Real World Characteristics and Outcomes of Patients with Relapsed and Refractory Diffuse Large B Cell Lymphoma; A Provincial Experience
Bibliographic record
Abstract
Introduction: Relapsed/refractory diffuse large B cell lymphoma (DLBCL) is an aggressive disease associated with a poor prognosis. Chimeric antigen receptor T cell (CAR-T) therapy is now approved for patients with relapsed/refractory DLBCL who have refractory or relapsed disease after two lines of systemic therapy. However, there is limited data that explores real world patient and disease characteristics in this high risk and fragile population to help determine what percentage of real world patients with relapsed/refractory DLBCL would be eligible for CAR-T cell therapy based on clinical trial criteria. Methods:Adult DLBCL patients under age 70 years who had relapsed or refractory disease after two lines of therapy from 2011-2018 in Alberta were retrospectively reviewed. Data was collected to determine baseline characteristics, disease factors and treatment outcomes at both diagnosis and second relapse. Results: In total, 90 patients were identified with refractory or relapsed DLBCL after two lines of systemic therapy. The median age at diagnosis was 58.2 years (IQR 54.0-65.0) and median age at second relapse was 60.4 (IQR 54.7-67.6). The majority of patients had de novo DLBCL (n=57s, 63.3%) while 33 patients (36.7%) had transformed disease. There were 10 patients (11.1%) who had had prior systemic therapy for an indolent lymphoma including 2 patients with previous autologous stem cell transplant. There were 59 patients who had refractory disease while the remaining 31 patients had relapsed disease. There were 43 patients (47.8%) patients who had received an autologous stem cell transplantation. At second relapse, 59 patients (65.6%) would not have qualified for CAR-T cell therapy based upon clinical trial criteria. These reasons included: 1) ECOG performance status 2-4 (n=49, 54.4%); 2) CNS disease at second relapse (n=10, 11.1%) 3) bone marrow involvement resulting in a platelet count <75 x 109/L or absolute neutrophil count <1.0 x 109/L (n=15, 16.7%). Outcomes were poor with a one year overall survival of 29.1% and a median overall survival from second relapse of 3.8 months. Patients who would have been eligible for CAR-T therapy based on clinical trial criteria had better survival (HR 0.41, CI 0.35-0.68, P<.05). Post second relapse treatment including salvage chemotherapy (n=37, 41.1%), radiation therapy (n=8, 8.9%), autologous stem cell transplantation (n=1, 1.1%), allogeneic stem cell transplantation (n=1, 1.1%) and palliation (n=42, 46.7%). Worse survival was observed in patients with refractory disease (HR 2.61, CI 1.58-4.32, p<.05) and in patients with an ECOG greater than or equal to 2 (HR 2.68, CI 1.65-4.34, p<.05). Conclusion:Patients with relapsed/refractory DLBCL have a very poor outcome and have high risk disease at relapse including advanced stage disease and poor performance status. Less than half of the patients in our study would qualify for CAR-T therapy based on clinical trial criteria. More real world data is needed to see how feasible and effective novel cellular therapy is for these high risk patients. Disclosures Stewart: AstraZeneca:Honoraria;Abbvie:Honoraria;Novartis:Honoraria;Roche:Honoraria;Janssen:Honoraria;Teva:Honoraria;Amgen:Honoraria;Gilead:Honoraria;Celgene:Honoraria;Sandoz:Honoraria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".