Plain Language Summary of the iNNOVATE Study: Ibrutinib Plus Rituximab is Well-Tolerated and Effective in People with Waldenström's Macroglobulinemia
Bibliographic record
Abstract
What is this summary about? This article provides a short summary of 5-year results from the iNNOVATE trial. The original paper was published in the Journal of Clinical Oncology in October 2021. People with Waldenström's macroglobulinemia (WM) were randomly divided into two groups of 75 people each. One group received a combination treatment composed of two drugs, ibrutinib plus rituximab, and the other group took placebo (“sugar pill”) plus rituximab. Ibrutinib (also known by the brand name Imbruvica®) is a drug that reduces cancer cells' ability to multiply and survive. Ibrutinib is an FDA-approved drug for the treatment of WM. Rituximab is a drug that helps the immune system find and kill cancer cells. Participants in the trial were treated and their health monitored for up to 5 years (63 months).What were the results? During the 5 years of monitoring, more people who took ibrutinib plus rituximab experienced an improvement in their disease and lived longer without their disease getting worse compared to those who took placebo plus rituximab. Side effects from ibrutinib and rituximab were manageable and generally decreased over time. Participants in both study groups reported improvements in quality of life, but those who took ibrutinib plus rituximab reported significantly greater improvement in their quality of life (as measured by FACT-An score) compared to those who took placebo plus rituximab.What do the results mean? These results show that ibrutinib plus rituximab is better than rituximab alone in people with WM and that ibrutinib plus rituximab is safe and effective in the long term. This information confirms the role of ibrutinib plus rituximab as a standard of care for WM. Clinical Trial Registration: NCT02165397 (ClinicalTrials.gov)To read the full Plain Language Summary of this article, click here to view the PDF.Link to original article here
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.047 | 0.014 |
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".