Prognostic Significance of Neutrophil to Lymphocyte Ratio (NLR) in Relapsed/Refractory Aggressive Lymphoma Salvage Chemotherapy — Analysis of Canadian Cancer Trials Group (CCTG) ly.10 Trial
Bibliographic record
Abstract
Abstract Background: The neutrophil to lymphocyte ratio (NLR) at the time of diagnosis has been shown as a prognostic marker to predict outcomes of treatment in patients with aggressive lymphoma in both non-Hodgkin (NHL) and Hodgkin lymphoma (HD). The growing evidence that tumor microenvironment, host immunity and inflammatory responses play an important role in progression of different malignancies supports this rationale. The prognostic significance of NLR has only been studied in the frontline setting in HD and NHL. Therefore the aim of this study is to evaluate correlation of NLR with response to salvage therapy in patients with relapsed or refractory aggressive lymphoma. Methods: This is a retrospective review of participants in the CCTG LY.10 trial, a phase 2 clinical trial evaluating treatment with Gemcitabine, Dexamethasone and Cisplatin (GDP) in patients with relapsed or refractory NHL and HD who are eligible for Autologous Stem Cell Transplantation (ASCT). Seventy-seven patients were treated with GDP, 23 with HD and 51 with NHL. The overall response rate (ORR) including complete and partial response to GDP salvage therapy was 69.5% in HD and 49% in NHL. NLR was calculated on all patients at the time of relapse. Biomarker Threshold Models (Chen et al, 2014, Computational Statistics and Data Analysis, V71, page 324-334) were applied to identify the optimal cut off point for NLR. Categorical variables were compared using Chi-square test and survival distributions were compared using KM curves and Log-rank test. Results: A NLR of 8.4 was determined to be the optimal cut-off for prognosis. Among the full cohort of 77 patients, ORR in those with a NLR of < 8.4 was 70.6%, as compared with 33.4% for those with a NLR of > 8.4 (p=0.005). In the HD cohort the RR was 86.7% vs 50% (P =0.059) and was 63.9% vs 26.7% in the NHL cohort (P =0.015). In NHL the ability to proceed to transplant was correlated with NLR of <8.4 with 52.7% vs 20% of patients proceeding to ASCT (P = 0.031). All patients with HD proceeded to transplant regardless of their NLR. Patients with NLR <8.4 had better progression free survival (PFS) at 12 months; 100% vs 71% in patients with HD (P = 0.028) and 27 % vs 11% in patients with NHL (P =0.05). Conclusion: NLR is a readily available marker correlated with outcomes (ORR, transplant rate and PFS) and can be used to identify high risk patients at the time of relapse of aggressive lymphoma. This easily measurable prognostic marker would be especially useful in the era of novel treatment options to identify higher risk patients. Further analysis on larger data sets are required to validate this finding. Disclosures Hay: Seattle Genetics: Research Funding; Roche: Research Funding; Janssen: Research Funding; Novartis: Research Funding; Amgen: Research Funding; Kite: Research Funding. Baetz:Merck: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Research Funding.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".