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Figure 1.
CONSORT Flow Diagram for the COACH (Improving Communication in Older Cancer Patients and Their Caregivers) Trial of Practice Clusters, Oncologists, Patients, and Caregivers
CONSORT Flow Diagram for the COACH (Improving Communication in Older Cancer Patients and Their Caregivers) Trial of Practice Clusters, Oncologists, Patients, and Caregivers

Follow-up at 4 to 6 weeks included 472 patients, at 3 months included 410 patients, and at 6 months included 348 patients. Follow-up included 348 caregivers at 4 to 6 weeks, 306 caregivers at 3 months, and 261 caregivers at 6 months. HCCQ indicates Health Care Climate Questionnaire.

aClusters that maintained institutional review board (IRB) approval but never enrolled any participants.

bPractices are no longer associated with their respective National Cancer Institute Community Oncology Research Program (NCORP) affiliate or with the University of Rochester NCORP Research Base.

cSigned consent and participated in screening process.

dSatisfaction with communication about aging-related concerns.

eConversations about aging-related conditions during clinic visit.

fIrretrievable, site miscommunication, technical difficulty, or protocol violation.

Figure 2.
Patient and Caregiver Satisfaction
Patient and Caregiver Satisfaction

A, Patient satisfaction with communication about aging-related concerns. B, Patient satisfaction with overall care. C, Caregiver satisfaction with communication about the patient’s age-related conditions. Scores were derived using modified versions of the Health Care Climate Questionnaire. The telephone assessment was 7 to 14 days after the audio-recorded clinic visit.

Figure 3.
Conversations About Aging-Related Conditions
Conversations About Aging-Related Conditions

The patient’s visit with the oncologist within 4 weeks of completing the geriatric assessment (GA) was audiorecorded, transcribed, and coded. We used an open coding approach of themes and subthemes to quantify the number of age-related conversations, the number of aging-related discussions with high-quality communication, and the number of conversations of GA-driven recommendations communicated to patients by oncologists.

1.
Arora  NK, Street  RL  Jr, Epstein  RM, Butow  PN.  Facilitating patient-centered cancer communication: a road map.  Patient Educ Couns. 2009;77(3):319-321. doi:10.1016/j.pec.2009.11.003PubMedGoogle ScholarCrossref
2.
Street  RL  Jr, Elwyn  G, Epstein  RM.  Patient preferences and healthcare outcomes: an ecological perspective.  Expert Rev Pharmacoecon Outcomes Res. 2012;12(2):167-180. doi:10.1586/erp.12.3PubMedGoogle ScholarCrossref
3.
Epstein  RM, Duberstein  PR, Fenton  JJ,  et al.  Effect of a patient-centered communication intervention on oncologist-patient communication, quality of life, and health care utilization in advanced cancer: the VOICE randomized clinical trial.  JAMA Oncol. 2017;3(1):92-100.PubMedGoogle Scholar
4.
Bernacki  R, Hutchings  M, Vick  J,  et al.  Development of the Serious Illness Care Program: a randomised controlled trial of a palliative care communication intervention.  BMJ Open. 2015;5(10):e009032. doi:10.1136/bmjopen-2015-009032PubMedGoogle ScholarCrossref
5.
Paladino  J, Bernacki  R, Neville  BA,  et al.  Evaluating an intervention to improve communication between oncology clinicians and patients with life-limiting cancer: a cluster randomized clinical trial of the Serious Illness Care Program.  JAMA Oncol. 2019;5(6):801-809. doi:10.1001/jamaoncol.2019.0292PubMedGoogle ScholarCrossref
6.
DeSantis  CE, Miller  KD, Dale  W,  et al.  Cancer statistics for adults aged 85 years and older, 2019  [published online August 7, 2019].  CA Cancer J Clin. doi:10.3322/caac.21577PubMedGoogle Scholar
7.
Smith  BD, Smith  GL, Hurria  A, Hortobagyi  GN, Buchholz  TA.  Future of cancer incidence in the United States: burdens upon an aging, changing nation.  J Clin Oncol. 2009;27(17):2758-2765. doi:10.1200/JCO.2008.20.8983PubMedGoogle ScholarCrossref
8.
Mohile  SG, Xian  Y, Dale  W,  et al.  Association of a cancer diagnosis with vulnerability and frailty in older Medicare beneficiaries.  J Natl Cancer Inst. 2009;101(17):1206-1215. doi:10.1093/jnci/djp239PubMedGoogle ScholarCrossref
9.
Mohile  SG, Fan  L, Reeve  E,  et al.  Association of cancer with geriatric syndromes in older Medicare beneficiaries.  J Clin Oncol. 2011;29(11):1458-1464. doi:10.1200/JCO.2010.31.6695PubMedGoogle ScholarCrossref
10.
Hurria  A, Dale  W, Mooney  M,  et al; Cancer and Aging Research Group.  Designing therapeutic clinical trials for older and frail adults with cancer: U13 conference recommendations.  J Clin Oncol. 2014;32(24):2587-2594. doi:10.1200/JCO.2013.55.0418PubMedGoogle ScholarCrossref
11.
Mohile  SG, Dale  W, Somerfield  MR,  et al.  Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology.  J Clin Oncol. 2018;36(22):2326-2347. doi:10.1200/JCO.2018.78.8687PubMedGoogle ScholarCrossref
12.
Mohile  SG, Magnuson  A, Pandya  C,  et al.  Community oncologists’ decision-making for treatment of older patients with cancer.  J Natl Compr Canc Netw. 2018;16(3):301-309. doi:10.6004/jnccn.2017.7047PubMedGoogle ScholarCrossref
13.
Fenton  JJ, Jerant  AF, Bertakis  KD, Franks  P.  The cost of satisfaction: a national study of patient satisfaction, health care utilization, expenditures, and mortality.  Arch Intern Med. 2012;172(5):405-411. doi:10.1001/archinternmed.2011.1662PubMedGoogle ScholarCrossref
14.
Safran  DG, Karp  M, Coltin  K,  et al.  Measuring patients’ experiences with individual primary care physicians: results of a statewide demonstration project.  J Gen Intern Med. 2006;21(1):13-21. doi:10.1111/j.1525-1497.2005.00311.xPubMedGoogle ScholarCrossref
15.
Grunfeld  E, Fitzpatrick  R, Mant  D,  et al.  Comparison of breast cancer patient satisfaction with follow-up in primary care versus specialist care: results from a randomized controlled trial.  Br J Gen Pract. 1999;49(446):705-710.PubMedGoogle Scholar
16.
 Hospital value-based purchasing: biggest bonuses and penalties: CMS percentage change in reimbursement based on process performance and patient satisfaction.  Mod Healthc. 2013;43(1):34.PubMedGoogle Scholar
17.
Mann  RK, Siddiqui  Z, Kurbanova  N, Qayyum  R.  Effect of HCAHPS reporting on patient satisfaction with physician communication.  J Hosp Med. 2016;11(2):105-110. doi:10.1002/jhm.2490PubMedGoogle ScholarCrossref
18.
Mariano  C, Hanson  LC, Deal  AM,  et al.  Healthcare satisfaction in older and younger patients with cancer.  J Geriatr Oncol. 2016;7(1):32-38. doi:10.1016/j.jgo.2015.11.005PubMedGoogle ScholarCrossref
19.
Institute of Medicine.  Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis. Washington, DC: National Academies Press; 2013.
20.
Nekhlyudov  L, Levit  L, Hurria  A, Ganz  PA.  Patient-centered, evidence-based, and cost-conscious cancer care across the continuum: translating the Institute of Medicine report into clinical practice.  CA Cancer J Clin. 2014;64(6):408-421. doi:10.3322/caac.21249PubMedGoogle ScholarCrossref
21.
Hurria  A, Naylor  M, Cohen  HJ.  Improving the quality of cancer care in an aging population: recommendations from an IOM report.  JAMA. 2013;310(17):1795-1796. doi:10.1001/jama.2013.280416PubMedGoogle ScholarCrossref
22.
Hurria  A, Levit  LA, Dale  W,  et al; American Society of Clinical Oncology.  Improving the evidence base for treating older adults with cancer: American Society of Clinical Oncology statement.  J Clin Oncol. 2015;33(32):3826-3833. doi:10.1200/JCO.2015.63.0319PubMedGoogle ScholarCrossref
23.
Mohile  SG, Hurria  A, Cohen  HJ,  et al.  Improving the quality of survivorship for older adults with cancer.  Cancer. 2016;122(16):2459-2568. doi:10.1002/cncr.30053PubMedGoogle ScholarCrossref
24.
Magnuson  A, Allore  H, Cohen  HJ,  et al.  Geriatric assessment with management in cancer care: current evidence and potential mechanisms for future research.  J Geriatr Oncol. 2016;7(4):242-248. doi:10.1016/j.jgo.2016.02.007PubMedGoogle ScholarCrossref
25.
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(24):2595-2603. doi:10.1200/JCO.2013.54.8347PubMedGoogle ScholarCrossref
26.
Fried  TR, Bradley  EH, Towle  VR, Allore  H.  Understanding the treatment preferences of seriously ill patients.  N Engl J Med. 2002;346(14):1061-1066. doi:10.1056/NEJMsa012528PubMedGoogle ScholarCrossref
27.
Wildiers  H, Mauer  M, Pallis  A,  et al.  End points and trial design in geriatric oncology research: a joint European Organisation for Research and Treatment of Cancer–Alliance for Clinical Trials in Oncology–International Society Of Geriatric Oncology position article.  J Clin Oncol. 2013;31(29):3711-3718. doi:10.1200/JCO.2013.49.6125PubMedGoogle ScholarCrossref
28.
Mohile  S, Dale  W, Hurria  A.  Geriatric oncology research to improve clinical care.  Nat Rev Clin Oncol. 2012;9(10):571-578. doi:10.1038/nrclinonc.2012.125PubMedGoogle ScholarCrossref
29.
Hamaker  ME, Te Molder  M, Thielen  N, van Munster  BC, Schiphorst  AH, van Huis  LH.  The effect of a geriatric evaluation on treatment decisions and outcome for older cancer patients—a systematic review.  J Geriatr Oncol. 2018;9(5):430-440. doi:10.1016/j.jgo.2018.03.014PubMedGoogle ScholarCrossref
30.
Caillet  P, Canoui-Poitrine  F, Vouriot  J,  et al.  Comprehensive geriatric assessment in the decision-making process in elderly patients with cancer: ELCAPA study.  J Clin Oncol. 2011;29(27):3636-3642. doi:10.1200/JCO.2010.31.0664PubMedGoogle ScholarCrossref
31.
Ramsdale  E, Lemelman  T, Loh  KP,  et al.  Geriatric assessment-driven polypharmacy discussions between oncologists, older patients, and their caregivers.  J Geriatr Oncol. 2018;9(5):534-539. doi:10.1016/j.jgo.2018.02.007PubMedGoogle ScholarCrossref
32.
Lowenstein  LM, Volk  RJ, Street  R,  et al.  Communication about geriatric assessment domains in advanced cancer settings: “missed opportunities”.  J Geriatr Oncol. 2019;10(1):68-73. doi:10.1016/j.jgo.2018.05.014PubMedGoogle ScholarCrossref
33.
Mohile  S, Dale  W, Magnuson  A, Kamath  N, Hurria  A.  Research priorities in geriatric oncology for 2013 and beyond.  Cancer Forum. 2013;37(3):216-221.PubMedGoogle Scholar
34.
Campbell  MK, Piaggio  G, Elbourne  DR, Altman  DG; CONSORT Group.  Consort 2010 statement: extension to cluster randomised trials.  BMJ. 2012;345:e5661. doi:10.1136/bmj.e5661PubMedGoogle Scholar
35.
Hurria  A, Gupta  S, Zauderer  M,  et al.  Developing a cancer-specific geriatric assessment: a feasibility study.  Cancer. 2005;104(9):1998-2005. doi:10.1002/cncr.21422PubMedGoogle ScholarCrossref
36.
Mohile  SG, Velarde  C, Hurria  A,  et al.  Geriatric assessment-guided care processes for older adults: a Delphi consensus of geriatric oncology experts.  J Natl Compr Canc Netw. 2015;13(9):1120-1130. doi:10.6004/jnccn.2015.0137PubMedGoogle ScholarCrossref
37.
Kehoe  LA, Xu  H, Duberstein  P,  et al.  Quality of life of caregivers of older patients with advanced cancer.  J Am Geriatr Soc. 2019;67(5):969-977. doi:10.1111/jgs.15862PubMedGoogle ScholarCrossref
38.
Hurria  A, Wildes  T, Blair  SL,  et al.  Senior adult oncology, version 2.2014: clinical practice guidelines in oncology.  J Natl Compr Canc Netw. 2014;12(1):82-126. doi:10.6004/jnccn.2014.0009PubMedGoogle ScholarCrossref
39.
Vallerand  RJ, O’Connor  BP, Blais  MR.  Life satisfaction of elderly individuals in regular community housing, in low-cost community housing, and high and low self-determination nursing homes.  Int J Aging Hum Dev. 1989;28(4):277-283. doi:10.2190/JQ0K-D0GG-WLQV-QMBNPubMedGoogle ScholarCrossref
40.
Fiscella  K, Franks  P, Srinivasan  M, Kravitz  RL, Epstein  R.  Ratings of physician communication by real and standardized patients.  Ann Fam Med. 2007;5(2):151-158. doi:10.1370/afm.643PubMedGoogle ScholarCrossref
41.
Shumway  D, Griffith  KA, Jagsi  R, Gabram  SG, Williams  GC, Resnicow  K.  Psychometric properties of a brief measure of autonomy support in breast cancer patients.  BMC Med Inform Decis Mak. 2015;15:51. doi:10.1186/s12911-015-0172-4PubMedGoogle ScholarCrossref
42.
Hsieh  HF, Shannon  SE.  Three approaches to qualitative content analysis.  Qual Health Res. 2005;15(9):1277-1288. doi:10.1177/1049732305276687PubMedGoogle ScholarCrossref
43.
Epstein  RM, Franks  P, Fiscella  K,  et al.  Measuring patient-centered communication in patient-physician consultations: theoretical and practical issues.  Soc Sci Med. 2005;61(7):1516-1528. doi:10.1016/j.socscimed.2005.02.001PubMedGoogle ScholarCrossref
44.
Cella  DF, Tulsky  DS, Gray  G,  et al.  The Functional Assessment of Cancer Therapy scale: development and validation of the general measure.  J Clin Oncol. 1993;11(3):570-579. doi:10.1200/JCO.1993.11.3.570PubMedGoogle ScholarCrossref
45.
Ware  J  Jr, Kosinski  M, Keller  SDA.  A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity.  Med Care. 1996;34(3):220-233. doi:10.1097/00005650-199603000-00003PubMedGoogle ScholarCrossref
46.
Given  CW, Given  B, Stommel  M, Collins  C, King  S, Franklin  S.  The caregiver reaction assessment (CRA) for caregivers to persons with chronic physical and mental impairments.  Res Nurs Health. 1992;15(4):271-283. doi:10.1002/nur.4770150406PubMedGoogle ScholarCrossref
47.
Hurria  A, Mohile  S, Gajra  A,  et al.  Validation of a prediction tool for chemotherapy toxicity in older adults with cancer.  J Clin Oncol. 2016;34(20):2366-2371. doi:10.1200/JCO.2015.65.4327PubMedGoogle ScholarCrossref
48.
van Buuren  S.  Multiple imputation of discrete and continuous data by fully conditional specification.  Stat Methods Med Res. 2007;16(3):219-242. doi:10.1177/0962280206074463PubMedGoogle ScholarCrossref
49.
Curran  D, Molenberghs  G, Thijs  H, Verbeke  G.  Sensitivity analysis for pattern mixture models.  J Biopharm Stat. 2004;14(1):125-143. doi:10.1081/BIP-120028510PubMedGoogle ScholarCrossref
50.
Bleustein  C, Rothschild  DB, Valen  A, Valatis  E, Schweitzer  L, Jones  R.  Wait times, patient satisfaction scores, and the perception of care.  Am J Manag Care. 2014;20(5):393-400.PubMedGoogle Scholar
51.
Ehlers  AP, Khor  S, Cizik  AM,  et al.  Use of patient-reported outcomes and satisfaction for quality assessments.  Am J Manag Care. 2017;23(10):618-622.PubMedGoogle Scholar
52.
Tsai  TC, Orav  EJ, Jha  AK.  Patient satisfaction and quality of surgical care in US hospitals.  Ann Surg. 2015;261(1):2-8. doi:10.1097/SLA.0000000000000765PubMedGoogle ScholarCrossref
53.
Will  KK, Johnson  ML, Lamb  G.  Team-based care and patient satisfaction in the hospital setting: a systematic review.  J Patient Cent Res Rev. 2019;6(2):158-171. doi:10.17294/2330-0698.1695PubMedGoogle ScholarCrossref
54.
Brown  H, Prescott  R. Applied Mixed Models in Medicine. 2nd ed. Edinburgh, UK: John Wiley & Sons, Ltd; 2006.
55.
Kenward  MG, Roger  JH.  Small sample inference for fixed effects from restricted maximum likelihood.  Biometrics. 1997;53(3):983-997. doi:10.2307/2533558PubMedGoogle ScholarCrossref
56.
Loh  KP, Mohile  SG, Epstein  RM,  et al.  Willingness to bear adversity and beliefs about the curability of advanced cancer in older adults.  Cancer. 2019;125(14):2506-2513. doi:10.1002/cncr.32074PubMedGoogle ScholarCrossref
57.
Loh  KP, Mohile  SG, Lund  JL,  et al.  Beliefs about advanced cancer curability in older patients, their caregivers, and oncologists.  Oncologist. 2019;24(6):e292-e302. doi:10.1634/theoncologist.2018-0890PubMedGoogle ScholarCrossref
58.
Guetterman  TC, Fetters  MD, Creswell  JW.  Integrating quantitative and qualitative results in health science mixed methods research through joint displays.  Ann Fam Med. 2015;13(6):554-561. doi:10.1370/afm.1865PubMedGoogle ScholarCrossref
59.
Singh  H, Beaver  JA, Kim  G, Pazdur  R.  Enrollment of older adults on oncology trials: an FDA perspective.  J Geriatr Oncol. 2017;8(3):149-150. doi:10.1016/j.jgo.2016.11.001PubMedGoogle ScholarCrossref
60.
Puts  MT, Santos  B, Hardt  J,  et al.  An update on a systematic review of the use of geriatric assessment for older adults in oncology.  Ann Oncol. 2014;25(2):307-315. doi:10.1093/annonc/mdt386PubMedGoogle ScholarCrossref
61.
Karuturi  M, Wong  ML, Hsu  T,  et al.  Understanding cognition in older patients with cancer.  J Geriatr Oncol. 2016;7(4):258-269. doi:10.1016/j.jgo.2016.04.004PubMedGoogle ScholarCrossref
62.
Detmar  SB, Muller  MJ, Schornagel  JH, Wever  LD, Aaronson  NK.  Health-related quality-of-life assessments and patient-physician communication: a randomized controlled trial.  JAMA. 2002;288(23):3027-3034. doi:10.1001/jama.288.23.3027PubMedGoogle ScholarCrossref
63.
Clayton  JM, Butow  PN, Tattersall  MH,  et al.  Randomized controlled trial of a prompt list to help advanced cancer patients and their caregivers to ask questions about prognosis and end-of-life care.  J Clin Oncol. 2007;25(6):715-723. doi:10.1200/JCO.2006.06.7827PubMedGoogle ScholarCrossref
64.
Basch  E, Deal  AM, Kris  MG,  et al.  Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial.  J Clin Oncol. 2016;34(6):557-565. doi:10.1200/JCO.2015.63.0830PubMedGoogle ScholarCrossref
65.
Corre  R, Greillier  L, Le Caër  H,  et al.  Use of a comprehensive geriatric assessment for the management of elderly patients with advanced non-small-cell lung cancer: the phase III randomized ESOGIA-GFPC-GECP 08-02 study.  J Clin Oncol. 2016;34(13):1476-1483. doi:10.1200/JCO.2015.63.5839PubMedGoogle ScholarCrossref
66.
Bakitas  M, Lyons  KD, Hegel  MT,  et al.  Effects of a palliative care intervention on clinical outcomes in patients with advanced cancer: the Project ENABLE II randomized controlled trial.  JAMA. 2009;302(7):741-749. doi:10.1001/jama.2009.1198PubMedGoogle ScholarCrossref
67.
Hahn  S, Puffer  S, Torgerson  DJ, Watson  J.  Methodological bias in cluster randomised trials.  BMC Med Res Methodol. 2005;5:10. doi:10.1186/1471-2288-5-10PubMedGoogle ScholarCrossref
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    Original Investigation
    November 7, 2019

    Communication With Older Patients With Cancer Using Geriatric Assessment: A Cluster-Randomized Clinical Trial From the National Cancer Institute Community Oncology Research Program

    Author Affiliations
    • 1Department of Medicine, University of Rochester, Rochester, New York
    • 2University of Rochester Cancer Center National Cancer Institute Community Oncology Research Program Research Base, Rochester, New York
    • 3Department of Family Medicine, University of Rochester, Rochester, New York
    • 4Department of Medical Oncology, City of Hope National Medical Center, Duarte, California
    • 5Department of Surgery, University of Rochester, Rochester, New York
    • 6Stakeholders for Care in Oncology and Research for our Elders, Rochester, New York
    • 7Department of Health Behavior, Society, and Policy, Rutgers University School of Public Health, Piscataway, New Jersey
    • 8Department of Health Services Research, University of Texas MD Anderson Cancer Center, Houston
    • 9University of Rochester School of Nursing, Rochester, New York
    • 10Novant Health Oncology Specialists, Winston-Salem, North Carolina
    • 11Southeast Clinical Oncology Research Consortium National Cancer Institute Community Oncology Research Program, Winston-Salem, North Carolina
    • 12Heartland Cancer Research National Cancer Institute Community Oncology Research Program, Decatur, Illinois
    • 13Metro Minnesota Community Oncology Research Program, St Louis Park
    • 14Department of Medicine, University of Chicago, Chicago, Illinois
    • 15Department of Supportive Care, City of Hope National Medical Center, Duarte, California
    JAMA Oncol. Published online November 7, 2019. doi:https://doi.org/10.1001/jamaoncol.2019.4728
    Key Points

    Question  Does providing a summary of geriatric assessment results and geriatric assessment–guided recommendations to oncologists improve communication about aging-related concerns?

    Findings  In this nationwide cluster-randomized clinical trial of 31 community oncology practices that enrolled 541 older patients with advanced cancer, providing a geriatric assessment summary with recommendations to oncologists improved postvisit patient satisfaction and caregiver satisfaction and increased the number of conversations about aging-related concerns. These results were significantly different between the intervention and usual care groups.

    Meaning  Integrating geriatric assessment into community oncology care improves patient and caregiver satisfaction and communication about aging-related concerns.

    Abstract

    Importance  Older patients with cancer and their caregivers worry about the effects of cancer treatment on aging-related domains (eg, function and cognition). Quality conversations with oncologists about aging-related concerns could improve patient-centered outcomes. A geriatric assessment (GA) can capture evidence-based aging-related conditions associated with poor clinical outcomes (eg, toxic effects) for older patients with cancer.

    Objective  To determine whether providing a GA summary and GA-guided recommendations to oncologists can improve communication about aging-related concerns.

    Design, Setting, and Participants  This cluster-randomized clinical trial enrolled 541 participants from 31 community oncology practices within the University of Rochester National Cancer Institute Community Oncology Research Program from October 29, 2014, to April 28, 2017. Patients were aged 70 years or older with an advanced solid malignant tumor or lymphoma who had at least 1 impaired GA domain; patients chose 1 caregiver to participate. The primary outcome was assessed on an intent-to-treat basis.

    Interventions  Oncology practices were randomized to receive either a tailored GA summary with recommendations for each enrolled patient (intervention) or alerts only for patients meeting criteria for depression or cognitive impairment (usual care).

    Main Outcomes and Measures  The predetermined primary outcome was patient satisfaction with communication about aging-related concerns (modified Health Care Climate Questionnaire [score range, 0-28; higher scores indicate greater satisfaction]), measured after the first oncology visit after the GA. Secondary outcomes included the number of aging-related concerns discussed during the visit (from content analysis of audiorecordings), quality of life (measured with the Functional Assessment of Cancer Therapy scale for patients and the 12-Item Short Form Health Survey for caregivers), and caregiver satisfaction with communication about aging-related patient concerns.

    Results  A total of 541 eligible patients (264 women, 276 men, and 1 patient did not provide data; mean [SD] age, 76.6 [5.2] years) and 414 caregivers (310 women, 101 men, and 3 caregivers did not provide data; mean age, 66.5 [12.5] years) were enrolled. Patients in the intervention group were more satisfied after the visit with communication about aging-related concerns (difference in mean score, 1.09 points; 95% CI, 0.05-2.13 points; P = .04); satisfaction with communication about aging-related concerns remained higher in the intervention group over 6 months (difference in mean score, 1.10; 95% CI, 0.04-2.16; P = .04). There were more aging-related conversations in the intervention group’s visits (difference, 3.59; 95% CI, 2.22-4.95; P < .001). Caregivers in the intervention group were more satisfied with communication after the visit (difference, 1.05; 95% CI, 0.12-1.98; P = .03). Quality of life outcomes did not differ between groups.

    Conclusions and Relevance  Including GA in oncology clinical visits for older adults with advanced cancer improves patient-centered and caregiver-centered communication about aging-related concerns.

    Trial Registration  ClinicalTrials.gov identifier: NCT02107443

    Introduction

    Patient-centered communication promotes high-quality conversations prioritizing patient and caregiver concerns so that decisions are aligned with their preferences and values. Effective communication is characterized by (1) informed and participatory patients and caregivers; (2) informed, receptive, and patient-centered clinicians; and (3) a health care system providing well-organized and responsive services that are tailored to patients’ and caregivers’ needs.1,2 Although studies have demonstrated benefits for interventions that facilitate oncologist-patient communication,3-5 these interventions were not tailored to address aging-related concerns of older adults receiving cancer treatment and their caregivers.

    Older adults represent most patients with advanced cancer seen in community oncology practices.6,7 Cancer treatment choices for older adults with aging-related conditions (ie, disability, comorbidity, and geriatric syndromes)8,9 are based on extrapolations of evidence derived from clinical trials that enroll younger patients or fit older adults.10 Many older adults have unidentified, uncommunicated, and therefore unaddressed aging-related conditions that are associated with morbidity and early mortality.11 A communication intervention for oncologists who care primarily for older adults—yet lack aging-related expertise—could improve patient and caregiver satisfaction by bringing attention to often-overlooked aging-related conditions.12 Despite controversy,13 satisfaction with physician communication is considered a metric for quality of health care and even modest improvements in survey scores are linked to increased reimbursement.14-18

    To address a “cancer care delivery system in crisis,”19(p1) the National Academy of Medicine (formally the Institute of Medicine),20,21 the American Society of Clinical Oncology (ASCO),22 the Cancer and Aging Research Group,10,23,24 and the International Society of Geriatric Oncology,25 have all called for improved care delivery that attends to aging-related conditions of older adults with cancer. A key component is geriatric assessment (GA), which uses validated patient-reported and objective measures to capture domains important to older adults such as function (ie, ability to remain independent) and cognition. As highlighted in a recent ASCO guideline,11 older adults and caregivers value these GA domains,26,27 and GA domains, when formally assessed, influence treatment decision-making.11,12,28-30 However, aging-related concerns are rarely addressed in oncology care, especially outside specialized academic settings.12,31,32

    To our knowledge, this study is the first randomized clinical trial evaluating whether GA can meaningfully influence oncology care processes for vulnerable older adults with advanced cancer. With outcome measure selection guided by input from older patients and caregivers,23,33 we hypothesized that providing GA information to oncologists would improve patient satisfaction with communication about aging-related concerns by increasing the number and quality of conversations during oncology clinic visits.

    Methods
    Overview

    In this cluster-randomized clinical trial, Improving Communication in Older Cancer Patients and Their Caregivers (COACH), community oncology practices were randomized to the intervention or usual care group (CONSORT diagram in Figure 1 and trial protocol in Supplement 1).34 We enrolled participants from October 29, 2014, to April 28, 2017. The University of Rochester and all participating sites obtained approval from their institutional review boards. Participants provided written informed consent.

    Settings and Participants

    We recruited community oncology practices within the University of Rochester National Cancer Institute Community Oncology Research Program (NCORP) Research Base network. Oncologists enrolled as participants12; only patients of enrolled oncologists were eligible to participate. Other patient eligibility criteria included aged 70 years or older, at least 1 GA domain impairment,11,25,35-37 an advanced solid tumor or lymphoma, cancer treatment with palliative intent, planned oncology visits for at least 3 months, ability to provide informed consent independently or via a health care proxy, and an understanding of English. Eligible patients chose 1 caregiver aged 21 years or older. Patients with no eligible caregivers could still enroll in the study.

    Study Groups

    All patients underwent a GA that evaluated 8 domains—functional status, physical performance, comorbidity, polypharmacy, cognition, nutrition, psychological health, and social support.11,25,35-37 The GA was mostly patient reported.37 Trained coordinators (J.G.) completed the objective performance and cognitive measures. At practices that were randomized to the intervention group, coordinators entered the GA scores into a locked web-based folder (http://www.mycarg.org) that created a tailored GA summary that was printed out for each patient. The summary included information on GA domain impairments and GA-guided recommendations based on literature review,11 guidelines,38 and expert consensus.36 As an example, the summary would include information that a patient recently fell, that falls increase the risk of chemotherapy toxic effects, and a recommendation for physical therapy to prevent falls.36 The summary and recommendations were provided to oncologists once prior to an audiorecorded clinic visit. At study entry, oncologists received a brief training about GA and were told that they had autonomy for if and how they wished to use GA for their enrolled patients. For the usual care group, oncologists were alerted only if patients had abnormal scores on depression and cognitive tests.

    Data Collection and Outcome Measures

    In both groups, 1 oncology clinic visit within 4 weeks of GA was audiorecorded and transcribed. Within 7 to 14 days of this visit, trained personnel called the patient to assess satisfaction with communication. During the telephone call, the patients completed 2 versions of the Health Care Climate Questionnaire (HCCQ).39,40 The first version measures satisfaction with patient-centered physician communication, such as whether the patient feels that the physician understands her or his perspective and encourages participation in decisions (score range, 0-20; higher scores indicate greater satisfaction). Similar to other research,41 the second version of the HCCQ modified the language of the questions in the HCCQ to address satisfaction with communication regarding aging-related concerns (HCCQ-age; score range, 0-28); this modified version of the HCCQ was designed with input from advocates who were not enrolled in the trial and was used for the primary outcome (eAppendix in Supplement 2).

    A secondary outcome included the number of aging-related concerns discussed at the visit. With experts and 4 coders, a content analysis framework42 outlined how to identify aging-related conversations, assess their quality (whether a concern was acknowledged and further explored by the oncologist), and determine whether an acknowledged concern motivated recommendations for specific GA-guided interventions.3,11,31,32,36,43 Team coding of the transcribed audiorecordings occurred until interrater reliability42 was 70% or greater. Subsequently, for each transcript, coding was performed independently by 2 trained coders, with 20% of transcripts coded by all 4 coders. Final interrater reliability was 82% for number of concerns and 92% for both quality and interventions.

    Other secondary outcomes evaluated patient and caregiver quality of life (QoL) as well as caregiver satisfaction with communication. Patients completed the Functional Assessment of Cancer Therapy scale44 at enrollment and 4 to 6 weeks, 3 months, and 6 months later. Caregiver QoL was assessed using the 12-Item Short Form Survey45 and burden was assessed using the Caregiver Reaction Assessment46 at the same time points as patients. Caregivers completed HCCQ surveys that assessed their satisfaction with communication about their concerns related to the patient’s aging-related conditions and overall care (score range for both surveys, 0-20).

    Randomization and Blinding

    Accrual records from University of Rochester NCORP studies were used to stratify practice clusters as large or small accruing sites to assure balance in randomization. Randomization was done at the practice cluster level and recruitment of all participants was based on the group to which their practice cluster was assigned. Other than the statisticians, all investigators were blinded to group; blinding was preserved among the telephone team, transcriptionists, and coders.

    Sample Size

    Sample size and power considerations were based on the primary aim of the HCCQ-age to address patient satisfaction with communication about aging-related concerns. This design had 80% power at the 0.05 significance level to detect a difference of 1.3 in HCCQ-age scores, with an intraclass correlation coefficient (ICC) of 0.14,3,32 corresponding to an effect size of 0.62. Assuming a withdrawal rate of 5% (based on observational cohort data47), the targeted accrual was 528 patients. The design had 80% power at the 0.05 significance level to detect a difference of 0.46 in the number of conversations about aging-related concerns, with an ICC of 0.12, corresponding to an effect size of 0.59.32 We originally aimed for participation by 16 NCORP practices. Because the recruitment was initially slower than anticipated, we allowed more practices to participate (as specified by the trial protocol in Supplement 1). The total patient sample size did not change.

    Statistical Analysis

    Descriptive statistics were used to evaluate demographics, GA results, and clinical information, and bivariate analyses were performed to compare between- group differences in characteristics of patients and caregivers. For the primary outcome, to follow the intent-to-treat principle and to assess the effect of missing values on the study results, we conducted additional analyses including all randomized eligible patients. Under missing at random assumptions, we evaluated the influence of missing data on the study results via multiple imputation.48 The examination of the reasons for missing data did not reveal any reason to suspect a missing not at random mechanism. Nevertheless, we also applied sensitivity analysis using pattern mixture models.49 Similar to prior research,50,51 we conducted responder analyses evaluating the proportion of participants who reported satisfaction scores within a half SD of the HCCQ score from the perfect score; achieving a perfect satisfaction score is commonly advocated as a metric for high quality in practice.52,53

    Because of the cluster-randomized study design, a linear mixed model method was applied.54 The outcome was the response, and the group was the fixed effect. Practices were entered as a random effect independent of residual error. Estimation was performed using restricted maximum likelihood, and the null hypothesis of zero mean difference between groups was tested using an F test.55 The results are presented as means (or mean difference) adjusted for the practice effect and evaluated as marginal means from the linear mixed model. Practice differences were assessed graphically using best linear unbiased predictors of the mean response for each.

    To assess the effect of the intervention on the outcomes over time, we used a longitudinal linear mixed model. An unstructured correlation matrix was used for the repeated measures from the same participant. The model was adjusted for practice cluster using a random effect independent of the within-participant random effects, and it was fit via restricted maximum likelihood.

    Every effort was made to facilitate participants’ completion of questionnaires. However, baseline data from some participants were missing, and there was participant withdrawal (Figure 1); anticipating that some patients would not be able to be reached by telephone, the protocol allowed for imputation of the 4- to 6-week HCCQ results to assess the primary aim. Analysis was performed with SAS, version 9.4 (SAS Institute Inc) and R, version 3.5.2 (R Foundation for Statistical Computing) software. All P values were from 2-sided tests, and the results were deemed statistically significant at P < .05.

    Results
    Participant Characteristics

    From October 29, 2014, to April 28, 2017, 31 practice clusters (17 intervention and 14 usual care) enrolled participants, including 131 oncologists, 541 eligible patients, and 414 eligible caregivers (Figure 1). Patients had a mean (SD) age of 76.6 (5.2) years (range, 70-96 years), and 264 (48.8%) were women; most patients had gastrointestinal and lung cancers (278 [51.4%]) and were receiving chemotherapy (369 [68.2%]) (eTable 1 in Supplement 2). There were no essential differences in demographics or clinical characteristics by group. Most patients had 2 or more GA domain impairments (mean [SD], 4.5 [1.5]); the prevalence of GA domain impairments ranged from 93.7% (n = 507) for physical performance to 25.1% (n = 136) for psychological status; 180 patients (33.3%) had possible cognitive impairment. A total of 487 of 541 patients (90.0%) had 3 or more GA domain impairments. More patients in the usual care group had impaired physical performance (239 of 248 [96.4%] vs 268 of 293 [91.5%]; P = .03) and social support (82 of 248 [33.1%] vs 74 of 293 [25.3%]; P = .05) (eFigure in Supplement 2). Caregivers (n = 414; mean [SD] age, 66.5 [12.5] years; range, 26-92 years) were most likely to be the patient’s spouse or partner (276 [66.7%]; eTable 2 in Supplement 2) and 310 [74.9%] were women. Baseline data for oncologists,12 patients,37,56,57 and caregivers37,56,57 have been published.

    Patient Satisfaction With Communication

    For 509 evaluable patients, the mean (SE) satisfaction score for communication about aging-related concerns was 22.8 (0.27) (range, 5-28 for HCCQ-age) after the clinic visit. The score in the intervention group was 1.09 points higher than in the usual care group (95% CI, 0.05-2.13; P = .04; ICC = 0.02). After the clinic visit, the mean (SE) satisfaction score for communication about overall care was 17.4 (0.16) (range, 5-20 for HCCQ). The proportion of patients within a half SD from a perfect score was higher in the intervention group (109 of 271 [40.2%] vs 71 of 238 [29.8%]). Over 6 months, patients in the intervention group were more satisfied with communication about aging-related concerns (difference in mean HCCQ-age score, 1.10; 95% CI, 0.04-2.16; P = .04) (Figure 2A) and reported greater satisfaction with overall care (difference in mean HCCQ score, 0.70; 95% CI, 0.06-1.25; P = .03) (Figure 2B).

    Number and Quality of Conversations About Aging-Related Concerns

    For 528 evaluable patients, the adjusted mean (SE) number of conversations about aging-related concerns during the oncology clinic visit was 6.34 (0.48) (range, 0-18). There was an adjusted mean of 8.02 conversations in the intervention group compared with 4.43 in usual care (difference, 3.59; 95% CI, 2.22-4.95; P < .001; ICC = 0.14; Figure 3). The intervention group had an adjusted mean of 4.60 high-quality conversations, compared with 2.59 in the usual care group (difference, 2.01 [adjusted by practice site]; 95% CI, 1.20-2.77; P < .001; ICC = 0.06). There was an adjusted mean of 3.20 conversations about recommendations in the intervention group compared with 1.14 in the usual care group (difference, 2.06; 95% CI, 0.99-3.12; P < .001; ICC = 0.30). eTable 3 in Supplement 2 is a joint display58 illustrating exemplar quotes with mean conversation numbers by domain.

    Patients’ and Caregivers’ Health-Related Quality of Life

    Analyses did not detect any statistically significant differences between groups in Functional Assessment of Cancer Therapy scale score for patients over 6 months (range, 23-108; difference [SE], −0.23 [1.03]; P = .82). In addition, there were no differences for caregiver 12-Item Short Form Survey total scores or Caregiver Reaction Assessment subscales.

    Caregiver Satisfaction With Communication

    At 4 to 6 weeks after the clinic visit, caregivers in the intervention group were more satisfied with their communication regarding their concerns about the patients’ aging-related conditions (range, 5-20; difference, 1.05; 95% CI, 0.12-1.98; P = .03). The proportion of caregivers within a half SD of a perfect score was higher in the intervention group (74 of 189 [39.2%] vs 42 of 158 [26.6%]). Caregivers were more satisfied with their own communication with oncologists with regard to overall care (range, 2-20; difference, 1.34; 95% CI, 0.50-2.18; P = .004). The differences in satisfaction scores were not significant when analyzed over 6 months (Figure 2C).

    Discussion

    The COACH cluster-randomized clinical trial is the first large multisite intervention study to demonstrate that providing a GA summary with GA-guided recommendations to community oncologists facilitates communication about aging-related concerns and improves patient and caregiver satisfaction with communication and care. COACH enrolled vulnerable older patients with cancer who had significant aging-related conditions—90% had 3 or more GA domain impairments. These patients represent less-fit individuals for whom there is limited evidence for the risks and benefits of cancer treatment,59 yet these patients are commonly seen in real-world community practices. Although patients had various cancer types, all were incurable and were treated with palliative intent.

    Evidence increasingly supports the use of GA for evaluation and management of older patients with cancer to guide shared decision-making between older patients, caregivers, and oncologists.11,25 As highlighted in the ASCO geriatric oncology guidelines11 and supported by systematic reviews,29,60 GA impairments are associated with chemotherapy toxic effects, lower treatment completion, functional decline, early mortality, and higher health care use. Like others, we found that older patients with a high prevalence of GA domain impairments still receive treatment for advanced cancer, including chemotherapy. Of particular concern is the one-third of patients who had positive screening results for possible cognitive impairment, given the limited evidence for the safety and efficacy of chemotherapy in this group.61 The higher prevalence of GA domain impairments compared with other trials reflects our expanded eligibility criteria and our use of a formal GA to evaluate often overlooked aging-related conditions.

    Despite patient and caregiver concerns and preferences for maintaining function and cognition,26,27 oncologists often do not discuss implications of aging-related conditions or inform older patients and caregivers of heightened risk of adverse events from treatment.32 We found that, when GA information was provided, community oncologists used it in communication during the clinic visit, similar to other nongeriatric studies that have systematically provided symptom and QoL information to oncologists.62,63 Our results align with this research showing that coordinated care for younger patients that captures patient-reported outcomes improves quality of care and outcomes; for older patients with cancer, personalized care requires attention to aging-related conditions.

    We recruited older patients who had several different cancers and treatments, which may have limited our ability to detect QoL effects. In addition, the intervention provided a GA summary during 1 clinic visit only to oncologists; studies that have reported survival and QoL benefits from structured interventions have incorporated evaluation and management of patient-reported outcomes over time64 or have used geriatrics-trained professionals.29,64 A randomized study of GA-directed therapy for older patients with advanced lung cancer demonstrated reduced toxic effects of treatment and less treatment discontinuation in the GA group owing to improved treatment allocation.65 Several ongoing clinical trials will evaluate if GA can help improve clinical outcomes (QoL, toxic effects, and survival) of patients through improved decision-making and GA-guided interventions.11

    A previous study using baseline COACH data reported that an increasing number of patient GA domain impairments is associated with poor caregiver emotional health and QoL.37 Similar to early palliative care models that used specialized nurse coaches to assess and provide management for patients and caregivers, GA-based interventions could be adapted for both patients and caregivers.66

    Strengths and Limitations

    Strengths of this study include recruitment of a large sample of vulnerable older patients and their caregivers who have rarely been included in cancer trials. This study also demonstrates the ability to conduct multisite trials incorporating GA in the community oncology setting. We attribute our successful completion of the trial in large part to our patient and caregiver research advocate partners from Scoreboard (Stakeholders for Care in Oncology and Research for our Elders) who provided ongoing input and solutions for barriers.23,33

    Limitations include risk of selection bias, as we enrolled a specific population of older patients; however, these are patients who are commonly seen in community oncology clinics and are underrepresented in research. Although cluster randomization is a strength, since we were testing a model of care as an intervention, there is a risk of selection bias inherent in cluster randomization.67 Oncologists in both groups were not blinded, and thus may have modified their discussions of aging; however, the strength of the findings shows that modifying oncologist behavior to increase communication about aging-related concerns is possible.

    Conclusions

    To our knowledge, the COACH cluster-randomized clinical trial is the first trial to demonstrate that provision of a formal GA to community oncologists, per ASCO guidelines,11 can improve satisfaction and communication for vulnerable older patients with advanced cancer and their caregivers. COACH demonstrated that a practical and convenient GA summary with recommendations for aging-sensitive interventions improves patient-centered outcomes and thus should be considered as the standard of care for older patients with cancer.

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    Article Information

    Accepted for Publication: August 22, 2019.

    Published Online: November 7, 2019. doi:10.1001/jamaoncol.2019.4728

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Mohile SG et al. JAMA Oncology.

    Corresponding Author: Supriya G. Mohile, MD, MS, Department of Medicine, University of Rochester, 601 Elmwood Ave, PO Box 704, Rochester, NY 14642 (supriya_mohile@urmc.rochester.edu).

    Author Contributions: Dr Mohile had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Mohile, Hurria, Heckler, Canin, Duberstein, Plumb, Mustian, Hopkins, Dale.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Mohile, Hurria, Heckler, Canin, Xu, Janelsins, Kleckner, Mustian, Hopkins, Dale.

    Critical revision of the manuscript for important intellectual content: Mohile, Epstein, Heckler, Culakova, Duberstein, Gilmore, Xu, Plumb, Wells, Lowenstein, Flannery, Janelsins, Magnuson, Loh, Kleckner, Mustian, Hopkins, Liu, Geer, Gorawara-Bhat, Morrow, Dale.

    Statistical analysis: Mohile, Hurria, Heckler, Culakova, Xu, Wells.

    Obtained funding: Mohile, Hurria, Morrow, Dale.

    Administrative, technical, or material support: Mohile, Hurria, Gilmore, Xu, Plumb, Wells, Lowenstein, Flannery, Magnuson, Loh, Kleckner, Morrow, Dale.

    Supervision: Mohile, Janelsins, Magnuson, Mustian, Morrow, Dale.

    Conflict of Interest Disclosures: Dr Mohile reported receiving a grant from the National Cancer Institute (NCI) and a contract from the Patient-Centered Outcomes Research Institute (PCORI) during the conduct of the study; and receiving grants from Carevive outside the submitted work. Dr Epstein reported receiving grants from NCI and American Cancer Society during the conduct of the study. Dr Hurria reported receiving a contract from PCORI during the conduct of the study; and consulting payments from Celgene, Novartis, GSK, Boehringer Ingelheim, Carevive, Sanofi, GTx Inc, Pierian Biosciences, and MJH Healthcare Holdings LLC outside the submitted work. Dr Canin reported receiving personal fees from the University of Rochester during the conduct of the study. Dr Culakova reported receiving a grant from NCI and a contract from PCORI during the conduct of the study. Dr Gilmore reported receiving grants from the University of Rochester during the conduct of the study. Ms Plumb reported receiving grants from the University of Rochester during the conduct of the study. Dr Lowenstein reported receiving a contract from PCORI during the conduct of the study. Dr Flannery reported receiving a contract from PCORI and a grant from NCI during the conduct of the study. Dr Magnuson reported receiving grants from the University of Rochester during the conduct of the study. Dr Kleckner reported receiving grants from NCI during the conduct of the study. Dr Morrow reported receiving a grant from NCI and a contract from PCORI during the conduct of the study; and grants from NCI outside the submitted work. No other disclosures were reported.

    Funding/Support: This study was partially funded by the Patient-Centered Outcomes Research Institute (contract CD-12-11-4634 to Dr Mohile). Support also came from the National Institute of Aging grant R21/R33AG059206 (Drs Mohile, Hurria, and Dale), National Cancer Institute grant UG1CA189961 (Drs Mustian and Morrow), National Cancer Institute grant R25CA102618 (Drs Janelsins and Morrow), and National Institute of Aging grant K24AG056589 (Dr Mohile).

    Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Disclaimer: The information presented in this manuscript is solely the responsibility of the author(s) and does not necessarily represent the views of the PCORI, its Board of Governors, or Methodology Committee. All information and materials published in the primary manuscript are original.

    Data Sharing Statement: See Supplement 3.

    Additional Contributions: We thank all the patients and caregivers of SCOREboard: Beverly Canin (Chair), Mary Whitehead, Margaret Sedenquist, Lorraine Griggs, Lynn Finch, John Aarne, Valerie Targia, Robert Harrison (deceased), Valerie Aarne, Dorothy Dobson, Jacquelyn Dobson, Burt Court, Polly Hudson, and Ray Hutchins (deceased). Susan Rosenthal, MD, University of Rochester Cancer Center National Cancer Institute Community Oncology Research Program Research Base, provided editing. Joseph J. Guido, MS, and Javier Bautista, MS, MBA, University of Rochester Cancer Center National Cancer Institute Community Oncology Research Program Research Base, assisted with data management. Dr Rosenthal, Mr Guido, and Mr Bautista were compensated for their contributions.

    Additional Information: Dr Hurria is deceased. Full protocol is available through University of Rochester NCORP: https://urcc-ccop.com/ccop/.

    References
    1.
    Arora  NK, Street  RL  Jr, Epstein  RM, Butow  PN.  Facilitating patient-centered cancer communication: a road map.  Patient Educ Couns. 2009;77(3):319-321. doi:10.1016/j.pec.2009.11.003PubMedGoogle ScholarCrossref
    2.
    Street  RL  Jr, Elwyn  G, Epstein  RM.  Patient preferences and healthcare outcomes: an ecological perspective.  Expert Rev Pharmacoecon Outcomes Res. 2012;12(2):167-180. doi:10.1586/erp.12.3PubMedGoogle ScholarCrossref
    3.
    Epstein  RM, Duberstein  PR, Fenton  JJ,  et al.  Effect of a patient-centered communication intervention on oncologist-patient communication, quality of life, and health care utilization in advanced cancer: the VOICE randomized clinical trial.  JAMA Oncol. 2017;3(1):92-100.PubMedGoogle Scholar
    4.
    Bernacki  R, Hutchings  M, Vick  J,  et al.  Development of the Serious Illness Care Program: a randomised controlled trial of a palliative care communication intervention.  BMJ Open. 2015;5(10):e009032. doi:10.1136/bmjopen-2015-009032PubMedGoogle ScholarCrossref
    5.
    Paladino  J, Bernacki  R, Neville  BA,  et al.  Evaluating an intervention to improve communication between oncology clinicians and patients with life-limiting cancer: a cluster randomized clinical trial of the Serious Illness Care Program.  JAMA Oncol. 2019;5(6):801-809. doi:10.1001/jamaoncol.2019.0292PubMedGoogle ScholarCrossref
    6.
    DeSantis  CE, Miller  KD, Dale  W,  et al.  Cancer statistics for adults aged 85 years and older, 2019  [published online August 7, 2019].  CA Cancer J Clin. doi:10.3322/caac.21577PubMedGoogle Scholar
    7.
    Smith  BD, Smith  GL, Hurria  A, Hortobagyi  GN, Buchholz  TA.  Future of cancer incidence in the United States: burdens upon an aging, changing nation.  J Clin Oncol. 2009;27(17):2758-2765. doi:10.1200/JCO.2008.20.8983PubMedGoogle ScholarCrossref
    8.
    Mohile  SG, Xian  Y, Dale  W,  et al.  Association of a cancer diagnosis with vulnerability and frailty in older Medicare beneficiaries.  J Natl Cancer Inst. 2009;101(17):1206-1215. doi:10.1093/jnci/djp239PubMedGoogle ScholarCrossref
    9.
    Mohile  SG, Fan  L, Reeve  E,  et al.  Association of cancer with geriatric syndromes in older Medicare beneficiaries.  J Clin Oncol. 2011;29(11):1458-1464. doi:10.1200/JCO.2010.31.6695PubMedGoogle ScholarCrossref
    10.
    Hurria  A, Dale  W, Mooney  M,  et al; Cancer and Aging Research Group.  Designing therapeutic clinical trials for older and frail adults with cancer: U13 conference recommendations.  J Clin Oncol. 2014;32(24):2587-2594. doi:10.1200/JCO.2013.55.0418PubMedGoogle ScholarCrossref
    11.
    Mohile  SG, Dale  W, Somerfield  MR,  et al.  Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology.  J Clin Oncol. 2018;36(22):2326-2347. doi:10.1200/JCO.2018.78.8687PubMedGoogle ScholarCrossref
    12.
    Mohile  SG, Magnuson  A, Pandya  C,  et al.  Community oncologists’ decision-making for treatment of older patients with cancer.  J Natl Compr Canc Netw. 2018;16(3):301-309. doi:10.6004/jnccn.2017.7047PubMedGoogle ScholarCrossref
    13.
    Fenton  JJ, Jerant  AF, Bertakis  KD, Franks  P.  The cost of satisfaction: a national study of patient satisfaction, health care utilization, expenditures, and mortality.  Arch Intern Med. 2012;172(5):405-411. doi:10.1001/archinternmed.2011.1662PubMedGoogle ScholarCrossref
    14.
    Safran  DG, Karp  M, Coltin  K,  et al.  Measuring patients’ experiences with individual primary care physicians: results of a statewide demonstration project.  J Gen Intern Med. 2006;21(1):13-21. doi:10.1111/j.1525-1497.2005.00311.xPubMedGoogle ScholarCrossref
    15.
    Grunfeld  E, Fitzpatrick  R, Mant  D,  et al.  Comparison of breast cancer patient satisfaction with follow-up in primary care versus specialist care: results from a randomized controlled trial.  Br J Gen Pract. 1999;49(446):705-710.PubMedGoogle Scholar
    16.
     Hospital value-based purchasing: biggest bonuses and penalties: CMS percentage change in reimbursement based on process performance and patient satisfaction.  Mod Healthc. 2013;43(1):34.PubMedGoogle Scholar
    17.
    Mann  RK, Siddiqui  Z, Kurbanova  N, Qayyum  R.  Effect of HCAHPS reporting on patient satisfaction with physician communication.  J Hosp Med. 2016;11(2):105-110. doi:10.1002/jhm.2490PubMedGoogle ScholarCrossref
    18.
    Mariano  C, Hanson  LC, Deal  AM,  et al.  Healthcare satisfaction in older and younger patients with cancer.  J Geriatr Oncol. 2016;7(1):32-38. doi:10.1016/j.jgo.2015.11.005PubMedGoogle ScholarCrossref
    19.
    Institute of Medicine.  Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis. Washington, DC: National Academies Press; 2013.
    20.
    Nekhlyudov  L, Levit  L, Hurria  A, Ganz  PA.  Patient-centered, evidence-based, and cost-conscious cancer care across the continuum: translating the Institute of Medicine report into clinical practice.  CA Cancer J Clin. 2014;64(6):408-421. doi:10.3322/caac.21249PubMedGoogle ScholarCrossref
    21.
    Hurria  A, Naylor  M, Cohen  HJ.  Improving the quality of cancer care in an aging population: recommendations from an IOM report.  JAMA. 2013;310(17):1795-1796. doi:10.1001/jama.2013.280416PubMedGoogle ScholarCrossref
    22.
    Hurria  A, Levit  LA, Dale  W,  et al; American Society of Clinical Oncology.  Improving the evidence base for treating older adults with cancer: American Society of Clinical Oncology statement.  J Clin Oncol. 2015;33(32):3826-3833. doi:10.1200/JCO.2015.63.0319PubMedGoogle ScholarCrossref
    23.
    Mohile  SG, Hurria  A, Cohen  HJ,  et al.  Improving the quality of survivorship for older adults with cancer.  Cancer. 2016;122(16):2459-2568. doi:10.1002/cncr.30053PubMedGoogle ScholarCrossref
    24.
    Magnuson  A, Allore  H, Cohen  HJ,  et al.  Geriatric assessment with management in cancer care: current evidence and potential mechanisms for future research.  J Geriatr Oncol. 2016;7(4):242-248. doi:10.1016/j.jgo.2016.02.007PubMedGoogle ScholarCrossref
    25.
    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(24):2595-2603. doi:10.1200/JCO.2013.54.8347PubMedGoogle ScholarCrossref
    26.
    Fried  TR, Bradley  EH, Towle  VR, Allore  H.  Understanding the treatment preferences of seriously ill patients.  N Engl J Med. 2002;346(14):1061-1066. doi:10.1056/NEJMsa012528PubMedGoogle ScholarCrossref
    27.
    Wildiers  H, Mauer  M, Pallis  A,  et al.  End points and trial design in geriatric oncology research: a joint European Organisation for Research and Treatment of Cancer–Alliance for Clinical Trials in Oncology–International Society Of Geriatric Oncology position article.  J Clin Oncol. 2013;31(29):3711-3718. doi:10.1200/JCO.2013.49.6125PubMedGoogle ScholarCrossref
    28.
    Mohile  S, Dale  W, Hurria  A.  Geriatric oncology research to improve clinical care.  Nat Rev Clin Oncol. 2012;9(10):571-578. doi:10.1038/nrclinonc.2012.125PubMedGoogle ScholarCrossref
    29.
    Hamaker  ME, Te Molder  M, Thielen  N, van Munster  BC, Schiphorst  AH, van Huis  LH.  The effect of a geriatric evaluation on treatment decisions and outcome for older cancer patients—a systematic review.  J Geriatr Oncol. 2018;9(5):430-440. doi:10.1016/j.jgo.2018.03.014PubMedGoogle ScholarCrossref
    30.
    Caillet  P, Canoui-Poitrine  F, Vouriot  J,  et al.  Comprehensive geriatric assessment in the decision-making process in elderly patients with cancer: ELCAPA study.  J Clin Oncol. 2011;29(27):3636-3642. doi:10.1200/JCO.2010.31.0664PubMedGoogle ScholarCrossref
    31.
    Ramsdale  E, Lemelman  T, Loh  KP,  et al.  Geriatric assessment-driven polypharmacy discussions between oncologists, older patients, and their caregivers.  J Geriatr Oncol. 2018;9(5):534-539. doi:10.1016/j.jgo.2018.02.007PubMedGoogle ScholarCrossref
    32.
    Lowenstein  LM, Volk  RJ, Street  R,  et al.  Communication about geriatric assessment domains in advanced cancer settings: “missed opportunities”.  J Geriatr Oncol. 2019;10(1):68-73. doi:10.1016/j.jgo.2018.05.014PubMedGoogle ScholarCrossref
    33.
    Mohile  S, Dale  W, Magnuson  A, Kamath  N, Hurria  A.  Research priorities in geriatric oncology for 2013 and beyond.  Cancer Forum. 2013;37(3):216-221.PubMedGoogle Scholar
    34.
    Campbell  MK, Piaggio  G, Elbourne  DR, Altman  DG; CONSORT Group.  Consort 2010 statement: extension to cluster randomised trials.  BMJ. 2012;345:e5661. doi:10.1136/bmj.e5661PubMedGoogle Scholar
    35.
    Hurria  A, Gupta  S, Zauderer  M,  et al.  Developing a cancer-specific geriatric assessment: a feasibility study.  Cancer. 2005;104(9):1998-2005. doi:10.1002/cncr.21422PubMedGoogle ScholarCrossref
    36.
    Mohile  SG, Velarde  C, Hurria  A,  et al.  Geriatric assessment-guided care processes for older adults: a Delphi consensus of geriatric oncology experts.  J Natl Compr Canc Netw. 2015;13(9):1120-1130. doi:10.6004/jnccn.2015.0137PubMedGoogle ScholarCrossref
    37.
    Kehoe  LA, Xu  H, Duberstein  P,  et al.  Quality of life of caregivers of older patients with advanced cancer.  J Am Geriatr Soc. 2019;67(5):969-977. doi:10.1111/jgs.15862PubMedGoogle ScholarCrossref
    38.
    Hurria  A, Wildes  T, Blair  SL,  et al.  Senior adult oncology, version 2.2014: clinical practice guidelines in oncology.  J Natl Compr Canc Netw. 2014;12(1):82-126. doi:10.6004/jnccn.2014.0009PubMedGoogle ScholarCrossref
    39.
    Vallerand  RJ, O’Connor  BP, Blais  MR.  Life satisfaction of elderly individuals in regular community housing, in low-cost community housing, and high and low self-determination nursing homes.  Int J Aging Hum Dev. 1989;28(4):277-283. doi:10.2190/JQ0K-D0GG-WLQV-QMBNPubMedGoogle ScholarCrossref
    40.
    Fiscella  K, Franks  P, Srinivasan  M, Kravitz  RL, Epstein  R.  Ratings of physician communication by real and standardized patients.  Ann Fam Med. 2007;5(2):151-158. doi:10.1370/afm.643PubMedGoogle ScholarCrossref
    41.
    Shumway  D, Griffith  KA, Jagsi  R, Gabram  SG, Williams  GC, Resnicow  K.  Psychometric properties of a brief measure of autonomy support in breast cancer patients.  BMC Med Inform Decis Mak. 2015;15:51. doi:10.1186/s12911-015-0172-4PubMedGoogle ScholarCrossref
    42.
    Hsieh  HF, Shannon  SE.  Three approaches to qualitative content analysis.  Qual Health Res. 2005;15(9):1277-1288. doi:10.1177/1049732305276687PubMedGoogle ScholarCrossref
    43.
    Epstein  RM, Franks  P, Fiscella  K,  et al.  Measuring patient-centered communication in patient-physician consultations: theoretical and practical issues.  Soc Sci Med. 2005;61(7):1516-1528. doi:10.1016/j.socscimed.2005.02.001PubMedGoogle ScholarCrossref
    44.
    Cella  DF, Tulsky  DS, Gray  G,  et al.  The Functional Assessment of Cancer Therapy scale: development and validation of the general measure.  J Clin Oncol. 1993;11(3):570-579. doi:10.1200/JCO.1993.11.3.570PubMedGoogle ScholarCrossref
    45.
    Ware  J  Jr, Kosinski  M, Keller  SDA.  A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity.  Med Care. 1996;34(3):220-233. doi:10.1097/00005650-199603000-00003PubMedGoogle ScholarCrossref
    46.
    Given  CW, Given  B, Stommel  M, Collins  C, King  S, Franklin  S.  The caregiver reaction assessment (CRA) for caregivers to persons with chronic physical and mental impairments.  Res Nurs Health. 1992;15(4):271-283. doi:10.1002/nur.4770150406PubMedGoogle ScholarCrossref
    47.
    Hurria  A, Mohile  S, Gajra  A,  et al.  Validation of a prediction tool for chemotherapy toxicity in older adults with cancer.  J Clin Oncol. 2016;34(20):2366-2371. doi:10.1200/JCO.2015.65.4327PubMedGoogle ScholarCrossref
    48.
    van Buuren  S.  Multiple imputation of discrete and continuous data by fully conditional specification.  Stat Methods Med Res. 2007;16(3):219-242. doi:10.1177/0962280206074463PubMedGoogle ScholarCrossref
    49.
    Curran  D, Molenberghs  G, Thijs  H, Verbeke  G.  Sensitivity analysis for pattern mixture models.  J Biopharm Stat. 2004;14(1):125-143. doi:10.1081/BIP-120028510PubMedGoogle ScholarCrossref
    50.
    Bleustein  C, Rothschild  DB, Valen  A, Valatis  E, Schweitzer  L, Jones  R.  Wait times, patient satisfaction scores, and the perception of care.  Am J Manag Care. 2014;20(5):393-400.PubMedGoogle Scholar
    51.
    Ehlers  AP, Khor  S, Cizik  AM,  et al.  Use of patient-reported outcomes and satisfaction for quality assessments.  Am J Manag Care. 2017;23(10):618-622.PubMedGoogle Scholar
    52.
    Tsai  TC, Orav  EJ, Jha  AK.  Patient satisfaction and quality of surgical care in US hospitals.  Ann Surg. 2015;261(1):2-8. doi:10.1097/SLA.0000000000000765PubMedGoogle ScholarCrossref
    53.
    Will  KK, Johnson  ML, Lamb  G.  Team-based care and patient satisfaction in the hospital setting: a systematic review.  J Patient Cent Res Rev. 2019;6(2):158-171. doi:10.17294/2330-0698.1695PubMedGoogle ScholarCrossref
    54.
    Brown  H, Prescott  R. Applied Mixed Models in Medicine. 2nd ed. Edinburgh, UK: John Wiley & Sons, Ltd; 2006.
    55.
    Kenward  MG, Roger  JH.  Small sample inference for fixed effects from restricted maximum likelihood.  Biometrics. 1997;53(3):983-997. doi:10.2307/2533558PubMedGoogle ScholarCrossref
    56.
    Loh  KP, Mohile  SG, Epstein  RM,  et al.  Willingness to bear adversity and beliefs about the curability of advanced cancer in older adults.  Cancer. 2019;125(14):2506-2513. doi:10.1002/cncr.32074PubMedGoogle ScholarCrossref
    57.
    Loh  KP, Mohile  SG, Lund  JL,  et al.  Beliefs about advanced cancer curability in older patients, their caregivers, and oncologists.  Oncologist. 2019;24(6):e292-e302. doi:10.1634/theoncologist.2018-0890PubMedGoogle ScholarCrossref
    58.
    Guetterman  TC, Fetters  MD, Creswell  JW.  Integrating quantitative and qualitative results in health science mixed methods research through joint displays.  Ann Fam Med. 2015;13(6):554-561. doi:10.1370/afm.1865PubMedGoogle ScholarCrossref
    59.
    Singh  H, Beaver  JA, Kim  G, Pazdur  R.  Enrollment of older adults on oncology trials: an FDA perspective.  J Geriatr Oncol. 2017;8(3):149-150. doi:10.1016/j.jgo.2016.11.001PubMedGoogle ScholarCrossref
    60.
    Puts  MT, Santos  B, Hardt  J,  et al.  An update on a systematic review of the use of geriatric assessment for older adults in oncology.  Ann Oncol. 2014;25(2):307-315. doi:10.1093/annonc/mdt386PubMedGoogle ScholarCrossref
    61.
    Karuturi  M, Wong  ML, Hsu  T,  et al.  Understanding cognition in older patients with cancer.  J Geriatr Oncol. 2016;7(4):258-269. doi:10.1016/j.jgo.2016.04.004PubMedGoogle ScholarCrossref
    62.
    Detmar  SB, Muller  MJ, Schornagel  JH, Wever  LD, Aaronson  NK.  Health-related quality-of-life assessments and patient-physician communication: a randomized controlled trial.  JAMA. 2002;288(23):3027-3034. doi:10.1001/jama.288.23.3027PubMedGoogle ScholarCrossref
    63.
    Clayton  JM, Butow  PN, Tattersall  MH,  et al.  Randomized controlled trial of a prompt list to help advanced cancer patients and their caregivers to ask questions about prognosis and end-of-life care.  J Clin Oncol. 2007;25(6):715-723. doi:10.1200/JCO.2006.06.7827PubMedGoogle ScholarCrossref
    64.
    Basch  E, Deal  AM, Kris  MG,  et al.  Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial.  J Clin Oncol. 2016;34(6):557-565. doi:10.1200/JCO.2015.63.0830PubMedGoogle ScholarCrossref
    65.
    Corre  R, Greillier  L, Le Caër  H,  et al.  Use of a comprehensive geriatric assessment for the management of elderly patients with advanced non-small-cell lung cancer: the phase III randomized ESOGIA-GFPC-GECP 08-02 study.  J Clin Oncol. 2016;34(13):1476-1483. doi:10.1200/JCO.2015.63.5839PubMedGoogle ScholarCrossref
    66.
    Bakitas  M, Lyons  KD, Hegel  MT,  et al.  Effects of a palliative care intervention on clinical outcomes in patients with advanced cancer: the Project ENABLE II randomized controlled trial.  JAMA. 2009;302(7):741-749. doi:10.1001/jama.2009.1198PubMedGoogle ScholarCrossref
    67.
    Hahn  S, Puffer  S, Torgerson  DJ, Watson  J.  Methodological bias in cluster randomised trials.  BMC Med Res Methodol. 2005;5:10. doi:10.1186/1471-2288-5-10PubMedGoogle ScholarCrossref
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