Approaches to aggressive B-cell lymphomas in less fit patients

Association between skeletal muscle mass and treatment response in patients with diffuse large B-cell lymphoma

Previous studies have demonstrated that a low skeletal muscle mass (SMM) is an adverse factor for overall survival (OS) in diffuse large B-cell lymphoma (DLBCL). However, its association with the treatment response has not been extensively investigated. This study aimed to determine the association between low skeletal muscle mass (SMM) and treatment response in DLBCL patients. We conducted a retrospective cohort study of 123 patients with DLBCL, in whom SMM was assessed using computed tomography before chemotherapy administration. The demographic characteristics of the patients with low SMM and those with normal SMM were not statistically different. However, there were notable differences in weight and BMI; patients with low SMM had a lower mean weight (59.2 vs 63, p = 0.002) and a higher proportion of patients with normal BMI (61.5% vs. 21.1%, p < 0.001). In addition, patients with low SMM were more likely to receive R-CHOP-like treatment (21.2% vs. 7%, p = 0.022) and experienced more delays in administration (42.9% vs. 33.3%, p = 0.452). Low SMM was not associated with failure to achieve CR (HR 1.9; 95% CI [0.9-4.1] p = 0.84), but it was reported to risk OS in univariate analysis (HR 2.1; 95% CI [1.03-4.2], p = 0.041). An interesting result was the interaction of low SMM with hypertension as a risk factor for not achieving CR (HR 2.7; 95% CI [1.1-6.5] p = 0.034) or OS (HR 7.9; 95% CI [3.4-18.8] p < 0.001). Low SMM was not a risk factor for achieving CR in patients with DLBCL and seemed to play a role in OS.

Pan-Cancer, Genome-Scale Metabolic Network Analysis of over 10,000 Patients Elucidates Relationship between Metabolism and Survival

Despite the high variability in cancer biology, cancers nevertheless exhibit cohesive hallmarks across multiple cancer types, notably dysregulated metabolism. Metabolism plays a central role in cancer biology, and shifts in metabolic pathways have been linked to tumor aggressiveness and likelihood of response to therapy. We therefore sought to interrogate metabolism across cancer types and understand how intrinsic modes of metabolism vary within and across indications and how they relate to patient prognosis. We used context specific genome-scale metabolic modeling to simulate metabolism across 10,915 patients from 34 cancer types from The Cancer Genome Atlas and the MMRF-COMMPASS study. We found that cancer metabolism clustered into modes characterized by differential glycolysis, oxidative phosphorylation, and growth rate. We also found that the simulated activities of metabolic pathways are intrinsically prognostic across cancer types, especially tumor growth rate, fatty acid biosynthesis, folate metabolism, oxidative phosphorylation, steroid metabolism, and glutathione metabolism. This work shows the prognostic power of individual patient metabolic modeling across multiple cancer types. Additionally, it shows that analyzing large-scale models of cancer metabolism with survival information provides unique insights into underlying relationships across cancer types and suggests how therapies designed for one cancer type may be repurposed for use in others.

The Management of older patients with Hodgkin lymphoma: implications of S1826

Classical Hodgkin lymphoma (cHL) is diagnosed in patients ages 60 and older in approximately 20%-25% of cases in Western populations. Outcomes in this subset of patients have historically been poor, with 5-year progression free survival (PFS) and overall survival rates significantly lower than those seen in younger patients. Challenges to overcome include age-related co-morbidities, and prominent and potentially lethal treatment-related toxicity. There have been increased efforts to study the older cHL patient population, including analysis of geriatric assessments and the integration of newer targeted therapies such as brentuximab vedotin (BV) and nivolumab (N) into treatment paradigms. A recent phase 3 clinical trial (S1826, NCT03907488) led by the North American oncology cooperative groups compared brentuximab vedotin, doxorubicin, vinblastine, and dacarbazine (BV-AVD) with nivolumab, doxorubicin, vinblastine, and dacarbazine (N-AVD). At a median follow-up of 1-year, N-AVD improved PFS vs BV-AVD in patients and few immune adverse events were observed. Moreover, in a pre-planned subset analyses of cHL patients ages ≥60 years, the 1-year PFS for N-AVD was 93% (95% CI, 79%-98%) versus 64% (95% CI, 45%-77%) for BV-AVD. In addition, N-AVD was largely better tolerated particularly in older patients, which included markedly less neuropathy, lower treatment discontinuation, and less nonrelapse mortality. As a result, N-AVD is poised to become a standard of care for older, advanced-stage cHL patients who are fit for full-dose anthracycline-based combination therapy. More studies are needed to continue to improve outcomes for older cHL patients, especially unfit and frail populations.

A comprehensive approach to therapy of haematological malignancies in older patients

Haematological malignancies are a heterogeneous group of diseases with diverse incidence. In Europe, the median age at diagnosis across all disease entities is 69 years. Incidence generally increases with age, reaching a maximum at 75-99 years, with the notable exceptions of Hodgkin lymphoma and acute lymphocytic leukaemia. Overall survival for patients aged 75 years and older with haematological malignancies is generally poor, particularly for acute leukaemias. Understanding the heterogeneity in outcomes for haematological malignancies, treatment challenges, and management of frailty and comorbidities among older patients could help physicians to better address the haematological cancer burden and mortality in ageing populations. The aim of this Series paper is to provide an updated overview of the knowledge accumulated over the past decade regarding treatment options and broader management considerations in older adults with haematological malignancies, focusing on the most common entities encountered across lymphoma, acute leukaemia, chronic leukaemia, and multiple myeloma disease categories. Future strategies, such as increasing enrolment rates of older adults in clinical trials and incorporating patient-reported outcome measurements in daily clinical practice, will assist in providing more individualised health care.