Wood, William A.

1564 Background: Physical function (PF) is a core outcome in cancer trials that can inform treatment tolerability. PF can be assessed across modalities including by patient (pt) report, clinician (clin) report, performance tests and digital sensors. The optimal approach for PF measurement has not been defined. Methods: In4M is a prospective observational study evaluating PF in pts initiating chemotherapy for breast cancer or lymphoma followed over 9 months. We used an electronic platform (Hugo) to aggregate serially assessed pt-reported PF, clin- and pt-reported ECOG performance status (PS), 6-minute walk test (6MWT) and wearable (Fitbit) data. We evaluated feasibility in all pts; associations among PF measures and the ability of PF measures to detect change were evaluated in pts with both baseline (BL) and 3-month (3M) data. We used Pearson correlations to assess the relationship of average daily steps with measures of PF. To assess change, we compared each PF measure from BL to 3M using a 2-sided α=.05 paired t-test. Results: Of the208 pts enrolled, 193 (93%) and 159 (76%) completed surveys, and 121 (58%) and 124 (60%) provided wearable data (evaluable: ≥1 day data) at BL and 3M, respectively. When requiring a stringent BL with 4+ days of data with ≥1 weekend day to be evaluable, 88 (42%) and 120 (58%) provided wearable data at BL and 3M. At both BL and 3M, pt-reported PF was generally more highly correlated with wearable-derived daily steps than clin-reported PF and 6MWT were (Table). Significant declines in PF were observed for pt- and clin-reported PF (all p<0.05), but not other modalities. Conclusions: Longitudinalassessment of multi-modal PF data including pragmatic wearable data collection was feasible in pts receiving chemotherapy. Pt-reported PF was the only modality that was both correlated with step count and able to detect change. Additional wearable metrics, correlations among PF measurements and outcomes, and clinically meaningful change scores will be reported. Optimal PF measurement may improve future reporting of treatment tolerability. Clinical trial information: NCT05214144 . [Table: see text]

Abstract There has been an increase in volume as well as an improvement in overall survival (OS) after hematopoietic cell transplantation (HCT) for hematologic disorders. It is unknown if these changes have affected racial/ethnic minorities equally. In this observational study from the Center for International Blood and Marrow Transplant Research of 79 904 autologous (auto) and 65 662 allogeneic (allo) HCTs, we examined the volume and rates of change of autoHCT and alloHCT over time and trends in OS in 4 racial/ethnic groups: non-Hispanic Whites (NHWs), non-Hispanic African Americans (NHAAs), and Hispanics across 5 2-year cohorts from 2009 to 2018. Rates of change were compared using Poisson model. Adjusted and unadjusted Cox proportional hazards models examined trends in mortality in the 4 racial/ethnic groups over 5 study time periods. The rates of increase in volume were significantly higher for Hispanics and NHAAs vs NHW for both autoHCT and alloHCT. Adjusted overall mortality after autoHCT was comparable across all racial/ethnic groups. NHAA adults (hazard ratio [HR] 1.13; 95% confidence interval [CI] 1.04-1.22; P = .004) and pediatric patients (HR 1.62; 95% CI 1.3-2.03; P &lt; .001) had a higher risk of mortality after alloHCT than NHWs. Improvement in OS over time was seen in all 4 groups after both autoHCT and alloHCT. Our study shows the rate of change for the use of autoHCT and alloHCT is higher in NHAAs and Hispanics than in NHWs. Survival after autoHCT and alloHCT improved over time; however, NHAAs have worse OS after alloHCT, which has persisted. Continued efforts are needed to mitigate disparities for patients requiring alloHCT.

Introduction: Allogeneic hematopoietic cell transplantation (HCT) remains the only therapy for long-term disease control for many high-risk hematologic malignancies (HM). HCT use in older HM patients (pts) continues to increase. However, concerns of excessive transplant-related morbidity and non-relapse mortality (NRM) limit referrals and broader application of curative intent HCT. The HCT-comorbidity index (HCT-CI) was initially developed to improve risk-stratification of NRM. More recently, geriatric assessment (GA) and biomarkers have emerged as promising additional tools that may refine estimates of these risks. We hypothesized that a combination of health assessments by GA and biomarkers would constitute a robust and valid model, CHARM, for accurate personalized estimation of one-year (1-yr) NRM. Here, we report the results of the largest, first of its kind, prospective study of older recipients of HCT through the Blood and Marrow Transplant Clinical Trials Network (BMT CTN) 1704 study (NCT03992352). Patients and Methods: Adults aged ≥60 years (yrs) with HM institutionally eligible for HCT were enrolled (n=1226) from 49 centers in the US between 2019 - 2021. Within 21 days of conditioning, 13 prospectively identified older pt.-specific health variables, informed from prior studies, were collected: age, HCT-CI, % of weight loss over the past yr, pt reported Karnofsky performance status, PROMIS physical function scale, instrumental activities of daily living (IADL), number of falls, PROMIS depression scale, number of prescribed medications, 4-meter walk speed, cognition by the Montreal Cognitive Assessment (MoCA), C-reactive protein (CRP) and albumin. The CHARM score to predict NRM within 1 yr was built using a multivariable (MVA) Fine-Gray model, with multiple imputation to handle modest missingness in covariates and grouped penalized variable selection using SCAD to identify variables to retain in the model. Final variables were used as continuous. The model further considered adjustment for conditioning intensity, CMV serostatus, and donor type. Area under the ROC curve (AUC) was calculated to validate the CHARM and compare to HCT-CI alone, with bootstrap sampling to correct for optimism in the within-sample AUC. MVA of overall survival (OS) within 1 yr used the CHARM score and adjusted for other significant variables derived from stepwise regression. Results: The primary analysis included 1105 pts who were confirmed eligible and proceeded to transplant. Median age was 67 (range 60-82) and 32% were ≥ 70 yrs. AML (45%) and MDS (30%) were the most common indications and matched donors the most frequent donor type at 72%. Reduced intensity conditioning with fludarabine (flu)-melphalan (38%) and flu-busulfan (20%) were the most common regimens. Baseline geriatric vulnerabilities among evaluable pts were frequent including slow walk speed (&lt;0.8 meter/second) in 22%, any IADL limitation in 37%, and cognitive impairment (MoCA &lt; 23) in 12%. 1-yr NRM was lower than expected at 14.4% with 1-yr OS of 72%. In the MVA model, albumin, CRP, HCT-CI, and weight loss were independently associated with NRM (Table) and comprised the CHARM. Of note, increasing age did not significantly affect NRM. The CHARM had within sample and bootstrap corrected AUC of 0.641 and 0.607 whereas the HCT-CI alone achieved corresponding AUC values of 0.601 and 0.598. NRM by tertiles is shown in Figure. Each point increase in the CHARM (median -2.2504, range -3.6327 to 0.1381), was associated with a hazard ratio (HR) of 2.83 (95% CI 2.12 - 3.78, p &lt; 0.0001) for NRM. The CHARM also predicted overall mortality within 1-yr with a HR of 2.04 (1.65- 2.53, p &lt;0.0001) per one point increase, independent of the disease risk index, which had a HR of 1.5 (95% CI 1.12 - 1.99, p =0.0059) for high/very high vs low/intermediate categories. Conclusions: We report on the first prospectively established tool, CHARM, to risk-stratify older adult HCT comprised of simple and readily available parameters in transplant and oncology clinics. Adopting CHARM in practice may promote HCT referrals and access for older pts, given low risks of NRM among CHARM lower 2/3 rd tertiles. Identifying high-risk CHARM pts pre-HCT will promote developing novel strategies to reduce NRM. Further analysis of the impacts of the 13 health assessment variables on geriatric morbidity such as disability trajectories is in-process.

Introduction Public reporting of outcomes drives healthcare improvement in many fields, including hematopoietic cell transplantation (HCT), although with possible unintended consequences. The Center for International Blood & Marrow Transplant Research (CIBMTR) publishes an annual Center-Specific Survival Analysis (CSA), which compares HCT centers' observed 1-year overall survival (OS) with their statistically modeled expected 1-year OS, with 95% confidence intervals (CI). Centers with OS within their 95% CI receive a 0 score, indicating as expected outcomes. Those with OS below / above their 95% CI receive a -1 / +1 score, indicating below / above expected OS, respectively. After a -1 report, centers may change their patient selection criteria, causing unintentional systematic exclusion of patient populations who could benefit from HCT. We analyzed how the CSA report influences patient selection practices among centers receiving a -1 score. Methods Centers receiving a -1 report between 2012 and 2016 that had ‘as expected’ survival in the preceding 2 years were classified as newly below expected OS centers (NBCs). The year of their -1 report was used as the index year. Centers with ‘as expected’ OS in the 3 years before and after each index year were identified as control centers, reflecting expected evolution of patient selection in the HCT field. The patient population variables analyzed are shown in Table 1. The difference in patient population characteristics in the 3 years before vs the 3 years after the index years defined the change in patient selection behavior at the NBCs and the controls. A multivariate model adjusting for baseline patient population characteristics and center size was used to compare the change in patient population from before and after the index year in the NBCs and that of the controls. The difference in differences (ΔinΔ) were calculated as ΔNBC - ΔControl. A significance threshold of p&lt;0.01 was used to account for multiple testing. Results After adjusting for overall trends, center size, and baseline patient population characteristics, no differences in patient selection behavior meeting the pre-specified threshold for statistical significance were identified when comparing the NBCs (n=24 centers) with the controls (n=195 centers). In the 3 years following the index years, 4,150 and 25,013 patients were transplanted at NBCs and controls, respectively. The proportion of patients receiving reduced intensity or non-myeloablative conditioning regimens decreased 4.1% in NBCs and increased 5.0% in controls, for a net difference of -9.1% (95% CI: -16.7% to -1.6%, p=0.02). All other patient characteristic proportions changed in the same direction at NBCs and controls, albeit to varying degrees (Table 1). In some high-risk characteristics, (e.g. HCT-CI &gt; 3), a greater increase was seen at NBCs vs controls (ΔinΔ 2.1% 95% CI: -2.8% to 6.9%, p=0.40). In others, (e.g. age 60+ years), a greater increase was seen at controls vs NBCs (ΔinΔ -2.6% 95% CI: -5.9% to 0.7%, p=0.12). To capture a holistic measure of centers' patient population risk, the predicted 1-year survival was compared in the NBCs vs controls using the logistic regression model generated for each year's CSA. The predicted OS increased by 3.08% and 3.30% in the NBCs and controls respectively, with no statistically significant difference (-0.23%, 95% CI: -1.4% to 0.9%, p=0.70, Figure 1). The observed overall survival (adjusted for predicted 1 year OS) also increased in both BECs and controls by 0.9% and 4.5% respectively, without statistically significant difference (-3.6%, 95% CI: -6.7% to -0.7%, p=0.02). Discussion For centers receiving a -1 report, no statistically significant changes were seen in patient population characteristics in the following 3 years when compared to centers with OS was as expected. There was variability in the changes in high-risk patient characteristics at the NBCs relative to the controls, and in some cases more patients with high-risk characteristics were selected at these centers compared to those at controls. The change in predicted overall survival at 1 year, a summary indicator of survival risk, was similar between BECs and control centers. Although the number of patients in centers with below expected OS was small, these findings suggest the public reporting of outcomes in HCT in the US does not unintentionally affect access to HCT for high-risk patients at NBCs.

ImportanceSystematic data on the association between anticancer therapies and thromboembolic events (TEEs) in patients with COVID-19 are lacking.ObjectiveTo assess the association between anticancer therapy exposure within 3 months prior to COVID-19 and TEEs following COVID-19 diagnosis in patients with cancer.Design, Setting, and ParticipantsThis registry-based retrospective cohort study included patients who were hospitalized and had active cancer and laboratory-confirmed SARS-CoV-2 infection. Data were accrued from March 2020 to December 2021 and analyzed from December 2021 to October 2022.ExposureTreatments of interest (TOIs) (endocrine therapy, vascular endothelial growth factor inhibitors/tyrosine kinase inhibitors [VEGFis/TKIs], immunomodulators [IMiDs], immune checkpoint inhibitors [ICIs], chemotherapy) vs reference (no systemic therapy) in 3 months prior to COVID-19.Main Outcomes and MeasuresMain outcomes were (1) venous thromboembolism (VTE) and (2) arterial thromboembolism (ATE). Secondary outcome was severity of COVID-19 (rates of intensive care unit admission, mechanical ventilation, 30-day all-cause mortality following TEEs in TOI vs reference group) at 30-day follow-up.ResultsOf 4988 hospitalized patients with cancer (median [IQR] age, 69 [59-78] years; 2608 [52%] male), 1869 had received 1 or more TOIs. Incidence of VTE was higher in all TOI groups: endocrine therapy, 7%; VEGFis/TKIs, 10%; IMiDs, 8%; ICIs, 12%; and chemotherapy, 10%, compared with patients not receiving systemic therapies (6%). In multivariable log-binomial regression analyses, relative risk of VTE (adjusted risk ratio [aRR], 1.33; 95% CI, 1.04-1.69) but not ATE (aRR, 0.81; 95% CI, 0.56-1.16) was significantly higher in those exposed to all TOIs pooled together vs those with no exposure. Among individual drugs, ICIs were significantly associated with VTE (aRR, 1.45; 95% CI, 1.01-2.07). Also noted were significant associations between VTE and active and progressing cancer (aRR, 1.43; 95% CI, 1.01-2.03), history of VTE (aRR, 3.10; 95% CI, 2.38-4.04), and high-risk site of cancer (aRR, 1.42; 95% CI, 1.14-1.75). Black patients had a higher risk of TEEs (aRR, 1.24; 95% CI, 1.03-1.50) than White patients. Patients with TEEs had high intensive care unit admission (46%) and mechanical ventilation (31%) rates. Relative risk of death in patients with TEEs was higher in those exposed to TOIs vs not (aRR, 1.12; 95% CI, 0.91-1.38) and was significantly associated with poor performance status (aRR, 1.77; 95% CI, 1.30-2.40) and active/progressing cancer (aRR, 1.55; 95% CI, 1.13-2.13).Conclusions and RelevanceIn this cohort study, relative risk of developing VTE was high among patients receiving TOIs and varied by the type of therapy, underlying risk factors, and demographics, such as race and ethnicity. These findings highlight the need for close monitoring and perhaps personalized thromboprophylaxis to prevent morbidity and mortality associated with COVID-19–related thromboembolism in patients with cancer.

Abstract Palliative care (PC) benefits patients undergoing hematopoietic stem cell transplantation (HSCT), but it remains underutilized. Although transplant physicians report concerns regarding how patients perceive PC, HSCT recipients’ perceptions about PC remain unaddressed. We conducted a multisite, cross-sectional survey of autologous and allogeneic HSCT recipients 3 to 12 months after transplant to assess their familiarity, knowledge, and perception of PC, as well as their unmet PC needs. We computed a composite score of patients’ perceptions of PC and used a generalized linear regression model to examine factors associated with these perceptions. We enrolled 69.6% (250/359) of potential participants (median age = 58.1; 63.1% autologous HSCT). Overall, 44.3.8% (109/249) reported limited knowledge about PC and 52% (127/245) endorsed familiarity with PC. Most patients felt hopeful (54%) and reassured (50%) when they heard the term PC; 83% saw referral as a sign their doctor cared about what was happening to them. In multivariate analyses, patients who were more knowledgeable about PC were more likely to have positive perceptions of PC (B = 7.54, standard error = 1.61, P &lt; .001). Patients’ demographics, HSCT features, quality of life, and symptom burden were not significantly associated with perceptions of PC. HSCT recipients have positive perceptions of PC, though many have limited knowledge about its role. Patients who were more knowledgeable about PC were more likely to have positive perceptions of PC. These data do not support transplant physicians’ negative concerns about how patients perceive PC and underscore the need to further educate patients and transplant physicians about PC.