Cancer in the aging population: Individualizing pretreatment assessment

Transcription

1 Cancer in the aging population: Individualizing pretreatment assessment Heidi D. Klepin, MD, MS Associate Professor of Internal Medicine, Section on Hematology and Oncology

2 Financial Disclosure(s) I have not had any relevant financial relations during the past 12 months to disclose.

3 Off-Label Use Disclosure(s) I do not intend to discuss an off-label use of a product during this activity.

4 Outline Background on cancer and aging Who cares and why The problem of individualized decision-making Evidence is lacking Utility of geriatric assessment to predict chemotherapy toxicity and mortality Highlights from available studies Next steps How can we use this information to improve outcomes for older patients? I have no conflicts of interest to disclose

5 The cancer care delivery system is in a crisis Factors contributing to the crisis: Complexity of care Work force shortages Limitations in tools for improving quality The aging population Reliance on family caregivers/direct care workers Rising cost of cancer care Adapted from: IOM report on Delivering High-Quality Cancer Care: charting a new course for a system in crisis, fall 2013

6 Cancer patients are older adults 70% 60% 50% 47% 53% 68% 41% 59% 40% 30% 32% Age < 65 Age 65 20% 10% 0% Cancer Diagnoses Cancer Deaths Cancer Survivors SEER Stat Fact Sheets: All Sites, NCI, 2012 ;Estimated U.S. Cancer Prevalence Counts: Method, NCI, 2013 Deaths: Leading Causes for 2009, NVSS, 2012

7 Older adults will keep getting older 75+ cohort is growing

8 There is little evidence to guide management decisions Older adults are under-represented on cancer clinical trials Example: only 30% of patients on registration trials 65 yrs Older adults on clinical trials are often not representative of those seen in practice Clinical trial patients A patient seen in practice 1.Hurria et al. J Clin Oncol June 10; 30 (17): Lewis et al. J Clin Oncol April 1; 21 (7):

9 Yet every patient deserves individualized information to inform any decision Will I tolerate and benefit from treatment? FIT VULNERABLE FRAIL Similar tolerance/benefit as middle-aged patients Decreased treatment tolerance Poor treatment tolerance

10 Treatment Decision The black box Characteristics of Tumor -Aggressive vs. indolent Characteristics of Treatment - Efficacy vs. Toxicity Characteristics of Patient - Life Expectancy - Reserve Capacity - Values Oncology training has historically been tumor centric

11 The complexity of aging complicates treatment of older cancer patients Comorbidity Cognitive Function Psychological Health Physical Function Nutrition Treatment Outcomes Social Support

12 Oncology tools to assess reserve capacity are inadequate 381 older cancer patients with ECOG 0-1 9% 38% ADL Disability IADL disability No Disability Repetto et al. J Clin Oncol 2002

13 Geriatric Assessment (i.e. a really good history and physical) may improve assessment of reserve capacity Parameter Assessment/Measure Physical Function Self reported ADLs, IADLs, mobility Objectively measured walking speed, grip strength Performance status Cognitive Function Cognition screens Capacity assessment Comorbidity Number of conditions/burden Compensated versus uncompenstated Individual conditions Socioeconomic issues Social support (caregivers, transportation) Income Psychological state Depression, distress, anxiety Geriatric Syndromes Dementia, delirium, falls, FTT Polypharmacy Number of medications, high risk meds Nutrition Weight loss, BMI, access to nutritional support

14 Predicting treatment tolerance Which characteristics matter most?

15 Can geriatric assessment predict chemotherapy toxicity in older adults? National multi-site study (N=500) Patients with any cancer type, age 65 years starting new chemotherapy regimen Geriatric assessment performed prior to start of chemotherapy Primary outcome: grade 3-5 toxicity during treatment Hurria et al. J Clin Oncol Sep 1;29(25):

16 Toxicity is common among older adults receiving chemotherapy Mean age 73 (range 65-91) 90% KPS>70 61% advanced disease Most common cancerslung, GI, GYN, breast 70% polychemotherapy 76% standard doses Majority (53%) experienced significant toxicity 12% 39% no severe toxicity grade 3 grade 4 grade 5

17 Geriatric assessment components: making it simple for oncology Domain Measures Physical Function Activities of Daily Living (ADLs) Instrumental Activities of Daily Living (IADLs) KPS(patient + physician rated) Number of Falls in Last 6 Months Get up and Go Test Comorbidity Cognition Social Functioning Social Support Psychological Nutrition Physical Health Section (OARS), self-reported Blessed Orientation-Memory-Concentration Test (Blessed-OMC) Medical Outcomes Survey (MOS) Social Activity Limitations Measure MOS Social Support Survey Hospital Anxiety and Depression Scale (HADS) Body Mass Index % Unintentional Weight Loss in the Last 6 Months Hurria et al. Cancer 2005, JCO 2011

18 Risk factors for Gr. 3-5 Toxicity OR (95% CI) Score Age 73 yrs 1.8 ( ) 2 GI/GU cancer 2.2 ( ) 3 Standard dose versus attenuated 2.1 ( ) 3 Poly-chemotherapy versus mono 1.8 ( ) 2 Hemoglobin (male: <11, female: <10) 2.2 ( ) 3 Creatinine Clearance 2.5 ( ) 3 1 or more falls in last 6 months 2.3 ( ) 3 Hearing impairment (fair or worse) 1.6 ( ) 2 Limited in walking 1 block (MOS) 1.8 ( ) 2 Assistance required in medication intake 1.4 ( ) 1 Decreased social activity (MOS) 1.3 ( ) 1 Range 0-25 Hurria et al. JCO 2011

19 Grade 3-5 Toxicities Prevalence of Toxicity by Score: More risk factors=higher toxicity 100% 80% 60% Low 27% (0 to 5) Mid 53% (6 to 11) 63% 76% High 83% ( 12) 92% 40% 45% 20% 21% 31% 0% 0 to to 8 9 to to N=39 N=64 N=161 N=123 N=50 N=36 Total Score Hurria et al. JCO 2011

20 Grade 3-5 toxicity Geriatric assessment improves risk stratification for chemotherapy toxicity MD-rated Karnofsky Performance Status Geriatric Assessment Score Low Mid High Low Mid High 83% 50% 51% 62% 53% 27% p< p< Hurria et al. JCO 2011

21 Refining the assessment for practical application: A web based risk assessment tool* Hurria et al. Cancer and Aging Research Group (CARG) *Validation in progress

22 Web based risk assessment tool Online risk calculator available from the Cancer and Aging Research Group at

23 Prevalence chemo toxicity Prevalence chemo toxicity Geriatric assessment adds value in oncology care: Building the evidence Multi-site study (N=518) to predict chemotherapy toxicity for cancer patients 70 years of age starting chemotherapy (CRASH) Hematologic Toxicity Non-hematologic Toxicity Score Score On-line risk calculator available through Moffitt Senior Adult Oncology Program Extermann et al. Cancer 2011

24 Looking for signals across studies to predict vulnerability to toxicity Study (N) Physical Limitations Sensory Impairment Hurria (500) Cognitive Impairment Depressive Symptoms Nutrition Extermann (518) N/A Aparacio Colon (123) Freyer Ovarian (83) Hamaker Breast (73) Polypharmacy N/A N/A N/A N/A Conclusions: Measures of physical function are the most consistent predictor of toxicity across studies (most common strategy is IADL assessment). Cumulative deficits matter

25 Predicting mortality

26 Predictors of early death (<6 months) with first line chemotherapy Multi-site observational study (N=348) Eligibility: age 70 years, first line chemotherapy, any stage, excluded breast Outcome: death within 6 months of treatment Patient characteristics assessed Function Cognition Depression Nutrition Comorbidity Pretreatment GA measures ADL, IADL, Timed Get Up and Go [GUG] Mini-mental state exam (MMSE) Geriatric depression scale (GDS) Mini-nutritional assessment (MNA) Cumulative illness rating scale (CIRSG) Soubeyran et al. J Clin Oncol 2011

27 Results: Who are these patients? Mean age 77 65% advanced disease 91% ECOG 0-2 Outcome: 16% died within 6 months 32% 31% 37% Colon/Stomach Lymphoma Lung, ovarian, bladder, prostate, pancreas

28 Percentage Impaired Impaired mobility and nutrition are associated with early mortality Predictors of Early Mortality OR (CI)* Advanced disease 3.9 ( ) 44 Male gender 2.4 ( ) Low MNA (nutrition) 2.8 ( ) ADL IADL GUG MMSE GDS MNA Slow Get Up and Go (GUG) time 2.6 ( ) * Statistically significant in multivariate analysis Conclusions: Mobility and nutrition were associated with early mortality Limitations: heterogenous patient population

29 A focus on specific conditions

30 % 30-Day Mortality The controversy of AML therapy Survival decreases with age Toxicity increases with age 32% 20 yo % 50 yo 65 yo % 75 yo 3% 5 (Swedish registry data , N=3205) Juliusson et al. Clinical Lymphoma Myeloma and Leukemia 11; Supplement S54 S59 0 < >75 Age (Years) Appelbaum et al. Blood 2006;107:

31 How do we better select patients for intensive therapy? Author Tumor characteristics Clinical variables Patient characteristics Outcomes Krug 1 (N=1406) Kantarjian 2 (N=446) Wheatley 3 (N=2483) Rollig 4 (N=909) Secondary AML Molecular/cytogenetics Body temp, Hgb, platelets, LDH, fibrinogen Age Complex karyotype Creatinine>1.3 Age ECOG PS Cytogenetic risk group Secondary AML Karyotype,NPM1 mutation status, CD34 expression WBC count Age ECOG PS Early death Early death WBC count, LDH Age Survival Survival (1 year) Predictive models for older adults treated with intensive therapy are weighted towards tumor biology 1. Krug et al. Lancet 2010; 376: Kantarjian et al. Blood 2010; 116: Wheatley et al. British Journal of Haematology 2009; 145: , Rollig et al. Blood 2010; 116:

32 Age is a surrogate measure Tumor characteristics Decreased response to therapy Poor treatment outcomes Decreased treatment tolerance Patient characteristics

33 Moving beyond chronologic age : a necessary step towards improved outcomes Will I tolerate and benefit from treatment? FIT VULNERABLE FRAIL Similar tolerance/benefit as middle-aged patients Decreased treatment tolerance Poor treatment tolerance Implications for trial design: 1) Enhanced subset selection to target for novel therapeutic approaches; 2) Refined eligibility criteria; 3) Target factors associated with vulnerability to improve treatment tolerance

34 Percent Impaired GA adds information to standard oncology assessment (N=54) 70% 60% 50% 40% 30% Overall ECOG 1 20% 10% 0% Depression Distress IADL Impairment Physical Performance (SPPB<9) Cognitive Impairment Comorbidity Klepin et al. Journal of the American Geriatrics Society 2010; 59:

35 Percent Impaired (%) The majority of patients were impaired in multiple geriatric domains (N=54) % Number of geriatric domain deficits Klepin et al. JAGS 2010; 59:

36 Impairments in physical performance and cognitive function were associated with worse survival among older adults with AML (N=74) Objective physical function testing Cognitive function testing P=0.018 P=0.002 Klepin et al. Blood, 2013; 121:

37 Physical performance and cognition are independently associated with survival Baseline Geriatric Assessment Measures Hazard Ratio for Mortality (95% Confidence Interval) Unadjusted Adjusted* Impaired physical performance (SPPB score <9) Cognitive impairment (3MS score <77) 1.9 ( ) 2.2 ( ) 2.4 ( ) 2.5 ( ) Depression (CES-D score 16) 1.4 ( ) 1.0 ( ) Distress (<4) 1.2 ( ) 1.0 ( ) IADL impairment (any) 1.2 ( ) 0.8 ( ) Comorbidity (HCT-CI score >1) 1.5 ( ) 1.2 ( ) *Adjusted model includes age, gender, ECOG performance status, cytogenetic risk group, prior MDS, hemoglobin Klepin et al. Blood, 2013; 121:

38 Geriatric assessment predicts survival in multiple myeloma Pooled analysis (N=869) with newly diagnosed MM treated on 3 clinical trials Baseline geriatric assessment measures used to create frailty score Variable HR for mortality Score Prevalence Age (years) ( ) 1 27% ADL impairment IADL impairment > ( ) 2 19% ( ) 1 14% ( ) 1 18% Comorbidity CCI ( ) 1 17% Palumbo et al. Blood 26 March 2015 Vol 125, no 13

39 Geriatric assessment predicts survival in multiple myeloma 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Fit (0) Vulnerable (1) Frail ( 2) Frail Fit Palumbo et al. Blood 26 March 2015 Vol 125, no 13

40 Take home points Geriatric assessment can be done in oncology Geriatric assessment detects impairments not routinely captured in clinical practice Specific impairments are associated with increased chemotherapy toxicity (strongest evidence for physical function) Cumulative deficits confer higher risk for toxicity

41 What are the next steps Risk prediction Validation of practical tools in various patient populations Dissemination of assessment tools Tailoring cancer treatment to vulnerable elders Design of clinical trials for vulnerable adults using validated criteria for inclusion Intervening upon vulnerability Testing interventions to improve treatment tolerance (ie. symptom management, exercise)

42 Conclusions Multiple studies suggest geriatric assessment can improve detection of vulnerability Practical tools for risk assessment will be increasingly available for use in clinical practice as measures are validated in clinical trials Clinical trials designed to test new therapies and interventions based on risk stratification will inform treatment decisions for older cancer patients

43 Thank you for your attention Questions?

44 Special thanks Patients/families Research staff (Rose Fries, Lauren Baber, Phyllis Babcock, Karen Taylor, Michele Harmon, Thomas Freeman, Judy Lovelace, Deanna Hissim, Megan Brown, Jessica Leach, Robin Harrelson, special heme lab) Leukemia team (attendings, APPs, residents, nursing staff, coordinators) Mentors: Bayard Powell, Stephen Kritchevsky, Jeff Williamson, Janet Tooze, Jack Rejeski, Ann Geiger CARG and Alliance