Evaluating the Impact of Socioeconomic Disparities on Access and Outcomes of CAR T-Cell Therapy for Relapsed/Refractory B-Cell Lymphomas in Ontario, Canada
Bibliographic record
Abstract
Background Chimeric antigen receptor T-cell therapy (CAR-T) for relapsed/refractory large B-cell lymphoma (R/R LBCL) is now standard of care in Canada. Only a limited number of centres provide this therapy. There are limited data on disparities related to social determinants on outcomes and influence on access. Purpose The aim of this study was to assess the impact of socioeconomic status, as measured by the Ontario Marginalization Index (ON-Marg), on the likelihood of undergoing CAR-T after referral and treatment outcomes in patients with R/R LBCL. This was a retrospective review of patients 18 years or older with R/R LBCL referred from Ontario centres to Princess Margaret Cancer Centre (PM) between April 2020 and November 2023 for CAR-T therapy. The ON-Marg consists of four dimensions: material resources (MR), racialized and newcomer population (RN), age and labor force (AL), and household and dwellings (HD). Descriptive statistics were used to analyze baseline characteristics and the four dimensions of ON-Marg. Each dimension was divided into quintiles, ranging from 1 (low marginalization) to 5 (high marginalization). Need for interpreter at consent, rural vs urban setting, and median household income determined by national census data were also explored. The cohort was grouped into median household income tertiles of <$83000, $83000-104000 and >$104000, which were chosen to allow for similar size cohorts. Results We included 163 patients; 77% received CAR T-cell therapy while 23% did not. The median age was 60 years (range: 20-81), and 64% were male. The median follow-up was 17.51 months (95% CI 14.69-21.26). Our analysis showed no significant disparities in the likelihood of receiving CAR T-cell therapy across the quintiles of the four marginalization dimensions. In terms of the MR, 24% of the patients who underwent CAR T-cell treatment were allocated in quintile 1, 67% in quintiles 2-4, and 9% in quintile 5. Among the patients who did not, 22% were in quintile 1, 68% in quintiles 2-4, and 11% in quintile 5 (p=0.91). Similarly, in the RN dimension, 14% of the patients who received treatment were in quintile 1, 63% in quintiles 2-4, and 23% in quintile 5. Among those who did not receive it, 14% were in quintile 1, 62% in quintiles 2-4, and 24% in quintile 5 (p=0.98). In the AL dimension, quintile 1 accounted for 19% of the patients who received CAR T-cell therapy, quintiles 2-4 for 60%, and quintile 5 for 21%. For the patients who did not receive treatment, quintile 1 was 22%, quintiles 2-4 were 51%, and quintile 5 was 27% (p=0.66). For the HD dimension, quintile 1 consisted of 26% of patients who received treatment and 27% who did not, quintiles 2-4 had 56% and 41%, and quintile 5 had 17% and 32% respectively (p=0.11). No significant delays among marginalization groups were found in terms of the time from referral to the initial appointment (all p>0.05), the date of the initial appointment to the date of infusion (all p>0.05) or the date of progression to the date of infusion (all p>0.05). Of the 126 patients who received CAR T-cell therapy, there were 39 deaths from all causes, with a 12-month overall survival (OS) rate of 63.8%. OS outcomes did not show any significant differences between marginalization groups in any of the four dimensions that were evaluated (MR p=0.52, RN p=0.53, AL p=0.77, HD p=0.70). There were no significant OS differences between urban/rural patients (p=0.21), use of interpreter (p=0.42) or by income tertile (p=0.37). There were 74 events of progression or death, with a 12-month progression free survival (PFS) rate of 43.3%. Similar to the OS analysis, PFS did not reveal any significant differences among marginalization groups (MR p=0.077, RN p=0.62, AL p=0.81, HD p=0.51). There were no significant PFS differences between urban/rural patients (p=0.32), use of interpreter (p=0.37) or by income tertile (p=0.36). CRS and ICANS were observed in 86% and 29% of the patients. No significant differences in these toxicities were found when evaluated based on the different marginalization groups, income tertiles, use of interpreter and urban/rural status. Conclusions This study did not find any statistically significant evidence of an impact of socioeconomic status on the likelihood of receiving CAR T-cell therapy or on treatment toxicity or outcomes in a single payer universal health care system. A limitation requiring further analysis is only referred patients were included.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".