Search

Geriatric assessment (GA) has been shown to decrease toxicity from systemic therapy, improve completion of chemotherapy, and reduce hospitalizations in older adults with cancer. Given the aging of the cancer population, this has the potential to have a positive impact on the care of a large swath of patients seen. Despite endorsement by several international societies, including the American Society of Clinical Oncology, uptake of GA has been low. Lack of knowledge, time, and resources has been cited as reasons for this. Although challenges to developing and implementing a cancer and aging program vary depending on the health care context, GA is adaptable to every health care context from low- to high-resource settings, as well as those in which geriatric oncology is a well-established or just emerging field. We provide an approach for clinicians and administrators to develop, implement, and sustain aging and cancer programs in a doable and sustainable way.

12010 Background: Older patients often experience more toxicity from cancer treatments due to their functional age and co-morbidities. The G8 is a geriatric screening tool designed to identify patients who are appropriate for a comprehensive geriatric assessment (CGA) which will inform and optimize oncology therapeutic decision making, reduce toxicities and improve outcomes. Using a nurse-led assessment approach, we have implemented an EMR embedded G8 tool across our cancer center since June 2020. We aim to describe the characteristics of those patients who scored abnormal (≤ 14) on the G8. Methods: The demographic and clinical characteristics were collected from the EMR for those who were ≥ 65 and have completed the G8 screening tool from June 2020 to Jan 2022. Summary statistics such as means, standard deviations and proportions were reported. Comparisons of various endpoints between dichotomized (≤ 14 vs. > 14) G8 scores were performed using pairwise two-sample t-test, pairwise proportion test, Fisher’s exact test and/or Pearson’s chi-squared test. Selected stakeholders were elicited for their perspectives on the implementation process. Results: 544 patients age ≥ 65 completed G8 screening with a mean score of 13.4 (± 2.3). The mean age was 75.2 (± 7.0), and 55.7% were females and 78.3% were non-Hispanic White. The most frequent cancer type was breast cancer (21.3%), followed by lung/respiratory cancer (18.2%), and GI cancer (15.8%). The percentage of patients appropriate for a CGA (based on an abnormal G8 score) was 59% (n = 332), of which only 10% (n = 31) were referred. A spearman correlation of 0.4 (p < 0.001) between G8 scores and age was obtained. A statistically significant association between ECOG and G8 groups was found, but not for any comorbidities. The prevalence of current/former smoking and extreme polypharmacy (> 10) is significantly higher in the G8 abnormal group. Implementation process evaluation found new patients with cancer overwhelmed with information, a lack of patient education and provider engagement, and an unstandardized referral process to CGA, were barriers for CGA referral. Conclusions: The G8 is an effective tool identifying patients appropriate for a CGA. An EMR embedded G8 steadily improved the G8 utilization uptake but not referral for CGA at our institution. To further improve awareness, utilization and referral, we are redesigning a hybrid workflow integrating patient-mediated MyChart implementation and nurse navigator engagement. EPIC enhancements are being designed to inform the oncologist of the patient’s G8 score, CGA referral status and the final CGA report.

OBJECTIVES: Polypharmacy (≥5 concurrent medications) is common among older patients with cancer (48%−80%) and associated with increased frailty, morbidity, and mortality. This study examined the relationship between polypharmacy and inpatient hospitalization among older adults with cancer treated with intravenous (IV) chemotherapy. MATERIALS AND METHODS: The main data source was the Surveillance, Epidemiology, and End Results-Medicare linked files. Patients (≥ 65 years) were included if they were diagnosed with prostate (n=1,430), breast (n=5,490), or lung cancer (n=7,309) in 1991–2013 and received IV chemotherapy in 2011–2014. The number of medications during the sixmonth window pre-IV chemotherapy initiation determined polypharmacy status. Negative binomial models were used to assess the association between polypharmacy and post-chemotherapy inpatient hospitalization. The results were presented as incidence rate ratios. RESULTS: We identified 13,959 patients with prostate, breast, or lung cancer treated with IV chemotherapy. The median number of prescription medications during the 6-month window pre-IV chemotherapy initiation was high: ten among patients with prostate cancer, nine among patients with breast cancer, and eleven among patients with lung cancer. Compared to patients taking < 5 prescriptions, post-chemotherapy hospitalization rate for patients with prostate cancer was 42%, 75%, and 114% higher among those taking 5–9, 10–14, and 15+ medications, respectively. Patients with breast and lung cancer demonstrated similar patterns. CONCLUSION: This large population-based study found that polypharmacy during the six-month window pre-IV chemotherapy is highly predictive of post-chemotherapy inpatient hospitalization. Further studies are needed to evaluate whether medication management interventions can reduce post-chemotherapy inpatient hospitalization among older patients with cancer.

Objectives Drug-drug interactions (DDIs) represent an escalating concern for older adults attributed to polypharmacy, multi-morbidity and organ dysfunction. Few studies have evaluated the prevalence of major DDIs and the variability between DDI detection software which confuses management. Materials and Methods Prevalence of major DDIs was examined as a secondary analysis of outpatients aged ≥65 years. Demographic and clinical information was collected from electronic health records including age, sex, race, cancer type, comorbidities, and medications. All DDIs were screened by a clinical pharmacist using Lexi-Interact® and Micromedex®. Major DDIs were defined as Lexi-Interact® category D or X and/or Micromedex® category major or contraindication. Summary statistics of patient characteristics and DDIs were computed. Results Our cohort included 142 patients (mean age, 77.7 years; 56% women, 73% Caucasian). The mean medications was 9.8 including 6.7 prescriptions, 2.6 non-prescriptions, and 0.5 herbals. Lexi-Interact® identified 310 major DDIs in 69% of patients (n = 98) with an average of 2.2 DDIs per patient. Micromedex® identified 315 major DDIs in 61% of patients (n = 87) with an average of 2.2 DDIs per patient. DDIs mostly involved opioids, antiplatelets, electrolyte supplements, antiemetics, and antidepressants. Variability existed with the severity rating reporting of the clinical decision support software. Conclusions There was a high prevalence of major DDIs in older adults with cancer. Utilizing clinical decision support software was beneficial for detecting DDIs however, variability existed with severity reporting. Future studies need to identify the relevant DDIs with clinical implications in order to optimize medication safety in this population.

Objectives Medication-related problems (MRP) affecting older adults are a significant healthcare concern and account for billions in medication-related morbidity. Cancer therapies can increase the prevalence of MRP. The objective of this study was to test the feasibility and effectiveness of implementing a pharmacist-led individualized medication assessment and planning (iMAP) intervention on the number and prevalence of MRP. Materials and Methods This prospective pilot study enrolled oncology outpatients aged ≥ 65 years. Intervention feasibility encompassed recommendation acceptance rate and intervention delivery time. The intervention was facilitated by pharmacists where patients received comprehensive medication management at baseline and at the 30- and 60-day follow-up. Results Forty-eight eligible patients enrolled and 41 patients (85.4%) were included in the analysis. Mean age was 79.1 years [range 65–101]; 66% women, 83% Caucasian, mean comorbidity count was 7.76. Forty-six percent of the pharmacist recommendations were accepted and the prevalence of MRP at baseline versus 60-day follow-up decreased by 20.5%. The average time to conduct the initial session was 22 min versus 15 min for the follow-up sessions. Resources needed included a tracking system for scheduling follow-up calls and a database for tracking acceptance of recommendations. A total of 123 MRP were identified in 95% of patients (N = 39) with a mean of 3 MRP per patient. The mean reduction in number of MRP (3 at baseline versus 1.6 at 60-day follow-up) was 45.5%. Conclusions The pharmacist-led iMAP intervention was feasible and effective at reducing MRP. Additional inter-professional medication safety based interventions measuring patient-reported outcomes are still needed.

Purpose The use of multiple and/or inappropriate medications in seniors is a significant public health problem, and cancer treatment escalates its prevalence and complexity. Existing studies are limited by patient self-report and medical record extraction compared with a pharmacist-led comprehensive medication assessment. Patients and Methods We retrospectively examined medication use in ambulatory senior adults with cancer to determine the prevalence of polypharmacy (PP) and potentially inappropriate medication (PIM) use and associated factors. PP was defined as concurrent use of five or more and less than 10 medications, and excessive polypharmacy (EPP) was defined as 10 or more medications. PIMs were categorized by 2012 Beers Criteria, Screening Tool of Older Person's Prescriptions (STOPP), and the Healthcare Effectiveness Data and Information Set (HEDIS). Results A total of 248 patients received a geriatric oncology assessment between January 2011 and June 2013 (mean age was 79.9 years, 64% were women, 74% were white, and 87% had solid tumors). Only 234 patients (evaluated by pharmacists) were included in the final analysis. Mean number of medications used was 9.23. The prevalence of PP, EPP, and PIM use was 41% (n = 96), 43% (n = 101), and 51% (n = 119), respectively. 2012 Beers, STOPP, and HEDIS criteria classified 173 occurrences of PIMs, which were present in 40%, 38%, and 21% of patients, respectively. Associations with PIM use were PP (P < .001) and increased comorbidities (P = .005). Conclusion A pharmacist-led comprehensive medication assessment demonstrated a high prevalence of PP, EPP, and PIM use. Medication assessments that integrate both 2012 Beers and STOPP criteria and consider cancer diagnosis, prognosis, and cancer-related therapy are needed to optimize medication use in this population.

With the emergence of telemedicine as a routine form of care in various venues, the opportunities to use technology to care for the most vulnerable, most ill cancer patients are extremely appealing. Increasingly, evidence supports early integration of palliative care with standard oncologic care, supported by recent NCCN guidelines to increase and improve access to palliative care. This review looks at the use of telemedicine to expand access to palliative care as well as provide better care for patients and families where travel is difficult, if not impossible. When telemedicine has been used, often in Europe, for palliative care, the results show improvements in symptom management, comfort with care as well as patient and family satisfaction. One barrier to use of telemedicine is the concerns with technology and technology-related complications in population that is often elderly, frail and not always comfortable with non-face-to-face physician care. There remain significant opportunities to explore this intersection of supportive care and telemedicine.

Background The proportion of older patients with cancer is expected to grow exponentially in the next two decades. This population has large heterogeneity and it is well known that chronologic age is a poor predictor of outcomes. Research has shown that these patients are best served with a Comprehensive Geriatric Assessment (CGA) to formulate individualized treatment plans for better outcomes. However, the best model for CGA has yet to be determined. Materials and Methods Our objective was to develop a highly functional model for the establishment of a comprehensive multidisciplinary geriatric oncology center in the setting of a university based NCI-designated cancer center. Each patient is evaluated by medical oncology, geriatric medicine, pharmacy, social work and nutrition. Expert navigation is provided to enhance the patient experience. At the conclusion, the inter-professional team meets to review each case and formulate a comprehensive treatment plan. The patient is classified as Fit, Vulnerable, or Frail based on the complete CGA. Results The average age of patients seen was 80.7 with the most common diagnoses being breast, colorectal and lung cancers. Twenty four percent of patients were determined to be Fit, 47% Vulnerable, and 29% Frail. Twenty one percent of patients determined to be Frail by CGA received an ECOG score of 0–1 by the oncologist. Our pharmacists made specific recommendations in over 75% of patients and social work provided assistance in over 50% of patients. Conclusions We were able to observe some interesting trends such as potential discordance with ECOG score and assessment of Fit/Vulnerable/Frail but due to limitations in the data, this paper is not able to illustrate definitive correlations. Several challenges with the development of the clinic include 1) patient related issues, 2) navigation, 3) financial reimbursement, 4) referral patterns, and 5) coordination of care during office hours. We feel that we have been able to establish a model for a comprehensive multidisciplinary geriatric oncology evaluation center in the setting of a university based cancer center.

Objectives The prevalence of complementary and alternative medication (CAM) use in senior adult oncology (SAO) patients is widely variable and little is known about whether polypharmacy (PP) and potentially inappropriate medication (PIM) use influences CAM use given the increased number of comorbidities and polypharmacy. One approach to optimize medication management is through utilization of pharmacists as part of a team-based, healthcare model. Materials and Methods Prevalence of CAM and factors influencing CAM use was examined in a secondary analysis of 248 patients who received an initial comprehensive geriatric oncology assessment between January 2011 and June 2013. Data was collected from electronic medical records. CAM was defined as herbal medications, minerals, or other dietary supplements, excluding vitamins. Patient characteristics influencing CAM use (e.g. comorbidities, PP and PIM use) were analyzed. Results Only 234 patients (evaluated by pharmacists) were included in the final analysis. Mean age was 79.9 years [range 61–98]; 64% women, 74% Caucasian, 87% with a solid tumor, mean comorbidities, 7.69. CAM prevalence was 26.5% (n = 62) and median CAM use was 0 (range 0–10). The proportion of CAM use (1, 2, and 3) was 19.2%, 6.4%, and 0.4%, respectively. Associations with CAM use (versus no-CAM) were polypharmacy (P = 0.045), vision impairment (P = 0.048) and urologic comorbidities (P = 0.021). Conclusions A pharmacist-led comprehensive medication assessment demonstrated a more precise estimation of CAM prevalence in the ambulatory SAO population. CAM use was associated with polypharmacy, ophthalmic and urologic medical conditions. Integrating pharmacists into team-based (geriatric and oncology) care models is an underutilized yet viable solution to optimize medication use.

Delirium and VTE are among the many complications that can derail rehabilitation efforts. These tips can help you keep treatment on track.

The American Cancer Society reports that more than 60% of all cancers and 80% of cancer-related deaths in the United States occur in patients older than age 65 (1,2). Epidemiologic data show that the likelihood of developing certain cancers in older age is higher than in younger individuals, and intuitively, this stands to reason, due to physiologic factors, time for the expression and development of genetically-related cancers, and a longer range of environmental exposures. However, many cancers may be more difficult to treat in older individuals due to higher incidence of medical co-morbidities, as well as the biology of certain tumors themselves. Heterogeneous behaviors of several cancers manifest as unique situations in elderly patients across a broad spectrum, including on average, more indolent estrogen-receptor-positive breast cancers, as well as more drug-resistant acute leukemias which may arise on a background of a long history of myelodysplasia. In addition, optimum dosing and prediction of treatment toxicity remains a difficult question, as older cancer patients are not well represented in clinical trials, for which often the inclusion criteria list a maximum age of 70. Furthermore, many cancers such as hematologic malignancies, may not be able to be treated with maximum aggressiveness such as high-dose chemotherapy followed by stem cell transplant or autologous stem cell rescue as would be tolerated by younger individuals (usually under the age to 60–65). In our quest as physicians to “first do no harm” (3,4), we wrestle with our best recommendations for our elderly patients, often in the face of frail physicality and potential for increased risk of infection and iatrogenically-induced side effects and morbidity. We present here 3 cases of advanced cancers in patients of advanced chronologic age, who also exhibit multiple medical co-morbidities. Their situations likely warrant specifically tailored treatment given their age, which would be markedly different if they presented in earlier decades of life. We pose the following clinical questions: (a) What treatments would you offer/feel comfortable offering these patients? (b) What factors are important in arriving at these decisions between and among the physician, patients, and families? (c) What modifications would you make to standard treatments if indicated for these particular patients?

In 2009, nearly 66 million Americans (three in 10 U.S. households) reported at least one person providing unpaid care as a family caregiver. More adults with chronic conditions and disabilities are living at home than ever before, and family caregivers have an even higher level of responsibility. Caring for loved ones is associated with several benefits, including personal fulfillment. However, caregiving is also associated with physical, psychological, and financial burdens. Primary care physicians can aid in the identification, support, and treatment of caregivers by offering caregiver assessments-interviews directed at identifying high levels of burden-as soon as caregivers are identified. Repeat assessments may be considered when there is a change in the status of caregiver or care recipient. Caregivers should be directed to appropriate resources for support, including national caregiving organizations, local area agencies on aging, Web sites, and respite care. Psychoeducational, skills-training, and therapeutic counseling interventions for caregivers of patients with chronic conditions such as dementia, cancer, stroke, and heart failure have shown small to moderate success in decreasing caregiver burden and increasing caregiver quality of life. Further research is needed to further identify strategies to offset caregiver stress, depression, and poor health outcomes. Additional support and anticipatory guidance for the care recipient and caregiver are particularly helpful during care transitions and at the care recipient's end of life.

e20532 Background: A Vulnerable Elders Survey (VES 13) score of ≥ 3 has been validated to predict vulnerability for community elders but not geriatric oncology patients. A test to accurately identi...

e20516 Background: PIM use in seniors is a public health problem linked to billions in health expenditures; cancer-related therapies further escalate its prevalence and complexity. Existing studies are limited by antiquated criteria and inherent pitfalls of patient self-report/chart extraction (versus a pharmacist-led assessment). Objectives: 1) Identify prevalence and associations with PIM use; 2) Determine the most inclusive PIM criteria. Methods: This retrospective study involved 248 patients (aged ≥ 60 years) referred for a geriatric-oncology assessment in January 2011 through June 2013 (data from physician/pharmacist electronic notes). Patients brought medications (prescription, non-prescription, herbals) for the pharmacist-led assessment. PIM use was determined by 2012 Beers, the Screening tool of older persons' potentially inappropriate prescriptions (STOPP) and the Healthcare and data information set (HEDIS) criteria. Results: Mean age was 79.9 years [range 61-98]; 64% women, 74% Caucasian, 87% so...