Carrie A. Thompson

Background: Perinatal and early-life factors may influence non-Hodgkin lymphoma (NHL) risk, but study results have been mixed and exposure data for childhood ages are limited. Herein, we investigated associations of these exposures with risk of NHL and common subtypes. Methods: This case–control study included 2280 NHL cases and 2253 controls, enrolled from 2002 to 2014 at the Mayo Clinic Rochester. Self-reported perinatal and early-life exposures included maternal age at birth, birth order, birthweight, time breastfed, height and weight at ages 7, 12, and 18 years relative to peers, and age and weight when growth ceased. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for design variables and potential confounders. Linear trend tests were performed for ordinal variables, and heterogeneity tests were performed to evaluate whether associations varied across four NHL subtypes. Results: After multivariable adjustment, greater birth weight (OR = 1.15 for quartile 4 vs. 1; p-trend = 0.04), weight at age 7 relative to peers (compared to average, OR = 1.05 for heavy and OR = 0.87 for thin; p-trend = 0.002), and weight when growth ceased (OR = 1.30 for quartile 4 vs. 1; p-trend < 0.001) were associated with increased NHL risk. An inverse association was observed for breastfeeding duration with NHL risk (OR = 0.77 for >6 months vs. never; 95% CI 0.61–0.97). Associations did not significantly vary by major NHL subtype (p-heterogeneity > 0.05). Other perinatal and early-life exposures were not associated with NHL risk. Conclusions: Greater body weight at birth and through childhood may be associated with increased NHL risk, potentially extending the life-course perspective on adiposity and lymphomagenesis, with implications for prevention.

Background: While some vaccines appear to be associated with lower risk of lymphoma, their impact on outcomes is largely unknown. Methods: Data from a large prospective lymphoma cohort study was utilized to estimate associations of self-reported history of vaccination against hepatitis A, hepatitis B, influenza, and yellow fever with event-free survival (EFS) and overall survival (OS) using Cox proportional hazard models. Results: None of the vaccines were associated with EFS (HRs 0.77-1.00) or OS (HRs 0.96-1.04). Similarly, there were no significant associations between the vaccines and outcome for each lymphoma subtype. Conclusions: Prior vaccination against selected viruses was not associated with EFS or OS among patients with lymphoma. Impact: We did not find evidence for an impact of prior vaccination on lymphoma prognosis.

Diffuse large B-cell lymphoma (DLBCL) poses a challenge in hematology given its varied symptoms, and the complex interplay between disease and treatment effects on health-related quality of life (HRQoL). The phase 3 POLARIX study demonstrated superior progression-free survival and a similar safety profile with polatuzumab vedotin plus rituximab, cyclophosphamide, doxorubicin, and prednisone (Pola-R-CHP) vs R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) in patients with previously untreated DLBCL. Here, we evaluate HRQoL through patient-reported outcome (PRO) instruments to fully characterize the patient experience in the POLARIX study. Changes from baseline in HRQoL, lymphoma symptoms, and gastrointestinal (GI) symptoms were assessed, as well as incidence and severity of common symptoms by PROs vs clinician-reported adverse events (AEs). Baseline characteristics of PRO-evaluable patients (N = 874) were consistent. Comparison between PROs and clinician-reported AEs revealed a notable discordance; patients generally reported a higher incidence of symptoms than clinicians, emphasizing the need for patient-centric tools to accurately capture the patient experience. Both treatments exhibited rapid and sustained improvements in HRQoL and lymphoma symptoms, with the most substantial improvements seen in global health status/QoL, lymphoma symptoms, fatigue, role, emotional, and social functioning. GI symptoms (diarrhea, constipation, nausea, and vomiting) were generally similar between treatment arms and returned to baseline levels after treatment completion. These HRQoL data underscore the complementarity of PROs, as an adjunct to clinician-reported AEs, in evaluating the efficacy and tolerability of new treatments, including Pola-R-CHP, which may represent a new benchmark for patient-reported HRQoL in previously untreated DLBCL. This trial was registered at www.clinicaltrials.gov as NCT03274492.

Patients with non-Hodgkin lymphoma (NHL), especially younger individuals, can face fertility risks from treatment. We assessed rates and predictors of fertility counseling and preservation in this population. The LEO cohort prospectively enrolled newly diagnosed NHL patients (2015-2020) at eight U.S. academic centers. We assessed responses to a 3-year survivorship questionnaire in those aged 18-50 at diagnosis; logistic regression evaluated predictors of fertility counseling. Of 77 respondents included (46% female, median age 40), 72.2% of females and 58.5% of males recalled having a fertility discussion at diagnosis. Fertility counseling was more likely to occur in those aged 18-39 versus 40-50 (OR 10.2, 95% CI 3.3-39.2) and in those receiving alkylating therapy (OR 9.0, 95% CI 2.3-45.5). Interventions are still needed to ensure adequate survivorship care.

Newly diagnosed patients with non‐Hodgkin lymphoma (NHL) often have a history of other diseases, and these comorbidities can impact patient treatment and management options, as well as overall survival (OS). We developed the Lymphoma Epidemiology of Outcomes (LEO) comorbidity index (LCI) as a sum of 10 comorbidities adapted from the Self‐Report‐Generated Charlson Comorbidity Index (SRG‐CCI) for use in the LEO cohort, a national prospective study of newly diagnosed NHL. Of the 5502 participants with self‐reported comorbidity data, 3107 (56.4%) were male and the mean age at diagnosis was 60.9 years (range, 18–99 years). The LCI ranged from 0 to 6, with 48.6% having 0, 30.2% having 1, 21.2% having 2 or more comorbidities. With a median follow‐up of 62.4 months among surviving participants, 2099 patients had an event and 1219 died. Continuous LCI similarly predicted both 1‐year mortality (c‐statistic = 0.654) and OS (c‐statistic = 0.655), while it showed a weaker but still statistically significant predictive ability for lymphoma‐specific (c‐statistics = 0.617) and event‐free (c‐statistic = 0.574) survival. Participants with 1 (HR = 1.21, 95% CI 1.05–1.39) and 2+ (HR = 1.80, 95% CI 1.56–2.08) comorbidities had inferior OS compared to those with no comorbidities after adjustment for age and sex (c‐statistic = 0.654), and performance strengthened after adjustment for the International Prognostic Index (c‐statistic = 0.672). LCI predicted OS most strongly in marginal zone (c‐statistics = 0.748) and weakest in T‐cell (c‐statistic = 0.579) lymphoma. The cumulative incidence of death due to lymphoma, lymphoma treatment, and other causes all increased with increasing comorbidities, with the greatest increase observed for death due to other causes. The LCI performs comparable to other published comorbidity indices, supporting its use in the LEO cohort to better model real‐world outcomes and more generally providing an approach to implementing comorbidity indices in cancer survivorship cohorts.

PURPOSE: Lymphomas are a heterogeneous group of diseases that develop in individuals of all ages and have variable prognoses. Improved survival resulting from therapy advances has led to the emergence of diverse late effects. Although several (US)–based organizations have developed survivorship guidelines, the distinct features of lymphoma subtypes and diverse therapies used raise concerns regarding their applicability to lymphoma survivors. We compared survivorship recommendations (outside primary disease monitoring) between US clinical guidelines. METHODS: We extracted information from 17 guidelines from five US-based organizations: ASCO (n = 11), American Cancer Society (n = 1), Children's Oncology Group (n = 1), Center for International Blood and Marrow Transplant Research (n = 1), and the National Comprehensive Cancer Network (n = 3). Guidelines were evaluated to determine whether they offer recommendations on physical effects , psychosocial and quality of life ( QOL ), and health promotion and prevention . Comparisons were focused on second primary malignancy, cardiovascular complications, and vaccination. RESULTS: Survivorship recommendations on physical effects and psychosocial and QOL mainly differ in the timing and approaches for screening. Vaccination recommendations were primarily derived from other cancer populations. Identified research gaps were a lack of understanding of the risk of late effects across lymphoma subtypes, the role of social determinants of health in survivorship, and the lack of a survivorship care model that integrates lymphoma subtypes and treatment exposures. CONCLUSION: This study raises awareness about the complexity and challenges of managing survivors under the umbrella diagnosis of lymphoma. The inconsistency and incompleteness of existing guidelines may lead to suboptimal survivorship care. We propose expert-based research priorities to address gaps and unmet needs to help develop risk-based follow-up recommendations to optimize survivorship care for lymphoma survivors.

Background:Diffuse large B-cell lymphoma (DLBCL) is clinically heterogeneous, and gene expression profiling has identified at least two biologically distinct DLBCL subtypes defined by their cell of origin (COO): germinal center B cell (GCB) and activate B cell (ABC) or non-GCB. We evaluated a variety of putative DLBCL risk factors for etiologic heterogeneity by the COO in a clinic-based study of newly diagnosed DLBCL cases (N = 638) and frequency-matched controls (N = 2,253).Methods:The COO was determined on formalin-fixed, paraffin-embedded tumor tissue, with DLBCL classified as GCB (N = 283), non-GCB (N = 188), or undetermined/missing (N = 167; mainly because of lack of tissue). Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI).Results:We identified heterogeneity by the COO for low socioeconomic status (SES), which was only associated with non-GCB DLBCL (OR = 1.88 for low vs. average SES; 95% CI, 1.08–3.27); alcohol use, which was only associated with GCB DLBCL (OR = 0.48 for former drinkers; 95% CI, 0.29–0.80 and OR = 0.47 for current drinkers; 95% CI, 0.32–0.71); and borderline heterogeneity for the regular use of regular/extra-strength aspirin, which was only associated with non-GCB DLBCL (OR = 0.36; 95% CI, 0.16–0.85). In contrast, there was no significant heterogeneity by the COO for family history, medical history, or other lifestyle factors.Conclusions:Although requiring confirmation, most risk factors for DLBCL did not show etiologic heterogeneity by the COO, with some notable exceptions including alcohol use, SES, and perhaps regular use of regular/extra-strength aspirin showing associations.Impact:Mechanistically, these findings suggest that most of the DLBCL risk factors evaluated here influence lymphomagenesis prior to differentiation into COO subtypes, with selected factors acting later.