royalties from UpToDate. The remaining authors have no conflicts to report.

      Appendix A. Supplementary data

      References

        • Dela Cruz C.S.
        • Tanoue L.T.
        • Matthay R.A.
        Lung cancer: epidemiology, etiology, and prevention.
        Clin Chest Med. 2011; 32: 605-644https://doi.org/10.1016/j.ccm.2011.09.001
        • Kenis C.
        • Decoster L.
        • Bastin J.
        • et al.
        Functional decline in older patients with cancer receiving chemotherapy: a multicenter prospective study.
        J Ger Oncol. 2017; 8: 196-205https://doi.org/10.1016/j.jgo.2017.02.010
        • Wong M.L.
        • Paul S.M.
        • Mastick J.
        • et al.
        Characteristics associated with physical function trajectories in older adults with Cancer during chemotherapy.
        J Pain Symptom Manag. 2018; 56: 678-688.e1https://doi.org/10.1016/j.jpainsymman.2018.08.006
        • Muhandiramge J.
        • Orchard S.G.
        • Warner E.T.
        • van Londen G.J.
        • Zalcberg J.R.
        Functional decline in the Cancer patient: a review.
        Cancers (Basel). 2022; 14https://doi.org/10.3390/cancers14061368
        • Decoster L.
        • Kenis C.
        • Schallier D.
        • et al.
        Geriatric assessment and functional decline in older patients with lung cancer.
        Lung. 2017; 195: 619-626https://doi.org/10.1007/s00408-017-0025-2
        • Granger C.L.
        • McDonald C.F.
        • Irving L.
        • et al.
        Low physical activity levels and functional decline in individuals with lung cancer.
        Lung Cancer. 2014; 83: 292-299https://doi.org/10.1016/j.lungcan.2013.11.014
        • Presley C.J.
        • Han L.
        • Leo-Summers L.
        • et al.
        Functional trajectories before and after a new cancer diagnosis among community-dwelling older adults.
        J Geriatr Oncol. 2019; 10: 60-67https://doi.org/10.1016/j.jgo.2018.05.017
        • Maione P.
        • Perrone F.
        • Gallo C.
        • et al.
        Pretreatment quality of life and functional status assessment significantly predict survival of elderly patients with advanced non-small-cell lung cancer receiving chemotherapy: a prognostic analysis of the multicenter Italian lung cancer in the elderly s.
        J Clin Oncol. 2005; 23: 6865-6872https://doi.org/10.1200/JCO.2005.02.527
        • Wedding U.
        • Röhrig B.
        • Klippstein A.
        • Brix C.
        • Pientka L.
        • Höffken K.
        Co-morbidity and functional deficits independently contribute to quality of life before chemotherapy in elderly cancer patients.
        Support Care Cancer. 2007; 15: 1097-1104https://doi.org/10.1007/s00520-007-0228-9
        • Fried T.R.
        • Bradley E.H.
        • Towle V.R.
        • Allore H.
        Understanding the treatment preferences of seriously ill patients.
        N Engl J Med. 2002; 346: 1061-1066https://doi.org/10.1056/NEJMsa012528
        • Wong M.L.
        • Shi Y.
        • Smith A.K.
        • et al.
        Changes in older adults’ life space during lung cancer treatment: a mixed methods cohort study.
        J Am Geriatr Soc. 2021; : 1-14https://doi.org/10.1111/jgs.17474
        • Presley C.J.
        • Arrato N.A.
        • Shields P.G.
        • et al.
        Functional trajectories & resilience among adults with advanced lung cancer.
        JTO Clin Res Rep. 2022; 3100334https://doi.org/10.1016/J.JTOCRR.2022.100334/ATTACHMENT/5D429E7F-99DC-45BB-82D6-93A993175116/MMC1.DOCX
        • 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.
        J Clin Oncol. 2018; 36: 2326-2347https://doi.org/10.1200/JCO.2018.78.8687
        • 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: 2595-2603https://doi.org/10.1200/JCO.2013.54.8347
        • Yates J.W.
        • Chalmer B.
        • McKegney F.P.
        Evaluation of patients with advanced cancer using the Karnofsky performance status.
        Cancer. 1980; 45: 2220-2224https://doi.org/10.1002/1097-0142(19800415)45:8<2220::aid-cncr2820450835>3.0.co;2-q
        • Crooks V.
        • Waller S.
        • Smith T.
        • Hahn T.J.
        The use of the Karnofsky performance scale in determining outcomes and risk in geriatric outpatients.
        J Gerontol. 1991; 46: M139-M144https://doi.org/10.1093/geronj/46.4.m139
        • Jolly T.A.
        • Deal A.M.
        • Nyrop K.A.
        • et al.
        Geriatric assessment-identified deficits in older cancer patients with normal performance status.
        Oncologist. 2015; 20: 379-385https://doi.org/10.1634/theoncologist.2014-0247
        • Hoppe S.
        • Rainfray M.
        • Fonck M.
        • et al.
        Functional decline in older patients with cancer receiving first-line chemotherapy.
        J Clin Oncol. 2013; 31: 3877-3882https://doi.org/10.1200/JCO.2012.47.7430
        • Aaronson N.K.
        • 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: 365-376https://doi.org/10.1093/jnci/85.5.365
        • 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.
        J Natl Compr Cancer Netw. 2021; 19: 1055-1062https://doi.org/10.6004/jnccn.2020.7684
        • Peel C.
        • Sawyer Baker P.
        • Roth D.L.
        • Brown C.J.
        • Brodner E.
        • Allman R.M.
        Assessing mobility in older adults: the UAB study of aging life-space assessment.
        Phys Ther. 2005; 85: 1008-1119
        • Johnson J.
        • Rodriguez M.A.
        • Al Snih S.
        Life-space mobility in the elderly: current perspectives.
        Clin Interv Aging. 2020; 15: 1665-1674https://doi.org/10.2147/CIA.S196944
        • Stewart C.M.L.
        • Wheeler T.L.
        • Markland A.D.
        • Straughn J.M.
        • Richter H.E.
        Life-space assessment in urogynecology and gynecological oncology surgery patients: a measure of perioperative mobility and function.
        J Am Geriatr Soc. 2009; 57: 2263-2268https://doi.org/10.1111/j.1532-5415.2009.02557.x
        • Yee J.
        • Davis G.M.
        • Beith J.M.
        • et al.
        Physical activity and fitness in women with metastatic breast cancer.
        J Cancer Surviv. 2014; 8: 647-656https://doi.org/10.1007/s11764-014-0378-y
        • Gattás-Vernaglia I.F.
        • Ramos P.T.
        • Perini M.L.L.
        • et al.
        Impact of the COVID-19 pandemic on the life-space mobility of older adults with cancer.
        J Geriatr Oncol. 2021; 12: 956-959https://doi.org/10.1016/j.jgo.2021.02.012
        • Iyer A.S.
        • Wells J.M.
        • Bhatt S.P.
        • et al.
        Life-space mobility and clinical outcomes in COPD.
        Int J Chron Obstruct Pulmon Dis. 2018; 13: 2731-2738https://doi.org/10.2147/COPD.S170887
        • Kennedy R.E.
        • Williams C.P.
        • Sawyer P.
        • et al.
        Life-space predicts health care utilization in community-dwelling older adults.
        J Aging Health. 2019; 31: 280-292https://doi.org/10.1177/0898264317730487
        • Mackey D.C.
        • Lui L.Y.
        • Cawthon P.M.
        • Ensrud K.
        • Yaffe K.
        • Cummings S.R.
        Life-space mobility and mortality in older women: prospective results from the study of osteoporotic fractures.
        J Am Geriatr Soc. 2016; 64: 2226-2234https://doi.org/10.1111/jgs.14474
        • Hurria A.
        • Gupta S.
        • Zauderer M.
        • et al.
        Developing a cancer-specific geriatric assessment: a feasibility study.
        Cancer. 2005; 104: 1998-2005https://doi.org/10.1002/cncr.21422
        • Katz S.
        • Ford A.B.
        • Moskowitz R.W.
        • Jackson B.A.
        • Jaffe M.W.
        Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function.
        JAMA. 1963; 185: 914-919https://doi.org/10.1001/jama.1963.03060120024016
        • Fillenbaum G.G.
        • Smyer M.A.
        The development, validity, and reliability of the OARS multidimensional functional assessment questionnaire.
        J Gerontol. 1981; 36: 428-434https://doi.org/10.1093/geronj/36.4.428
        • Podsiadlo D.
        • Richardson S.
        The timed “up & go”: a test of basic functional mobility for frail elderly persons.
        J Am Geriatr Soc. 1991; 39: 142-148https://doi.org/10.1111/j.1532-5415.1991.tb01616.x
        • Guralnik J.M.
        • Simonsick E.M.
        • Ferrucci L.
        • et al.
        A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission.
        J Gerontol. 1994; 49: M85-M94https://doi.org/10.1093/geronj/49.2.m85
        • Hurria A.
        • Cirrincione C.T.
        • Muss H.B.
        • et al.
        Implementing a geriatric assessment in cooperative group clinical cancer trials: CALGB 360401.
        J Clin Oncol. 2011; 29: 1290-1296https://doi.org/10.1200/JCO.2010.30.6985
        • Mohile S.G.
        • Epstein R.M.
        • Hurria A.
        • et al.
        Communication with older patients with Cancer using geriatric assessment: a cluster-randomized clinical trial from the National Cancer Institute Community oncology research program.
        JAMA Oncol. 2020; 6: 196-204https://doi.org/10.1001/jamaoncol.2019.4728
        • Nasreddine Z.S.
        • Phillips N.A.
        • Bédirian V.
        • et al.
        The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment.
        J Am Geriatr Soc. 2005; 53: 695-699https://doi.org/10.1111/j.1532-5415.2005.53221.x
        • Pergolotti M.
        • Langer M.M.
        • Deal A.M.
        • Muss H.B.
        • Nyrop K.
        • Williams G.
        Mental status evaluation in older adults with cancer: development of the mental health Index-13.
        J Geriatr Oncol. 2019; 10: 241-245https://doi.org/10.1016/j.jgo.2018.08.009
        • Sherbourne C.D.
        • Stewart A.L.
        The MOS social support survey.
        Soc Sci Med. 1991; 32: 705-714https://doi.org/10.1016/0277-9536(91)90150-b
        • Bischel L.E.
        • Ritchie C.
        • Kober K.M.
        • et al.
        Age differences in fatigue, decrements in energy, and sleep disturbance in oncology patients receiving chemotherapy.
        Eur J Oncol Nurs. 2016; 23: 115-123https://doi.org/10.1016/j.ejon.2016.07.002
        • Lee K.A.
        • Hicks G.
        • Nino-Murcia G.
        Validity and reliability of a scale to assess fatigue.
        Psychiatry Res. 1991; 36: 291-298https://doi.org/10.1016/0165-1781(91)90027-m
        • Sagberg L.M.
        • Jakola A.S.
        • Solheim O.
        Quality of life assessed with EQ-5D in patients undergoing glioma surgery: what is the responsiveness and minimal clinically important difference?.
        Qual Life Res. 2014; 23: 1427-1434https://doi.org/10.1007/s11136-013-0593-4
        • Zeng L.
        • Chow E.
        • Zhang L.
        • et al.
        An international prospective study establishing minimal clinically important differences in the EORTC QLQ-BM22 and QLQ-C30 in cancer patients with bone metastases.
        Support Care Cancer. 2012; 20: 3307-3313https://doi.org/10.1007/s00520-012-1484-x
        • Abdulaziz K.
        • Perry J.J.
        • Taljaard M.
        • et al.
        National Survey of geriatricians to define functional decline in elderly people with minor trauma.
        Can Geriatr J. 2016; 19: 2-8https://doi.org/10.5770/cgj.19.192
        • Hurria A.
        • Soto-Perez-de-Celis E.
        • Allred J.B.
        • et al.
        Functional decline and resilience in older women receiving adjuvant chemotherapy for breast Cancer.
        J Am Geriatr Soc. 2019; 67: 920-927https://doi.org/10.1111/jgs.15493
        • Kennedy R.E.
        • Sawyer P.
        • Williams C.P.
        • et al.
        Life-space mobility change predicts 6-month mortality.
        J Am Geriatr Soc. 2017; 65: 833-838https://doi.org/10.1111/jgs.14738
        • Kennedy R.E.
        • Almutairi M.
        • Williams C.P.
        • Sawyer P.
        • Allman R.M.
        • Brown C.J.
        Determination of the minimal important change in the life-space assessment.
        J Am Geriatr Soc. 2019; 67: 565-569https://doi.org/10.1111/jgs.15707
      1. StataCorp. Published online 2021.

        • Vaismoradi M.
        • Turunen H.
        • Bondas T.
        Content analysis and thematic analysis: implications for conducting a qualitative descriptive study.
        Nurs Health Sci. 2013; 15: 398-405https://doi.org/10.1111/nhs.12048
        • Portegijs E.
        • Rantakokko M.
        • Viljanen A.
        • Sipilä S.
        • Rantanen T.
        Identification of older people at risk of ADL disability using the life-space assessment: a longitudinal cohort study.
        J Am Med Dir Assoc. 2016; 17: 410-414https://doi.org/10.1016/j.jamda.2015.12.010
        • Al Snih S.
        • Peek K.M.
        • Sawyer P.
        • Markides K.S.
        • Allman R.M.
        • Ottenbacher K.J.
        Life-space mobility in Mexican Americans aged 75 and older.
        J Am Geriatr Soc. 2012; 60: 532-537https://doi.org/10.1111/j.1532-5415.2011.03822.x
        • Taylor J.K.
        • Buchan I.E.
        • van der Veer S.N.
        Assessing life-space mobility for a more holistic view on wellbeing in geriatric research and clinical practice.
        Aging Clin Exp Res. 2019; 31: 439-445https://doi.org/10.1007/S40520-018-0999-5/TABLES/2
        • Webber S.C.
        • Porter M.M.
        • Menec V.H.
        Mobility in older adults: a comprehensive framework.
        Gerontologist. 2010; 50: 443-450https://doi.org/10.1093/GERONT/GNQ013
        • Nightingale G.
        • Battisti N.M.L.
        • Loh K.P.
        • et al.
        Perspectives on functional status in older adults with cancer: an interprofessional report from the International Society of Geriatric Oncology (SIOG) nursing and allied health interest group and young SIOG.
        J Ger Oncol. 2021; 12: 658-665https://doi.org/10.1016/j.jgo.2020.10.018
        • Hamaker M.
        • Lund C.
        • te Molder M.
        • et al.
        Geriatric assessment in the management of older patients with cancer - a systematic review (update).
        J Geriatr Oncol. 2022; (Published online May 8)https://doi.org/10.1016/j.jgo.2022.04.008
        • Phillips J.L.
        • Lam L.
        • Luckett T.
        • Agar M.
        • Currow D.
        Is the life space assessment applicable to a palliative care population? Its relationship to measures of performance and quality of life.
        J Pain Symptom Manag. 2014; 47: 1121-1127https://doi.org/10.1016/j.jpainsymman.2013.06.017
        • Viret O.
        • Schwarz J.
        • Senn N.
        • Mueller Y.
        Discussing age-related functional decline in family medicine: a qualitative study that explores both patient and physician perceptions.
        Age Ageing. 2020; 49: 292-299https://doi.org/10.1093/AGEING/AFZ158
        • Brehaut J.C.
        • O’Connor A.M.
        • Wood T.J.
        • et al.
        Validation of a decision regret scale.
        Med Decis Mak. 2003; 23: 281-292https://doi.org/10.1177/0272989X03256005
        • Thanarajasingam G.
        • Basch E.
        • Mead-Harvey C.
        • et al.
        An exploratory analysis of the “was it worth it?” questionnaire as a novel metric to capture patient perceptions of Cancer treatment.
        Value Health. 2022; 25: 1081-1086https://doi.org/10.1016/j.jval.2021.11.1368