Ahlstrom, Jennifer M.

Abstract Background: Social determinants of health (SDOH) are critical drivers of cancer care access and outcomes. In multiple myeloma (MM), access to cellular therapies including autologous stem cell transplantation and CAR-T therapy often depends on formal or informal caregiver support. Traditional SDOH measures (e.g., race, income, or education) are often used as proxies for access to care; however, these measures may overlook individual realities pertaining to cellular therapies where a caregiver is generally required. In response to feedback from a HealthTree Patient Advisory Board questioning the practice of inferring caregiver support, this study evaluated a simple survey question by a large cross-sectional survey. Methods: After development of a dedicated single-question (“What best describes your current caregiving support?”) through iterative feedback from the Patient Advisory Board and MM experts, four key answers were settled on: (1) cohabitation with dedicated caregiver(s) to support care (“family support”); (2) presence of non-cohabiting caregiver(s) to provide dedicated support (“external support”); (3) lack of dedicated caregiver, hence support is arranged when needed (“arrangeable support ”); or (4) lack of dedicated caregiver, hence finding any support is a struggle (“inadequate support”). We deployed this new demographic question from February through July 2025 through HealthTree. Responses were analyzed across SDOH variables using Fisher exact or chi square tests, and random forest classifiers were employed for predictive modeling. Results: Of 1231 respondents, 71% had dedicated caregivers (68%, n=839, with family support, and 3%, n=41, with external support). In contrast, 23% (n=287) of patients routinely arranged support while 5% (n=64) had inadequate support (struggle to find support). The inadequate-support group had significant demographic differences from the sample as a whole: a higher proportion were women (78% vs 56%, p = 0.04), Black (9% vs 4%, p < 0.01), lived >50 miles from their treatment center (17% vs 6%, p < 0.01), and had an annual income <$50,000 (17% vs 6%, p = 0.02). This group had a numerically higher proportion of patients whose employment status was disabled (12% vs 5%, p=0.08) as well. No proportion difference in age (67 ± 9 yr), military status, or severity of diagnosis - precursor disease (17%) v. multiple myeloma (81%). Rates of inadequate support were overall low in patients who lived with only their spouse (1%) or lived with their spouse & children (3%). In contrast, rates of inadequate support were higher (than 5%) in patients who lived alone (21%), divorced (20%), lived with adult children (14%), lived with friends (13%), separated (11%), or widowed (9%) (p < 0.001). However, the arrangeable-support group comprised 12% of patients who lived only with their spouse, 19% of patients who lived with their spouse and children, and 61% of patients who lived with their adult children (p < 0.001). Finally, a random forest classifier failed to identify any individual in the inadequate-support category, suggesting that unmeasured or more complex patterns may underlie this classification. Conclusions: To our knowledge, this is the largest analysis of caregiver support and its relationship with other SDOH in patients with MM to date. Despite the importance of caregiving to transplantation and CAR-T therapy, we found that 5% of patients with MM struggle to find caregiver support; this figure likely underestimates the true prevalence, given potential selection bias among patients who are digitally engaged through the HealthTree platform. Even among patients who lived with their spouses, an additional 10-20% of patients routinely had to arrange caregiving support on a visit-by-visit basis; for patients who lived with their adult children, this proportion was over 60%. The requirement to arrange caregiving support can create time toxicity and financial toxicity for patients, although these factors were not directly queried in our study. Finally, caregiver availability cannot be routinely inferred from traditional SDOH variables. Our data highlight the importance of including caregiver status as a standard demographic question in clinical and research settings. Further interventions are needed to improve caregiver support for vulnerable patients with MM as well as to reduce the duration of caregiver requirements for procedures such as CAR-T therapy.

Abstract Introduction Detecting genetic abnormalities is mandatory during diagnostic workup and for potential individualization of therapy selection in multiple myeloma (MM) and its precursor conditions. At present, this requires invasive bone marrow (BM) biopsies, severely limiting early detection, patient monitoring, and the precise selection of therapy. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect point mutations and other clinically relevant alterations. Consequently, the IMS-IMWG guidelines were recently updated to require next-generation sequencing for the classification of high-risk MM. Moreover, the importance of identifying alterations in therapeutic targets (e.g., BCMA, GPRC5D) for guiding immunotherapies is becoming increasingly recognized. To address this need, we recently launched GenoPredicta, a CLIA-approved Laboratory Developed Test that enables routine monitoring, informing diagnosis, and treatment selection by comprehensively and robustly characterizing MM genomes with whole genome sequencing (WGS) from a minimum of ~50 circulating tumor cells (CTCs) isolated from peripheral blood (PB) or tumor cells from BM. Here, we describe the characterization of clinical and research samples with GenoPredicta, highlighting resistance-conferring genetic alterations that can only be detected by sequencing and that are consistent with patients' clinical histories, while further demonstrating the complete concordance of GenoPredicta with prior FISH results. Methods Tumor cells were isolated from BM and/or PB samples using fluorescence-activated cell sorting (FACS) (after CD138+ enrichment for PB) and subjected to whole genome sequencing (WGS), from which we identified copy number alterations, structural variants, and single nucleotide variants and indels. For a subset of samples, the BM was also characterized by FISH, using a standard clinical panel for characterizing MM; for other samples prior FISH results were available from patients' clinical records. Results The analytical validation of GenoPredicta, conducted on a retrospective cohort of >60 viably frozen samples from >30 patients, showed complete concordance between BM and PB for detected genomic abnormalities, with all clinically relevant events (11 translocations and 125 CNVs) observed in BM recapitulated in PB (100% recall). All events identified by FISH in 14 samples (8 translocations and 30 CNVs) were also identified in the BM (100% recall), with 50 translocations and 30 CNVs not detected by FISH also absent in the WGS data (100% precision). The abnormalities detected in these samples also included multiple high-risk events not assayed by FISH, including biallelic TP53 loss (Del 17p coupled with a deleterious TP53 mutation, observed in 4 patients) and MYC::IGL translocations (2 patients). Moreover, for all fresh peripheral blood clinical samples with FISH results available from patients' histories, GenoPredicta recalled 100% of reported events. Among these clinical samples, we notably observed a case with both a biallelic GPRC5D deletion and a TNFRSF17 (BCMA) deletion combined with a truncating mutation on the remaining allele. This was consistent with the patient's clinical history showing progression after therapy with talquetamab (anti-GPRC5D bispecific), and previous nonresponse to teclistamab (anti-BCMA bispecific) after prior therapy with Cilta-cel (BCMA-directed CAR T). GenoPredicta also detected other mutations likely to confer resistance to immunotherapies, including loss-of-function mutations in IKZF3 and deletions of FCRL5 in frozen peripheral blood research samples. Conclusion We demonstrate that WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis and monitoring, with blood-based measurements enabling comprehensive profiling of the myeloma cancer genome. Importantly, this includes genetic alterations that confer resistance to therapy, allowing for both early detection of such alterations and more precise selection of therapy.

Introduction: Light-chain amyloidosis (ALA) is a rare plasma cell disorder characterized by multiorgan involvement. Patients often present with non-specific symptoms, which can lead to a delay in diagnosis. This is associated with progressive organ involvement and shorter survival. Reducing the time from symptom onset to diagnosis is a critical step in improving outcomes. This study was designed to evaluate the clinical prodrome and challenges associated with the diagnosis of ALA from the patient perspective. Methods: This retrospective study surveyed patients with ALA through the online HealthTree® Cure Hub platform, which helps patients navigate their disease in a holistic way. The survey consisted of 32 questions, including 23 multiple-choice, 7 date-entry, and two free-response questions. Data on diagnosis and demographics were extracted from the electronic health record and self-reported data linked to HealthTree® Cure Hub. Results were reported as numbers and percentages, and comparisons were made by age (≥70 vs. <70 years) and sex. The following statistical methods were used: Fisher's exact test for categorical data, two-sample t-test and F-test for normally distributed continuous data, Wilcoxon rank-sum test for skewed data and Spearman correlation coefficient. Results: We surveyed 248 patients. Of those, a total of 87 patients with a self-reported diagnosis of ALA completed the questionnaire between March 12, 2023, and May 8, 2024. The median age was 66 years; 55% were female, and 91% were white. The most common initial symptoms prompting patients to seek medical evaluation were fatigue/weakness (47%), swelling (38%), shortness of breath (28%), chest pain (23%), and foamy urine (22%). Pain in hands/feet, carpal tunnel syndrome, loss of appetite, hoarseness, macroglossia, diarrhea, periorbital puffiness, nail changes, and erectile dysfunction each accounted for <10% of cases. Signs and symptoms were first detected by patients themselves in 58% of cases, by a physician in 33% and by a family member or friend for the rest. The median number of symptoms per individual was 2; 31% reported only one symptom, 37% 2-3, 18% 4-6, and 14% >6; with chest pain being the most common (39%), followed by swelling (22%), shortness of breath (13%), and foamy urine (13%); one patient reported erectile dysfunction and another reported arrhythmias as their only symptom. There was a correlation between hoarseness and nail changes (ρ=0.71), and carpal tunnel syndrome and orthostatic hypotension (ρ=0.63). Only 16% were aware of ALA as a condition prior to symptom onset. Thirty six percent presented to a general practitioner for initial evaluation; about 50% sought a specialist, including a myeloma/amyloid specialist (21%), and 14% were first evaluated in the emergency department. While most patients (45%) were diagnosed by a hematologist/oncologist, patients reported seeing a median of 3 physicians (range: 1-10) before the diagnosis was established. Among responders, 61% reported having myeloma at the time of testing. After diagnosis, about 50% were referred to a center specialized in ALA, and 72% met with a stem cell transplant specialist. Most patients reported receiving multidisciplinary care, with a median of 3 additional specialists participating in ALA care (range: 0-16). More than half of patients (59%) felt the diagnosis was delayed; among those, 42%, 24%, 24%, and 11% reported a delay of 1-6, 7-12, 13-24, and >24 months, respectively. The proportion of patients reporting >12-month delay was higher among older patients (54% vs. 27%, P=0.02). A quarter of responders felt their treatment was delayed. Half of patients felt the diagnostic delay contributed to a decrease in treatment efficacy and 48% did not feel that all medical professionals were knowledgeable about ALA. Only 38% felt the diagnostic process was simple and easy within their healthcare system. Conclusion: Most patients with AL amyloidosis initially present with non-specific symptoms, with fatigue/weakness being the most common. Over a third were evaluated first by a general practitioner, and about a third reported a diagnostic delay of >12 months. The diagnostic process is associated with high healthcare utilization, even among patients with concurrent multiple myeloma. Increasing disease awareness among patients and medical providers may shorten the time to diagnosis and contribute to improved outcomes.

Introduction Talquetamab (Tal) is a bispecific antibody therapy approved for patients with relapsed/refractory multiple myeloma (MM), targeting both GPRC5D x CD3 receptors. Clinical studies demonstrate that Tal creates deep and durable responses, but less is known about the patient experience. This study aimed to explore the experiences of patients from the patient and physician perspectives to help understand what to expect with this first-in-class novel therapy. Methods This qualitative study consisted of two components. First, patients with documented use of Tal were identified and recruited through the HealthTree Cure Hub. Individual patients then took part in 2-hour, semi-structured virtual interviews. Patients were asked to discuss their experiences 1-2 months prior to starting Tal and 4-5 months after beginning therapy. Patients discussed GPRC5D-related symptoms (including oral, skin-related, and nail-related symptoms), overall impact, and satisfaction. Participants were US adults diagnosed with MM who took Tal for at least 4 months, either in a clinical trial or commercial setting. Interviews were conducted February-April 2024. Second, patients and physicians gathered in a facilitated roundtable discussion to review findings and generate ideas for symptom management. The roundtable lasted 2.5 hours and took place in Chicago, IL in May 2024. Results Eight men and 4 women (n=12) aged 52-79 years participated in the interviews. Interviewed participants were mostly white (84%) and college-educated (84%). Seven (58%) received Tal in a clinical trial, and 9 were still receiving Tal. Roundtable participants included 3 patients (2 male, 1 female; all white and college educated), and 3 physicians with Tal experience. In the interviews, patients reported high overall satisfaction, with most (75%) rating their satisfaction an 8 or higher on a 10-point scale. Satisfaction was largely driven by the effectiveness of therapy, with all reporting clinical improvements in their MM disease. Patients reported improvements in their energy/strength and decreased fatigue. They also reported increased physical activities and ability to work, volunteer, or engage in hobbies. Physicians affirmed these findings as consistent with their observations and noted they are also very satisfied with Tal. Oral symptoms such as distorted taste/loss of taste and dry mouth were common with varying severity. Although all interviewees (n=12) reported taste symptoms (typically starting within the first month of therapy), five said their symptoms fully improved (3 after 1 year on treatment, and 2 after stopping treatment), and 4 experienced partial recovery. Ten lost weight, but most (92%) maintained adequate nutrition. Patients and physicians suggested coping strategies including diet modifications, use of strong flavors (e.g., spices, cinnamon), monitoring weight, prioritizing adequate calories, using mouthwashes/lozenges, drinking water while eating, taking small bites, and consuming foods that are easier to swallow. They also noted that it is important to educate patients on expected symptoms before starting the treatment. Skin- and nail-related symptoms were also common but less impactful on quality of life. All patients (n=12) experienced skin- and nail-related symptoms, but most considered these symptoms mild. Skin-related symptoms such as dry skin and skin exfoliation occurred once and typically lasted 1-2 months. Nail symptoms were primarily cosmetic, and the duration varied. Suggested management strategies include skin moisturizers, nail thickeners/hardeners, keeping nails short, and wearing protective gloves. Physicians noted it's helpful to reassure patients that nail loss is not harmful. Overall, GPRC5D-related symptoms were not treatment-limiting, and no patients had to miss a dose due to these symptoms. Patients perceived these symptoms as bearable but noted the treatment was effective at controlling the disease. Conclusions This study described patient experiences and reflected how patients perceive the benefit/risk profile of talquetamab. Symptoms were perceived as bearable and high satisfaction scores were driven by strong clinical effectiveness. Patients and physicians agreed that real-world feedback from patients, practical tips, and management strategies are vitally important for patients and physicians using this novel therapy.

Introduction: Understanding patient preferences and decision-making processes is crucial in managing relapsed multiple myeloma (RRMM). Shared decision-making has become a key element of patient-centered care, allowing patients to collaborate with healthcare providers in choosing treatments that align with their health and quality of life goals. This study examines how the perceived severity of treatment side effects influences patient decision-making autonomy and communication patterns, providing insights into decision-making practices in hematology. Methods: A survey was conducted with 784 RRMM patients as of January 1, 2024, using HealthTree Cure Hub (PMID: 35271305). Among the participants, 333 experienced a relapse and responded to the question about how side effect severity affected their treatment choices. Of these, 54% (n=181) considered side effects to be very or extremely influential (VE), whereas 46% (n=152) regarded them as somewhat, slightly, or not influential at all (SSN). Participants evaluated these factors on 5-point Likert scales: 1 (very poor) to 5 (very good); 0 (not at all influential) to 4 (extremely influential). The survey assessed patient involvement in final treatment decisions, discussions with fellow patients, family or caregivers, and the time allocated and used for decision-making. Results: Patients in the VE group reported a better understanding of the likely side effects of treatment options compared to the SSN group (VE: 3.9±1.0; SSN: 3.6±1.0, p<0.05), with a higher proportion reporting a very good understanding (VE: 31%, n=45; SSN: 18%, n=29, p=0.036). A weak relationship confirmed VE patients engaged in additional side effect education before making a change in treatment decisions (r=0.164, p=0.004). VE patients also reported a better understanding of the balance between effectiveness and potential side effects of treatments than SSN patients (VE: 3.8±1.0; SSN: 3.5±1.1, p<0.05), with more VE patients reporting a very good understanding (29%, n=41 vs. 15%, n=24, p=0.006). A weak relationship confirmed that VE patients more closely evaluated the trade-offs of treatment options when choosing a new treatment regimen (r=0.197, p<0.001). Likely to achieve a better understanding, more VE patients talked with fellow patients (VE: 19%, n=24; SSN: 7%, n=11, p = 0.003) and rated these conversations as more influential than SSN (VE: 1.5±1.5; SSN: 1.1±1.4, p<0.05). Additionally, VE patients were more likely to discuss treatment options with family or caregivers before making a final decision (VE: 49%, n=61; SSN: 29%, n=43, p<0.05). Moreover, VE patients reported greater involvement in their doctor-patient communication approach (VE: 3.2±0.8; SSN: 2.8±0.8, p<0.05), with scores ranging from 1 (“...follow the doctor's suggestions”) to 4 (“...we discuss my preferences... and I make the final decision”). Furthermore, VE patients reported more self-determination in the treatment decision-making process than SSN patients, with more VE patients making the final treatment decision themselves rather than having their doctor decide (“I made the final decision” - VE: 66%, n=93; SSN: 52%, n=81; “My doctor made the final decision” - VE: 34%, n=47; SSN: 46%, n=72, p=0.013). VE patients reported being provided 1.5 more weeks of time to make a treatment decision than the SSN (4.8±8.9 v. 3.3±6.0 wks, p<0.05). Subsequently, VE patients reported using 79% more time than SSN patients to arrive at a final decision (VE: 2.5±6.0; SSN: 1.4±1.9 wks, p<0.05), likely attributed to time spent gaining a better understanding, having more conversations with patients and family, more shared decision making and self-determination in their treatment decision. Conclusion: The study highlights that RRMM patients who consider side effects to be very or extremely influential in their treatment decisions report being more proactive in understanding and discussing their treatment options. These patients engage more with healthcare providers, peers, and family members and are granted more time to make informed decisions. This emphasis on understanding and communication underscores the importance of personalized patient education and shared decision-making in the treatment of RRMM, especially for patients who are highly influenced by potential side effects. Together, these findings underscore the ongoing need for patient-centered care and education to optimize treatment choices.

Introduction: As therapeutic options for cancer increase at an unprecedented rate, understanding patient's awareness and attitudes is imperative to optimize their participation in shared decision making. Patient surveys are a powerful tool to gain insight into patient awareness but are cumbersome to administer on a large scale. With the advent of technology and virtual care, electronic surveys are being utilized more widely but their validity compared to approaching the patients in-person has not been established. We conducted a survey regarding awareness and preferences for clinical trials in-person and electronically and compared results systematically in a matched cohorts of patients with MM. Methods: A 52-question survey (including the domains: knowledge, trust, fear, external influence and optimism) was administered in-person to cancer patients at Mayo Clinic campuses (NCT04630431), of which patients with MM were identified for this analysis. The same survey was administered to MM patients enrolled in the online portal HealthTree® Cure Hub. Observations from the in-person and online cohorts were matched and weighted based on coarsened exact matching utilizing the “MatchIt” package based on age, gender, race, ethnicity, education, and marital status. Question responses were converted to an agreeance score scaled from 1 (Strongly Disagree) to 5 (Strongly Agree). Mean and standard deviation measurements were calculated. Weighted t-tests were conducted using these numeric scores and the matched weights. Results: Final matched cohorts included 83% (n=65) of the in-person and 69% (n=149) of the online participants. Mean age was 63.5 (± 8.5) years with 52% females for in-person vs. 65.9 (± 7.5) years and 54% females in the online participants. In-person cohort included 83% White, 14% Black and 12% Hispanic participants while online cohort had 94% White, 5% Black and 13% Hispanics/Latinos. Education level with 4-year degree or higher was reported by 66% in-person and 75% online participants. Both cohort respondents on average rated a strong likelihood of participating in a clinical trial (in-person 4.04, CI: 3.73-4.35; online 4.34, CI: 4.19-4.5). There was significant agreeance between the 2 cohorts on majority of the questionnaire domains. For basic knowledge about clinical trials, while none of the individual questions in the category were significantly different, the online group had a higher aggregate agreeance score of 3.91 vs. 3.73 for the in-person group with a significant difference of 0.18 (CI: 0.5-0.31, p=0.008). For external influence, the online group had a higher aggregate agreeance score (3.52) than the in-person group (3.15; Difference: 0.37, CI: 0.22-0.52, p<0.001), with the only question-level significant difference being for the question that regulatory agencies effectively control what is being advertised by the pharmaceutical industry (4.46 ± 0.64 vs. 3.48 ± 0.76, p<0.001). Conclusions: Online surveys are an effective tool for gaining insight into patient understanding, attitudes and awareness on a variety of topics and can be conducted efficiently on a larger scale than in-person studies, which may be more time and resource intensive. Our study provides evidence of general agreeance between a matched cohort of in-person and online survey respondents, providing validity to carefully conducted, planned online survey tools. The online cohort in our study overall had better knowledge about clinical trials and a better understanding about external influences on available clinical trial result information. These results will help boost studies to collect patient-level responses such that their beliefs and awareness can be better understood and incorporated in optimizing healthcare resource utilization.