Rodday, Angie Mae

ImportanceAnthracycline-containing regimens are highly effective for diffuse large B-cell lymphoma (DLBCL); however, patients with preexisting heart failure (HF) may be less likely to receive anthracyclines and may be at higher risk of lymphoma mortality.ObjectiveTo assess the prevalence of preexisting HF in older patients with DLBCL and its association with treatment patterns and outcomes.Design, Setting, and ParticipantsThis longitudinal cohort study used data from the Surveillance, Epidemiology, and End Results (SEER)–Medicare registry from 1999 to 2016. The SEER registry is a system of population-based cancer registries, capturing more than 25% of the US population. Linkage to Medicare offers additional information from billing claims. This study included individuals 65 years and older with newly diagnosed DLBCL from 2000 to 2015 with Medicare Part A or B continuously in the year prior to lymphoma diagnosis. Data were analyzed from September 2020 to December 2022.ExposuresPreexisting HF in the year prior to DLBCL diagnosis ascertained from billing codes required one of the following: (1) 1 primary inpatient discharge diagnosis, (2) 2 outpatient diagnoses, (3) 3 secondary inpatient discharge diagnoses, (4) 3 emergency department diagnoses, or (5) 2 secondary inpatient discharge diagnoses plus 1 outpatient diagnosis.Main Outcomes and MeasuresThe primary outcome was anthracycline-based treatment. The secondary outcomes were (1) cardioprotective medications and (2) cause-specific mortality. The associations between preexisting HF and cancer treatment were estimated using multivariable logistic regression. The associations between preexisting HF and cause-specific mortality were evaluated using cause-specific Cox proportional hazards models with adjustment for comorbidities and cancer treatment.ResultsOf 30 728 included patients with DLBCL, 15 474 (50.4%) were female, and the mean (SD) age was 77.8 (7.2) years. Preexisting HF at lymphoma diagnosis was present in 4266 patients (13.9%). Patients with preexisting HF were less likely to be treated with an anthracycline (odds ratio, 0.55; 95% CI, 0.49-0.61). Among patients with preexisting HF who received an anthracycline, dexrazoxane or liposomal doxorubicin were used in 78 of 1119 patients (7.0%). One-year lymphoma mortality was 41.8% (95% CI, 40.5-43.2) with preexisting HF and 29.6% (95% CI, 29.0%-30.1%) without preexisting HF. Preexisting HF was associated with higher lymphoma mortality in models adjusting for baseline and time-varying treatment factors (hazard ratio, 1.24; 95% CI, 1.18-1.31).Conclusions and RelevanceIn this study, preexisting HF in patients with newly diagnosed DLBCL was common and was associated with lower use of anthracyclines and lower use of any chemotherapy. Trials are needed for this high-risk population.

PURPOSE The International Prognostic Score (IPS) has been used in classic Hodgkin lymphoma (cHL) for 25 years. However, analyses have documented suboptimal performance of the IPS among contemporarily treated patients. Harnessing multisource individual patient data from the Hodgkin Lymphoma International Study for Individual Care consortium, we developed and validated a modern clinical prediction model. METHODS Model development via Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis guidelines was performed on 4,022 patients with newly diagnosed advanced-stage adult cHL from eight international phase III clinical trials, conducted from 1996 to 2014. External validation was performed on 1,431 contemporaneously treated patients from four real-world cHL registries. To consider association over a full range of continuous variables, we evaluated piecewise linear splines for potential nonlinear relationships. Five-year progression-free survival (PFS) and overall survival (OS) were estimated using Cox proportional hazard models. RESULTS The median age in the development cohort was 33 (18-65) years; nodular sclerosis was the most common histology. Kaplan-Meier estimators were 0.77 for 5-year PFS and 0.92 for 5-year OS. Significant predictor variables included age, sex, stage, bulk, absolute lymphocyte count, hemoglobin, and albumin, with slight variation for PFS versus OS. Moreover, age and absolute lymphocyte count yielded nonlinear relationships with outcomes. Optimism-corrected c-statistics in the development model for 5-year PFS and OS were 0.590 and 0.720, respectively. There was good discrimination and calibration in external validation and consistent performance in internal-external validation. Compared with the IPS, there was superior discrimination for OS and enhanced calibration for PFS and OS. CONCLUSION We rigorously developed and externally validated a clinical prediction model in > 5,000 patients with advanced-stage cHL. Furthermore, we identified several novel nonlinear relationships and improved the prediction of patient outcomes. An online calculator was created for individualized point-of-care use.

Background: While HL is a highly curable cancer, patients (pts) with advanced stage disease experience increased risk of relapse. Delineation of prognosis is desired to compare cohorts and outcomes between trials, and to define groups of pts for whom reduction in treatment may be appropriate or where novel therapeutic approaches are needed. The International Prognostic Score (IPS), which was derived from a discovery set of 1,618 HL pts with complete data, was a seminal publication in the field (Hasenclever and Diehl NEJM 1998). However, these data were published >20 years ago with a significant minority of pts having received chemotherapy regimens no longer in clinical use. More contemporary analyses have shown altered utility of the IPS (e.g., Moccia JCO 2012; Diefenbach BJH 2015). In addition, prior studies identified bulk disease as an adverse prognostic factor in advanced stage HL (Laskar JCO 2004; Johnson JCO 2010). Our objective was to leverage individual pt data (IPD) from HoLISTIC (www.hodgkinconsortium.com) to discover a new, robust, and modern prognostication index for advanced-stage HL pts applicable to diverse settings across the world. Methods: We created a data repository of IPD from clinical trials for newly diagnosed HL pts, which includes 4,085 advanced-stage (III or IV) pts treated in 8 large, prospective studies completed in the modern era (ie, IIL HD9601: Gobbi JCO 2005; Italian HD2000: Federico JCO 2009; ECOG 2496: Gordon JCO 2013; SWOG 0816: Press JCO 2016; IIL HD0801: Zinzani JCO 2016; RATHL: Johnson NEJM 2016; GITIL HD0607: Gallamini JCO 2017; and COG AHOD 0831: Kelly BJH 2019) as well as prominent cancer registries (eg, the Mayo/Iowa Molecular Epidemiologic Resource (MER)). The discovery analysis herein included pts from the ECOG 2496, HD0801 IIL, GITIL HD0607, and SWOG 0816 studies. Furthermore, it was restricted to pts (n=1,279) on these trials with complete data for all 9 covariates of interest: age; sex; advanced stage (III vs IV); B symptoms; any bulk; and values of hemoglobin, white blood count (WBC), lymphocyte count, and albumin. Using Cox proportional hazard (PH) models, we evaluated univariate associations between 5-year progression-free survival (PFS) and overall survival (OS) with the aforementioned prognostic variables. Age was categorized based on plots and optimum model fit (c statistic). Lab values were dichotomized using cut-points from the 1998 IPS. Per convention, treatment factors were not included in the model. To identify independent prognostic factors of PFS and OS, a parsimonious Cox PH model was fit using backward selection of all potential risk factors (P<0.05). Hazard ratios (HR) with 95% confidence interval (CI) were reported. Kaplan Meier (KM) plots were also reported for risk factors in the multivariable (MVA) models to visualize differences. Results: Among all pts, characteristics included: median age of 32.9 years (IQR 25.4-44, range 15-83); 55% male; 49% stage IV; 63% B symptoms; 26% bulk >10 cm; 20% hemoglobin <10.5 g/dL; 15% WBC count ≥15,000/mm3; 9% lymphocyte count <600/mm3; and 63% with albumin <4g/dL. For analysis of age, we observed a U-shaped relationship with PFS (Fig A), which helped delineate optimal cut points of 15-24 years (23.1%), 25-49 years (61.4%), and ≥50 years (15.6%). In univariate analysis: age, stage, B symptoms, bulk, anemia, low lymphocyte count, and low albumin were associated with worse survival. In the MVA model, age >50 years, stage IV disease, B symptoms, and bulky disease were associated with worse PFS; and age >50 years, stage IV disease, bulky disease, anemia, and low albumin were associated with worse OS (Fig B). KM plots for age, stage, and bulk are presented in Fig C. Conclusions. In this international, multi-study analysis of advanced stage HL in the modern era, we identified several factors that were associated with both worse PFS and OS on MVA (ie, age, stage IV disease, and bulky disease). The finding of bulky disease as a significant prognostic factor warrants further investigation. In addition, we detected an age-related U-shaped impact on PFS with inferior outcomes for pts ages 15-25 years and ≥50 years, the latter in an increasing linear fashion. Altogether, these data will serve as a training cohort for a modern HL prognostication index that will be augmented and analyzed with a large independent validation cohort (vis-à-vis the remaining HL data in the HoLISTIC consortium), which will be presented at the ASH meeting. Disclosures Parsons: Seattle Genetics: Consultancy. Advani:Astra Zeneca, Bayer Healthcare Pharmaceuticals, Cell Medica, Celgene, Genentech/Roche, Gilead, KitePharma, Kyowa, Portola Pharmaceuticals, Sanofi, Seattle Genetics, Takeda: Consultancy; Celgene, Forty Seven, Inc., Genentech/Roche, Janssen Pharmaceutical, Kura, Merck, Millenium, Pharmacyclics, Regeneron, Seattle Genetics: Research Funding. Federico:Spectrum: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sandoz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mundipharma s.r.l.: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cephalon/Teva: Research Funding. Friedberg:Acerta Pharma - A member of the AstraZeneca Group, Bayer HealthCare Pharmaceuticals.: Other; Bayer: Consultancy; Kite Pharmaceuticals: Research Funding; Portola Pharmaceuticals: Consultancy; Roche: Other: Travel expenses; Seattle Genetics: Research Funding; Astellas: Consultancy. Hutchings:Genmab: Research Funding; Janssen: Research Funding; Roche: Consultancy; Genmab: Consultancy; Takeda: Consultancy; Roche: Research Funding; Celgene: Research Funding; Daiichi: Research Funding; Sankyo: Research Funding; Novartis: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; Roche: Honoraria; Genmab: Honoraria; Takeda: Honoraria. Johnson:MorphoSys: Honoraria; Kymera: Honoraria; Kite Pharma: Honoraria; Incyte: Honoraria; Celgene: Honoraria; Epizyme: Consultancy, Research Funding; Novartis: Honoraria; Takeda: Honoraria; Oncimmune: Consultancy; Boehringer Ingelheim: Consultancy; Janssen: Consultancy; Oncimmune: Consultancy; Janssen: Consultancy; Genmab: Honoraria; Bristol-Myers: Honoraria; Epizyme: Consultancy, Research Funding. Radford:Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Speakers Bureau; ADCT: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; GlaxoSmithKline: Current equity holder in publicly-traded company, Other: Spouse; AstraZeneca: Current equity holder in publicly-traded company, Other: Spouse; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Zinzani:MSD: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; EUSA Pharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sandoz: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Immune Design: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Eusapharma: Consultancy, Speakers Bureau; Verastem: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kyowa Kirin: Consultancy, Speakers Bureau; TG Therapeutics, Inc.: Honoraria, Speakers Bureau; Kirin Kyowa: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen-Cilag: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celltrion: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; ADC Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Portola: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Immune Design: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Merck: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Cerhan:NanoString: Research Funding; BMS/Celgene: Research Funding. Evens:Abbvie: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria, Research Funding; MorphoSys: Consultancy, Honoraria; Research To Practice: Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria; Epizyme: Consultancy, Honoraria, Research Funding; Merck: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria; Mylteni: Consultancy, Honoraria.