COMPARATIVE EFFECTIVENESS OF SALVAGE CHEMOTHERAPY AND CHIMERIC ANTIGEN T‐CELL RECEPTOR THERAPIES IN R/R DLBCL: A SYSTEMATIC REVIEW AND NETWORK META‐ANALYSIS
Bibliographic record
Abstract
David Hodgson and John Kuruvilla are co-senior investigators Introduction: The optimal salvage chemotherapy (SC) regimen for relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) prior to autologous stem cell transplant (ASCT) remains unclear. Head-to-head comparison of chimeric antigen receptor T cell (CAR-T) therapies for second line use in primary refractory DLBCL is lacking. Given these limitations, we conducted a systematic review and network meta-analysis (NMA) of randomized clinical trials (RCTs) to assess the efficacy and safety of SC and CAR-T therapies for R/R DLBCL. Methods: We searched MEDLINE, EMBASE and CENTRAL from Jan 1 2006 to July 7 2022 for RCTs enrolling patients diagnosed with R/R DLBCL following treatment (trt) with at least 1 prior regimen. The primary outcome was overall survival (OS), and secondary outcomes were progression free survival (PFS) and grade ≥ 3 adverse events (AEs). NMA was conducted using a fixed-effect model to synthesize evidence. Surface under the cumulative ranking curve was used to rank the relative effect of compared trt. Results: A total of 22 RCTs (n=4505) met eligibility criteria, 13 included for qualitative synthesis only. NMA of SC (6 RCTs, n=1831) compared 7 trt: GDP (gemcitabine, dexamethasone, cisplatin), rituximab (R)-GDP, ICE (ifosfamide, mesna, carboplatin, etoposide), R-ICE, DHAP (dexamethasone, cytarabine, cisplatin), R-DHAP, ofatumumab (O)-DHAP, ESHAP (etoposide, cytarabine, cisplatin, methylprednisolone). Results indicated that R-GDP had improved OS and PFS over other regimens (Table), and ranked highest for OS and PFS. NMA of AEs showed no differences for infection. NMA of 3 CAR-T RCTs (axi-cel, liso-cel, tisa-cel; n=733) showed that axi-cel and liso-cel had improved PFS over SC and ASCT, while no OS difference was observed. Comparing between CAR-T products, both axi-cel and liso-cel had improved OS and PFS over tisa-cel. Liso-cel ranked highest for PFS. NMA of AEs showed that tisa-cel and axi-cel had higher risk of cytokine release syndrome over SC, while axi-cel had higher risk of neurologic toxicity over SC. Conclusions: Our results suggest that R-GDP may be the optimal regimen for R/R DLBCL prior to ASCT. Both axi-cel and liso-cel had improved PFS over SC and ASCT, while tisa-cel did not. Although liso-cel ranked highest for PFS, longer follow-up is required for comparative survival analysis as data matures. Keywords: Aggressive B-cell non-Hodgkin lymphoma, Therapeutics and Clinical Trials in Lymphoma - Other No conflicts of interests pertinent to the abstract.
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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 | 0.020 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".