International Working Group consensus response evaluation criteria in lymphoma (RECIL 2017)
Bibliographic record
Abstract
In recent years, the number of approved and investigational agents that can be safely administered for the treatment of lymphoma patients for a prolonged period of time has substantially increased. Many of these novel agents are evaluated in early-phase clinical trials in patients with a wide range of malignancies, including solid tumors and lymphoma. Furthermore, with the advances in genome sequencing, new "basket" clinical trial designs have emerged that select patients based on the presence of specific genetic alterations across different types of solid tumors and lymphoma. The standard response criteria currently in use for lymphoma are the Lugano Criteria which are based on [18F]2-fluoro-2-deoxy-D-glucose positron emission tomography or bidimensional tumor measurements on computerized tomography scans. These differ from the RECIST criteria used in solid tumors, which use unidimensional measurements. The RECIL group hypothesized that single-dimension measurement could be used to assess response to therapy in lymphoma patients, producing results similar to the standard criteria. We tested this hypothesis by analyzing 47 828 imaging measurements from 2983 individual adult and pediatric lymphoma patients enrolled on 10 multicenter clinical trials and developed new lymphoma response criteria (RECIL 2017). We demonstrate that assessment of tumor burden in lymphoma clinical trials can use the sum of longest diameters of a maximum of three target lesions. Furthermore, we introduced a new provisional category of a minor response. We also clarified response assessment in patients receiving novel immune therapy and targeted agents that generate unique imaging situations.
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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 | 0.046 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".