Geriatric assessment-informed treatment decision making and downstream outcomes

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Tina Hsu ◽  
Bonnie Leung ◽  
Caroline Mariano
2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e21703-e21703 ◽  
Author(s):  
Nitya Nathwani ◽  
Supriya Gupta Mohile ◽  
Brea Lipe ◽  
Karen Carig ◽  
Laura DiGiovanni ◽  
...  

e21703 Background: Multiple myeloma (MM) is a disease of older adults (OAs) with > 60% of diagnoses and nearly 75% of deaths occurring in patients > 65 years old (YO). Geriatric Assessment (GA) is associated with toxicity and survival in OAs with MM, but not routinely used in practice. This project pilot tests a tablet-based modified Geriatric Assessment (mGA) that presents compiled GA results, including (the Palumbo) frailty score, to clinicians at a treatment decision-making visit in a single screen dashboard. Methods: In this multisite ongoing study, 210 patients with MM ≥65 YO facing a decision point for care will complete a mGA that includes the Charlson Comorbidity Index (CCI), Katz Activity of Daily Living (ADL) Score, and Lawton Instrumental Activity of Daily Living (IADL) Score prior to meeting with a physician. mGA results, including composite frailty score, are provided to physicians at the start of a visit. Results: Thirty-six patients have been enrolled to date; enrollment continues. Participants are 69% (n = 25) white, 64% (n = 23) male, and mean age of 72 YO (range 65-87). Most (74%, n = 20) currently receive ≥1 therapy and have few co-morbidities (CCI median 1, SD 1.95, range 0-8); 57% require assistance with IADLs and 37% require assistance with ADLs. Based on Palumbo score, 36% of participants were frail (n = 13), 33% intermediate (n = 12), and 31% fit (n = 11). Providers report mGA results influenced treatment decision (54%, n = 28) and frailty score was the most frequently cited result to impact treatment decision-making (61%, n = 39). The most common way the mCGA influenced decision-making was to reduce dose/dose intensity (25%, N = 8). Clinicians on average spent 5 minutesreviewing the mGA results. Patients reported an average of 7 minutes to complete the survey, most independently (83%, n = 30), and were satisfied with the electronic program overall (80%, n = 29), including how easy it was to use (88%, n = 32). Conclusions: Preliminary data support feasibility, usability, and acceptability of the tablet-based mGA and that frailty score influences provider decision-making ≥50% of the time. Future analyses will explore the relationship of the mGA with toxicity, dose modification and/or treatment discontinuation in OAs with MM.


2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 147-147
Author(s):  
Howard J. Lee ◽  
Carolyn L. Qian ◽  
Sophia L. Landay ◽  
Deirdre O'Callaghan ◽  
Emilia Kaslow-Zieve ◽  
...  

147 Background: Preoperative therapy for localized pancreatic cancer represents an emerging treatment paradigm with the potential to provide significant benefits, yet with complex risks. Research is lacking about whether clinicians effectively communicate key components of informed decision-making for patients considering this treatment. Methods: From 2017-2019, we conducted a two-part, mixed methods study. In part 1, we conducted interviews with clinicians (medical/radiation/surgical oncology, n = 13) and patients with pancreatic cancer who had received preoperative therapy (n = 18) to explore perceptions of information needed to make informed decisions about preoperative therapy, from which we generated a list of key elements. In part 2, we audio recorded the initial multidisciplinary visits of patients with pancreatic cancer eligible for preoperative therapy (n = 20). Two coders (94% concordance) independently identified whether clinicians discussed key elements from part 1. Patients also completed a post-visit survey reporting whether clinicians discussed the key elements. We explored discordance between audio recordings and patient reports using qualitative, explanatory themes. Results: In part 1, we identified 13 key elements of informed treatment decision-making, including treatment logistics, alternatives, and potential risks/benefits. In part 2, recordings showed that most visits included discussions about logistics, such as the chemotherapy schedule (n = 20) and use of a port-a-cath (n = 20), whereas few included discussions about risks, such as the potential for hospitalizations (n = 7), urgent visits (n = 6), or needing help with daily tasks (n = 6). Patients reported hearing about potential benefits, such as likelihood of achieving surgery (n = 10) and cure (n = 7), even when these were not discussed. Qualitative themes across these discordant cases included clinician optimism regarding present day results versus historical findings and mentions of positive outcomes from prior patients without citing specific data or potential adverse outcomes. Conclusions: We identified key elements of information patients with pancreatic cancer need to make informed decisions about preoperative therapy. Although clinicians frequently disclosed much of this information, we found multiple cases of patient-clinician discordance for certain key elements, which underscores the need for interventions to enhance patient-clinician communication regarding pancreatic cancer treatment decisions.


2008 ◽  
Vol 73 (2) ◽  
pp. 363-370 ◽  
Author(s):  
Sarah T. Hawley ◽  
Nancy K. Janz ◽  
Ann Hamilton ◽  
Jennifer J. Griggs ◽  
Amy K. Alderman ◽  
...  

Author(s):  
Luke L Wang ◽  
Weranja K.B. Ranasinghe

Our objective was to review the current literature on patient participation and decision-making in the treatment selection process for localised prostate cancer, and to evaluate capacity for improvement. Methods: 42 articles from our literature search were deemed eligible and relevant for review. We reviewed studies on all facets of the treatment decision-making process with most number of articles (16) on treatment preferences. Results: The majority of the patients prefer an active or collaborative role in decision-making. Patients are seeking information from a myriad of sources but the recommendation from their treating physician is often the most influential on the final decision. Radical prostatectomy is more likely to be selected in patients who view a cure for cancer as being of the utmost importance and radiation therapy is preferred in patients who are concerned about treatment side effects. Conclusion: Currently no ideal tool exists to assist patients in making informed treatment decisions that also takes into account patients’ values and preferences. We encourage collaborative partnership in a multidisciplinary setting to optimise this process and individualised risk-based decision-making tools may provide a better pathway to assist patients reach decisions.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 2373-2373 ◽  
Author(s):  
Tanya M Wildes ◽  
Carrie T. Stricker ◽  
William Dudley ◽  
Diana Harris ◽  
Nitya Nathwani ◽  
...  

Abstract Background: More than 60% of multiple myeloma (MM) diagnoses and nearly 75% of deaths occur in patients over 65 years old. Because older adults (OAs) experience more treatment-related toxicities, treatment disruptions or dose reductions may be based on age and performance status alone, despite their poor predictive value for patient outcomes. Comprehensive Geriatric Assessment (CGA), including frailty indices, has shown predictive validity for toxicity and survival in OAs with MM, but is not routinely used in practice due to time and complexity, a lack of clarity about optimal tools and technologies to implement them, and clinician knowledge gaps on how to incorporate CGA into decision-making and care. Purpose: This project aims to address these gaps by pilot testing a tablet-based modified (m)CGA in 120 patients that presents compiled CGA results, including a frailty score, back to clinicians interacting with patients at the time of a treatment decision. Outcomes include feasibility, usability, utility, and impact on treatment decision-making, from both patient and provider perspectives. Pre-study implementation processes and milestones, including development of the mCGA, clinical workflow planning processes, training and other site-initiation activities are presented herein. Methods: The mCGA was developed using an iterative and dynamic consensus-driven process that included: 1) literature review and expert input to identify CGA domains for potential inclusion and 2) consensus building within a multi-disciplinary panel of gero-oncology experts, nurse scientists, and psychometricians. Domains and measures were selected based on predictive ability, length, and ability to administer via patient self-report so as to reduce clinician assessment burden. Study training and implementation procedures were developed using the same approach, as well as through workflow analysis and clinical team consensus building at the participating sites. Results: The Palumbo frailty index (FI) was chosen as the core of the mCGA tool given correlation with clinical outcomes specifically in OAs with MM. In addition to the 4 mGA measures comprising the Palumbo FI (age, comorbidity, ADL, and IADL), other GA variables were also chosen based on their strong predictive ability, clinical feasibility, and relevance to the MM population. This summary of results is displayed for ease of provider use within the Carevive dashboard (see Figure 1). Given prevalent knowledge gaps in use of CGA for MM treatment decision-making and care, a certified medical education self-study course was developed for training prior to the study intervention. Four geographically-dispersed academic and community hospitals who treat high volumes of diverse MM patients are participating to date. All 4 sites developed a process for ensuring treating providers would have easy access to the platform. Conclusions: Real-world, comprehensive and innovative solutions, combining education, geriatric assessment (GA) tools to determine a patient's fit/frailty status, realistic clinical work flow processes, and technology tools are needed to support and enhance treatment-decision making for patients with MM as well as their providers. Figure 1 Screenshot: Touch-screen based dashboard results display example Figure 1. Screenshot: Touch-screen based dashboard results display example Disclosures Wildes: Carevive Systems: Consultancy. Stricker:Carevive Systems, Inc.: Employment, Equity Ownership. Dudley:Carevive Systems, Inc.: Consultancy. Harris:Carevive Systems, Inc.: Consultancy. Nathwani:Carevive Systems, Inc.: Research Funding. Brant:Carevive Systems, Inc.: Research Funding. Kurtin:Carevive Systems, Inc.: Research Funding. Hurria:Boehringer Ingelheim Pharmaceuticals: Consultancy; GTx, Inc: Consultancy; Carevive: Consultancy; Celgene: Other: Research; Optum Health Care SOlutions: Consultancy, Other: Conference panel, research; Sanofi: Consultancy; Novartis: Other: Research.


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