Abstract: Introduction: Chimeric antigen receptor (CAR) T-cell therapy can lead to durable responses in patients with relapsed/refractory hematologic malignancies. Immune effector cell-associated neurotoxicity syndrome (ICANS) occurs in up to 64% of patients. There is concern that ICANS places patients at risk for longer-term cognitive impairment. This study examined changes in patients' perceived cognition from prior to CAR T-cell therapy to days 90 and 360 in patients diagnosed with non-Hodgkins lymphoma, as well as CAR T-cell therapy-specific risk factors (e.g., ICANS, cytokine release syndrome [CRS]) and non-specific risk factors (e.g., age, education) associated with changes in cognition. Methods: Patients' perceived cognition was assessed at baseline and at days 90 and 360 with the Everyday Cognition Questionnaire (ECog), that provides scores for global cognition (which includes subscales for memory, language, visuospatial abilities, planning, organization, divided attention), and satisfaction with cognition. Quality of life was scored using the Patient-Reported Outcomes Measurement Information System-29. Frailty was examined with the hand grip strength test. Cognitive reserve was examined with the Weschler Test of Adult Reading. Clinical variables were extracted from medical records. Demographic variables were self-reported by participants. Percentages of patients reporting clinically significant worsening, clinically significant improvement, and unchanged cognition over time were calculated. Piecewise mixed models were used to examine average change in perceived cognition from baseline to day 90 and from day 90 to day 360, as well as to explore potential risk factors of average change in global cognition. Risk factors included demographic (i.e., age, education) and clinical factors (i.e., grade & gt;2 CRS, grade & gt;2 ICANS, disease response at days 90 and 360, baseline grip strength, baseline cognitive reserve) as well as baseline quality of life variables (i.e., fatigue, physical function, pain, depression, anxiety). Results: A total of 118 participants provided data (mean age 61, 59% male, 86% diagnosed with large B-cell lymphomas, 87% received axicabtagene ciloleucel). At day 90, relative to baseline, 17% of participants reported worsened global cognition, 10% improved global cognition, and 73% no change in global cognition (Figure 1). At day 360, relative to baseline, 28% reported worsened global cognition, 11% improved global cognition, and 61% no change in global cognition (Figure 1). Piecewise mixed models indicated that from baseline to day 90, there were no changes on average in global cognition or in any cognitive domain (ps & gt;.05). In contrast, from day 90 to 360, participants reported, on average, worsened global cognition (p=.01), language (p=.04), visuospatial abilities (p=.04), divided attention (p=.03) and satisfaction with cognition (p=.01). At baseline, greater fatigue, anxiety and depression were associated with worse concurrent perceived cognition (p & lt;.01). From baseline to day 90, physical functioning was associated with worsening cognition such that participants with better baseline physical functioning reported better perceived cognition at day 90 relative to participants with worse baseline physical functioning (p=.05). No other risk factors (e.g., CRS, ICANS) were associated with changes in global cognition from baseline to day 90 or from day 90 to day 360 (ps & gt;.05). Post-hoc analyses indicated no differences in cognition by disease status at day 360 (ps & gt;.05). Conclusions: Results suggest that perceived cognition worsens on average beyond day 90, with patients reporting worse baseline physical functioning being at risk of worse perceived cognition by day 90. Results should be incorporated when preparing patients about what to expect when receiving CAR T-cell therapy. Further research is needed regarding objective neurocognitive performance after CAR T-cell therapy. Figure 1 Figure 1. Disclosures Barata: Grifols: Current holder of individual stocks in a privately-held company; Almirall: Current holder of individual stocks in a privately-held company. Gonzalez: SureMed Compliance Equity: Consultancy; Elly Health, Inc.: Consultancy. Kirtane: Oncternal Therapeutics: Current holder of individual stocks in a privately-held company; Seattle Genetics: Current holder of individual stocks in a privately-held company; Myovant Sciences: Current holder of individual stocks in a privately-held company; Veru: Current holder of individual stocks in a privately-held company. Jain: Kite/Gilead: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Mokhtari: Kite: Consultancy. Chavez: ADC Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: Speakers Bureau; AstraZeneca: Research Funding; Merck: Research Funding; Novartis: Consultancy; Epizyme: Speakers Bureau; BeiGene: Speakers Bureau; Kite/Gilead: Consultancy; Adaptive: Research Funding; Karyopharm Therapeutics: Consultancy; MorphoSys: Speakers Bureau; Abbvie: Consultancy. Lazaryan: Kadmon: Consultancy; Avrobio: Membership on an entity's Board of Directors or advisory committees; Humanigen: Membership on an entity's Board of Directors or advisory committees. Shah: Novartis: Consultancy, Other: Expenses; Pfizer: Consultancy, Other: Expenses; Amgen: Consultancy; Precision Biosciences: Consultancy; Kite, a Gilead Company: Consultancy, Honoraria, Other: Expenses, Research Funding; Pharmacyclics/Janssen: Honoraria, Other: Expenses; Acrotech/Spectrum: Honoraria; BeiGene: Consultancy, Honoraria; Incyte: Research Funding; Jazz Pharmaceuticals: Research Funding; Servier Genetics: Other; Bristol-Myers Squibb/Celgene: Consultancy, Other: Expenses; Adaptive Biotechnologies: Consultancy. Locke: Gerson Lehrman Group: Consultancy; Emerging Therapy Solutions: Consultancy; EcoR1: Consultancy; Cowen: Consultancy; Umoja: Consultancy, Other; Wugen: Consultancy, Other; Takeda: Consultancy, Other; Novartis: Consultancy, Other, Research Funding; Legend Biotech: Consultancy, Other; Janssen: Consultancy, Other: Scientific Advisory Role; Kite, a Gilead Company: Consultancy, Other: Scientific Advisory Role, Research Funding; Iovance Biotherapeutics: Consultancy, Other: Scientific Advisory Role; GammaDelta Therapeutics: Consultancy, Other: Scientific Advisory Role; Cellular Biomedicine Group: Consultancy, Other: Scientific Advisory Role; Calibr: Consultancy, Other: Scientific Advisory Role; BMS/Celgene: Consultancy, Other: Scientific Advisory Role; Bluebird Bio: Consultancy, Other: Scientific Advisory Role; Amgen: Consultancy, Other: Scientific Advisory Role; Allogene Therapeutics: Consultancy, Other: Scientific Advisory Role, Research Funding; Moffitt Cancer Center: Patents & Royalties: field of cellular immunotherapy. Jim: Kite pharma: Research Funding; Merck: Consultancy; Janssen Scientific Affairs: Consultancy; RedHill Biopharma: Consultancy.

Abstract: Background: Hematopoietic cell transplantation (HCT) survivors have a complex and multiphase recovery period. Health care delivery and psychosocial interventions for HCT survivors are challenging as many HCT recipients live great distances from the facility where they had their HCT. Therefore, identifying factors associated with a patient's capability to self-manage symptoms is an important focus of survivorship research. A patient's self-efficacy may be important for the successful management of major stressors associated with treatments and recovery. Here, we aimed to evaluate the impact of perceived self-efficacy on distress, quality of life (QoL), depression, and fatigue, and identify the factors associated with lower self-efficacy. Methods: This cross-sectional study analyzed baseline data from a randomized controlled internet based self-management intervention trial (INSPIRE, NCT01602211) in adult (age 18 and older) survivors 2-10 years post HCT. Patients with recurrence or subsequent malignancy requiring cancer treatment during the two years prior to enrollment, inability to read and understand English and lack of access to email and the Internet were excluded. Data included medical records and patient-reported outcomes (PROs) including Cancer and Treatment Distress (CTXD) with 6 subscales, Patient Health Questionnaire depression scale (PHQ-8), Short Form 12 Health Survey (SF-12) physical function (PCS) and mental function (MCS) scores, Brief Fatigue Inventory (BFI) and Health Self-Efficacy. Pearson correlations were used to test bivariate associations for self-efficacy with CTXD, SF-12, BFI, and PHQ8. General linear models were used to test the independent association for CTXD and SF-12 outcomes with self-efficacy, controlling for selected sociodemographic and treatment covariates. Tenability of statistical model assumptions were examined, and no remediation was necessary. Results: Total of 1078 HCT survivors were included in the analysis. Participants were 18 to 76 years (mean age 51), 53% male, and over 90% white and non-Hispanic. Only 16% reported living in a rural area. A majority received an autologous HCT (55%) and were less than 5 years from their first HCT (54%). Among the allogeneic HCT recipients, more than half (60%) had active chronic Graft-versus-Host (cGVHD) and nearly 40% were on active systemic treatment. The mean self-efficacy score was 3.01 (SD 0.49). Female gender (p=0.014), younger age at HCT, younger age at cGVHD presentation, moderate to severe currently active cGVHD (p=0.003) and household income less than $40,000 (p & lt; 0.001) were associated with lower self-efficacy. In bivariate analyses, self-efficacy was negatively correlated with mean total CTXD (r -0.5, p & lt;0.001) and each of the CTXD subscales including family strain (r -0.41, p & lt;0.0001), identity (r -0.37, p & lt;0.0001), uncertainty (r -0.5, p & lt;0.0001), interference (r -0.47, p & lt;0.0001), medical (r -0.36, p & lt;0.0001) and health burden (r -0.42, p & lt;0.0001). HCT survivors with higher self-efficacy also reported better physical (r 0.48, p & lt;0.001) and mental function on the SF-12 (r 0.57, p & lt;0.001). Moreover, self-efficacy was negatively correlated with symptoms such as fatigue (r -0.44, p & lt;0.001) and depression (r -0.48, p & lt;0.001). In a regression model investigating the impact of self-efficacy on CTXD controlled for demographics and disease characteristics , lower self-efficacy was independently associated with higher CTXD (beta -0.232; 95% CI (-0.294, -0.169), p & lt; 0.001) (Table 1). Moreover, there was a significant positive relationship between self-efficacy and both mental (beta 4.68; 95% CI (3.82, 5.54); p & lt;0.001) (Table 2) and physical (beta 2.69; 95% CI (1.74, 3.64); p & lt;0.001) (Table 3) components of QoL. Conclusion: Our study demonstrates that lower levels of self-efficacy reported by HCT survivors was independently associated with higher levels of symptoms such as fatigue and depression, lower QoL, and more cancer -related distress. Furthermore, self-efficacy is more likely to be impaired in females, younger adults, those with lower incomes, and survivors with active cGVHD. These findings support the value of self-management interventions focused on improving self-efficacy as having the potential to improve multiple symptoms and QoL in HCT survivors. Figure 1 Figure 1. Disclosures Farhadfar: Incyte: Consultancy. Jim: RedHill Biopharma: Consultancy; Janssen Scientific Affairs: Consultancy; Merck: Consultancy; Kite pharma: Research Funding. Majhail: Anthem, Inc: Consultancy; Incyte Corporation: Consultancy. Wingard: Merck: Consultancy; AlloVir: Consultancy; Celgene: Consultancy; Shire: Consultancy; Janssen: Consultancy; Cidara Therapeutics: Consultancy.

Abstract: Following up on single institution studies suggesting that engaging patients in exercise and/or stress reduction techniques during hematopoietic cell transplantation (HCT) improves functional status and quality of life, we conducted a randomized study through the Blood and Marrow Transplant Clinical Trials Network (BMT CTN). METHODS: Patients (n=711) at 21 US centers provided symptom and quality of life data at enrollment. They were randomized to 1 of 4 groups using a 2x2 factorial design, stratified by center and transplant type. Prior to HCT, each group received a 15 minute stress management training session or a 15 minute exercise training session, both, or neither, with trained personnel to discuss the importance of managing stress and/or keeping active during HCT. The 3 intervention groups were also given a DVD, pamphlet and diary to track participation in exercise and/or stress management. The trainer reviewed the goals of practicing the intervention, proper technique, identification of barriers and plans to overcome them. Exercise training also included calculation of target heart rate. The exercise goal was walking 3-5 times a week for at least 20-30 minutes at 50-75% of estimated heart rate reserve. The stress management goal was to use paced abdominal breathing, progressive muscle relaxation with guided imagery, and coping self-statements to decrease stress. The interventionists re-contacted patients at 30 and 60 days after HCT to review the training goals, discuss barriers and provide encouragement. The fourth group was a usual care control group. All groups received a DVD of general information about HCT. Participants provided self-reported assessments at 30, 60, 100 and 180 days after transplant. The primary endpoints were the physical (PCS) and mental (MCS) component subscales of the SF36 at day 100. The study was designed to have 85% power to detect a difference of 0.5 STD in the exercise or stress management groups on each of the two endpoints, maintaining an overall type I error rate of 0.05. Primary analysis was on an intention to treat (ITT) basis with values assigned to patients who died or otherwise did not provide information. Enrollment occurred from January 2011-June 2012. Results The groups were well-balanced for baseline characteristics. There were no differences in the primary endpoints of PCS and MCS at day +100 among any of the groups based on the ITT analysis (Table). Results were similar using other conditional and imputed methods. Higher PCS at day +100 was associated with higher PCS at enrollment (p 〈 0.0001), being employed (coefficient 1.85, p=0.01), and having an autologous transplant rather than a myeloablative allogeneic HCT (coefficient 4.47, p 〈 0.0001) or reduced intensity/non-myeloablative allogeneic HCT (coefficient 3.10, p=0.0003). There was no difference between the two types of allogeneic conditioning intensities (p=0.12). Higher MCS at day +100 was associated with higher enrollment MCS (p 〈 0.0001) and higher income (greater than $50,000, coefficient 3.3, p 〈 0.0001). Patients assigned to stress management training reported using these techniques more than those who did not get stress management training. Patients assigned to exercise training did not report greater exercise up to day 100 but this group did report greater activity at day +180 (p=0.04) and better PCS scores at day +180 (coefficient 1.84, p=0.02), although the effect was not significant (p=0.20) in a model including multiple imputation. There were no differences observed in overall survival, hospitalization days until day +100 or in other patient-reported outcomes, including treatment-related distress, sleep quality, pain, and nausea. Conclusions No improvements in functional status as measured by PCS and MCS at day +100 were evident between the groups. Functional status was highly associated with pre-transplant functioning and type of transplant but not with conditioning regimen intensity.TableDay 100 SF36 scoresExercise (n=358) Median (25th-75th)No Exercise (n=353) Median (25th-75th)p-valuePCS37.5 (19.7-46.7)39.7 (27.1-47.7)0.14MCS49.4 (27.3-57.7)50.1 (34.2-57.8)0.33Stress Management (n=356) Median (25th-75th)No Stress Management (n=355) Median (25th-75th)PCS37.8 (22.1-46.6)39.7 (25.7-47.9)0.21MCS50.7 (31.0-58.2)49.1 (30.5-56.8)0.30 Disclosures: No relevant conflicts of interest to declare.

Abstract: INTRODUCTION: Patient reported outcomes (PROs) including symptoms and health related quality of life (HRQOL) predict mortality in multiple cancers, such as myeloma, head and neck, lung and prostate cancer. The relationship of PROs with survival is not clear in hematopoietic cell transplantation (HCT). We tested three hypotheses about the relationship between HRQOL and survival after HCT: (1) Pre-HCT HRQOL (particularly physical HRQOL) reflects functional status and predicts survival after allogeneic (allo) HCT independently of traditional risk factors and indices; (2) Post-HCT change in physical HRQOL reflects the “toll” of the HCT and predicts subsequent outcomes, including survival, among early survivors; (3) Since autologous (auto) HCT is associated with lower risks for treatment-related morbidity and mortality, PROs may not be as predictive for this group. METHODS: We tested these hypotheses using data from the 711 participants in BMT CTN 0902 (sponsored by NHLBI and NCI, NCT 01278927), a randomized study of pre-transplant exercise and stress management training for patients undergoing auto or allo HCT. Because the primary analysis for BMT CTN 0902 did not show a significant effect for exercise or stress management training, intervention groups were combined for these analyses. However, auto and allo recipients were analyzed separately because of the expected substantial differences in the subsequent risks for morbidity and mortality in the two populations. The HRQOL measures used were the physical component score (PCS) and mental component score (MCS) from the SF-36, measured pre-HCT and at day 100. RESULTS: Among 310 alloHCT recipients with a median follow-up of 23 months, while there were no pre-HCT clinical covariates (including age, conditioning intensity, donor type, graft source, disease, disease stage) that predicted survival, pre-HCT physical HRQOL (PCS on the SF-36) was strongly prognostic for survival (HR for death of 0.72 per 10 points increase, 95% CI 0.60-0.85, p 〈 0.001) while pre-HCT MCS was not (HR 0.99, 95% CI 0.84-1.16, p=0.29). Survival estimates for the first, second, third, and fourth quartiles of baseline PCS were, respectively, 67%, 72%, 81%, and 91% at 6 months and 50%, 65%, 75%, and 83% at one year (Figure 1). Among the eight SF-36 subscales, higher pre-HCT Physical Functioning and General Health scores were strongly associated with better survival. Among day 100 survivors, the PCS change score from baseline to Day 100 was also strongly prognostic for subsequent survival after adjusting for pre-HCT PCS (HR 0.55 per 10 points improvement, 95% CI 0.42-0.72, p 〈 0.001) as was the MCS change score after adjusting for pre-HCT MCS (HR 0.70, 95% CI 0.56-0.89, p=0.003). In models that included patient age and the Hematopoietic Cell Transplantation-specific Comorbidity Index (HCT-CI), the EBMT Score, or the Disease Risk Index (DRI), the findings for both pre-HCT values and change scores remained statistically significant with similar hazard ratios, suggesting that PROs convey independent prognostic information for survival despite inclusion of traditional risk factors. Analyses of transplant-related mortality (TRM) in alloHCT recipients showed similar patterns. Higher pre-HCT PCS was predictive of lower TRM. Among patients alive and disease-free at day 100, PCS change score was also associated with lower TRM after adjusting for pre-HCT PCS (HR 0.28, 95% CI 0.17-0.47, p 〈 0.001) and the HCT-CI, EBMT and DRI; pre-HCT MCS and change in MCS did not predict TRM. Among autoHCT recipients (n=337), there were no pre-HCT clinical covariates that predicted survival. Pre-HCT HRQOL also was not prognostic of survival in autoHCT (physical PCS from the SF-36 p=0.82, mental MCS from the SF-36, p=0.56), nor were early changes in either the PCS or the MCS. CONCLUSION: In summary, among alloHCT recipients who participated in BMT CTN 0902, lower pre-HCT physical HRQOL and early decline in physical HRQOL were strongly predictive for worse overall survival and higher transplant-related mortality. These results suggest that patient-reported data are an important component of risk assessment and could assist in clinical decision-making. High-risk individuals could be targeted for different management strategies or more aggressive supportive care interventions to reduce treatment-related morbidity and mortality in this population. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.