234 | POST HOC ANALYSIS OF OUTCOMES BY POD24 STATUS FROM THE inMIND STUDY OF TAFASITAMAB PLUS LENALIDOMIDE AND RITUXIMAB IN RELAPSED OR REFRACTORY FOLLICULAR LYMPHOMA
Bibliographic record
Abstract
Introduction: Patients with follicular lymphoma (FL) commonly experience relapse; prognosis is worse in patients with disease progression within 24 months (POD24). inMIND (NCT04680052), a phase 3, double-blind, randomised, placebo (pbo)-controlled, multicentre international trial reported a significant, clinically meaningful 57% reduction in risk of progression, relapse or death with tafasitamab (tafa) added to lenalidomide (len) plus rituximab (R) (tafa+len+R) compared with addition of pbo to len plus R (pbo+len+R) in patients with relapsed or refractory (R/R) FL (Sehn LH, et al. Blood. 2024;144(Suppl. 2):LBA1). PFS benefit was observed regardless of POD24 status, defined as disease progression within 24 months of initial FL diagnosis. This post hoc analysis reports PFS and other outcomes with POD24 defined as disease progression within 24 months of start of initial treatment, to assess whether the positive outcomes observed with tafa+len+R compared to pbo+len+R were maintained regardless of the definition of POD24. Additionally, PFS in patients with progression of disease within 12 months of start of initial treatment (POD12) was assessed. Methods: Patients ≥ 18 y with R/R CD19+ and CD20+ FL (grade 1–3A), ECOG PS ≤ 2, requiring treatment after ≥ 1 prior systemic therapy including an anti-CD20 monoclonal antibody (mAb), were randomised 1:1 to receive tafa+len+R or pbo+len+R for 12 cycles. Endpoints evaluated included investigator-assessed PFS, PET-CR, ORR, and TTNT. Results: As defined from start of initial treatment: 249 patients (45.4%) were POD24 positive, 282 (51.5%) were POD24 negative, and 17 (3.1%) had unknown status. Overall, patient characteristics were similar across treatment arms (not shown) and POD24-positive versus POD24-negative groups (median age, 63.0 vs. 66.0 y; GELF criteria met, 82.7% vs. 83.0%; median prior lines of therapy, 1.0 in each group). However, more POD24-positive patients had negative prognostic factors: high-risk FLIPI (57.4% vs. 46.8%); refractory to prior anti-CD20 mAb (66.7% vs. 20.2%). Investigator-assessed PFS was significantly longer with tafa+len+R among POD24-positive and POD24-negative patients (hazard ratio [95% CI], 0.4 [0.3, 0.7] and 0.5 [0.3, 0.7]). Tafa+len+R also improved PET-CR, ORR and TTNT (Table). Addition of tafa to len+R improved PFS by investigator regardless of POD12 status compared to pbo (Table). Conclusions: POD24 is a known predictor of early mortality in FL. In inMIND, tafa+len+R reduced the risk of progression, relapse or death in patients with R/R FL regardless of POD24 status and the definition of POD24 used. Benefit of adding tafa was also observed regardless of POD12 status, and in other outcomes including PET-CR, ORR and TTNT. Thus, tafa+len+R represents a potential new treatment option for these patients with R/R FL regardless of their disease progression status. Research funding declaration: Incyte Corporation, Wilmington, DE Encore Abstract: ASCO 2025; EHA 2025 Keywords: combination therapies; immunotherapy; indolent non-Hodgkin lymphoma Potential sources of conflict of interest: L. H. Sehn Consultant or advisory role: AbbVie, Acerta, Apobiologix, AstraZeneca, Celgene, Debiopharm, Genentech, Genmab, Gilead Sciences, Incyte Corporation, Janssen, Karyopharm Therapeutics, Kite Pharma, Lundbeck, Merck, MorphoSys, Novartis, Sandoz, Takeda, TG Therapeutics, Verastem Oncology, Teva, Roche, Seattle Genetics Other remuneration: Teva, Roche, Seattle Genetics K. Hübel Consultant or advisory role: AbbVie, Beigene, Bristol Myers Squibb, EUSA/Recordati, Gilead Sciences, Incyte Corporation, Novartis, Roche, Servier Other remuneration: AbbVie, Beigene, Bristol Myers Squibb, EUSA/Recordati, Gilead Sciences, Incyte Corporation, Novartis, Roche, Servier S. Luminari Consultant or advisory role: AbbVie, Bristol Myers Squibb, Genmab, Incyte Corporation, Janssen, Kite, Novartis, Regeneron, Roche C. W. Scholz Consultant or advisory role: Bristol Myers Squibb, Celgene, Daiichi Sankyo, Gilead Sciences, Hexal, Incyte Corporation, Janssen, Merck Serono, Novartis, Roche, Takeda Honoraria: AstraZeneca, Gilead Sciences, Janssen, Pfizer, Roche A. Salar Consultant or advisory role: AbbVie, AstraZeneca, Beigene, Incyte Corporation, Ipsen, Roche, Sandoz Other remuneration: AbbVie, AstraZeneca, Beigene, Incyte Corporation, Ipsen, Roche, Sandoz, Gilead Sciences S. Paneesha Honoraria: AbbVie, Beigene, Celgene, Gilead Sciences, Janssen, Roche B. E. Wahlin Consultant or advisory role: Roche Honoraria: Incyte Corporation, MorphoSys Other remuneration: Gilead Sciences H. Lee Consultant or advisory role: AstraZeneca, BeiGene, Gilead Sciences Honoraria: Roche A. Jiménez-Ubieto Consultant or advisory role: AbbVie, AstraZeneca, Genmab, Kite, Lilly Other remuneration: AbbVie, Incyte Corporation, Janssen, Kite, Novartis, Roche J. Sancho Consultant or advisory role: AbbVie, AstraZeneca, Beigene, Bristol Myers Squibb-Celgene, Gilead-Kite, Incyte Corporation, Janssen, Lilly, Myltenyi Biomedicine, Novartis, Roche, Sobi Honoraria: AbbVie, Beigene, Bristol Myers Squibb-Celgene, Gilead-Kite, Incyte Corporation, Janssen, Lilly, Roche T. M. Kim Consultant or advisory role: Amgen, AstraZeneca/MedImmune, Boryung, Daiichi-Sankyo, HK inno.N, IMBDx. Inc., Janssen, Novartis, Regeneron, Roche/Genentech, Samsung Bioepis, Takeda, Yuhan E. Domingo Domenech Consultant or advisory role: BeiGene, Bristol Myers Squibb-Celgene, Ideogen, Takeda Other remuneration: BeiGene, Bristol Myers Squibb-Celgene, Ideogen, Takeda T. Kumode Honoraria: Janssen, Ono Pharmaceutical C. Poh Consultant or advisory role: Acrotech, AstraZeneca, Ipsen, Seagen Other remuneration: Astex, Dren Bio, Incyte Corporation, Seagen C. Thieblemont Consultant or advisory role: AbbVie, Amgen, Bayer, Bristol Myers Squibb/Celgene, Gilead Sciences Inc, Incyte Corporation, Janssen, Kite, Novartis, Roche, Takeda Honoraria: AbbVie, Amgen, Bayer, Bristol Myers Squibb/Celgene, Gilead Sciences Inc, Incyte Corporation, Janssen, Kite, Novartis, Roche, Takeda Educational grants: AbbVie, Amgen, Bayer, Bristol Myers Squibb/Celgene, Gilead Sciences Inc, Janssen, Kite, Novartis, Roche, Takeda Other remuneration: AbbVie, Amgen, Bayer, Bristol Myers Squibb/Celgene, Gilead Sciences Inc, Incyte Corporation, Janssen, Kite, Novartis, Roche, Takeda, Janssen, Roche D. Deeren Consultant or advisory role: Alexion, Bristol Myers Squibb, Incyte Corporation, Novartis, Sanofi, Sobi, Takeda Other remuneration: Alexion, Amgen, Novartis, Roche, and Sobi E. de Wit Employment or leadership position: Incyte Stock ownership: Incyte M. Arbushites Employment or leadership position: Incyte Stock ownership: Incyte O. Bortolami Employment or leadership position: Incyte Stock ownership: Incyte M. Trneny Consultant or advisory role: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Gilead Sciences, Incyte Corporation, Janssen, MorphoSys, Roche, Takeda Honoraria: AbbVie, Amgen, Bristol Myers Squibb, Gilead Sciences, Incyte Corporation, Janssen, MorphoSys, Roche, Takeda Educational grants: AbbVie, Bristol Myers Squibb, Gilead Sciences, Janssen, Roche, Takeda
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".