Abstract 5053: Epstein-Barr virus prevalence in classical Hodgkin lymphoma tumors is explained by histologic subtype, not race/ethnicity in a multiethnic US population
Bibliographic record
Abstract
Abstract Epstein-Barr virus (EBV) is present in a varying proportion of classical Hodgkin lymphoma (cHL) tumors reportedly associated with age, sex, race/ethnicity and histologic subtype. As part of a study to examine the tumor microenvironment and survival in a multiethnic set of US cHL cases, we examined the distribution of EBV expression in tumor blocks from a subset of 269 of the available cases. We confirmed cHL diagnosis and histological subtype in H&E sections of FFPE tumor blocks of excisions and core biopsies from cases provided by Southern California Kaiser, Winship Cancer Center at Emory University, City of Hope National Medical Center, Grady Memorial Hosiptal, University of California Los Angeles and University of Southern California hospitals diagnosed from 1996-2016. Immunostain results were available for most cases. Tissue microarrays were constructed with two 2 mm cores from each case with 29 cases on each array. EBER was assessed using in situhybridization and scored as negative, positive in HRS cells or positive in the surrounding normal infiltrate. Demographic and clinical information, including the biopsy anatomic site, subtype, race/ethnicity (Hispanic, African American, Asian, non-Hispanic white), age at diagnosis and gender. Multiple logistic regression was conducted to assess the relationship between age, race/ethnicity, gender, subtype and EBV tumor status. Race/ethnicity data was available at this time for 237 cases. Of these, 186 were nodular sclerosis (NS), 53 were mixed cellularity (MC), 8 were lymphocyte depleted (LD), 3 were lymphocyte rich (LR), and 10 were not otherwise specified (NOS). Fifty-seven cases were African American, 48 were non-Hispanic white, 115 were Hispanic, 16 were Asian and one was other race. 106 were female (42%). Age at diagnosis ranged from 5-84 years, with 118 (50%) in the adolescent/young adult (AYA) range (15-35). EBV prevalence in HRS cells by subtype was 0% for LD, 47% for MC, 33% for LR, 23% for NS and 50% for NOS. When restricted to the two most common subtypes, NS and MC, histologic subtype alone was a statistically significant predictor of EBV tumor status (p=.0008) and when adjusting for age, sex, site and race/ethnicity (p=.0011). In NS cases, EBV HRS cell positivity was highest in non-Hispanic whites (31%), followed by Hispanics (23%) and African Americans (18%). Among MC cases, it was very high among African Americans (80%) compared to Hispanics and non-Hispanic whites (33-39%). The patterns were similar when restricted to the AYA age group. 6.5%, 4% and 20% of EBV-negative NS, MC and NOS cases, respectively, had EBV present in non-malignant lymphocytes but not in HRS cells. Histologic subtype was the strongest predictor of EBV HRS cell positivity in this set of multiethnic cHL patients. Unlike previous reports, EBV-positive tumors were not more common among non-whites, except for African American MC cases. Citation Format: Rachel Bolanos, Amie Hwang, Chun Chao, Christopher Flowers, Sheeja Pullarkat, Jose Aparicio, Sophia Wang, Karen Mann, Leon Bernal-Mizrachi, Joo Song, Christian Steidl, Christine Lee, Wendy Cozen, Iran Siddiqi. Epstein-Barr virus prevalence in classical Hodgkin lymphoma tumors is explained by histologic subtype, not race/ethnicity in a multiethnic US population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5053.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 0.001 |
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".