A low lymphocyte‐to‐monocyte ratio (LMR) predicts PFS, POD24 and OS in previously untreated, high tumor burden follicular lymphoma (FL): an analysis from the RELEVANCE trial
Bibliographic record
Abstract
Introduction: The peripheral blood LMR has been postulated as an accessible piece of information about the composition of the tumor microenvironment. In a single-center, retrospective, unselected cohort of FL, a low LMR was shown to be associated with an older age and higher tumor burden and to predict for a shorter progression-free and overall survival (PFS, OS) and a higher risk of histological transformation and second primary malignancies (Mozas, Leuk & Lymph, 2020). We explored the impact of the LMR in patients included in the phase III RELEVANCE trial (Morschhauser, NEJM, 2018 and JCO, 2022), which compared rituximab-chemotherapy (R-chemo) with rituximab-lenalidomide (R2) in patients with previously untreated, high tumor burden FL. Methods: Xtile and the maxstat package of R software were used to find the best LMR cutoff based on PFS data and then validated using a truncated power basis spline method. Baseline characteristics, PFS per investigator assessment, early relapse (POD24) and OS were compared between LMR risk groups. Multivariable Cox regression models including the FLIPI score and the treatment arm were built for survival analyses and uni/multivariable logistic regression was used for POD24 analysis. Results: Among the 1030 patients included in the RELEVANCE study, 1018 had LMR data available. The median LMR was 2.5 (range, 0–93) and a LMR cutoff of 2 was found to best predict PFS. Patients with a LMR ≤2 (n = 372, 37%) were older and displayed higher-risk features (Figure A). In the global cohort, a LMR ≤2 was predictive of a shorter PFS (HR = 1.39 Figure B and C) and OS (HR = 1.44), but its negative impact in the multivariable model remained statistically significant solely for PFS (HR for LMR = 1.31). Likewise, a LMR ≤2 was associated with a higher risk of POD24 (univariable OR = 1.84; multivariable OR = 1.71). No significant interaction was observed in the PFS analysis between treatment arms and the LMR, despite the fact that the LMR was significantly associated to PFS only in the R-chemo arm (P = 0.001) and not in the R2 arm (P = 0.08). The research was funded by: The RELEVANCE trial was supported by Celgene, a Bristol Myers Squibb Company, and the Lymphoma Academic Research Organisation (LYSARC). Keywords: Diagnostic and Prognostic Biomarkers, Indolent non-Hodgkin lymphoma, Targeting the Tumor Microenvironment Conflicts of interests pertinent to the abstract. A. Martín García-Sancho Other remuneration: Janssen, Roche, BMS, Kyowa Kirin, Clinigen, Eusa Pharma, Novartis, Gilead/Kite, Incyte, Lilly, Takeda, ADC Therapeutics America, Miltenyi, Ideogen, Abbvie P. Abrisqueta Consultant or advisory role: Janssen, Roche, Abbvie, BMS, Astrazeneca, Gilead, Beigene Honoraria: Janssen, Roche, Abbvie, BMS, Astrazeneca, Gilead Educational grants: Janssen, Abbvie, Roche M. Crump Other remuneration: Kyte/Gilead, Novartis F. Morschhauser Consultant or advisory role: Roche, Gilead, Genmab, Novartis, Abbvie Honoraria: Chugai (scientific lectures)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".