THE PROGNOSTIC IMPACT OF CLINICAL FACTORS AND IMMUNOARCHITECTURAL PATTERNS FOR NODULAR LYMPHOCYTE‐PREDOMINANT HODGKIN LYMPHOMA: AN INTERNATIONAL STUDY BY GLOW
Bibliographic record
Abstract
Introduction: Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) is a rare entity. Studies evaluating outcomes for patients of all ages with scoring of immunoarchitectural patterns (IAPs) are needed to inform optimal management. We sought to perform an international multicenter study of pediatric and adult patients with all stages of NLPHL to develop a prognostic model and assess the impact of IAP. Methods: Thirty-seven centers participated in the Global nLPHL One Working Group (GLOW) to retrospectively identify cases of NLPHL diagnosed from 1992 to 2021. Pathology was reviewed at individual centers with scoring of IAPs when available. For analysis, the presence of any variant IAP pattern (C-F) in biopsies were scored as variant cases. We measured progression-free survival (PFS), overall survival (OS), transformation rate, and lymphoma-specific death rate. We performed uni- and multivariable (MVA) Cox regression stratified by management type to select factors for inclusion in the lymphocyte-predominant international prognostic score (LP-IPS). Time-dependent ROC modeling was used to test model performance with bootstrapping for internal validation. Analyses were two-tailed and significant with p < 0.05 (R version 4.2.2). Results: We identified 2193 patients with a median age of 37 years (quartiles: 2–23, >23–37, >37–51, >51). Median follow up was 6.3 years (IQR = 3.5–10.8). Most patients were male (74.8%) and had stage I-II (73.3%) disease. A minority had B-symptoms (9.9%) or splenic involvement (5.1%) at presentation. IAP data was available for 916 patients (41%), of which 73.8% were pattern A/B, 8.5% C, 9.0% D, 7.3% E, and 1.4% F. Upfront management included: chemotherapy alone (32.0%), combined modality therapy (30.9%), radiotherapy alone (24.0%), observation after excision (4.6%), rituximab alone (4.0%), active surveillance (3.4%), and rituximab and radiotherapy (1.1%). PFS, OS, transformation, and lymphoma-specific death rates at 10 years were 71.1%, 91.7%, 4.9%, and 3.2% respectively. Individual IAPs were not significantly associated with PFS or OS on MVA, but pattern E was significantly associated with higher risk of transformation on MVA (HR = 1.81, p = 9.2e-3). Based on our MVA, model AUC statistics, and similar HR sizes, we developed the LP-IPS which assigns 1 point each for age ≥45, stage III–IV, Hb < 10.5 g/dL, or splenic involvement. Increasing LP-IPS was significantly associated with worse PFS (HR = 1.53), OS (HR = 2.34), lymphoma specific death (HR = 2.67), and higher rates of transformation (HR = 1.53) per risk point (p < 0.05). Keywords: diagnostic and prognostic biomarkers, Hodgkin lymphoma Conflicts of interests pertinent to the abstract K. J. Savage Employment or leadership position: Beigene Consultant or advisory role: Celgene, Seagen, BMS, Merck, Gilead, Astra Zeneca, Janssen, Abbvie Honoraria: BMS, Merck, Gilead, Astra Zeneca, Janssen, Abbvie Other remuneration: DSMC: Regeneron F. Vega Research funding: CRISP Therapeutics, Allogene, and Geron corporation Other remuneration: supported by a R01CA222918 from the National Cancer Institute A. Prica Honoraria: Astra-Zeneca, Abbvie, Kite Gilead D. Talaulikar Honoraria: Roche, Janssen, Beigene, MSL, EUSA, CSL, Amgen Research funding: Roche, Janssen, Beigene, MSL, EUSA, CSL, Amgen D. A. Eichenauer Honoraria: Takeda and Sanofi-Genzyme
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".