Prognostic impact of diagnosis-to-treatment interval in follicular lymphoma patients treated with immunochemotherapy: Evidence from an international cohort with independent validation
Abstract
Abstract Introduction Short diagnosis-to-treatment interval (DTI) is associated with aggressive disease biology and inferior outcomes in diffuse large B-cell lymphoma (DLBCL), and is recognized as a potential source of selection bias in clinical trials if not properly addressed. However, its prognostic significance in follicular lymphoma (FL) remains poorly characterized. We aimed to evaluate the prognostic significance of DTI in newly diagnosed FL patients who received frontline (1L) immunochemotherapy (IC), using a large international dataset and an independent external validation cohort. Methods For the discovery dataset, we evaluated patients diagnosed between 2002 and 2018 from ten observational cohorts as part of the FLIPI24 Consortium. External validation was conducted using data from patients enrolled in the Lymphoma Epidemiology of Outcomes (LEO) Cohort between 2010 and 2015. All patients had FL grade 1–3A and received 1L IC within 100 days of diagnosis. Patients with a concurrent DLBCL were excluded. Missing baseline laboratory values were addressed via multiple imputation. The primary endpoint was event-free survival at 24 months (EFS24); secondary endpoint was 5-year overall survival (OS), both calculated from treatment initiation. DTI was analyzed as continuous (via splines) and dichotomized variable (≤14 vs >14 days; as defined in DLBCL). Results In the discovery cohort (n=3,907), median age was 61 years (IQR 53–69), and 50% were male; 49% of patients were high-risk according to FLIPI, 26% according to PRIMA-PI, and 38% according to FLIPI24. Included patients received R-CHOP (54%), R-CVP (26%), or B-R (20%) as 1L treatment, followed by anti-CD20 maintenance in 60%. The median DTI was 30 days (IQR 17–48). Using the 14-day cut-off, 851 patients (22%) had short DTI. These patients had more adverse baseline characteristics, including B symptoms (42% vs 32%, P<0.01), ECOG performance status ≥2 (15% vs 8%, P<0.01), elevated LDH (51% vs 40%, P<0.01), hemoglobin <12 g/dL (30% vs 17%, P<0.01), and elevated β2-microglobulin (56% vs 44%, P<0.01). Prognostic indices (PIs) were also more frequently high-risk in the short-DTI group: FLIPI (56% vs 47%), PRIMA-PI (36% vs 24%), and FLIPI24 (51% vs 34%, all P<0.01). Spline modeling showed a decreasing EFS24 rate with increasing DTI, reaching a plateau at 30–40 days. In logistic regression model, each additional week of DTI improved EFS24 (OR 0.92, P<0.01). DTI attenuated but remained prognostic after adjusting for PIs (OR 0.93 for FLIPI, 0.95 for PRIMA-PI, 0.96 for FLIPI24, all P<0.01). When analyzed as a dichotomized variable, short DTI was associated with inferior EFS24: OR 1.74 adjusted for FLIPI, 1.63 for PRIMA-PI, and 1.53 for FLIPI24 (all P<0.01). The 2-year EFS of short vs long DTI groups was 71% vs 82% (HR 1.50, 95% CI 1.34–1.67, P<0.01), 5-year OS was 80% vs 86% (HR 1.38, 95% CI 1.21–1.56, P<0.01), and the 5-year cumulative risk of histologic transformation was 7.7% vs. 5.4% (P<0.01). In the validation cohort (n=516), median age was 61 years (IQR 52–69 years), 55% were male; 36% of patients were high-risk according to FLIPI; 29% according to PRIMA-PI, and 33% according to FLIPI24. Patients received B-R (59%) or R-CHOP (41%) as 1L treatment. The median DTI was 31 days (IQR 19–48), 84 patients (16%) had DTI ≤14 days. Similar patterns were observed; patients with short DTI had adverse baseline characteristics, PIs, and shorter 2-year EFS (72% vs 84%, HR 1.69, 95% CI 1.13–2.55, P=0.01). DTI remained associated with EFS24 when analyzed as a continuous variable (per week: OR 0.88 unadjusted, 0.90 with FLIPI, 0.89 with PRIMA-PI, and 0.89 with FLIPI24), and dichotomized (≤14 vs >14 days: OR 1.83 adjusted for FLIPI, 1.88 for PRIMA-PI, and 1.73 for FLIPI24). Conclusion Short DTI, defined as ≤14 days (observed in 22% of FL patients vs 46% in DLBCL), is a strong and independent predictor of inferior outcomes in newly diagnosed FL patients treated with IC. While DTI correlates with adverse baseline features and established PIs, it retains independent prognostic value. Although a 14-day threshold is reasonable for risk modeling, DTI contains greater informational value when modeled as a continuous variable. Among PIs, FLIPI24 most strongly attenuated the DTI effect, underscoring its superior discriminative power over FLIPI and PRIMA-PI. Clinical trials designs should mitigate any potential barriers to enrollment of FL patients requiring urgent therapy.
Article Details
Authors (35)
Prokop Vodička
1First Department of Medicine, First Faculty of Medicine Charles University and General Hospital, Prague, Czech Republic
Tarec Christoffer El-Galaly
3Departments of Hematology, Clinical Epidemiology, and Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
Vit Prochazka
Christopher Flowers
1Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX
Diego Villa
8Division of Medical Oncology, BC Cancer Centre for Lymphoid Cancer and The University of British Columbia, Vancouver, Canada
Caroline Dietrich
1Karolinska Institutet, Clinical Epidemiology Division, Department of Medicine Solna, Solna, Sweden
Hervé Ghesquieres
Hopital Lyon Sud, Claude Bernard Lyon 1 University, Pierre-Benite, France
Michael Roost Clausen
2Vejle Hospital, Sygehus Lillebaelt, Department of Hematology, Vejle, Denmark
Robert Kridel
Princess Margaret Cancer Centre, Toronto
Chan Cheah
20Sir Charles Gairdner Hospital, Nedlands, Australia
Eliza Hawkes
1Olivia Newton-John Cancer Research Institute, Heidelberg, Australia
Björn Wahlin
15Department of Hematology, Karolinska University Hospital, Stockholm, Sweden
Maher Gandhi
2University of Queensland, Mater Research Institute, Brisbane, Australia
Melissa Larson
2Mayo Clinic, Rochester, United States
Elliot Cahn
2Mayo Clinic, Department of Quantitative Health Sciences, Rochester, United States
Jonathan Friedberg
15Wilmot Cancer Center, University of Rochester, Department of Medicine, Hematology/Oncology, Rochester, United States
Peter Martin
Dai Chihara
Jonathon Cohen
15Winship Cancer Institute, Emory University, Atlanta CA
Thomas Habermann
2Mayo Clinic, Rochester, United States
Carla Casulo
18Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY
Yucai Wang
State Key Laboratory of Immune Response and Immunotherapy, Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine
Peter Brown
Eric Mou
24Division of Hematology, Oncology, and Blood and Marrow Transplantation, Department of Internal Medicine, University of Iowa, Iowa City, IA
David Belada
4th Department of Internal Medicine - Haematology, University Hospital and Faculty of Medicine, Hradec Kralove, Czech Republic
Andrea Janíková
26Department of Internal Medicine, Hematology and Oncology, University Hospital Brno and Faculty of Medicine, Masaryk University, Brno, Czech Republic
Heidi Mocikova
Richard Burack
Izidore S. Lossos
29Division of Hematology, Department of Medicine, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
Brad Kahl
8Washington University, Division of Oncology, St. Louis, United States
Karin Ekstroem Smedby
4Karolinska Institutet, Division of Clinical Epidemiology, Department of Medicine Solna, Stockholm, Sweden
Laurie Sehn
3BC Cancer Centre for Lymphoid Cancer and The University of British Columbia, Vancouver, Canada
Marek Trneny
James Cerhan
2Mayo Clinic, Rochester, United States
Matthew Maurer
2Mayo Clinic, Rochester, United States