Survival By Race/Ethnicity in Children and Adolescents with Hodgkin Lymphoma Treated on Cooperative Group Trials in the U.S. and Canada: A Pooled Analysis of Children's Oncology Group Trials
Bibliographic record
Abstract
Introduction: While survival in Hodgkin Lymphoma (HL) is excellent, disparities by race/ethnicity have been described. Population-based and single center studies of children and adolescents with HL suggest that those who are black or Hispanic (vs. non-Hispanic white) have worse outcomes (Grubb Pediatr Blood Cancer 2016; Metzger JCO 2008). Whether race/ethnicity is predictive of survival in children and adolescents with HL after adjusting for clinical features and treatment-related variables is unknown. Our objective was to examine whether race/ethnicity was predictive of event-free survival (EFS), relapse, and overall survival (OS) in patients enrolled on contemporary Children9s Oncology Group (COG) trials with response-based therapy for treatment of newly diagnosed HL. Methods: We conducted a pooled analysis of individual level data in children and adolescents enrolled on 3 consecutive Phase III clinical trials for treatment of intermediate, low and high-risk HL (AHOD0031, AHOD0431, AHOD0831). Five-year EFS and OS were compared across racial/ethnic groups and were estimated using the Kaplan-Meier method. Cumulative incidence of relapse was similarly constructed with K-sample tests. Cox regression models were constructed to examine the influence of race/ethnicity on EFS and OS, and were adjusted for age, sex, insurance status, histology, Ann Arbor stage, B symptoms, bulk disease, COG study, and radiation therapy (RT). Results: Between 2002 and 2012, 2155 patients 1-21 years of age enrolled on 3 COG trials, 2071 (96%) of whom were included in this analysis. Patients treated outside the US and Canada (n=84) were excluded. The distribution of race/ethnicity as reported to COG by treating institutions was: 64% non-Hispanic white (N=1334), 11% non-Hispanic black (N=236), 16% Hispanic (N=329), 3% Asian/Pacific Islander (N=66), and 5% other (N=106). Compared to other groups, more non-Hispanic white patients had private (vs. government) insurance (p Survival: In pooled analysis, with a median follow-up of 6.9 years, 5-year EFS was 83%, OS was 97%, and neither outcome differed by race/ethnicity (EFS: p=0.98; OS: p=0.29). Cumulative incidence of relapse was 16.8% and did not differ by race/ethnicity (p=0.93). In the multivariable model for EFS, there was no significant effect of race/ethnicity (p=0.95). Similarly, race/ethnicity was not significant in the multivariable model for OS (p=0.14). Finally, race/ethnicity was not significantly associated with EFS or OS in multivariable models by individual study, accounting for risk group. Conclusion: We observed no difference in survival by race/ethnicity among children and adolescents treated for HL with contemporary, risk adapted response-based therapy on COG Phase III trials. This suggests that the survival gap observed in population-based studies is largely reduced by access to clinical trials and by receipt of comparable therapy between cohorts. In light of this, it can be hypothesized that inequities in access to high-quality care, rather than differences in individual disease biology may underlie racial disparities observed in the community oncology setting. To examine whether response-based paradigms mitigated biologic differences between groups, further analyses will explore early response to treatment by race/ethnicity. Further analyses will also examine treatment-related toxicities and second malignant neoplasms by race/ethnicity, as well as the independent contribution of socioeconomic status to outcomes. Disclosures No relevant conflicts of interest to declare.
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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 | 0.027 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.013 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".