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Evaluation of a Pharmacist-led Medication Assessment to Identify the Prevalence of Polypharmacy and Potentially Inappropriate Medication (PIM) Use Among Ambulatory Seniors with Cancer Ginah Nightingale, Pharm.D., BCOP Assistant Professor, Department of Pharmacy Practice Jefferson School of Pharmacy, Thomas Jefferson University Philadelphia, Pennsylvania, USA October 24, 2014

Jefferson In the News!

Study Investigators Ginah Nightingale, Pharm.D., BCOP 1, Principal Investigator Assistant Professor, Department of Pharmacy Practice Emily Hajjar, Pharm.D., BCPS, BCACP, CGP 1 Associate Professor, Department of Pharmacy Practice Kristine Swartz, MD 2 Assistant Professor, Division of Community and Family Medicine, Department of Geriatrics and Palliative Care Jocelyn Andrel-Sendecki, MSPH 3 Biostatistician, Division of Biostatistics, Department of Pharmacology and Experimental Therapeutics Andrew Chapman, DO 2 Clinical Associate Professor, Department of Medical Oncology, Co-Director of the Jefferson Senior Adult Oncology Center 1 Jefferson School of Pharmacy, Thomas Jefferson University, Philadelphia, PA 2 Thomas Jefferson University Hospital, Philadelphia, PA 3 Thomas Jefferson University, Philadelphia, PA

Faculty Disclosures This study was supported by the American Association of Colleges of Pharmacy (AACP) 2013 New Investigator Award Grant Program Study investigators and key personnel do not have any disclosures

Background The American Cancer Society estimates that by 2030 70% of all cancers in the U.S. will be diagnosed in senior adults 1 The elders are coming! Excessive medication consumption and potentially inappropriate medication (PIM) use in the elderly is recognized as a significant public health problem linked to billions in health expenditures 2 Cancer-related treatment and supportive care therapies escalate its prevalence and complexity and can increase the risk for adverse drug events, drug-drug interactions, non-adherence 3-7 1 Smith BD, et al. J Clin Oncol 2009; 27:2758 65 2 Fu FZ, et al. Med Care 2007; 45:472-476 3 Riechelmann T, et al. J Natl Cancer Inst. 2007; 99: 592-600 4 Riechelmann T, et al. J Pain Symptom Manage. 2008; 35:535-43 5 Riechelmann T, et al. Cancer Chemother Pharmacol. 2005; 56: 286-90 6 Puts M, et al. Drugs Aging 2009; 26: 519-36 7 Scripture C, et al. Nat Rev Cancer 2006; 6: 546-558

Background Literature and guidelines for senior adult oncology (SAO) management recommend medication evaluations as a standard component of the geriatric oncology assessment 8-9 A comprehensive medication assessment includes: Prescription medications Non-prescription medications Complementary and alternative medications Conventional studies that previously examined prevalence of polypharmacy (PP) and PIM use in the SAO population 10-12 were limited by: Inherent pitfalls of patient self-report/chart extraction Use of antiquated definitions and screening criteria Lack of evaluation of excessive polypharmacy 8 Extermann M, et al. J Clin Oncol 2007; 25:1824 31 9 The NCCN Clinical Practice Guidelines in Oncology Senior Adult Oncology (version 2.2014) 10 Lichtman SM, et al. J Clin Oncol 2009 ;27:Abstract 9507 11 Maggiore RJ, et al. J Clin Oncol 2011; 29:Abstract 19501 12 Prithviraj GK, et al. J Geriatr Oncol 2012; 3:228 37

Objectives and Design Primary: To identify the prevalence of PP, excessive polypharmacy (EPP), and PIM use among SAO patients Secondary: To identify characteristics associated with PP and PIM use Study Design: Prospective patient-pharmacist session (comprehensive medication assessment) Retrospective data collection (Physicians/Pharmacists e-notes) Patients brought in all medications from home for review

Methods Inclusion criteria: Geriatric-oncology multidisciplinary assessment (1/2011-6/2013) Cancer diagnosis (new diagnosis, recurrence, progression) Data collection included the following: Age, gender, race, tumor type, stage Medications (prescription, non-prescription, complementary/herbals) Medical comorbidities (number and type) Eastern Cooperative Oncology Group (ECOG) status 13 Functional status 14 based on geriatrician assessment Fit (Minimal co-morbidity and no functional dependence) Vulnerable (Some dependence IADLs, controlled co-morbidities, geriatric syndrome) Frail (3+ co-morbidities, dependence in 1+ ADLs, significant geriatric syndrome) 13 Oken MM, et al. Am J Clin Oncol. 1982; 5:649-655 14 Balducci L, et al. The Oncologist. 2000; 5:224-237

Study terms and definitions Polypharmacy (PP) and excessive polypharmacy (EPP) 15-17 PP - concurrent use of 5 and < 10 medications EPP - concurrent use of 10 medications Potentially inappropriate medication use (3 indices) 18-20 2012 Beers criteria Screening tool of older persons potentially inappropriate prescriptions (STOPP) Healthcare and data information set (HEDIS) 15 Montamat SC, et al. Clin Geriatr Med. 1992;8:143-58 16 Hajjar ER, et al. Am J Geriatr Pharmacother. 2007;5:345-51 17 Hovstadium B, et al. Clin Geriatr Med. 2012;28(2):159-172 18 American Geriatrics Society Updated Beers Criteria for Potentially Inappropriate Medication Use in Older Adults. J Am Geriatr Soc 2012 19 O Mahony D, et al. European Geriatric Medicine 2010;1: 45 51 20 National Committee on Quality Assurance. Drugs to be avoided in the elderly. March 2014

Age, mean (SD) Baseline demographics and characteristics, n=248 79.9 (6.84) years Female gender, n (%) 159 (64%) Race, n (%) Caucasian African American Solid malignancies, n (%) Colorectal Breast Lung Urinary tract (bladder, renal, urethral, urothelial) Upper Gastrointestinal (pancreatic, bile duct, gall bladder) Esophageal Neuroendocrine Gastric Prostate Hematologic malignancies, n (%) Lymphoma Results 184 (74%) 48 (19%) 216 (87%) 46 (19%) 45 (18%) 39 (16%) 18 (7.3%) 15 (6%) 9 (3.6%) 8 (3.2%) 7 (2.8%) 7 (2.8%) 32 (13%) 13 (5%)

Results Baseline demographics and characteristics, n=248 Cancer stage, n (%) Stage I Stage II Stage III Stage IV Recurrence (local and metastatic) Staging not applicable * ECOG performance status, n (%) 0 1 2 3 ** Functional status, n (%) Fit Vulnerable Frail 31 (13%) 59 (24%) 46 (19%) 65 (26%) 34 (14%) 8 (3.2%) 71 (29%) 108 (44%) 58 (23%) 9 (4%) 57 (23%) 120 (49%) 68 (28%) Number of comorbidities (excluding cancer diagnosis), mean (SD) 7.69 (3.47) *ECOG performance status (N=247); ECOG 4 = 1 (0.4%) **Functional status (N=245)

Results 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 230 (93%) 117 (47%) Comorbidity prevalence*, n (%) 88 (36%) 108 (44%) 43 (17%) 89 (36%) 91 (37%) 68 (27%) 162 (65%) 82 (33%) 68 (27%) *Sample size (N=248)

Results Medication Use, n=234 Total medications Total medications, mean (SD), [range] 2163, 9.23 (4.79), [1 30] Prescription medications Total medications, mean (SD), [range] 1430, 6.1 (3.58), [0 20] Non-prescription medications Total medications, mean (SD), [range] 647, 2.76 (2.11), [0 10] Complementary medications Total medications, mean (SD), [range] 86, 0.38 (0.88), [0-10] *Sample size based on number of patients evaluated by a pharmacist

Results 96 (41%) 96 (95%) 101 (43%) 5 (5%) 37 (16%) No Polypharmacy Polypharmacy Excessive Polypharmacy Extreme Polypharmacy *Sample size (N=234)

Prescription Medication Use, n=234 Prescription category N % Cardiovascular (Alpha-adrenergic agonists/antagonists, antiarrhythmics, beta-adrenergic antagonist, calcium channel antagonists, renin-angiotensin aldosterone antagonists, vasodilators) 180 76.9 Dislipidemics (Statins, ezetimibe, niacin, fenofibrate) 124 53 Gastrointestinal (Antiemetics, constipation/diarrhea, histamine-2 antagonist, PPIs) 96 41 Diuretic 94 40.2 Endocrine (Antidiabetic orals/injectable, thyroid replacement, antithyroid agents) 87 37.2 Analgesic (Non-steroidal anti-inflammatory drugs, opioids/non-opioids, neuropathic pain drugs) 69 29.5 Antiplatelet/anticoagulant 53 22.7 Neuropsychiatric (Antidepressants, antiparkinson agents, antipsychotics, anticonvulsants) 51 21.8 Vitamin/minerals 45 19.2 Pulmonary/respiratory (Inhalers, oral tablets) 44 18.8

Potentially inappropriate medication use prevalence**, n (%) 2012 Beers, STOPP criteria and HEDIS collectively identified 173 PIM occurrences which was present in 40% (n=94), 38% (n=88), 21% (n=49) of patients, respectively.

Potentially Inappropriate Medication Use, n=234 Medication category N % Benzodiazepine 38 16.2 Gastrointestinal (Antiemetics, anticholinergic/antispasmodics, constipation/diarrhea, PPIs) 22 9.4 Non-steroidal anti-inflammatory drugs 20 8.6 Antiplatelet 19 8.1 Antihistamine (First generation) 14 6 Beta-adrenergic antagonist 13 5.6 Sedative hypnotic 7 3 Neuropsychiatric (Antipsychotics) 6 2.6 Cardiovascular (Antiarrhythmics, calcium channel antagonists) 6 2.6 Endocrine (Sulfonylureas, sliding scale insulin, dessicated thyroid) 6 2.6

Results Patient characteristics associated with polypharmacy No PP (n=37) < 5 medications Any PP (n=197) 5 medications P-value Age, mean (SD) 79.03 (7.4) 79.93 (6.65) 0.491 Female gender, n (%) 27 (72.97) 123 (62.44) 0.265 Race, n (%) Caucasian African American 25 (67.57) 9 (24.32) 148 (75.13) 36 (18.27) 0.861 Number of comorbidities, mean (SD) PIM use, n (%) 4.59 (2.19) 8.6 (3.4) <0.001 7 (18.92) 112 (56.85) <0.001

Results Patient characteristics associated with PIM use No PIM (n=115) PIM (n=119) P-value Age, mean (SD) 80.3 (7.2%) 79.3 (6.3%) 0.260 Female gender, n (%) 76 (66%) 74 (62%) 0.534 Race, n (%) Caucasian African American Number of comorbidities, mean (SD) Polypharmacy, n (%) No polypharmacy Polypharmacy ( 5 and < 10 meds) Excessive Polypharmacy (>10 meds) 80 (70%) 24 (21%) 93 (78%) 21 (18%) 0.437 7.3 (3.4) 8.7 (3.6) 0.005 30 (26.1%) 54 (47%) 31 (27%) 7 (5.9%) 42 (35.3%) 70 (58.8%) <0.001

Summary A pharmacist-led comprehensive medication assessment demonstrated a high prevalence of PP, EP and PIM use among ambulatory SAO patients High pill burden (increased use of medication) was associated with: Increased comorbidity count Increased PIM use STOPP and 2012 Beers criteria were most inclusive for identifying PIMs 2012 Beers and the STOPP criteria mutually identified 66 (38%) PIM occurrences supporting the fact both tools may be complementary

Limitations Single-center study Small cohort Pharmacist recommendations were made but not tracked to assess primary provider s acceptance Our SAO functions as a consultative center Captured medication use at a single (initial) visit Most patients were not on anti-cancer treatment at initial visit Medication use in this population changes continuously Heterogeneous cancer types / cancer stages

What s Next Future Directions Another funded research study! 2014 American Society of Health-System Pharmacists (ASHP) New Investigator Award A Pharmacist-led Intervention to Identify and Reduce Medication Related Problems (MRP) during SAO Transitions of Care Development of an easy to apply modified PIM screening tool (integrates 2012 Beers and STOPP criteria) and considers: Cancer diagnosis and prognosis Cancer treatment Supportive care therapies

Acknowledgements I would like to acknowledge and thank the following individuals who assisted with this research investigation: Laura Pizzi, Pharm.D., MPH Joshua Schoppe, MPH, CCRP Vittorio Maio, Pharm.D., MS, MSPH Krystal Guo, Pharm.D. Stephanie Komura, Pharm.D. Eric Urnoski, Pharm.D. Candidate 2015