Validation of the <scp>MCL</scp>35 gene expression proliferation assay in randomized trials of the European Mantle Cell Lymphoma Network
Bibliographic record
Abstract
Mantle cell lymphoma (MCL) is still considered incurable and the course of the disease is highly variable. Established risk factors include the Mantle Cell Lymphoma International Prognostic Index (MIPI) and the quantification of the proliferation rate of the tumour cells, e.g. by Ki-67 immunohistochemistry. In this study, we aimed to validate the prognostic value of the gene expression-based MCL35 proliferation assay in patient cohorts from randomized trials of the European Mantle Cell Lymphoma Network. Using this assay, we analysed the gene expression proliferation signature in routine diagnostic lymph node specimens from MCL Younger and MCL Elderly trial patients, and the calculated MCL35 score was used to assign MCL patients to low (61%), standard (27%) or high (12%) risk groups with significantly different outcomes. We confirm here in our prospective clinical trial cohort of MCL patients, that the MCL35 assay is strongly prognostic, providing additional information to the Ki-67 index and the MIPI. Thus, this robust assay may assist in making treatment decisions or in devising risk-adapted prospective clinical trials in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".