Das, Saurav

e19094 Background: WM/LPL is an indolent B-cell Non-Hodgkin Lymphoma with prolonged survival and predisposition to secondary malignancies (SM) influencing clinical outcomes and survivorship care. We evaluated the incidence, demography, treatment utilization, and outcomes of SM in patients with WM/LPL using population-based data. Methods: SEER-22 database was used to identify patients with LPL/WM diagnosed between 2000–2022 and stratified by SM. Overall survival (OS) was analyzed using Kaplan–Meier survival analysis and propensity score matched Cox regression was used to assess mortality risk. Hazard ratios were reported, with p<0.05 deemed significant. Results: 22,170 patients with WM/LPL were identified, with a median age of 71 years (IQR 16); the cohort was predominantly male (59.0%), White (84.0%), had a median household income of $50,000–$75,000 (48.9%), and resided primarily in urban areas (89.5%). Among all WM/LPL patients, 20.8% (n=4,615) developed a SM. Patients who developed SM were older than those without (median age 75 vs 70 years, p<0.0001) with 45.2% alive at predefined follow-up. The most common solid organ SM were gastrointestinal adenocarcinoma (16%), prostate cancer (14%), and lung adenocarcinoma (9%), while the leading hematologic SM were plasma cell myeloma (6%), diffuse large B-cell lymphoma (5%), and myelodysplastic syndrome (2%). 35.3% of the cohort received chemotherapy, while 0.1% received cancer-related surgery or radiation. On multivariable analysis, older age (OR 0.82, 95% CI 0.81–0.83), male sex (OR 0.59, 95% CI 0.44–0.80), urban residence (OR 1.99, 95% CI 1.24–3.18), and higher income (OR 2.16, 95% CI 1.13–4.15) were significantly associated with SM diagnosis. Kaplan–Meier analysis demonstrated inferior survival among patients with SM (54.8% vs 45.2%, p<0.0001), with shorter median OS (9 vs 14 years, log-rank p<0.001). Similarly, Propensity-matched analysis revealed worse OS in patients with SM (HR 1.15, 95% CI 1.09–1.22, p<0.001). Median OS varied substantially by SM site (see Table). Conclusions: Our study demonstrates a substantial burden of SMs among patients with WM/LPL and are associated with substantially inferior survival despite the indolent nature of the disease. The marked heterogeneity in SM types and outcomes highlights the need for risk-adapted surveillance, survivorship-focused care, and equitable strategies to address disparities and improve long-term outcomes in this population. SM Site Median OS (years) IQR p-value Hepatopancreatobiliary 1 0 <0.05 CNS 3.5 9 <0.05 Breast 3 6 <0.05 Colorectal 4 3.5 <0.05 Lymph Node 5 8 <0.05 Blood 6 7 <0.05 Lung 7 9 <0.05 Head & Neck 6.5 8.5 <0.05 Melanoma 9 10 <0.05 Urogenital 10.5 7 <0.05

e15708 Background: AFTT is characterized by physical, nutritional, and psychosocial decline. In GIC, AFTT arises from malnutrition, disease progression, or treatment-related toxicity resulting in poor quality of life. We evaluated the association between AFTT and IM, length of stay (LOS), and hospital charges (HC) in hospitalized GIC patients. Methods: The National Inpatient Sample (2016-21) was used to identify adult hospitalizations with GIC using ICD-10 codes, which were stratified as primary or secondary diagnoses by AFTT. Clinical characteristics and primary outcomes including IM, LOS, and HC were extracted. Multivariable regression models adjusting for demographics, insurance, comorbidity burden, census tract income, and hospital teaching status were evaluated. Results: Among 2,732,505 GIC hospitalizations, colorectal (46.9%) and pancreatic (20.4%) cancer predominated; 121,035 (4.4%) had AFTT. Patients with AFTT vs non-AFTT, were older (mean = 69.3 vs 66.5 yrs), more often male (58.1% vs 57%), and from the lowest income quartile (27.7% vs 26%). AFTT cohort had higher comorbidity burden (mean CCI = 7.24 vs 6.26), more Black patients (19.1% vs 12.8%), higher Medicare use (62.7% vs 56.0%), increased palliative care consultation (37.4% vs 13.6%), risk of malnutrition, AKI, and dementia (all p< 0.001). AFTT was associated with higher IM, longer LOS, and lower HC. Higher age, males, and self-pay were associated with increased IM and HC, but shorter LOS. Lower CCI was associated with reduced IM, LOS, HC, whereas urban hospitals showed lower IM but higher LOS and HC. Black patients had higher IM and LOS but lower HC, contrary to Hispanic patients. Conclusions: The grave impact of AFTT and variability in survival and practice patterns is driven multifactorially, raising concerns about inequitable care access and differences in healthcare utilization. Standardized guidelines and multidisciplinary interventions are urgently needed to combat AFTT in GIC. Predictor IM aOR (95% CI) LOS Adj. Ratio (95% CI) HC Adj. Ratio (95% CI) AFTT Status (vs. Non-AFTT) 1.96 (1.93-2.00) 1.13 (1.12-1.14) 0.86 (0.85-0.86) Age (/year increase) 1.02 (1.02-1.02) 1.00 (1.00-1.00) 1.00 (1.00-1.00) Sex (vs. Female) Male 1.18 (1.17-1.19) 0.99 (0.98-0.99) 1.05 (1.05-1.06) CCI Score (vs. High, ≥5) Low (≤2) Mid (3-4) 0.33 (0.32-0.33) 0.48 (0.47 - 0.48) 0.87 (0.87 - 0.88) 0.93 (0.93 - 0.94) 0.93 (0.93 - 0.94) 1.02 (1.02 - 1.02) Insurance (vs. Medicare) Private Medicaid Self-Pay 1.03 (1.01 - 1.05) Ref in model 1.29 (1.24 - 1.33) 0.92 (0.91 - 0.92) 0.96 (0.95 - 0.97) 0.98 (0.97 - 1.00) 1.03 (1.02 - 1.03) 1.06 (1.05 - 1.06) 0.96 (0.95 - 0.97) Race (vs. White) Black 1.03 (1.00 - 1.06) 1.07 (1.06 - 1.08) 0.95 (0.94 - 0.96) Facility Status (vs. Rural) Urban Non-Teaching Urban Teaching 0.87 (0.85 - 0.89) 0.78 (0.77 - 0.80) 1.10 (1.09 - 1.11) 1.18 (1.17 - 1.19) 1.64 (1.63 - 1.65) 1.86 (1.84 - 1.87)

e14111 Background: Primary CNSL (PCNSL) is a rare, aggressive B-cell non-Hodgkin lymphoma limited to the CNS, while secondary CNSL (SCNSL) represents CNS involvement from systemic lymphoma. Previous observations focused on CNSL have limited data clinically comparing PSNSL and SCNSL. We aimed to evaluate overall survival and associated factors in patients with PCNSL vs SCNSL using a large population database. Methods: We conducted a retrospective cohort study using the SEER-22 database to identify patients diagnosed with CNSL between 2020-2022. Group comparisons used t-tests or ANOVA for continuous variables, chi-square tests for categorical variables, and Kaplan–Meier survival analysis, with all analyses performed in RStudio 4.1.1 and significance deemed as p<0.05. Results: 14,964 patients with CNS lymphoma were identified, with 84.6% PCNSL and 15.4% SCNSL cases. The overall median age was 65 years (IQR 20), with 52% male, 66% White patients, residing in urban areas (90%) and median household income of $50,000–$75,000 (52%). Compared with PCNSL, patients with SCNSL were significantly older (72 vs 64 years, p<0.0001). SCNSL more frequently involved the cerebrum (39% vs 34%) and cerebellum (5.5% vs 4.5%), but less commonly affected the nerves (12.0% vs 12.5%) and spinal cord (4.2% vs 5.1%) (p<0.05). Disease was predominantly unilateral (95.8%) in both groups. Chemotherapy (55% vs 56%) and radiotherapy (19% vs 18%) utilization did not differ significantly, with external beam radiation comprising 94.3% of radiated cases. PCNSL patients were more likely to undergo surgical intervention than SCNSL patients (31.8% vs 28.7%; p=0.0027). Diffuse large B-cell lymphoma was the most common histologic subtype in both PCNSL (70.1%) and SCNSL (74.3%). Median overall survival was shorter in SCNSL (1.64 years) than PCNSL (1.99 years). Survival improved significantly across diagnostic eras (2000–2005 to 2016–2020; log-rank p<0.001), while lower income (<$50,000) and rural residence were associated with inferior outcomes (p=0.028 and p=0.033). Conclusions: Survival in CNS lymphoma remains poor, with SCNSL associated with worse outcomes compared with PCNSL. Greater understanding of treatment variation and disease differences is needed to optimize therapy and improve patient outcomes. Characteristic PCNSL SCNSL Total p-Value N 12667 2297 14964 Population Distribution 0.033 Urban 11426 2038 13464 Rural 1241 259 1500 Surgery 0.0027 Yes 3630 730 4360 No 9037 1567 10604 Months from Diagnosis to Rx(Mean, SD) 0.31 (0.86) 0.27 (0.65) 0.30 (0.83) 0.0077 Death Status <0.0001 Dead 8603 1772 10375 Alive 4064 525 4589 Overall Survival (in years, Mean, SD) 1.99 (2.85) 1.64 (2.31) 1.93 (2.77) <0.0001

Abstract Background: MM is the second most common hematologic malignancy, which despite significant therapeutic advancements, remains incurable. The complexity of MM and its intricate management creates substantial informational demands for patients navigating their care. Methods: A cross-sectional survey study (Mayo Clinic IRB # 25-004671) was conducted to assess MM patients’ awareness about disease basics. A voluntary English language survey (47 questions) encompassing multiple domains of patient MM awareness was administered (REDCap) via the patient EMR portal (Mayo Clinic) and MM support groups nationally. Responses were analyzed using descriptive and inferential statistics (R; Bluesky Statistics, V 10.3.4). Multiple model logistic regression was used for multivariate analysis using age (≤70 or &gt;70 yrs), gender, education (high school or less vs bachelor's and above), income (≤$74999 vs ≥$75000) and insurance status (private vs public). Results: The survey was completed by 2353 patients (pts) with 2177 MM (83.4% active, 16.6% smoldering) and 176 MGUS. Among MM pts median age was 63 yrs with 52.5% males, 91.5% white and 95.7% non-Hispanic. 17.5% had a prior diagnosis of MGUS and 20.2% of smoldering MM prior to MM, and 79.5% were not aware of MM prior to their own diagnosis. Majority (77%) depended most on their doctors to gain MM information but 24.3% reported not having sufficient discussion about MM at diagnosis. 31.2% were not sure what type of MM they had, 22.9% could not correctly report the cell of MM origin (plasma cell), 40.6% did not receive MM stage information at diagnosis, 45.4% were either unsure or reported wrong risk factors for MM and 22% were unsure or mistaken about MM symptoms. Majority (62.9%) did not understand genetic risk categories of MM, 32.3% did not report adequate understanding of MM tests and 31.9% did not understand the difference between response and remission. 57.5% reported not understanding about MRD status and 57.1% never had MRD testing. Majority (86.8%) felt they got adequate opportunity to participate in treatment decisions but only 54.2% felt confident in managing MM with their current knowledge and 28.2% had not discussed their prognosis although 77.7% wanted to know about it. Majority (64.4%) felt they had knowledge gaps about MM and its management. Multivariate analysis showed that females were less likely (OR 0.67) while those with public insurance were more likely (OR 1.35) to report receiving adequate information at diagnosis. Older pts (OR 0.55), males (OR 0.43), with lower education (OR 0.5), lower income (OR 0.5) and public insurance (OR 0.72) were less likely to identify the cell of MM origin correctly. These same groups were significantly less likely to be aware of types of MM as well. Older pts (OR 0.73), with lower education (OR 0.6), lower income (OR 0.77) and public insurance (OR 0.76) were less likely to be aware of MM genetic risk categories. Females (OR 0.81), with lower education (OR 0.68) and lower income (OR 0.63) were less likely to understand MM lab tests. Females and those with lower income were significantly less likely to report receiving adequate information about treatment options. Females reported that they did not get adequate opportunities to participate in treatment decisions (OR 0.65). Older pts, and those with lower income, lower education or public insurance were less likely to understand minimal residual disease (MRD) and all these groups were less likely to have had MRD testing. Those with lower income (OR 0.75) and lesser education (OR 0.72) felt less confident in managing MM with current knowledge. Older pts, females and those with lesser education, lower income and public insurance were also significantly less likely to have discussed about MM prognosis. Conclusion: This study demonstrates substantial basic knowledge deficits integral to managing and prognosticating MM among patients. Patients from unfavorable sociodemographic-economic groups were more likely to have awareness gaps and report lack of information which is integral to having adequate understanding of MM being provided to them. These findings highlight the critical need for structured, comprehensive educational interventions that address fundamental disease concepts to empower pts, overcome healthcare disparities, and engage pts in shared decision-making.

e13661 Background: MM survival has improved significantly, resulting in increased survivorship and caregiver burden and is crucial to understand the real-world impact of MM. We analyzed results from a large, prospective MM patient survey using ML models to identify key predictive factors for survivorship and caregiver burden. Methods: A 45-item questionnaire spanning sociodemographics, treatment preferences, symptom burden and caregiver impact was distributed to MM patients at Mayo Clinic and International Myeloma Foundation support groups. Questions about quality of life (QOL) and treatment satisfaction (TS) represented survivorship outcomes while caregiver workday loss (WL) and job loss (JL) were surrogates for caregiver burden. 6 ML models (multinomial, random forest (RF), XGB (XGBoost), k-NN, GBM, Naïve Bayes) with a training: testing cohort of 80:20 were used to predict each of the 4 outcomes independently, considering model accuracy, C-index, precision, recall, and F1 score (Table), and using R studio (V4.4.1) and Bluesky Statistics (V10.3.4). Results: 2,239 participants (54% male, 89% Whites) with median age 68 yrs completed the survey. 71% respondents had a college degree, 44% resided in Midwest states, 62% reported household income >$75,000, and 67% had Medicare/Medicaid. Median age at MM diagnosis was 67 yrs with 58% diagnosed within the past 5 yrs and 73% currently receiving MM treatment. 72% reported their spouse as the primary caregiver. XGB was the best predictive model for QOL with gender, household income, stem cell transplant, CAR-T therapy, support from medical staff, and symptom burden (pain, neuropathy, mental well-being) as significant predictors. The RF model was the best for TS with pain and neuropathy levels as the most impactful predictors. For caregiver burden, XGB was the best model for WL with gender, household income, CAR-T therapy, financial strain, lack of support from medical staff, self-workdays missed, self-job loss, and pain and neuropathy levels as significant predictors. For JL, RF was the best model with significant variables being workdays missed by self, increased healthcare needs, symptom burden (pain, neuropathy, and mental well-being), and restricted physical activity. Conclusions: Our study shows the significant impact of MM survivorship and efficiently identifies predictive factors associated with survivorship and caregiver burden from a large prospective dataset using validated ML models. These findings highlight the complex challenges from MM and provide contemporary ML methods to better understand their interplay such that a framework of real-world interventions can be developed. Outcome Best ML Model Accuracy C-Index Precision Recall F1 score QOL XG 0.996 0.996 0.996 0.997 0.996 TS RF 0.984 0.900 0.937 0.948 0.937 WL XGB 0.984 1.000 0.944 0.947 0.945 JL RF 0.989 0.800 0.829 0.848 0.835

Introduction: Therapeutic advancements for MM have led to improved patient survival, but notable differences in management exist. Novel treatment options are resource-intensive and require adequate patient awareness as well as consideration of patient preferences such that informed decision making is practiced. Despite this, detailed understanding of factors that impact patient decisions regarding healthcare choices, and potentially contribute to variability in healthcare utilization, are under-studied. Additionally, with improved survivorship, the medical, psychosocial, and financial burden of MM management needs to be better understood. Methods: An anonymous, online, 45-question English survey exploring demographics, social determinants of health, selected clinical characteristics, treatment preferences, and survivorship burden was distributed to MM patients within Mayo Clinic and to all International Myeloma Foundation (IMF) support groups. Descriptive statistics were utilized to document participant socio-demographic characteristics, selected treatment history, factors affecting their preferences, and MM survivorship burden. Results: A total of 2239 participants responded to the survey with 54% males, median age 68 years (range 21-95) and median age at MM diagnosis of 67 years. Non-Hispanic Whites (NHW) were the largest (89%) racial-ethnic group. Most participants (71%) had a college degree and 67% had Medicare or Medicaid as primary insurance. MM was diagnosed within 5 years in 58% and 73% were currently on MM treatment at the time of responding to the survey. Majority (76%) had never been on a clinical trial, 59% had received stem cell transplant, 8% had undergone CAR-T therapy and 8% had received Bispecific antibodies as part of their MM management. Majority (64%) preferred oral drugs while 19% preferred injections and 14% infusion therapy.17% had ≥4 healthcare visits per month for MM treatment, 91% used their personal vehicle as the mode of transport for these appointments and the median time to travel to the treatment facility was 30-minutes.Survey participants reported that &gt;10 days of work were missed per year due to MM management among 15% of the patients and 9% of the caregivers, while 15% reported suffering job loss related to MM management. Top factors for treatment decisions were physician recommendations (92%), effectiveness of treatment option (88%), understanding of the treatment(74%), side effects (57%), and family/caregiver input (38%). Psychological challenges and financial strain were reported by 38% and 18% of the respondents, respectively. Increase in healthcare needs since MM diagnosis were reported by 48% and majority reported ongoing symptom burden including fatigue (78%), pain (53%) and neuropathy (60%). Furthermore, of the participants with these symptoms, 67% reported that their fatigue was not relieved by rest, 73% reported their pain to be moderate to severe, and 29% reported their neuropathy to be moderate to severe. Only 42% reported being fully active with the rest reporting varying degrees of functional inabilities. Nearly half (47%) of the participants reported lack of interest or enjoyment in activities they used to like prior to MM diagnosis, however majority (74%) still reported “good” or “excellent” quality of life. A small number of participants reported lack of support from family and friends (4%), lack of support from their healthcare team (3%), difficulty accessing healthcare due to financial hardship (7%) or difficulty accessing healthcare due to job commitments (3%). Conclusions: Decision-making for MM treatment is complex and there are several factors that affect patients behavior. Improved survival in MM is associated with significant survivorship and caregiver burden which can also affect the patient's treatment choices for subsequent therapy. These factors must be addressed systematically to achieve equitable healthcare utilization, shared decision making, and optimal clinical, psychosocial and financial wellbeing of patients with MM.

Introduction: Ven is a BCL2 inhibitor that has shown clinical efficacy in RRMM patients (pts) particularly those that harbor t(11;14). Ven has been evaluated in clinical trials as a single agent, in combination with dexamethasone (dex), immunomodulatory drugs (IMiD), proteasome inhibitors (PI), and anti-CD38 monoclonal antibodies (MAb) yet its place in the therapeutic landscape remains in question. In this retrospective analysis, we aim to evaluate the real-world efficacy of Ven-based regimens in RRMM pts treated outside of a clinical trial across the 3-site MCCC. Methods: We retrospectively analyzed the medical records of pts with RRMM treated with Ven-based regimens between January 2015 and October 2023 at the MCCC. Refractoriness was defined by progression on or within 60 days of stopping treatment. Categorical variables were compared with Chi-square tests and continuous variables were compared with t-tests. Outcomes were estimated using the Kaplan-Meier method and curves were compared between the groups using log-rank tests. Results: 83 pts were included in the analysis. The median age was 71 (39-93), 63% were male, 93% were white, 27% had ISS III, 18% had high risk cytogenetics (HRCyto), 76% had t(11;14), the median prior lines of therapy (LOT) was 4 (1-15), 68% received ≥ 4 prior LOT, 87% received prior autologous transplant, 58% were triple-class refractory (TCR), 64%/23% were penta-drug exposed/refractory (PDE/R), 8% received prior BCMA-directed therapies (BDT), 58% received Ven+dex, 25% received Ven+PI +/-dex, 6 % received Ven+anti-CD38 MAb+/-dex and 11% received Ven+other. The median follow-up time from start of a Ven-based regimen was 29 months (mo). The median Ven dose was 800mg (20-1600) with 25% of pts receiving Ven ramp-up dosing. The overall response rate (ORR) to a Ven-based regimen was 58% and was 64% for pts with t(11;14) and 40% for pts without t(11;14); p=0.06. Ven-treated pts with HRCyto had inferior PFS (3mo) and OS (8mo) compared to patients who did not have HRCyto who had a PFS of 9mo (p=0.020) and OS of 80mo (p&lt;0.001). The ORR for TCR and PDR pts were 52% and 42%, respectively. No significant ORR differences were noted across the different Ven-based regimens (p=0.32). The median PFS for pts with t(11;14) was 10mo compared to 2mo for pts w/o t(11;14); p=&lt;0.001. The median OS for pts with t(11;14) was 80mo compared to 10mo for pts without t(11;14); p=0.001. Ven-treated pts who received 1-3 prior LOT has superior ORR, median PFS, and median OS; 89%, 25mo, and 99mo, respectively, compared to pts who received ≥4 prior LOT who achieved an ORR of 43% (p&lt;0.001), median PFS of 5mo (p&lt;0.001) and median OS of 25mo (p&lt;0.001). Ven-treated pts that were TCR had inferior PFS (5mo) and OS (26mo) compared to pts who were not TCR who achieved a PFS of 12mo (p&lt;0.001) and a median OS of 80mo (p=0.02).Ven-treated pts that were PDR had inferior PFS (4mo) and OS (22mo) compared to pts who were not PDR who achieved a PFS of 9mo (p&lt;0.001) and a median OS of 80mo (p=0.02).Ven-treated pts who received prior BDT (n=7) achieved an ORR of 29% and had a median PFS and OS of 2mo and 6mo, respectively on a Ven-based therapy. 59 pts received additional therapy in the post Ven-progression setting. The ORR to post-Ven progression therapies was 53% (n=31/59), the median PFS was 9mo and median OS was 35mo. The most common post-Ven progression regimens used were PI-based (n=16; ORR=56%), anti-CD38 MAb-based (n=14; ORR=50%), BDT (n=12; ORR=83%), selinexor-based (n=3; ORR=0%) with BDT resulting in highest ORR (p=0.048) and PFS (p=0.005). Conclusions: Ven-based regimens are effective in heavily pre-treated pts with RRMM however they are more effective when used within 1-3 prior LOT, in pts with t(11;14), and in pts without HRCyto, TCR or PDR MM. BDT appear to be the most efficacious therapies in the post-Ven progression setting.

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&lt;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&lt;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.

Abstract Multiple myeloma (MM) therapeutics have evolved tremendously in recent years, with significant improvement in patient outcomes. As newer treatment options are developed, stem cell transplant (SCT) remains an important modality that provides excellent disease control and delays the progression of disease. Over the years, SCT use has increased overall in the U.S., but two distinct gaps remain, including suboptimal use overall, and racial-ethnic disparities. We evaluated the National Cancer Database (NCDB) to study what sociodemographic factors might play a role within a given racial-ethnic group leading to disparate SCT utilization, such that targeted approaches can be developed to optimize SCT use for all. In nearly 112,000 cases belonging to mutually exclusive categories of non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), Hispanics, non-Hispanic Asians (NHA), and others, we found certain factors including age, comorbidity index, payor type, facility type (academic vs. community) and facility volume to be uniformly associated with SCT use for all the racial-ethnic groups, while gender was not significant for any of the groups. There were several other factors which had a differential impact on SCT utilization among the various race-ethnicity groups studied, including year of diagnosis (significant for NHW, NHB and Hispanics), income level (significant for NHW and Hispanics), literacy level (significant for NHW and NHB), and geographic location of the treatment facility (significant for NHW and NHA). The suboptimal SCT utilization overall in the U.S., suggests that there may be room for improvement for all, even including the majority NHW, while we continue to work on factors that lead to disparities for the traditionally underserved populations. This study helps identify sociodemographic factors that may play a role specifically in each group and paves the way to devise targeted solutions such that resource utilization and impact can be maximized.

SummaryThis phase II study evaluated time‐limited (24 cycles) treatment with ibrutinib and ixazomib in newly diagnosed (NDWM; n = 9) and relapsed/refractory (RRWM; n = 12) Waldenström macroglobulinaemia (WM). The overall response rate (ORR) was 76.2% (n = 16) in 21 evaluable patients with no patient achieving a complete response (CR). The median duration of treatment was 15.6 months, and after a median follow‐up time of 25.7 months, the median progression‐free survival (PFS) was 22.9 months. While the primary end‐point was not met (CR rate at any time) and 28.5% discontinued treatment due to toxicity, ibrutinib plus ixazomib led to a clinically meaningful ORR and PFS. Combined Bruton's tyrosine kinase (BTK) and proteasome inhibition merits further evaluation in WM.