Plain language summary of the ECHELON-3 study: brentuximab vedotin combination treatment in people with diffuse large B-cell lymphoma
Bibliographic record
Abstract
Plain Language SummaryWhat is this summary about?This is a summary of the results of a study called ECHELON-3. This study compared a brentuximab vedotin (BV) combination (BV, lenalidomide, and rituximab) and a placebo combination (placebo, lenalidomide, and rituximab). This analysis looked at how well the medicines worked and their side effects in people with a type of cancer called diffuse large B-cell lymphoma (DLBCL) that had relapsed or was refractory after previous treatments. The ECHELON-3 study is ongoing, and the results summarized here are not final.What were the results?In this study, 230 people with relapsed or refractory DLBCL were randomly assigned to receive either the BV combination (112 people) or the placebo combination (118 people).How long did they live?At least half of the people who received the BV combination lived for 13.8 months compared with 8.5 months for people who received the placebo combination. This benefit was seen in different subgroups of people, including people at high risk and people who had tried other advanced treatments.Did their tumors shrink or become undetectable on scans?More people who received the BV combination (72 out of 112, or 64%) had their cancer shrink or become undetectable (was not visible) on scans than people who received the placebo combination (49 out of 118, or 42%). Cancer became undetectable on scans for 45 out of 112 people (40%) who received the BV combination and 22 out of 118 people (19%) who received the placebo combination.Did they have any side effects from the medicines?Most people who received either the BV combination (109 out of 112, or 97%) or the placebo combination (113 out of 116, or 97%) experienced side effects. However, most side effects in the study were manageable.What do the results mean?This study showed that compared with people who took the placebo combination, people who took the BV combination lived longer; more people who took the BV combination had their cancer shrink or become undetectable on scans. For both treatments, side effects were similar and generally manageable.This is an abstract of the Plain Language Summary of Publication article.View the full Plain Language Summary PDF of this article to read the full-text
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.056 | 0.010 |
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".