The impact of marginalization on outcomes in patients with Hodgkin lymphoma
Bibliographic record
Abstract
Abstract Background Hodgkin lymphoma (HL) has become one of the most curable hematologic malignancies with survival rates exceeding 85%. Despite improved outcomes, there remain certain populations that have a significantly worse survival, including those from a lower socioeconomic status, with limited Canadian data in this cancer population. In a publicly funded healthcare setting with universal access, understanding how marginalization impacts survival for HL patients is crucial. Methods We performed a retrospective population-based study of adult patients (≥18 years) diagnosed with HL from 2006 until 2022 using administrative healthcare databases from Ontario, Canada. The Ontario Marginalization Index (ON-Marg) uses unique census variables to score four dimensions of neighborhood-level marginalization: Households and Dwellings (types and density of residential accommodations), Material Resources (related closely to financial status), Age and Labour force (indicators for population not actively working), and Racialized and Newcomer Populations (recent immigrants or visible minority groups). Quintiles divide the population from least (1st quintile) to most (5th quintile) marginalized. The primary outcome of this study was 2-year overall survival (OS) from date of diagnosis, based on ON-Marg quintiles. A secondary outcome of this study was the rate of health resource utilization (HRU: defined as an emergency department (ED) visit or hospitalization) based on ON-Marg quintiles. Cox regression analyses were used to identify demographic features associated with OS and HRU. Results A total of 4,733 patients (median age 39 years; 54% male) were diagnosed with HL in Ontario during the study period (ABVD treated: 3,907 (83%), escBEACOPP: 107 (2%), Other/None: 719 (15%)). Within the follow-up period, 18.6% of patients (n=880) died. Patients in the most marginalized Material Resources Q5 had significantly worse 2-year OS (HR 1.54, 95% CI 1.16-2.04, p=0.003) on multivariable analysis than those in Q1, while other domains showed no significant effect. The OS analysis for the entire cohort demonstrated that those in the most marginalized Racialized Newcomer Population domain had improved OS compared to those in Q1 (HR 0.78, 95% CI 0.63-0.96, p=0.023). In the first 2-years post-diagnosis, 71.3% (n=3375) of all patients presented to the ED, with a median of 2 visits per person. Within the ABVD treated cohort, 45.3% (n=1,765) of patients presented to ER within the first 6 months from diagnosis, and 27.5% (n=1,071) had at least one hospitalization. Of ABVD patients with HRU within the first 6 months from diagnosis, 28.92% (n=643) of visits were for an infectious complication. There was a significant increase in health services utilization within 2 years of follow-up for patients in Q5 of the Households and Dwellings (Rate Ratio (RR) 1.15, 95% CI 1.08-1.22, p<0.001), Material Resources (RR 1.27, 95% CI 1.20-1.35, p<0.001), and Age and Labour force (RR 1.15, CI 1.09-1.22, p<0.001) domains. Patients in Q5 of the Racialized Newcomer Population domain, had a significant decrease in healthcare services utilization (RR =0.78, 95% CI 0.74-0.83, p<0.001). Conclusion Our study demonstrates that patients with HL who are most marginalized from a material resources perspective (indicating financial stress) have a lower 2 yr OS. This domain is closely related to socioeconomic status and is in keeping with previous data showing that patients with lower neighbourhood SES had worse OS. Despite a universal healthcare system, there are still disparities in survival for patients from a lower SES. Our study also suggests that patients most marginalized in several domains have higher healthcare utilization with respect to ED and hospitalization rates during treatment and in early follow-up. In contrast, racialized newcomer populations had lower healthcare utilization and improved overall survival which may reflect the healthy immigrant effect, whereby immigrant patients are healthier than their Canadian-born counterparts. Cultural factors may also have a protective role. Finally, we uniquely demonstrated the unexpectedly high health care resource use (ED and hospitalizations) during ABVD chemotherapy. These novel findings highlight the complex relationship between social determinants of health and outcomes in HL and emphasize the need for care strategies to better support marginalized HL populations, particularly during treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".