A low lymphocyte‐to‐monocyte ratio is independently associated with early relapse (POD24) in high tumour burden follicular lymphoma: A RELEVANCE subanalysis
Bibliographic record
Abstract
The peripheral blood lymphocyte-to-monocyte ratio (LMR) has been shown to predict outcomes in follicular lymphoma (FL). Among 1018 patients from the RELEVANCE trial (for previously untreated, high tumour burden FL), the median LMR was 2.5 (range, 0.3-93.5) and an LMR cut-off of 2 was mostly associated with survival end-points. Patients with an LMR ≤2 (n = 372; 37%) were older and had higher risk disease. An LMR ≤2 was associated with a shorter progression-free survival (PFS) (hazard ratio [HR] = 1.39, p = 0.002) and overall survival (OS) (HR = 1.44, p = 0.049). The association of the LMR with PFS was significant in the rituximab plus chemotherapy arm (p = 0.01) and inconclusive in the rituximab plus lenalidomide arm (p = 0.08). Within the three Follicular Lymphoma International Prognostic Index risk categories, the LMR retained its association with PFS only in the low-risk group (p = 0.03). An LMR ≤2 was also associated with a higher risk of progression of disease within 24 months of treatment initiation (univariable odds ratio (OR) = 1.84, p < 0.001; multivariable OR = 1.58, p = 0.02). In conclusion, the LMR is an easily accessible parameter informative of outcomes in FL patients in need of treatment, being especially helpful in otherwise low-risk patients. Whether the incorporation of immunomodulators such as lenalidomide will reduce its negative prognostic value needs to be further investigated.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".