Abstract
Age-stratified prognostic performance of patient- vs disease-related IPI factors in large B-cell lymphoma
Blood, Vol.146, 4516
11/03/2025
DOI: 10.1182/blood-2025-4516
Abstract
Introduction The International Prognostic Index (IPI, NEJM, 1993) has guided risk stratification in large B-cell lymphoma (LBCL) for over three decades. Its simplicity and clinical utility have driven its widespread adoption, even in the era of precision medicine. However, the prognostic value of the IPI and its components may not be uniform across the age spectrum of LBCL patients. We evaluated the contemporary prognostic performance of the IPI in a large international cohort, focusing on age-stratified performance and the relative contributions of its individual components, grouped as patient- and disease-related factors.
Methods We harmonized and pooled data from 6,941 patients with newly diagnosed systemic LBCL treated with R-CHOP-like regimens (R-CHOP, R-miniCHOP, DA-EPOCH-R, R-CHOEP, R-CHOP+X) with complete IPI data from three prospective cohorts: NiHiL (Czech Republic, n=4,590; 2010–2023), LEO (USA, n=1,789; 2015–2020), and MER (USA, n=562; 2010–2015). IPI components included age, ECOG performance status (PS) as patient-related, and Ann Arbor clinical stage, serum lactate dehydrogenase (LDH), and extranodal (EN) involvement as disease-related factors. Prognostic performance was evaluated using multivariable Cox regression models and C-statistics. Age-stratified analysis was performed for: ≤40 years (7%; n=492), 41–60 years (28%; n=1,909), 61–80 years (59%; n=4,080), and >80 years (7%; n=460). The primary endpoint was overall survival (OS).
Results In the pooled cohort, the median age was 66 years (range 18–95). Compared to the original IPI cohort (n=3,273), our cohort was older (age >60 years: 66% vs 41%) but otherwise comparable: ECOG PS 2–4 (25% vs 24%), clinical stage III–IV (63% vs 66%), elevated LDH (60% vs 52%), and >1 EN involvement (32% vs 30%).
In multivariable analysis, age (≤60 vs >60 years) was the strongest predictor of OS (HR=2.78; vs HR=1.96 in original IPI report), followed by ECOG PS (HR=2.07; vs 1.80), clinical stage (HR=1.50; vs 1.47), LDH (HR=1.41; vs 1.85, all P<0.01); EN involvement was not significant (P=0.50, HR=1.03 vs 1.48). Risk group distribution shifted from the original IPI: 28% were low-risk (0–1 factor; vs 35%), 23% low-intermediate (2; vs 27%), 24% high-intermediate (3; vs 22%), and 25% high-risk (4–5; vs 16%). Corresponding 2-year OS rates were 95%, 86%, 78%, and 63%, superior to those of the original IPI cohort (87%, 67%, 55%, 44%; pre-rituximab era).
Age was associated with an increasing risk of mortality, with a more pronounced rise beyond 60 years. In a piecewise Cox model, the HR per year was 1.04 for ages ≤60 (linear), 1.05 for 61–69 (accelerated), and 1.06 for ≥70 years (exponential, all P<0.01). ECOG PS retained prognostic significance across age groups: HRs were 1.87 (P=0.06) for ≤40 years, 1.63 (P<0.01) for 41–60, 2.22 (P<0.01) for 61–80, and 1.43 (P<0.01) for >80 years. The strength of other IPI components declined with age. Clinical stage showed decreasing impact: HR 2.08 (P=0.09), 1.97 (P<0.01), 1.49 (P<0.01), and 1.31 (P=0.05). LDH was significant only up to age 80 years: HRs were 2.07 (P=0.04), 1.96 (P<0.01), 1.32 (P<0.01), and 1.21 (P=0.13). EN involvement was non-significant across all groups: HRs were 1.37 (P=0.34), 1.26 (P=0.05), 0.98 (P=0.74), and 1.06 (P=0.67). The IPI C-statistics was 0.676 overall and declined with age: ≤40 years (0.708), 41–60 years (0.683), 61–80 years (0.641), and >80 years (0.598).
We next stratified the IPI factors into patient- (age, ECOG PS) and disease-related (clinical stage, LDH, EN involvement). In patients ≤40 years, disease-related factors outperformed patient-related (C-index 0.693 vs 0.602), as in the 41–60 group (C-index 0.677 vs 0.589). In patients aged 61–80, predictive values were comparable (0.613 vs 0.622). In >80-year-olds, both declined substantially (0.580 vs 0.568).
Conclusion The IPI remains a valuable prognostic tool in LBCL, particularly among younger patients. However, its overall predictive accuracy declines with age. In patients ≤60 years old, prognosis is primarily driven by disease-related factors, suggesting a role for molecular classifiers to enhance risk stratification. In older patients, incorporation of additional patient-level factors, such as comorbidities and nutritional status could be considered. These findings underscore the need for more individualized prognostic tools for LBCL patients.
Funding: NU21-03-00411, P50 CA97274, U01 CA195568, Charles University Haematology-Oncology Cooperatio Program.
Vodicka:AbbVie: Consultancy (Includes expert testimony); Honoraria Hoffmann-La Roche: Consultancy (Includes expert testimony); Honoraria Janssen: Honoraria Swixx BioPharma: Honoraria Maurer:BMS: Research Funding MD Education: Honoraria Roche/Genentech: Research Funding Wang:Abbvie: Consultancy (Includes expert testimony); Research Funding Genentech: Research Funding Genmab: Consultancy (Includes expert testimony); Research Funding Incyte: Consultancy (Includes expert testimony); Research Funding InnoCare: Consultancy (Includes expert testimony); Research Funding Kite: Consultancy (Includes expert testimony) Loxo/Eli Lily: Consultancy (Includes expert testimony); Research Funding Merck: Research Funding Morphosys: Research Funding Novartis: Research Funding Flowers:4D: Research Funding Abbvie: Consultancy (Includes expert testimony); Research Funding Acerta: Research Funding Adaptimmune: Research Funding Allogene: Research Funding Amgen: Research Funding Bayer: Consultancy (Includes expert testimony); Research Funding BeiGene: Consultancy (Includes expert testimony) BostonGene: Research Funding Burroughs Wellcome Fund: Research Funding Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding Celgene: Consultancy (Includes expert testimony); Research Funding Cellectis EMD: Research Funding Denovo Biopharma: Consultancy (Includes expert testimony) Eastern Cooperative Oncology Group: Research Funding Foresight Diagnostics: Consultancy (Includes expert testimony); Current holder of stock options in a privately-held company Genentech/Roche: Consultancy (Includes expert testimony); Research Funding Genmab: Consultancy (Includes expert testimony) Gilead: Consultancy (Includes expert testimony); Research Funding Guardant: Research Funding Iovance: Research Funding Janssen Pharmaceutical: Research Funding Karyopharm: Consultancy (Includes expert testimony) Kite: Research Funding Morphosys: Research Funding National Cancer Institute: Research Funding Nektar: Research Funding Novartis: Research Funding N-Power Medicine: Consultancy (Includes expert testimony); Current holder of stock options in a privately-held company Pfizer: Research Funding Pharmacyclics: Research Funding Pharmacyclics/Janssen: Consultancy (Includes expert testimony) Sanofi: Research Funding SeaGen: Consultancy (Includes expert testimony) Spectrum: Consultancy (Includes expert testimony) Takeda: Research Funding TG Therapeutics: Research Funding V Foundation: Research Funding Xencor: Research Funding Ziopharm: Research Funding Lossos:ADC Therapeutics: Honoraria; Research Funding Genentech, Inc.: Research Funding NCI: Research Funding Ďuraš:AbbVie: Consultancy (Includes expert testimony); Honoraria AstraZeneca: Consultancy (Includes expert testimony) Bristol Myers Squibb: Consultancy (Includes expert testimony) Eli Lilly: Consultancy (Includes expert testimony) Johnson and Johnson: Consultancy (Includes expert testimony) Roche: Consultancy (Includes expert testimony); Honoraria Swixx: Consultancy (Includes expert testimony) Takeda: Consultancy (Includes expert testimony) Cohen:Adct: Consultancy (Includes expert testimony); Research Funding Astra Zeneca: Consultancy (Includes expert testimony); Research Funding Bms: Research Funding Genentech: Research Funding Incyte: Consultancy (Includes expert testimony) Lilly: Research Funding Merck: Consultancy (Includes expert testimony) Novartis: Research Funding Nurix: Research Funding Takeda: Research Funding Casulo:Abbvie: Consultancy (Includes expert testimony); Honoraria Genentech: Consultancy (Includes expert testimony); Honoraria Genmab: Consultancy (Includes expert testimony); Honoraria Incyte: Consultancy (Includes expert testimony); Honoraria Roche: Honoraria Kahl:AbbVie: Consultancy (Includes expert testimony) ADC Therapeutics: Consultancy (Includes expert testimony) ADCT: Consultancy (Includes expert testimony) AstraZeneca: Consultancy (Includes expert testimony); Research Funding BeiGene: Consultancy (Includes expert testimony); Research Funding BeOne Medicines: Consultancy (Includes expert testimony); Research Funding BMS: Consultancy (Includes expert testimony) GSK: Consultancy (Includes expert testimony) Incyte: Consultancy (Includes expert testimony) Lilly: Consultancy (Includes expert testimony) Merck: Consultancy (Includes expert testimony) Pfizer: Consultancy (Includes expert testimony) Roche/Genentech: Consultancy (Includes expert testimony); Research Funding SeaGen: Consultancy (Includes expert testimony) Mou:Abbvie: Consultancy (Includes expert testimony) Martin:AbbVie: Consultancy (Includes expert testimony) AstraZeneca: Consultancy (Includes expert testimony) Beigene: Consultancy (Includes expert testimony) Genentech: Consultancy (Includes expert testimony) Janssen: Consultancy (Includes expert testimony) Merck: Consultancy (Includes expert testimony) Pepromene: Consultancy (Includes expert testimony) Nze:Biegene/BeOne: Research Funding Bristol Myers Squibb foundation: Research Funding Cardinal Health: Honoraria Cohere Health: Consultancy (Includes expert testimony) Daiichi Sankyo: Research Funding MD Anderson Cancer Center: Current Employment Nowakowski:AbbVie,: Consultancy (Includes expert testimony) Bristol Myers Squibb/Celgene: Consultancy (Includes expert testimony) Celgene: Consultancy (Includes expert testimony); Research Funding Debiopharm Group: Consultancy (Includes expert testimony) Genentech: Consultancy (Includes ex
Details
- Title: Subtitle
- Age-stratified prognostic performance of patient- vs disease-related IPI factors in large B-cell lymphoma
- Creators
- Prokop Vodicka - Charles UniversityMatthew Maurer - Mayo ClinicPavel Klener - Charles UniversityGeorge Cholack - Mayo ClinicVit Prochazka - University Hospital OlomoucYucai Wang - Mayo ClinicDavid Belada - University Hospital Hradec KrálovéChristopher Flowers - The University of Texas MD Anderson Cancer CenterDavid Salek - Masaryk UniversityIzidore S. Lossos - Sylvester Comprehensive Cancer CenterHeidi Mocikova - Charles UniversityAndrew Feldman - Mayo ClinicJuraj Ďuraš - University Hospital OstravaJonathon Cohen - Emory UniversityKaterina Steinerova - Charles UniversityCarla Casulo - University of Rochester MedicineJan Pirnos - Nemocnice České BudějoviceBrad Kahl - Saint Louis UniversityKamila Polgarova - Charles UniversityEric Mou - University of IowaAndrea Janikova - Masaryk UniversityPeter Martin - Cornell UniversityAlice Sykorova - University Hospital Hradec KrálovéAles Obr - Palacký University OlomoucDavid Jaye - Emory UniversityVit Campr - Charles UniversityDiana Malarikova - Charles UniversityShaun Riska - Mayo ClinicMichal Kascak - University Hospital OstravaAlexandra Suri - Charles UniversityChijioke Nze - The University of Texas MD Anderson Cancer CenterJozef Michalka - Masaryk UniversityRadek Jaksa - Charles UniversityGrzegorz Nowakowski - Mayo ClinicJitka Dlouha - Lymphoma Study AssociationPetra BlahovcovaThomas Habermann - Mayo ClinicKaterina Benesova - Charles UniversityJames Cerhan - Mayo ClinicMarek Trneny - Charles University
- Resource Type
- Abstract
- Publication Details
- Blood, Vol.146, 4516
- DOI
- 10.1182/blood-2025-4516
- ISSN
- 0006-4971
- eISSN
- 1528-0020
- Publisher
- Elsevier Inc
- Grant note
- Charles University Haematology-Oncology Cooperatio Program: P50 CA97274, U01 CA195568, NU21-03-00411
NU21-03-00411, P50 CA97274, U01 CA195568, Charles University Haematology-Oncology Cooperatio Program.
- Language
- English
- Date published
- 11/03/2025
- Academic Unit
- Hematology, Oncology, and Blood & Marrow Transplantation; Epidemiology; Internal Medicine
- Record Identifier
- 9985222846202771
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