Predictive performance of the LEO comorbidity index in patients aged 80+ years with large B-cell lymphoma
Abstract
Abstract Introduction The LEO Comorbidity Index (LCI), comprising ten equally weighted comorbidity categories (respiratory, cardiovascular, digestive, hepatic, renal, autoimmune, diabetes, cancer history, HIV, and stroke), has demonstrated prognostic utility in patients with non-Hodgkin lymphomas. However, its predictive accuracy may vary with increasing age, due to age-related rises in comorbidity burden and physiological vulnerability. To investigate these dynamics, we evaluated the age-stratified predictive performance of LCI in patients with large B-cell lymphoma (LBCL), with a focused analysis on individuals aged 80+ years. We also examined which specific comorbidities most strongly influenced overall survival (OS) and developed a simplified, clinically applicable index tailored to this population. Methods We first included adults ≥40 years with newly diagnosed LBCL and recorded comorbidities from the LEO registry (USA, 2015–2020; n=1,652) to assess age-stratified predictive performance of LCI using the C-index. Next, we focused on patients 80+ years (n=263), pooled from the LEO cohort (n=147) and NiHiL registry (restricted to General Hospital, Prague, Czech Republic, 2010–2023; n=116). Comorbidities were collected from patient self-reports (LEO) and/or medical records (LEO/NiHiL). Univariate and multivariate Cox models were used. The primary endpoint was OS. Results Among the total LBCL population (n=1,652), LCI predictive performance improved by age category with C-index for patients <65 of 0.584, 65–79 years 0.579, and ≥80 years 0.647, indicating stronger discrimination in the 80+ group. Subsequent analysis focused on patients aged 80+ years (n=263; median age 83). Within this cohort, 34% had ECOG performance status (PS) 2–4, 66% stage III–IV disease, 59% elevated lactate dehydrogenase, 35% >1 extranodal site involved, and 58% International Prognostic Index (IPI) score of 3–5. A total of 377 comorbidities were reported, averaging 1.43 per patient (1.22 in LEO; 1.61 in NiHiL). LCI distribution was: 0 points in 24% (n=62), 1 point in 33% (n=88), and 2–5 points in 43% (n=113). Higher LCI scores had worse ECOG PS 2–4: 19% (LCI=0), 33% (LCI=1), and 43% (LCI ≥2; P=0.01), and inferior OS (median 6.9 years LCI=0, 3.0 years LCI=1, and 2.8 years LCI≥2, resp.; P=0.02). Presence of ≥1 comorbidity was associated with shorter OS compared to no comorbidities (HR=1.67, P=0.01). The LCI was an independent predictor of OS after adjusting for age (HR=1.18, P=0.01, C-index 0.623), IPI (HR=1.16, P=0.03, C-index 0.628) as well as for recently proposed SENIOR-IPI (HR=1.14, P=0.049, C-index 0.665). When evaluating individual comorbidities, heart disease (HR=1.54, P=0.01), stroke (HR=1.89, P=0.03), and recent malignancy (HR=1.99, P=0.02) were independent predictors of OS. Based on these findings, we developed a simplified LCI (sLCI) for use in 80+ patients incorporating only the three comorbidities (1 point each). Patients were categorized as sLCI: 0 (49%, n=129), 1 (44%, n=115), and 2–3 points (7%, n=19). sLCI scores 0, 1, 2–3 were associated with ECOG PS 2–4 27%, 37%, and 63%, respectively (P=0.01) and inferior OS: median 5.3 years (0), 2.5 years (1), and 1.4 years (2–3; P<0.01). sLCI remained an independent and strong predictor of OS after adjusting for age (HR=1.71, P<0.01, C-index 0.636), IPI (HR=1.66, P<0.01, C-index 0.635), and SENIOR-IPI (HR=1.60, P<0.04, C-index 0.659). The results were consistent in both NiHiL and LEO cohorts and remained significant among patients treated with anthracyclines (sLCI adjusted for age: HR=1.58, P<0.01, C-index 0.607; for IPI: HR=1.53, P=0.01, C-index 0.623; for SENIOR-IPI: HR=1.51, P=0.01, C-index 0.633). Conclusion Comorbidity burden becomes increasingly prognostic with higher age in LBCL patients. In the 80+ individuals, comorbidities – particularly heart disease, recent cancer, and stroke – have an independent impact on OS. While the original LCI captures the impact of broadly defined comorbidities, its prognostic utility attenuates in the 80+ patients, likely reflecting limited relevance of indolent chronic conditions in this population's constrained survival horizon. The sLCI, focused on the most prognostically relevant comorbidities, offers practical risk stratification. Incorporation of sLCI into clinical decision-making – alongside other prognostic indices – could better identify high-risk individuals and guide treatment strategies. Funding: NU21-03-00411, U01 CA195568.
Article Details
Authors (33)
Prokop Vodička
1First Department of Medicine, First Faculty of Medicine Charles University and General Hospital, Prague, Czech Republic
Michal Masar
1First Faculty of Medicine, Charles University and General Hospital, First Department of Medicine, Prague, Czech Republic
Carrie Thompson
1Mayo Clinic College of Medicine, Rochester, MN
Katerina Benesova
6Department of Haematology and Oncology, Faculty of Medicine, Charles University and University Hospital Pilsen, Pilsen, Czech Republic
Izidore S. Lossos
29Division of Hematology, Department of Medicine, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
Diana Malarikova
2First Department of Medicine, First Faculty of Medicine, Charles University and General Hospital, Prague, Czech Republic
Annalynn Williams
13Wilmot Cancer Institute, University of Rochester, Rochester, United States
Kamila Polgarova
1First Faculty of Medicine, Charles University and General Hospital, First Department of Medicine, Prague, Czech Republic
Chijioke Nze
6MD Anderson Cancer Center, Houston, United States
Jan Koren
2First Department of Medicine, First Faculty of Medicine, Charles University and General Hospital, Prague, Czech Republic
Jonathon Cohen
15Winship Cancer Institute, Emory University, Atlanta CA
Jana Salkova
1First Faculty of Medicine, Charles University and General Hospital, First Department of Medicine, Prague, Czech Republic
Andrew Feldman
2Mayo Clinic, Rochester, United States
Josef Karban
1First Faculty of Medicine, Charles University and General Hospital, First Department of Medicine, Prague, Czech Republic
Eric Mou
24Division of Hematology, Oncology, and Blood and Marrow Transplantation, Department of Internal Medicine, University of Iowa, Iowa City, IA
Petra Kovarikova
Elliot Cahn
2Mayo Clinic, Department of Quantitative Health Sciences, Rochester, United States
Eva Konirova
1First Faculty of Medicine, Charles University and General Hospital, First Department of Medicine, Prague, Czech Republic
Peter Martin
Jitka Dlouha
10Czech Lymphoma Study Group, Datacenter, Prague, Czech Republic
Mazie Tsang
2Mayo Clinic Comprehensive Cancer Center, Phoenix, United States
Dilan Patel
9Washington University School of Medicine in St. Louis, Division of Oncology, St. Louis, United States
Petra Blahovcova
2General University Hospital in Prague, Brno, Czech Republic, First Department of Medicine, Prague, Czech Republic
Patrick Reagan
5University of Rochester, Rochester, United States
David Jaye
8Emory, Atlanta, United States
Magdalena Klanova
Jonathan Friedberg
15Wilmot Cancer Center, University of Rochester, Department of Medicine, Hematology/Oncology, Rochester, United States
Christopher Flowers
1Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX
Pavel Klener
Matthew Maurer
2Mayo Clinic, Rochester, United States
Thomas Habermann
2Mayo Clinic, Rochester, United States
Marek Trneny
James Cerhan
2Mayo Clinic, Rochester, United States