Background High intensity treatments such as hematopoietic cell transplantation (HCT) can be curative for patients with hematologic malignancies, but this needs to be balanced by the high risk of nonrelapse mortality (NRM) during the first 2 years after HCT. Sarcopenia (low muscle mass) is associated with physical disability and premature mortality in individuals with nonmalignant diseases and may be a predictor of NRM and poor overall survival in patients undergoing HCT. Methods This was a retrospective cohort study of 859 patients with acute leukemia or myelodysplastic syndrome who underwent a first HCT as adults (≥18 years) between 2007 and 2014. Sarcopenia was assessed from pre-HCT abdominal computed tomography scans. Two-year cumulative incidence of NRM was calculated, with relapse/progression considered as a competing risk event. Fine-Gray subdistribution hazard ratio estimates and 95% confidence intervals (CI) were obtained and adjusted for relevant covariates. Kaplan-Meier method was used to examine overall survival. All statistical tests were two-sided. Results Median age at HCT was 51 years (range = 18–74 years); 52.5% had a high [≥3] HCT-comorbidity index; 33.7% had sarcopenia pre-HCT. Sarcopenia was an independent predictor of higher NRM risk (hazard ratio = 1.58, 95% CI = 1.16 to 2.16) compared with patients who were not. The 2-year incidence of NRM approached 30% in patients with sarcopenia and high (≥3) HCT-comorbidity index. Patients with sarcopenia had on average a longer hospitalization (37.2 days vs 31.5 days, P < .001) and inferior overall survival at 2 years (55.2%, 95% CI = 49.5% to 61.0% vs 66.9%, 95% CI = 63.0% to 70.8%, P < .001). Conclusions Sarcopenia is an important and independent predictor of survival after HCT, with potential additional downstream impacts on health-economic outcomes. This information can be used to facilitate treatment decisions prior to HCT and guide interventions to decrease the risk of treatment-related complications after HCT.

ABSTRACT We study the impact of baryonic processes and massive neutrinos on weak lensing peak statistics that can be used to constrain cosmological parameters. We use the BAHAMAS suite of cosmological simulations, which self-consistently include baryonic processes and the effect of massive neutrino free-streaming on the evolution of structure formation. We construct synthetic weak lensing catalogues by ray tracing through light-cones, and use the aperture mass statistic for the analysis. The peaks detected on the maps reflect the cumulative signal from massive bound objects and general large-scale structure. We present the first study of weak lensing peaks in simulations that include both baryonic physics and massive neutrinos (summed neutrino mass Mν = 0.06, 0.12, 0.24, and 0.48 eV assuming normal hierarchy), so that the uncertainty due to physics beyond the gravity of dark matter can be factored into constraints on cosmological models. Assuming a fiducial model of baryonic physics, we also investigate the correlation between peaks and massive haloes, over a range of summed neutrino mass values. As higher neutrino mass tends to suppress the formation of massive structures in the Universe, the halo mass function and lensing peak counts are therefore modified as a function of Mν. Over most of the S/N range, the impact of fiducial baryonic physics is greater (less) than neutrinos for 0.06 and 0.12 (0.24 and 0.48) eV models. Both baryonic physics and massive neutrinos should be accounted for when deriving cosmological parameters from weak lensing observations.

Introduction: High intensity treatments such as autologous hematopoietic cell transplantation (HCT) can be curative for patients with relapsed/refractory lymphoma (Hodgkin [HL], non-Hodgkin [NHL]), but this needs to be balanced by the risk of non-relapse mortality (NRM) associated with HCT and potentially sub-optimal disease response with less intensive treatments. Measures of pre-treatment body composition such as quantity and quality of muscle are prognostic in patients with solid tumors, but their association with post-HCT outcomes is unknown. We examined the prognostic significance of muscle depletion prior to HCT, defined by having both low muscle quantity (lumbar skeletal muscle index [SMI]) and quality (muscle attenuation [MA]) on computed tomography (CT) imaging, in a population-based cohort of patients undergoing autologous HCT for lymphoma. Next, we examined the prognostic significance of muscle depletion after HCT in a subset of patients with normal muscle composition prior to HCT, allowing us to examine the impact of change in body composition over time. Methods: 440 consecutive patients with lymphoma, age ≥18y, who underwent a first HCT between 2009 and 2014 at a single institution were included in the study. Measures of muscle quantity (SMI) and quality (MA) were ascertained from pre- and post-HCT abdominal CT scans using image analysis software (SliceOmatic; Tomovision, Quebec, Canada). SMI was calculated as the ratio of skeletal muscle area (cm2) divided by height (m)2. Sex and body mass index (BMI)-specific cutoff values of low SMI and MA were used to identify patients with muscle depletion (J Clin Oncol 2013 31:1539). Measurements were made by trained researchers blinded to patient demographics and HCT outcome (Figure 1); 3rd lumbar vertebra was used as a landmark because of its high correlation with whole-body muscle mass (J Clin Oncol 2016 34:1339). This report is limited to 321 (73%) patients with CT scans performed ≤90 days from HCT. Cumulative incidence of NRM was calculated taking into consideration competing risk of disease-related mortality. Kaplan-Meier method was used to examine overall survival (OS). Multivariable Cox regression analysis was used to calculate the hazard ratio (HR) estimates and 95% confidence intervals (CI), adjusted for relevant covariates (demographics, diagnosis, pre-HCT Karnofsky performance score [KPS] and comorbidity index [HCT-CI]). Results: Sixty-two (19.3%) patients had muscle depletion pre-HCT. Median age at HCT was 53y (range: 18-78); 62.0% were male; 54.0% were non-Hispanic white; Diagnoses: HL (N=84 [26.2%]), NHL (N=237 [73.8%]); KPS ≤80 (N=87 [27.1%]); HCT-CI ≥3 (N=52 [16.2%]). Impact of pre-HCT muscle depletion: Patients with pre-HCT muscle depletion had significantly worse 5-y OS (56.4% vs. 77.8%, p<0.001; Figure 2) and higher NRM (11.4% vs. 5.1%, p=0.05) when compared to those with normal body composition. OS was especially poor for patients who were obese (BMI ≥30 kg/m2) and had muscle depletion (20.0% vs. 77.1%, p<0.001) pre-HCT. Median length of hospitalization was also significantly longer (27d vs. 23d; p=0.03) among patients with muscle depletion. Muscle depletion was associated with a 2.2-fold (HR=2.2 [CI: 1.0-4.5]) risk of NRM and 1.8-fold (HR=1.8 [CI: 1.1-3.1]) risk of all-cause mortality when compared to those with normal body composition. Impact of post-HCT muscle depletion: Among 223 patients with normal body composition prior to HCT, 24 (9.3%) developed muscle depletion after HCT, detected at a median 63d (range 27-165) from HCT. In these patients, there was a 3-fold (HR=3.1 [CI: 1.5-6.4]) risk of all-cause mortality compared to those who maintained normal muscle composition throughout HCT. Conclusion: Muscle depletion is an important and independent predictor of outcomes after HCT, with potential additional downstream impacts on health-economic outcomes such as length of hospitalization and the burden of chronic morbidity in long-term survivors. Taken together, these data form the basis for real-time decision making prior to HCT (e.g. pre-habilitation, less intensive treatment approaches), or during HCT (e.g. dietary optimization, increased supportive care services, resistance training), setting the stage for innovative strategies to improve outcomes after HCT. Disclosures Chen: Affimed: Research Funding; Merck & Co., Inc.: Consultancy, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Research Funding; Seattle Genetics: Consultancy, Honoraria, Research Funding, Speakers Bureau; Genentech Inc.: Consultancy; Millennium Pharmaceuticals: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding. Forman:Mustang Therapeutics: Other: Licensing Agreement, Patents & Royalties, Research Funding.