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Original Article| Volume 56, ISSUE 5, P678-688.e1, November 2018

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Characteristics Associated With Physical Function Trajectories in Older Adults With Cancer During Chemotherapy

Open AccessPublished:August 22, 2018DOI:https://doi.org/10.1016/j.jpainsymman.2018.08.006

      Abstract

      Context

      Studies on physical function trajectories in older adults during chemotherapy remain limited.

      Objectives

      The objective of this study was to determine demographic, clinical, and symptom characteristics associated with initial levels as well as trajectories of physical function over two cycles of chemotherapy in adults aged ≥65 years with breast, gastrointestinal, gynecological, or lung cancer.

      Methods

      Older adults with cancer (n = 363) who had received chemotherapy within the preceding four weeks were assessed six times over two cycles of chemotherapy using the Short Form-12 Physical Component Summary (PCS) score. Hierarchical linear modeling was used to evaluate for interindividual variability in initial levels and trajectories of PCS scores.

      Results

      Mean age was 71.4 years (SD 5.5). Mean PCS score at enrollment was 40.5 (SD .45). On average, PCS scores decreased slightly (i.e., 0.21 points) at each subsequent assessment. Lower PCS scores at enrollment were associated with older age, greater comorbidity, being unemployed, lack of regular exercise, higher morning fatigue, lower evening energy, occurrence of pain, lower trait anxiety, and lower attentional function. Only higher morning fatigue and lower enrollment PCS scores were associated with decrements in physical function over time.

      Conclusion

      While several symptoms were associated with decrements in PCS scores at enrollment in older adults with cancer receiving chemotherapy, morning fatigue was the only symptom associated with decreases in physical function over time. Regular assessments of symptoms and implementation of evidence-based interventions should be considered to maintain physical function in older adults during chemotherapy.

      Key Words

      Introduction

      As the incidence of cancer among older adults in the U.S. increases to 2.3 million by 2030,
      • Smith B.D.
      • Smith G.L.
      • Hurria A.
      • Hortobagyi G.N.
      • Buchholz T.A.
      Future of cancer incidence in the United States: burdens upon an aging, changing nation.
      the impact of cancer treatment on physical function will become increasingly important. Pretreatment functional impairment and decline during treatment are associated with worse quality of life
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      • Klippstein A.
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      Co-morbidity and functional deficits independently contribute to quality of life before chemotherapy in elderly cancer patients.
      and overall survival.
      • Maione P.
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      • 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 study.
      • Kenis C.
      • Decoster L.
      • Bastin J.
      • et al.
      Functional decline in older patients with cancer receiving chemotherapy: a multicenter prospective study.
      In addition, the impact of cancer treatment on physical function is critically important to patients. In a study of adults aged ≥60 years with limited life expectancy, more than 70% of those with cancer reported that they would not choose a treatment that results in functional impairment, even if it improved survival.
      • Fried T.R.
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      Understanding the treatment preferences of seriously ill patients.
      Despite the importance of functional outcomes to older cancer patients, studies on the effect of treatment on physical function remain limited,
      • 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.
      • Given B.
      • Given C.
      • Azzouz F.
      • Stommel M.
      Physical functioning of elderly cancer patients prior to diagnosis and following initial treatment.
      • Given C.W.
      • Given B.
      • Azzouz F.
      • Stommel M.
      • Kozachik S.
      Comparison of changes in physical functioning of elderly patients with new diagnoses of cancer.
      • van Abbema D.
      • van Vuuren A.
      • van den Berkmortel F.
      • et al.
      Functional status decline in older patients with breast and colorectal cancer after cancer treatment: a prospective cohort study.
      • Owusu C.
      • Margevicius S.
      • Schluchter M.
      • et al.
      Vulnerable elders survey and socioeconomic status predict functional decline and death among older women with newly diagnosed nonmetastatic breast cancer.
      • Puts M.T.E.
      • Monette J.
      • Girre V.
      • et al.
      Changes in functional status in older newly-diagnosed cancer patients during cancer treatment: a six-month follow-up period. Results of a prospective pilot study.
      with only two studies focusing specifically on physical function during chemotherapy.
      • 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.
      In these European studies, pretreatment depression, abnormal nutritional status, and dependency in instrumental activities of daily living (IADL) were associated with decrements in activities of daily living (ADL) during chemotherapy.
      • 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.
      Chemotherapy for a new diagnosis of cancer was associated with decrements in IADL.
      • Kenis C.
      • Decoster L.
      • Bastin J.
      • et al.
      Functional decline in older patients with cancer receiving chemotherapy: a multicenter prospective study.
      However, both of these studies examined changes in physical function between only two time points, which may miss acute within cycle, potentially nonlinear changes in physical function during treatment. Acute changes in physical function after each chemotherapy infusion may be especially important in older adults with cancer because their limited physiologic reserve may make recovering from any functional decline more challenging.
      • Repetto L.
      Greater risks of chemotherapy toxicity in elderly patients with cancer.
      Furthermore, while both studies examined the association between depression and functional decline during chemotherapy, the impact of other symptoms such as morning and evening fatigue, morning and evening energy, sleep disturbance, and state and trait anxiety on physical function remains unknown.
      Given the limited research on changes in and predictors of decrements in physical function in older adults during chemotherapy, the purposes of our study, in a sample of older adults with breast, gastrointestinal (GI), gynecological (GYN), and lung cancer who received chemotherapy (n = 363), were to evaluate for interindividual differences in physical function and to determine which demographic, clinical, and symptom characteristics were associated with initial levels as well as with trajectories of physical function over six time points during two cycles of chemotherapy.

      Patients and Methods

      Patients and Settings

      The procedures for the parent cohort study are described in detail elsewhere.
      • Wright F.
      • D'Eramo Melkus G.
      • Hammer M.
      • et al.
      Predictors and trajectories of morning fatigue are distinct from evening fatigue.
      • Miaskowski C.
      • Cooper B.A.
      • Melisko M.
      • et al.
      Disease and treatment characteristics do not predict symptom occurrence profiles in oncology outpatients receiving chemotherapy.
      The objective of the parent study was to characterize symptom clusters in patients with cancer receiving chemotherapy.
      • Miaskowski C.
      • Cooper B.A.
      • Melisko M.
      • et al.
      Disease and treatment characteristics do not predict symptom occurrence profiles in oncology outpatients receiving chemotherapy.
      • Ward Sullivan C.
      • Leutwyler H.
      • Dunn L.B.
      • et al.
      Differences in symptom clusters identified using symptom occurrence rates versus severity ratings in patients with breast cancer undergoing chemotherapy.
      • Sullivan C.W.
      • Leutwyler H.
      • Dunn L.B.
      • et al.
      Stability of symptom clusters in patients with breast cancer receiving chemotherapy.
      • Miaskowski C.
      • Cooper B.A.
      • Aouizerat B.
      • et al.
      The symptom phenotype of oncology outpatients remains relatively stable from prior to through 1 week following chemotherapy.
      Eligible patients in the parent study were ≥18 years of age; had a diagnosis of breast, GI, GYN, or lung cancer; had received chemotherapy within the preceding four weeks; were scheduled to receive at least two additional cycles; and were able to read, write, and understand English. We chose to enroll patients who had received at least one prior cycle of chemotherapy to better understand their ongoing risk of decrements in physical function during subsequent cycles of chemotherapy. Patients were recruited from two Comprehensive Cancer Centers, one Veteran's Affairs hospital, and four community-based oncology programs. A total of 2234 patients were approached and 1343 consented to participate (60.1% response rate). For this analysis, patients who were ≥65 years of age (n = 363) were included.

      Instruments

      Demographic and Clinical Characteristics

      Patients completed a demographics questionnaire, the Karnofsky Performance Status scale,
      • Karnofsky D.
      Performance Scale.
      • Schnadig I.D.
      • Fromme E.K.
      • Loprinzi C.L.
      • et al.
      Patient-physician disagreement regarding performance status is associated with worse survivorship in patients with advanced cancer.
      • Ando M.
      • Ando Y.
      • Hasegawa Y.
      • et al.
      Prognostic value of performance status assessed by patients themselves, nurses, and oncologists in advanced non-small cell lung cancer.
      and Self-Administered Comorbidity Questionnaire.
      • Sangha O.
      • Stucki G.
      • Liang M.H.
      • Fossel A.H.
      • Katz J.N.
      The Self-Administered Comorbidity Questionnaire: a new method to assess comorbidity for clinical and health services research.
      Medical records were reviewed for disease and treatment characteristics. The MAX2 index
      • Extermann M.
      • Chen H.
      • Cantor A.B.
      • et al.
      Predictors of tolerance to chemotherapy in older cancer patients: a prospective pilot study.
      • Extermann M.
      • Bonetti M.
      • Sledge G.W.
      • et al.
      MAX2--a convenient index to estimate the average per patient risk for chemotherapy toxicity; validation in ECOG trials.
      estimated the average risk for Grade 3 to 4 toxicity for each chemotherapy regimen.

      Assessment of Physical Function

      Changes in physical function over two cycles of chemotherapy were assessed using the Physical Component Summary (PCS) score from the Medical Outcomes Study–Short Form-12 (SF-12),
      • Ware Jr., J.
      • Kosinski M.
      • Keller S.D.
      A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity.
      • Annunziata M.A.
      • Muzzatti B.
      • Giovannini L.
      • et al.
      Is long-term cancer survivors' quality of life comparable to that of the general population? An Italian study.
      • Briggs K.K.
      • Soares E.
      • Bhatia S.
      • Philippon M.J.
      Postoperative alpha angle not associated with patient-centered midterm outcomes following hip arthroscopy for FAI.
      • Gallo R.A.
      • Plakke M.
      • Mosher T.
      • Black K.P.
      Outcomes following impaction bone grafting for treatment of unstable osteochondritis dissecans.
      • Gautschi O.P.
      • Corniola M.V.
      • Smoll N.R.
      • et al.
      Sex differences in subjective and objective measures of pain, functional impairment, and health-related quality of life in patients with lumbar degenerative disc disease.
      • Gautschi O.P.
      • Smoll N.R.
      • Corniola M.V.
      • et al.
      Sex differences in lumbar degenerative disc disease.
      • Gerhardt D.
      • De Visser E.
      • Hendrickx B.W.
      • Schreurs B.W.
      • Van Susante J.L.C.
      Bone mineral density changes in the graft after acetabular impaction bone grafting in primary and revision hip surgery.
      • Howard L.M.
      • Flach C.
      • Mehay A.
      • Sharp D.
      • Tylee A.
      The prevalence of suicidal ideation identified by the Edinburgh Postnatal Depression Scale in postpartum women in primary care: findings from the RESPOND trial.
      • Mendes de Leon C.F.
      • Czajkowski S.M.
      • Freedland K.E.
      • et al.
      The effect of a psychosocial intervention and quality of life after acute myocardial infarction: the Enhancing Recovery in Coronary Heart Disease (ENRICHD) clinical trial.
      • Newman J.T.
      • Briggs K.K.
      • McNamara S.C.
      • Philippon M.J.
      Revision hip arthroscopy: a matched-cohort study comparing revision to primary arthroscopy patients.
      • Preede L.
      • Saebu M.
      • Perrin P.B.
      • et al.
      One-year trajectories of mental and physical functioning during and after rehabilitation among individuals with disabilities.
      • Roelen C.
      • van Rhenen W.
      • Schaufeli W.
      • et al.
      Mental and physical health-related functioning mediates between psychological job demands and sickness absence among nurses.
      • Tang Y.
      • Green P.
      • Maurer M.
      • et al.
      Relationship between accelerometer-measured activity and self-reported or performance-based function in older adults with severe aortic stenosis.
      • van Oldenrijk J.
      • Scholtes V.A.B.
      • van Beers L.
      • et al.
      Better early functional outcome after short stem total hip arthroplasty? A prospective blinded randomised controlled multicentre trial comparing the Collum Femoris Preserving stem with a Zweymuller straight cementless stem total hip replacement for the treatment of primary osteoarthritis of the hip.
      • Zhang X.
      • Brown J.C.
      • Schmitz K.H.
      Association between body mass index and physical function among endometrial cancer survivors.
      which assesses various aspects of physical and mental health. The PCS score consists of six items: health limitations with moderate activities, climbing several flights of stairs, accomplishing less than you would like, limitations in work or other activities, pain interference with normal work, and overall health rating. PCS scores can range from 0 to 100, with higher scores indicating better physical functioning. PCS results are scored using a norm-based algorithm with a standardized mean of 50 and an SD of 10 in the general U.S. adult population.
      • Ware J.
      • Kosinski M.
      • Keller S.
      SF-12: How to Score the SF-12 Physical and Mental Health Summary Scales.
      The SF-12 and PCS scores have well-established validity and reliability
      • Ware Jr., J.
      • Kosinski M.
      • Keller S.D.
      A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity.
      and have been used in other studies of patients with cancer.
      • Jacobs B.L.
      • Lopa S.H.
      • Yabes J.G.
      • et al.
      Association of functional status and treatment choice among older men with prostate cancer in the Medicare Advantage population.
      • Kroenke K.
      • Johns S.A.
      • Theobald D.
      • Wu J.
      • Tu W.
      Somatic symptoms in cancer patients trajectory over 12 months and impact on functional status and disability.

      Assessment of Symptoms

      To evaluate common symptoms, patients completed separate Lee Fatigue Scale questionnaires
      • Lee K.A.
      • Hicks G.
      • Nino-Murcia G.
      Validity and reliability of a scale to assess fatigue.
      that evaluated diurnal variations (i.e., morning and evening) in fatigue severity and decrements in energy. Morning and evening fatigue and morning and evening energy are distinct symptoms both from phenotypic and genotypic perspectives.
      • Aouizerat B.E.
      • Dhruva A.
      • Paul S.M.
      • et al.
      Phenotypic and molecular evidence suggests that decrements in morning and evening energy are distinct but related symptoms.
      • Eshragh J.
      • Dhruva A.
      • Paul S.M.
      • et al.
      Associations between neurotransmitter genes and fatigue and energy levels in women after breast cancer surgery.
      • Kober K.M.
      • Smoot B.
      • Paul S.M.
      • et al.
      Polymorphisms in cytokine genes are associated with higher levels of fatigue and lower levels of energy in women after breast cancer surgery.
      • Abid H.
      • Kober K.M.
      • Smoot B.
      • et al.
      Common and distinct characteristics associated with trajectories of morning and evening energy in oncology patients receiving chemotherapy.
      • Wright F.
      • Hammer M.
      • Paul S.M.
      • et al.
      Inflammatory pathway genes associated with inter-individual variability in the trajectories of morning and evening fatigue in patients receiving chemotherapy.
      • Kober K.M.
      • Cooper B.A.
      • Paul S.M.
      • et al.
      Subgroups of chemotherapy patients with distinct morning and evening fatigue trajectories.
      In addition, patients completed the General Sleep Disturbance Scale,
      • Lee K.A.
      Self-reported sleep disturbances in employed women.
      Center for Epidemiological Studies–Depression Scale,
      • Radloff L.S.
      The CES-D Scale: a self-report depression scale for research in the general population.
      Brief Pain Inventory,
      • Daut R.L.
      • Cleeland C.S.
      • Flanery R.C.
      Development of the Wisconsin Brief Pain Questionnaire to assess pain in cancer and other diseases.
      Attentional Function Index,
      • Cimprich B.
      • Visovatti M.
      • Ronis D.L.
      The Attentional Function Index--a self-report cognitive measure.
      and Spielberger State-Trait Anxiety Inventories.
      • Spielberger C.G.
      • Gorsuch R.L.
      • Suchene R.
      • Vagg P.R.
      • Jacobs G.A.
      Manual for the State-Anxiety (Form Y): Self Evaluation Questionnaire.
      State anxiety measures a person's temporary anxiety response to a specific situation while trait anxiety measures a person's predisposition to anxiety as part of one's personality.

      Study Procedures

      The study was approved by the institutional review board at each study site. Written informed consent was obtained from all participants. Depending on the length of their chemotherapy cycles (i.e., 14 days, 21 days, 28 days), patients completed study questionnaires in their homes a total of six times over two cycles of chemotherapy: before chemotherapy administration (i.e., recovery from previous chemotherapy cycle; Assessments 1 and 4), approximately one week after chemotherapy administration (i.e., acute symptoms in the week after infusion; Assessments 2 and 5), and approximately two weeks after chemotherapy administration (i.e., potential nadir; Assessments 3 and 6).

      Statistical Analyses

      Descriptive statistics and frequency distributions were generated on the sample characteristics and symptom severity scores at enrollment using the Statistical Package for the Social Sciences (SPSS, Version 24, IBM Corporation, Armonk, NY).
      Hierarchical linear modeling (HLM) based on full maximum likelihood estimation was performed in two stages using software developed by Raudenbush and Bryk.
      • Raudenbush S.W.
      • Bryk A.
      Hierarchical Linear Models: Applications and Data Analysis Methods.
      The HLM methods are described in detail elsewhere.
      • Wright F.
      • D'Eramo Melkus G.
      • Hammer M.
      • et al.
      Predictors and trajectories of morning fatigue are distinct from evening fatigue.
      In brief, the HLM analysis evaluated for changes over time in PCS scores. During Stage 1, intraindividual variability in PCS scores over time was examined. Three Level 1 models were compared to determine whether the patients' level of physical function did not change over time (i.e., no time effect), changed at a constant rate (i.e., linear time effect), or changed at a rate that accelerated or decelerated over time (i.e., quadratic effect). Then, the Level 2 model was constrained to be unconditional (i.e., no predictors), and likelihood ratio tests were used to determine the best model.
      The second stage of the HLM analysis examined interindividual differences in the trajectories of PCS scores by modeling individual change parameters (i.e., intercept, linear slope) as a function of proposed predictors at Level 2. Supplementary Table 1 presents a list of demographic, clinical, and symptom characteristics that were evaluated as potential predictors based on a literature review of physical function in cancer patients.
      • 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.
      • Given B.
      • Given C.
      • Azzouz F.
      • Stommel M.
      Physical functioning of elderly cancer patients prior to diagnosis and following initial treatment.
      • Given C.W.
      • Given B.
      • Azzouz F.
      • Stommel M.
      • Kozachik S.
      Comparison of changes in physical functioning of elderly patients with new diagnoses of cancer.
      • Owusu C.
      • Margevicius S.
      • Schluchter M.
      • et al.
      Vulnerable elders survey and socioeconomic status predict functional decline and death among older women with newly diagnosed nonmetastatic breast cancer.
      • Puts M.T.E.
      • Monette J.
      • Girre V.
      • et al.
      Changes in functional status in older newly-diagnosed cancer patients during cancer treatment: a six-month follow-up period. Results of a prospective pilot study.
      To improve estimation efficiency and construct a parsimonious model, bivariable exploratory Level 2 analyses were performed in which each characteristic was added as a predictor to determine whether it improved the model. Characteristics with an absolute t-value <2.0 were dropped from subsequent models. All potential significant predictors from the exploratory analyses were entered into the HLM models to predict each change parameter. Only those characteristics that maintained a statistically significant contribution in conjunction with other characteristics were retained in the final HLM model. A P-value of <0.05 indicates statistical significance.
      One advantage of HLM is that patients with some missing data on the dependent variable (i.e., PCS score) are not eliminated from the analysis. They contribute as many assessments as were possible for them to provide. By contrast, missing data are not allowed for predictor variables so patients with any missing predictor variables were not included in the HLM analyses.

      Results

      Sample Characteristics

      Demographic, clinical, and symptom characteristics of the sample (N = 363) are presented in Table 1. The sample was predominately female (68.3%) with a mean age of 71.4 (SD 5.5) years. Patients had an average of 16.5 (SD 3.1) years of education, BMI of 26.1 (SD 5.3), and Karnofsky Performance Status score of 82.6 (SD 12.6). Patients were 2.9 (SD 5.2) years from their cancer diagnosis (median 0.49 years) and primarily being treated with 21-day chemotherapy cycles (55.1%) for metastatic disease (73.6%). At enrollment, the mean morning energy score on the Lee Fatigue Scale was below the clinically meaningful cutoff. Over 67% of patients reported experiencing pain and 25.1% had a depression score of ≥16 suggesting depressive symptoms that warrant a clinical evaluation. In addition, the mean sleep disturbance and trait anxiety scores were above the cutoff scores for clinically meaningful levels of sleep disturbance and trait anxiety, respectively.
      Table 1Demographic, Clinical, and Symptom Characteristics of Older Adults With Cancer Receiving Chemotherapy (N = 363)
      Characteristicsn (%) or Mean (SD)
      Demographic characteristics
       Age, yrs; mean (SD)71.4 (5.5)
       Age, yrs; median (range)69 (65–90)
       Female gender248 (68.3)
       Ethnicity
      White289 (80.1)
      Black24 (6.6)
      Asian/Pacific Islander23 (6.4)
      Hispanic/mixed/other25 (6.9)
       Education, yrs; mean (SD)16.5 (3.1)
       Married or partnered211 (59.1)
       Lives alone106 (29.8)
       Currently employed78 (21.7)
       Child care responsibilities17 (4.8)
       Income
      Less than $30,00075 (23.9)
      $30,000 to <$70,00079 (25.2)
      $70,000 to <$100,00055 (17.5)
      More than $100,000105 (33.4)
      Clinical characteristics
       Number of comorbidities, mean (SD)2.8 (1.5)
       Self-Administered Comorbidity Questionnaire score, mean (SD)6.2 (3.4)
       Specific comorbidities reported
      Hypertension167 (46.0)
      Back pain95 (26.2)
      Osteoarthritis85 (23.4)
      Lung disease73 (20.1)
      Depression64 (17.6)
      Diabetes52 (14.3)
      Heart disease42 (11.6)
      Anemia33 (9.1)
      Liver disease26 (7.2)
      Ulcer or stomach disease16 (4.4)
      Rheumatoid arthritis13 (3.6)
      Kidney disease7 (1.9)
       Body mass index, kg/m2; mean (SD)26.1 (5.3)
       Hemoglobin, gm/dL; mean (SD)11.5 (1.4)
       Karnofsky Performance Status score, mean (SD)82.6 (12.6)
       Karnofsky Performance Status score, median (range)90 (40–100)
       Current or former smoker169 (47.5)
       Exercise on a regular basis235 (66.2)
       Cancer diagnosis
      Breast84 (23.1)
      Gastrointestinal119 (32.8)
      Gynecological79 (21.8)
      Lung81 (22.3)
       Time since cancer diagnosis, yrs; mean (SD)2.9 (5.2)
       Time since cancer diagnosis, yrs; median (range)0.49 (0.06–38.3)
       Any prior cancer treatments269 (76.2)
       Number of prior cancer treatments, mean (SD)1.7 (1.5)
       Chemotherapy MAX2 index, mean (SD)0.152 (0.1)
       Chemotherapy cycle length
      14 days124 (34.2)
      21 days200 (55.1)
      28 days39 (10.7)
       Metastatic disease at the time of study265 (73.6)
       Number of metastatic sites including lymph node involvement, mean (SD)1.4 (1.2)
       Number of metastatic sites excluding lymph node involvement, mean (SD)0.9 (1.1)
      Symptom characteristics at enrollment
      Clinically meaningful symptom cut-point scores: Lee Fatigue Scale score ≥3.2 for morning fatigue, ≥5.6 for evening fatigue, ≤6.2 for morning energy, ≤3.5 for evening energy25; General Sleep Disturbance Scale score ≥4326; Center for Epidemiological Studies–Depression Scale score ≥1627; State Anxiety score ≥32.2; Trait Anxiety score ≥31.830; Attentional Function Index score ≤5.29 Higher scores for Lee Fatigue Scale, General Sleep Disturbance Scale, Center for Epidemiological Studies-Depression Scale, State Anxiety Scale, and Trait Anxiety Scale indicate higher levels of symptoms. Lower scores on the Attentional Function Index and Lee Energy Scale indicate worse attentional function and lower levels of energy, respectively.
       Lee Fatigue Scale: morning fatigue score, mean (SD)2.6 (2.1)
       Lee Fatigue Scale: evening fatigue score, mean (SD)4.8 (2.2)
       Lee Fatigue Scale: morning energy score, mean (SD)4.3 (2.5)
       Lee Fatigue Scale: evening energy score, mean (SD)3.8 (2.1)
       General Sleep Disturbance Scale score, mean (SD)48.7 (18.5)
       Center for Epidemiological Studies–Depression Scale score, mean (SD)10.9 (9.1)
       Pain present242 (67.2)
       State Anxiety score, mean (SD)32.0 (12.0)
       Trait Anxiety score, mean (SD)33.8 (10.5)
       Attentional Function Index score, mean (SD)6.5 (1.8)
      a Clinically meaningful symptom cut-point scores: Lee Fatigue Scale score ≥3.2 for morning fatigue, ≥5.6 for evening fatigue, ≤6.2 for morning energy, ≤3.5 for evening energy
      • Extermann M.
      • Bonetti M.
      • Sledge G.W.
      • et al.
      MAX2--a convenient index to estimate the average per patient risk for chemotherapy toxicity; validation in ECOG trials.
      ; General Sleep Disturbance Scale score ≥43
      • Ware Jr., J.
      • Kosinski M.
      • Keller S.D.
      A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity.
      ; Center for Epidemiological Studies–Depression Scale score ≥16
      • Annunziata M.A.
      • Muzzatti B.
      • Giovannini L.
      • et al.
      Is long-term cancer survivors' quality of life comparable to that of the general population? An Italian study.
      ; State Anxiety score ≥32.2; Trait Anxiety score ≥31.8
      • Gautschi O.P.
      • Corniola M.V.
      • Smoll N.R.
      • et al.
      Sex differences in subjective and objective measures of pain, functional impairment, and health-related quality of life in patients with lumbar degenerative disc disease.
      ; Attentional Function Index score ≤5.
      • Gallo R.A.
      • Plakke M.
      • Mosher T.
      • Black K.P.
      Outcomes following impaction bone grafting for treatment of unstable osteochondritis dissecans.
      Higher scores for Lee Fatigue Scale, General Sleep Disturbance Scale, Center for Epidemiological Studies-Depression Scale, State Anxiety Scale, and Trait Anxiety Scale indicate higher levels of symptoms. Lower scores on the Attentional Function Index and Lee Energy Scale indicate worse attentional function and lower levels of energy, respectively.

      Changes in Physical Function Over Time

      The first HLM analysis examined how physical function (i.e., PCS scores) changed over two cycles of chemotherapy. As shown in Fig. 1a, a linear model fits the data best. As shown in Table 2, the intercept in the unconditional model represents the estimated level of physical function (i.e., PCS score of 40.719 on a 0–100 scale) before the initiation of the next cycle of chemotherapy (i.e., Assessment 1). The estimated linear rate of change in physical function for each additional assessment was −0.212 (P < .01). As illustrated in Fig. 1a, physical function decreased slightly over the two cycles of chemotherapy.
      Figure thumbnail gr1
      Fig. 1a) Model of mean Physical Component Summary scores for six assessment points over two cycles of chemotherapy: before chemotherapy administration (i.e., recovery from previous chemotherapy cycle; Assessments 1 and 4), approximately one week after chemotherapy administration (i.e., acute symptoms in the week after infusion; Assessments 2 and 5), and approximately two weeks after chemotherapy administration (i.e., potential nadir; Assessments 3 and 6). b) Spaghetti plot of individual Physical Component Summary score trajectories for a 10% random sample of patients over two cycles of chemotherapy.
      Table 2Hierarchical Linear Model of Physical Function
      Physical Function Model CharacteristicsCoefficient (SE)
      Unconditional ModelFinal Model
      Fixed effects
       Intercept40.719 (0.544)
      P < 0.001.
      40.536 (0.450)
      P < 0.001.
       Linear rate of change per assessment−0.212 (.079)
      P < 0.01.
      −0.212 (0.077)
      P < 0.01.
      Time-invariant covariates
       Intercept
      Age−0.176 (0.082)
      P < 0.05.
      Employed2.479 (1.107)
      P < 0.05.
      SCQ score−0.577 (0.147)
      P < 0.001.
      Exercise on a regular basis4.141 (0.980)
      P < 0.001.
      Morning fatigue score at enrollment−0.871 (0.278)
      P < 0.01.
      Evening energy score at enrollment0.576 (0.223)
      P < 0.05.
      Pain present at enrollment−3.821 (1.029)
      P < 0.001.
      Trait Anxiety score at enrollment0.120 (0.057)
      P < 0.05.
      Attentional Function Index score at enrollment0.754 (0.341)
      P < 0.05.
       Linear slope
      Morning fatigue score at enrollment−0.080 (0.038)
      P < 0.05.
      PCS score at enrollment−0.020 (0.007)
      P < 0.01.
      Variance components
       In intercept96.256
      P < 0.001.
      62.198
      P < 0.001.
       In linear slope0.753
      P < 0.001.
      0.625
      P < 0.001.
      Goodness-of-fit deviance (parameters estimated)11,768.510 (6)11,613.847 (17)
      Model comparison (x2)154.663 (11)
      P < 0.001.
      SE = standard error; SCQ = Self-Administered Comorbidity Questionnaire; PCS = Physical Component Summary.
      a P < 0.001.
      b P < 0.01.
      c P < 0.05.
      While a small sample-wide decline in PCS scores was found over time, there was a considerable interindividual variability in the intercept for physical function and moderate interindividual variability in the slope (Table 2). A spaghetti plot of a random 10% of the sample demonstrates the interindividual variability in PCS scores over the two cycles of chemotherapy (Fig. 1b). These results supported additional analyses of predictors of interindividual differences in initial levels as well as in the trajectories of PCS scores.

      Characteristics Associated With Interindividual Differences in Functional Status

      The second stage of the HLM analysis evaluated how the pattern of change over time in physical function varied based on demographic, clinical, and symptom characteristics. While 18 characteristics were associated with PCS score at enrollment in exploratory analyses (Supplementary Table 1), only nine characteristics were associated with PCS score at enrollment in the final HLM model (Table 2). Lower PCS scores at enrollment were associated with older age, greater comorbidity, being unemployed, lack of regular exercise, higher morning fatigue, lower evening energy, occurrence of pain, lower trait anxiety, and lower attentional function. Only higher morning fatigue (P = 0.04) and lower enrollment PCS score (P = 0.01) were associated with decrements in PCS score over time. Of note, neither the MAX2 index nor chemotherapy cycle length was associated with PCS scores at enrollment or with decrements in PCS scores over time.
      To illustrate the effects of each of these characteristics on patients' enrollment levels and trajectories of physical function, Fig. 2a–d display the adjusted change curves for PCS scores estimated based on differences in age (i.e., younger/older calculated based on one SD below and above the mean age), employment status, comorbidity score (i.e., lower/higher calculated based on one SD below and above the mean comorbidity score), and exercise status, respectively. Fig. 3a–e display the adjusted change curves for PCS scores based on differences in symptoms at enrollment: morning fatigue, evening energy, occurrence of pain, trait anxiety, and attentional function (i.e., lower/higher calculated based on one SD below and above the mean score for each symptom). Fig. 3f displays the adjusted change curve for physical function based on differences in PCS score at enrollment. All mean PCS scores for the various characteristics depicted in the figures are estimated or predicted means based on the HLM analyses.
      Figure thumbnail gr2
      Fig. 2Influence of a) age, b) employment status, c) Self-Administered Comorbidity Questionnaire score, and d) exercise on a regular basis at enrollment on interindividual differences in the intercept for physical function. In (a) and (c), values for one SD below and above the mean are plotted as examples. Patients were assessed six times over two cycles of chemotherapy: before chemotherapy administration (i.e., recovery from previous chemotherapy cycle; Assessments 1 and 4), approximately one week after chemotherapy administration (i.e., acute symptoms in the week after infusion; Assessments 2 and 5), and approximately two weeks after chemotherapy administration (i.e., potential nadir; Assessments 3 and 6).
      Figure thumbnail gr3
      Fig. 3Influence of symptoms including a) morning fatigue, b) evening energy, c) pain, d) trait anxiety, e) attentional function, and f) Physical Component Summary (PCS) score at enrollment on interindividual differences in the intercept for physical function. For morning fatigue and PCS score at enrollment, interindividual differences in the slope parameters for physical function are shown. In (f), values for one SD below and above the mean PCS score at enrollment are plotted as examples. Patients were assessed six times over two cycles of chemotherapy: before chemotherapy administration (i.e., recovery from previous chemotherapy cycle; Assessments 1 and 4), approximately one week after chemotherapy administration (i.e., acute symptoms in the week after infusion; Assessments 2 and 5), and approximately two weeks after chemotherapy administration (i.e., potential nadir; Assessments 3 and 6).

      Discussion

      In a large sample of older adults with cancer who were entering a second or subsequent cycle of chemotherapy, we identified numerous demographic (i.e., older age, not working), clinical (i.e., higher comorbidity, lack of regular exercise), and symptom characteristics (i.e., higher morning fatigue, lower evening energy, occurrence of pain, higher trait anxiety, lower attentional function) associated with lower levels of physical function at enrollment. By contrast, only morning fatigue and PCS scores at enrollment were associated with modest decrements in physical function over time. This study is the first to identify that higher level of morning fatigue was the only symptom associated with functional decline during chemotherapy. In addition, this study is the first to assess physical function at multiple time points over two cycles of chemotherapy in older adults and to analyze changes in physical function as a trajectory, rather than as a dichotomous outcome of functional decline between two time points. It should be noted that at enrollment, the mean PCS score for our sample was 4.2 points lower than the age-based normative score of 44.9 (adults aged 65 to 74 years) based on the 2001 Utah Health Status Survey.
      Office of Public Health Assessment
      Health Status in Utah: The Medical Outcomes Study SF-12 (2001 Utah Health Status Survey Report).
      Fatigue is one of the most common and distressing symptoms reported by patients with cancer and can result in decreased quality of life.
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      In this study, we identified that higher levels of morning fatigue was associated with modest decreases in physical function during chemotherapy. Specifically, as illustrated in Fig. 3a, the predicted mean PCS score for Assessment 1 (intercept) was 42.4 for patients with higher morning fatigue (one SD above the mean morning fatigue score) and 38.7 for patients with lower morning fatigue (one SD below the mean evening fatigue score). At Assessment 6, the predicted mean PCS score was 42.2 for patients with higher morning fatigue and 36.8 for patients with lower morning fatigue.
      In comparison, evening fatigue, morning energy, and evening energy were not associated with changes in physical function over time. Of note, both higher morning fatigue and lower evening energy were associated with lower levels of physical function at enrollment. This finding highlights the importance of assessing for diurnal variations in fatigue severity
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      In addition, research from our group demonstrated distinct characteristics associated with the trajectories of morning and evening fatigue and energy in patients with cancer,
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      supporting the need for comprehensive assessment of fatigue both in research and clinical care. Furthermore, management strategies for cancer-related fatigue, such as energy conservation and exercise,
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      may impact morning and evening fatigue differently. Therefore, morning and evening fatigue should be evaluated as distinct outcomes in addition to overall fatigue to determine how interventions modify each symptom.
      In a prior study of physical function among older adults with cancer receiving chemotherapy,
      • Kenis C.
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      no association was found between fatigue and functional decline. The lack of association between fatigue and functional decline in the prior study may be related to differences in the measurement of fatigue (single global measure using the Mobility-Tiredness Test vs. morning and evening fatigue and energy levels using the Lee Fatigue Scale in our study), measurement of physical function (change in ADL and IADL vs. PCS score in our study), and the timing of the assessments (two time points before treatment and at two to three months vs. six time points over two cycles of chemotherapy in our study). In another study of functional decline during first-line chemotherapy in older adults,
      • Hoppe S.
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      Functional decline in older patients with cancer receiving first-line chemotherapy.
      its association with fatigue was not evaluated. Therefore, our result warrants confirmation in future research to determine if improvements in morning fatigue may mitigate decrements in physical function.
      In addition, we found that lower physical function at enrollment (i.e., before next dose of chemotherapy) was associated with older age, greater comorbidity, being unemployed, lack of regular exercise, presence of pain, lower trait anxiety, and lower attentional function. While older age, greater comorbidity, and pain are risk factors for decrements in physical function,
      • Given B.
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      Physical functioning of elderly cancer patients prior to diagnosis and following initial treatment.
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      Comparison of changes in physical functioning of elderly patients with new diagnoses of cancer.
      • Vallerand A.H.
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      Factors that affect functional status in patients with cancer-related pain.
      unemployment and lack of regular exercise may reflect risk factors for and/or outcomes of poorer physical function. Interestingly, in our sample, higher trait anxiety, a disposition toward experiencing anxiety,
      • Elwood L.S.
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      • Olatunji B.O.
      Measurement of anxious traits: a contemporary review and synthesis.
      was associated with higher physical function scores at enrollment. Higher trait anxiety was associated with moderate intensity physical activity in a study of community-dwelling older adults,
      • Smith J.C.
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      • Motl R.W.
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      The Contributions of Self-efficacy, Trait Anxiety, and Fear of Falling to Physical Activity Behavior Among Residents of Continuing Care Retirement Communities.
      which supports our finding. While the association between lower attentional function and lower physical function suggests that both processes are interrelated,
      • Montero-Odasso M.
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      Mobility and cognition in seniors. Report from the 2008 Institute of Aging (CIHR) mobility and cognition workshop.
      further research is needed to understand how the two processes interact in older adults during cancer treatment.
      Consistent with a previous report,
      • Kenis C.
      • Decoster L.
      • Bastin J.
      • et al.
      Functional decline in older patients with cancer receiving chemotherapy: a multicenter prospective study.
      we did not identify an association between depression at enrollment and initial levels or trajectories of physical function in our sample of older adults with cancer. The proportion of patients reporting depressive symptoms in the previous report (20.6%)
      • Kenis C.
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      was similar to 25.1% in our study. These findings contrast with another study, where 44.5% of patients reported depressive symptoms and a positive association was found between depression and increased risk of functional decline after one cycle of first-line chemotherapy.
      • Hoppe S.
      • Rainfray M.
      • Fonck M.
      • et al.
      Functional decline in older patients with cancer receiving first-line chemotherapy.
      Additional research is needed to better characterize the association between depression and functional decline in older adults with cancer.
      While a previous study found that older adults receiving first-line chemotherapy for a new diagnosis of cancer were more likely to experience decline in IADL than those treated for progression/relapse,
      • Kenis C.
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      • Bastin J.
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      we did not detect any associations between time since cancer diagnosis or the number of prior cancer treatments and decrements in physical function in our sample. Because all our patients had received at least one cycle of chemotherapy within the four weeks before enrollment, patients treated for a new diagnosis may have already experienced some decrements in physical function before our assessments.
      Strengths of our study include the focused appraisal of physical function at multiple points over two cycles of chemotherapy, which allows for the examination of acute within-cycle changes in function that may occur as a result of toxicities immediately after chemotherapy infusion into nadir and recovery. While prior studies of physical function in older adults during chemotherapy have focused on changes after one cycle
      • Hoppe S.
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      • Fonck M.
      • et al.
      Functional decline in older patients with cancer receiving first-line chemotherapy.
      or several months after the initiation of chemotherapy,
      • Kenis C.
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      • Bastin J.
      • et al.
      Functional decline in older patients with cancer receiving chemotherapy: a multicenter prospective study.
      our study design allowed us to evaluate for acute changes in physical function within a chemotherapy cycle. In addition, we analyzed physical function over time as a trajectory, rather than a dichotomous outcome of functional decline between two time points. This approach allowed us to examine more subtle changes in physical function and evaluate for different possible trajectories (e.g., linear, quadratic).
      Our study has several limitations. First, while patients were uniformly assessed at three specific points (i.e., before chemotherapy administration and at approximately one and two weeks after administration) across two cycles of chemotherapy, they were recruited at various cycles in their chemotherapy treatment. As a result, changes in physical function from the initiation of chemotherapy cannot be evaluated in this study. In addition, because our study design may have excluded older adults who discontinued chemotherapy after their initial cycle(s) due to functional decline, our results may underestimate the true degree of functional decline in this population. Furthermore, additional common geriatric assessment domains such as nutrition
      • Mohile S.G.
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      and frailty
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      that could contribute to decrements in physical function were not assessed. Finally, physical function was not assessed using objective measures (e.g., gait speed) or assessments of ADL or IADL. However, the SF-12 PCS score is a valid and reliable measure of physical function that includes assessments of ability to perform moderate activities, climb stairs, and accomplish work and other activities.
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      Although the number of studies of serial comprehensive geriatric assessment during cancer treatment is increasing, the large number of studies that measure quality of life using instruments that include physical function subscales such as the SF-12, SF-36, and European Organization for Research and Treatment of Cancer QLQ-C30
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      provides additional opportunities to understand changes in physical function during cancer treatment.
      It is important to note that within the geriatric oncology literature, it is crucial to highlight analyses that include function as an outcome because functional outcomes are extremely important to older adults with cancer and are not assessed in many studies. Given the numerous studies that have used the SF-12 or SF-36, which closely overlaps other measures of physical function such as the Patient-Reported Outcomes Measurement Information System Physical Function item bank,
      • Rose M.
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      The PROMIS Physical Function item bank was calibrated to a standardized metric and shown to improve measurement efficiency.
      • Fries J.F.
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      secondary analyses of cancer studies with SF-12 or SF-36 data are important to suggest future directions for research.

      Conclusions

      This study is the first to identify morning fatigue as a potentially modifiable characteristic associated with decrements in physical function in older adults with cancer who were entering a second or subsequent cycle of chemotherapy. Interventions focused on improving morning fatigue may prevent functional decline in older adults receiving chemotherapy and should be studied. Because our study enrolled older adults who had already started their chemotherapy treatment, the current findings should be confirmed in patients who are assessed at the initiation of chemotherapy and followed through to treatment completion or discontinuation. Future studies need to investigate the impact of multiple co-occurring symptoms and symptom clusters on the trajectories of physical function during chemotherapy.

      Disclosures and Acknowledgments

      This study was funded by the National Cancer Institute (NCI; R01CA134900). Dr. Wong is supported by the National Institute on Aging (NIA; T32AG000212, R03AG056439, P30AG044281) and National Center for Advancing Translational Sciences (KL2TR001870). Dr. Ritchie is supported by the NIA (P30AG044281). Dr. Steinman is supported by the NIA (K24AG049057, P30AG044281). Dr. Walter is supported by the NIA (K24AG041180, P30AG044281). Dr. Miaskowski is supported by a grant from the American Cancer Society and NCI (K05CA168960). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH or the American Cancer Society.
      The authors have no conflicts of interest to report.

      Appendix

      Supplementary Table 1Characteristics Evaluated as Potential Predictors of Intercept and Linear Slope for Physical Function
      CharacteristicsInterceptLinear Slope
      Demographic characteristics
       Age
       Sex
       Ethnicity (white vs. nonwhite)
       Education
       Marital status
       Live alone
       Employment status
       Child care responsibilities
      Clinical characteristics
       Body mass index
       Current or former smoker
       Hemoglobin
       Karnofsky Performance Status score
       Self-Administered Comorbidity Questionnaire score
       Exercise on a regular basis
       Cancer type
       Time since cancer diagnosis
       Any prior cancer treatments
       Number of prior cancer treatments
       Presence of metastatic disease
       Number of metastatic sites including lymph node involvement
       Number of metastatic sites excluding lymph node involvement
       Chemotherapy MAX2 index
       Chemotherapy cycle length
      Symptom characteristics at enrollment
       Lee Fatigue Scale: morning fatigue score
       Lee Fatigue Scale: evening fatigue score
       Lee Fatigue Scale: morning energy score
       Lee Fatigue Scale: evening energy score
       General Sleep Disturbance Scale score
       Center for Epidemiological Studies–Depression Scale score
       Pain present
       State Anxiety score
       Trait Anxiety score
       Attentional Function Index score
       Physical Component Summary scoreN/A
      N/A = not applicable.
      ▪ = Characteristics with an absolute t-value ≥2.0 in bivariable exploratory analyses that advanced to testing in multivariable models.

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