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  • 1
    In: Blood, American Society of Hematology, Vol. 136, No. Supplement 1 ( 2020-11-5), p. 42-43
    Abstract: Introduction: Understanding decisional involvement and information preferences in patients with hematologic malignancies may help to optimize physician-patient communication about treatment decisions and align the decision-making processes with patients' preferences. Exploring how patients perceive their length of life compared to an average person (prognostic optimism) may allow tailoring of conversations about treatment and prognosis. We described and examined factors associated with decisional involvement preferences, information preference, and prognostic optimism. Methods: In a multicenter observational study, we recruited patients with hematologic malignancies of any stage from 9/2003 to 6/2007. Patients were asked about: 1) Decisional involvement preference (Control Preferences Scale), 2) Information sources (including most useful source of information), 3) Preferences for types of information, 4) Preferences for presentation of treatment success information by their oncologists, and 5) Self-perceived length of life compared to patient estimates of an average person of the same disease type and stage (0-6 months, 6-12 months, 1-3 years, 3-5 years, 5-10 years, and & gt;10 years); prognostic optimism was defined as present if patients perceived that they would live longer than their estimates of an average person with the same disease type and stage. We used multivariate logistic regressions to determine demographic and clinical factors associated with: 1) Decisional involvement preference, 2) Usefulness of information sources, and 3) Prognostic optimism. Results: Among 216 patients, median age was 55 years (range 22-79); 39% had lymphoma, 19% had acute leukemia, and 13% had multiple myeloma. In terms of decisional involvement preferences, patient-directed, shared, and physician-directed approaches were preferred in 34%, 38%, and 28% of patients, respectively (Figure 1a). On multivariate analysis, none of the demographics or clinical factors were associated with decisional involvement preferences. Common sources for patients to obtain information on disease or treatment options included their physician (98%), computer/internet (87%), print and broadcast media (71%), and family/friends/other patients/patient support group (78%). Utilization of computer/internet was higher among patients aged & lt;60 years compared to those ³60 years (91.2% vs. 80.5%, P=0.02).. On multivariate analysis, patients with less than a college education (vs. postgraduate education) were less likely to perceive their physician as the most useful source [Adjusted Odds Ratio (OR) 0.46, p=0.05]. Patients with acute leukemia were more likely to perceive their physician as the most useful source (OR 2.49, p=0.03) compared to patients with other blood cancer Over 90% of participants indicated that they would like to discuss each of the following disease and treatment issues: treatment options, goals, impact of disease and treatment on lifestyle, likelihood of treatment success, average survival, physician recommendations for treatment, things they can do to help with recovery, and emotional response to the disease. When asked about their preferences for information presentation about treatment success rates, 70% had ≥1 preferred methods. Most participants (88%) preferred presentation in percentages, 59% wanted to hear about a previous patient that the physician had treated, 37% preferred qualitative descriptions and 30% preferred presentation in fractions. Compared to younger adults, older adults were less likely to prefer presentation in percentages (82% vs. 91%, p=0.04). Prognostic optimism occurred in 31% (Figure 1b). On multivariate analysis, only older age was associated with prognostic optimism (OR 1.05, p=0.03). Conclusions: Our study suggests that decisional involvement and information preferences vary among patients with hematologic malignancies and should be assessed explicitly as part of each decision-making encounter to ensure patients' needs are being met. In addition, approximately one-third of patients had prognostic optimism. Although most studies find that physicians follow the same script with their patients and present invariant information, given the heterogeneity of patient preferences, physicians need to tailor their encounters. Disclosures Loh: Seattle Genetics: Consultancy; Pfizer: Consultancy. Leblanc:Agios, AbbVie, and Bristol Myers Squibb/Celgene: Speakers Bureau; UpToDate: Patents & Royalties: Royalties; American Cancer Society, BMS, Duke University, NINR/NIH, Jazz Pharmaceuticals, Seattle Genetics: Research Funding; AbbVie, Agios, Amgen, AstraZeneca, CareVive, BMS/Celgene, Daiichi-Sankyo, Flatiron, Helsinn, Heron, Otsuka, Medtronic, Pfizer, Seattle Genetics, Welvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Research Funding. Lee:Pfizer: Consultancy, Research Funding; Incyte: Consultancy, Research Funding; AstraZeneca: Research Funding; Kadmon: Research Funding; Novartis: Research Funding; Takeda: Research Funding; Syndax: Research Funding; Amgen: Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2020
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 2
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 2245-2245
    Abstract: Introduction: Hematopoietic cell transplantation (HCT) advances in reduced intensity conditioning, donor identification, and supportive care have led to its increased use over the last few decades. HCT is a complex process that requires coordination at multiple levels, and there may be disparities in its utilization. To better understand these access disparities, we conducted a systematic review of studies that assessed barriers to referral and/or receipt of HCT. Additionally, we focused on a subgroup of older patients (aged ≥65 at transplant), who we hypothesized would be at higher risk for access barriers to HCT. Methods: A systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched for articles published in English from PubMed, Embase, Cumulative Index for Nursing and Allied Health, and Cochrane Central Register of Controlled Trials between the database inception and January 12th, 2018. Inclusion criteria were: 1) clinical trials, observational, qualitative, cross-sectional, or mixed-method study designs; 2) study assessed barriers to HCT or factors associated with referral for or receipt of HCT (except for country-specific economic factors as these are less likely to be targetable), 3) included patients ≥18 years with cancer. Narrative review articles and abstracts without full text were excluded. Two authors independently reviewed all titles and abstracts (N=3,262) and assessed studies for full-text eligibility (N=153). A third reviewer resolved any discrepancies. Eighteen studies met eligibility criteria and an additional 5 studies (not identified on our search strategy) were included on review of the bibliographies. Literature on subgroup of patients aged ≥65 was also assessed. Results: Among the 23 studies included, 16 were published after 2010. Studies were retrospective (N=18; 14 from registry data), cross-sectional (N=4; 2 from registry data), and mixed-method (N=1), and primarily conducted in the US (N=21). Barriers were assessed at the patient level (N=19; sample size ranged from 350 to 38,420), healthcare professional level (N=3; 1 study assessed both patients and healthcare professionals), or country level (N=2). Fourteen studies included some information on age of the patients and 10 studies included some patients aged 60 and above. Seventeen studies only included patients with hematologic malignancies. Age was the most common barrier identified (N=16 out of 16 studies identified older age as a barrier). Fourteen studies showed that older age was associated with lower odds of referral for or receipt of HCT, and the remaining 2 studies provided descriptive data showing lower percentages of patients receiving HCT compared to the younger age groups. Table 1 shows other potential barriers or factors associated with lower referral for or receipt of HCT at the patient, disease, physician, and organizational levels. These included race (N=14 out of 16 studies identified non-white race as a barrier), insurance or financial capacity (N=11/12), comorbidity (N=8/9), gender (N=7/17; primarily female), disease status (N=5/5), patient preferences (N=5/5), time of diagnosis (N=5/5), cancer type (N=4/6), and socioeconomic status (N=4/5). Only one study evaluated factors associated with receipt of HCT in a subgroup of patients ≥65 years. Older age, female gender, and a diagnosis of leukemia other than acute myeloid leukemia were associated with lower odds of receiving HCT. Conclusions: There are limited prospective studies evaluating access barriers to HCT in adult patients with cancer. Older age is the most commonly reported barrier to both autologous and allogeneic HCT, although studies have not addressed specific mechanisms for this disparity. In addition, other potential barriers identified such as gender, race, insurance status, and comorbidity have not been well studied in the context of older age. While some barriers may be difficult to intervene upon (e.g. comorbidity, disease status, performance status), many are amenable to interventions (e.g. socioeconomic status, distance to transplant center, social support). With the increasing trend for HCT in older patients, there is a critical need for prospective studies that better describe these access barriers and their mechanisms in order to design future interventions to reduce disparities in HCT access. Figure. Figure. Disclosures Liesveld: Onconova: Other: DSMB; Abbvie: Honoraria. Aljitawi:Medpace: Consultancy; The University of Rochester Medical Center: Patents & Royalties: Pending patent related to decellularized Wharton's jelly matrix. Klepin:Genentech Inc: Consultancy. Stock:Jazz Pharmaceuticals: Consultancy. Wildes:Janssen: Research Funding. Majhail:Incyte: Honoraria; Anthem, Inc.: Consultancy; Atara: Honoraria.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2018
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 3
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 2246-2246
    Abstract: Introduction: Despite data supporting the safety and efficacy of treatment for many older adults with AML, 〈 40% of adults aged ≥65 receive any leukemia-directed therapy. The reasons for why the majority of older patients with AML do not receive therapy are unclear. The use of objective fitness measures (e.g. physical function and cognition) has been shown to predict outcomes and may assist with treatment decision-making, but is underutilized. As most patients are initially evaluated in community practices, exploring clinical decision-making and the barriers to performing objective fitness assessments in the community oncology setting is critical to understanding current patterns of care. We conducted a qualitative study: 1) to identify factors that influence treatment decision making from the perspectives of the community oncologists and older patients with AML, and 2) to understand the barriers to performing objective fitness assessments among oncologists. The findings will help to inform the design of a larger study to assess real-life treatment decision-making among community oncologists and patients. Methods: We conducted semi-structured interviews with 13 community oncologists (9 states) and 9 patients aged ≥60 with AML at any stage of treatment to elicit potential factors that influence treatment decisions. Patients were recruited from the outpatient clinics in a single institution and oncologists were recruited via email using purposive samples (patients: based on treatment received and stage of treatment; oncologists: based on practice location). Interviews were audio-recorded and transcribed. We utilized directed content analysis and adapted the decision-making model introduced by Zafar et al. to serve as a framework for categorizing the factors at various levels. A codebook was provisionally developed. Using Atlas.ti, two investigators independently coded the initial transcripts and resolved any discrepancies through an iterative process. The coding scheme was subsequently applied to the rest of the transcripts by one coder. Results: Median age of the oncologists was 37 years (range 34-64); 62% were females, 92% were white, 38% had practiced more than 15 years, and 92% reported seeing 〈 10 older patients with AML annually. Median age of the patients was 70 years (64-80), 33% were females and all were Caucasian. In terms of treatment, 66% received intensive induction therapy, 22% received low-intensity treatment, and 11% received both. Three patients also received allogeneic hematopoietic stem cell transplant. Eighty-nine percent were initially evaluated and 56% were initially treated by a community oncologist. Factors that influenced treatment decision-making are shown in Figure 1. When making treatment decisions, both patients and oncologists considered factors such as patient's overall health, chronological age, comorbidities, insurance coverage, treatment efficacy and tolerability, and distance to treatment center. Nonetheless, there were distinct factors considered by patients (e.g. quality of care and facility, trust in their oncologist/team) and by oncologists (e.g. local practice patterns, availability of transplant/clinical trials, their own clinical expertise and beliefs) when making treatment decisions. The majority of oncologists do not perform an objective assessment of fitness. Most common reasons provided included: 1) Do not add much to routine assessments (N=8), 2) Lack of time, resources, and expertise (N=7), 3) Lack of awareness of the tools or the evidence to support its use (N=4), 4) Specifics are not important (e.g. impairments are clinically apparent and further nuance is not necessarily helpful; N=5), 5) Impairments are usually performed by other team members (N=2), and 6) Do not want to rely on scores (N=2). Conclusions: Treatment decision-making for older patients with AML is complex and influenced by many factors at the patient, disease/treatment, physician, and organizational levels. Despite studies supporting the utility of objective fitness assessments, these were not commonly performed in the community due to several barriers. Our framework will be useful to guide a larger study to assess real-life treatment decision-making in the community settings. We also identified several barriers raised by community oncologists that could be targeted to allow incorporation of objective fitness assessments. Figure 1. Figure 1. Disclosures Liesveld: Onconova: Other: DSMB; Abbvie: Honoraria. Stock:Jazz Pharmaceuticals: Consultancy. Majhail:Anthem, Inc.: Consultancy; Atara: Honoraria; Incyte: Honoraria. Wildes:Janssen: Research Funding. Klepin:Genentech Inc: Consultancy.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2018
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 4
    In: Blood Advances, American Society of Hematology, Vol. 4, No. 21 ( 2020-11-10), p. 5492-5500
    Abstract: Understanding decisional involvement and information preferences in patients with hematologic malignancies may help to optimize physician-patient communication about treatment decisions and align the decision-making processes with patients’ preferences. We described and examined factors associated with preferences of patients with hematologic malignancies for decisional involvement, information sources, and presentation of information. In a multicenter observational study, we recruited 216 patients with hematologic malignancies of any stage from September 2003 to June 2007. Patients were asked about their decisional involvement preferences (Control Preferences Scale), information sources (including most useful source of information), and preferences for their oncologists’ presentation of treatment success information. We used multivariate logistic regressions to identify factors associated with decisional involvement preferences and usefulness of information sources (physicians vs nonphysicians). Patient-directed, shared, and physician-directed approaches were preferred in 34%, 38%, and 28% of patients, respectively. Physicians and computer/Internet were the most common information sources; 42% perceived physicians as the most useful source. On multivariate analysis, patients with less than a college education (vs postgraduate education) were less likely to perceive their physician as the most useful source (adjusted odds ratio [AOR], 0.46; 95% confidence interval (CI), 0.21-1.00), whereas patients with acute leukemia (vs other blood cancers) were more likely to perceive their physician as the most useful source (AOR, 2.49; 95% CI, 1.07-5.80). In terms of communicating treatment success rates, 70% preferred ≥1 method(s), and 88% preferred presentation in percentages. Our study suggests that deci sional involvement and information preferences vary and should be assessed explicitly as part of each decision-making encounter.
    Type of Medium: Online Resource
    ISSN: 2473-9529 , 2473-9537
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2020
    detail.hit.zdb_id: 2876449-3
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