HOSPITAL CAPACITY USE IN DIFFUSE LARGE B-CELL LYMPHOMA CARE: A POPULATION-BASED TREATMENT-PATHWAY MODEL
Author(s)
Michiel Zietse, MSc1, Aart Beeker, MD2, Roy Bleumink, MSc3, Marcel Nijland, MD4, Roelof Van Leeuwen, PhD5, Frederick W. Thielen, MSc, PhD6.
1PhD-Candidate, Erasmus MC, Rotterdam, Netherlands, 2Spaarne Gasthuis, Hoofddorp, Netherlands, 3Delta4Health, Arnhem, Netherlands, 4University Medical Center Groningen, Groningen, Netherlands, 5Healthbridgers BV, Den Haag, Netherlands, 6Erasmus University Rotterdam, Rotterdam, Netherlands.
1PhD-Candidate, Erasmus MC, Rotterdam, Netherlands, 2Spaarne Gasthuis, Hoofddorp, Netherlands, 3Delta4Health, Arnhem, Netherlands, 4University Medical Center Groningen, Groningen, Netherlands, 5Healthbridgers BV, Den Haag, Netherlands, 6Erasmus University Rotterdam, Rotterdam, Netherlands.
OBJECTIVES: Approximately 20 to 40% of patients with diffuse large B-cell lymphoma (DLBCL) develop relapsed/refractory (r/r) disease after first-line (1L) chemoimmunotherapy. Subsequent lines rely on resource-intensive strategies, including chimeric antigen receptor (CAR) T-cell therapy and stem-cell transplantation, placing substantial demands on hospital infrastructure and specialised staff. We developed a population-based treatment-pathway model to quantify hospital capacity use across DLBCL treatment lines in the Netherlands.
METHODS: A deterministic, cohort-based model simulated the 2025 incident population of adult DLBCL patients (n = 1,605) of which 79% received active 1L treatment. Patients were allocated across 1L, second-line (2L), and third-line (3L) pathways using fixed proportions from Dutch hematology guidelines, registry data, and Health Technology Assessment reports. Capacity outcomes included outpatient chair time, inpatient bed days, and nursing time expressed in hours and full-time equivalents (FTE). An independent external validation followed the AdVISHE framework.
RESULTS: Of 1,605 newly diagnosed patients, 1,268 were estimated to receive 1L, 331 received 2L, and 220 a 3L of therapy. First-line care accounted for the largest outpatient activity (26,817 outpatient hours; 6,704 nursing hours, 5 FTE). Capacity shifted markedly towards inpatient care in later lines: 2L generated 2,426 inpatient days and 41,160 nursing hours (53 FTE). Third-line care added 1,396 inpatient days and 25,493 nursing hours (19 FTE). Across the r/r population (n = 368), combined 2L and 3L treatment accounted for 10.4 inpatient days and 181.1 nursing hours per patient.
CONCLUSIONS: Hospital capacity use in DLBCL care is concentrated disproportionately in r/r disease, driven by CAR T-cell therapy and intensive salvage pathways despite smaller patient numbers in later lines. By translating treatment sequencing into workforce and infrastructure requirements, this adaptable model supports budget impact analysis, capacity planning, and implementation feasibility of emerging therapies and alternative delivery models.
METHODS: A deterministic, cohort-based model simulated the 2025 incident population of adult DLBCL patients (n = 1,605) of which 79% received active 1L treatment. Patients were allocated across 1L, second-line (2L), and third-line (3L) pathways using fixed proportions from Dutch hematology guidelines, registry data, and Health Technology Assessment reports. Capacity outcomes included outpatient chair time, inpatient bed days, and nursing time expressed in hours and full-time equivalents (FTE). An independent external validation followed the AdVISHE framework.
RESULTS: Of 1,605 newly diagnosed patients, 1,268 were estimated to receive 1L, 331 received 2L, and 220 a 3L of therapy. First-line care accounted for the largest outpatient activity (26,817 outpatient hours; 6,704 nursing hours, 5 FTE). Capacity shifted markedly towards inpatient care in later lines: 2L generated 2,426 inpatient days and 41,160 nursing hours (53 FTE). Third-line care added 1,396 inpatient days and 25,493 nursing hours (19 FTE). Across the r/r population (n = 368), combined 2L and 3L treatment accounted for 10.4 inpatient days and 181.1 nursing hours per patient.
CONCLUSIONS: Hospital capacity use in DLBCL care is concentrated disproportionately in r/r disease, driven by CAR T-cell therapy and intensive salvage pathways despite smaller patient numbers in later lines. By translating treatment sequencing into workforce and infrastructure requirements, this adaptable model supports budget impact analysis, capacity planning, and implementation feasibility of emerging therapies and alternative delivery models.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE695
Topic
Clinical Outcomes, Economic Evaluation, Health Service Delivery & Process of Care
Topic Subcategory
Budget Impact Analysis, Cost/Cost of Illness/Resource Use Studies
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, Oncology