Phase Ib study of avadomide (CC‐122) in combination with rituximab in patients with relapsed/refractory diffuse large B‐cell lymphoma and follicular lymphoma
Bibliographic record
Abstract
Abstract The multicenter, phase Ib CC‐122‐DLBCL‐001 dose‐expansion study (NCT02031419) explored the cereblon E3 ligase modulator (CELMoD) agent avadomide (CC‐122) plus rituximab in patients with relapsed/refractory (R/R) diffuse large B‐cell lymphoma (DLBCL) or follicular lymphoma (FL). Patients received avadomide 3 mg/day 5 days on/2 days off plus rituximab 375 mg/m2 on day 8 of cycle 1, day 1 of cycles 2 through 6, and day 1 of every third subsequent cycle for 2 years. Primary endpoints were safety and tolerability; preliminary efficacy was a secondary endpoint. A total of 68 patients were enrolled (DLBCL [n = 27], FL [n = 41; 31 lenalidomide‐naïve, 10 lenalidomide‐treated]). Median age was 62 years (range, 33–84 years), and patients had received a median of 3 (range, 1–8) prior regimens. Among patients with DLBCL, 66.7% had primary refractory disease (partial response or less to initial therapy). Among patients with FL, 65.9% were rituximab‐refractory at study entry and 10.0% were lenalidomide‐refractory. The most common any‐grade avadomide‐related adverse events (AEs) were neutropenia (63.2%), infections/infestations (23.5%), fatigue (22.1%), and diarrhea (19.1%). The most common grade 3/4 avadomide‐related AEs were neutropenia (55.9%) infections/infestations (8.8%), and febrile neutropenia (7.4%). In patients with DLBCL, overall response rate (ORR) was 40.7% and median duration of response (mDOR) was 8.0 months. In patients with FL, ORR was 80.5% and mDOR was 27.6 months; response rates were similar in lenalidomide‐naïve and ‐treated patients. Avadomide plus rituximab was well tolerated, and preliminary antitumor activity was observed in patients with R/R DLBCL and FL, including subgroups with typically poor outcomes. These results support further investigation of novel CELMoD agents in combination with rituximab in R/R DLBCL and FL.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".