National landscape of real-world pediatric blinatumomab care delivery in the United States: A report from the Children's Oncology Group
Bibliographic record
Abstract
Abstract Introduction: The Children's Oncology Group (COG) Trial AALL1731 demonstrated a remarkable reduction in relapse risk with the addition of blinatumomab to the standard frontline chemotherapy backbone for pediatric B-cell acute lymphoblastic leukemia (B-ALL). These results, along with recent FDA approval for pediatric patients, fundamentally altered the treatment paradigm such that blinatumomab is now considered a new standard of care. However, successful delivery of blinatumomab is made challenging by its administration as a 28-day continuous intravenous infusion, associated requirement for drug bag replacements at variable intervals dependent on institutional clinic capacity and homecare service availability, and complex insurance reimbursement. In this analysis, we sought to characterize the real-world landscape of pediatric blinatumomab care delivery in the United States (US) from the perspective of treating centers. Methods: We administered a 28-question REDCap survey to US COG institutions from February-March 2025 assessing each institution's clinical practice with blinatumomab. Care delivery barriers (i.e. toxicity concerns, insurance coverage, lack of homecare, institutional challenges, pharmacy staffing, nursing staffing, family declining, family distance, limited family resources, limited non-English resources) were reported using a 5-point Likert scale rating each barrier's impact on their ability to deliver blinatumomab outpatient. For this analysis, a barrier was considered major if an institution rated it ≥4. Descriptive frequencies and statistics were tabulated. We compared the most frequently reported major barriers by site characteristics (US census region, site-reported annual ALL volume, site-reported years of experience with blinatumomab, COG-verified experience with blinatumomab measured by number of AALL1731 blinatumomab-arm enrollments) using chi-square tests. We examined characteristics of institutions who were not administering blinatumomab to populations with specific challenges: infant (delivery challenges associated with low weight) and Ph+ (not part of the FDA approval) ALL. Results: Of 195 active US COG institutions, 149 completed the survey (76% response rate) representing 44 states and Puerto Rico. More than 90% of centers reported utilizing blinatumomab as their institutional standard of care for standard risk (SR)-average, SR-high, and high risk (HR) B-ALL. Fewer centers reported utilizing blinatumomab for infant (56%) and Ph+ (65%) B-ALL. Centers not utilizing blinatumomab for infants were more likely to be small volume i.e. <10 ALL cases per year (39% vs. 16%, p<0.001), have no history of AALL1731 blinatumomab-arm enrollments (20% vs. 6%, p=0.007), and have <5 years of prior experience with blinatumomab (42% vs. 18%, p=0.002). Similar patterns were observed for Ph+ ALL. Most centers (62%) reported at least one major care delivery barrier in the outpatient setting with 36% reporting ≥3. The most frequently reported barriers were lack of homecare companies (50%), family distance to treating center (28%), and insurance coverage for homecare (26%). Compared to the Midwest (44%) and South (43%) census regions, centers based in the Northeast (61%) and West (71%, p=0.07) trended towards having more issues with lack of homecare companies. Lack of homecare companies did not otherwise differ by site characteristics. Centers not utilizing blinatumomab for infant (60% vs. 43%, p=0.06) and Ph+ ALL (67% vs. 41%, p=0.002) were more likely to lack homecare companies. Conclusion: Despite its complex care delivery requirements, the majority of COG institutions have quickly adapted to blinatumomab as frontline standard of care for most higher risk pediatric B-ALL subgroups following AALL1731 trial results and FDA approval. However, there is substantial heterogeneity in infant and Ph+ ALL. Issues related to homecare (lack of companies, insurance coverage, and family distance to treating center) are a predominant theme of current challenges. The national variability in pediatric homecare is an important health system issue given potential implications for blinatumomab-related family burden in terms of inpatient admissions and emergency room visits, resource burden on hospitals, and our ability to implement large-scale pediatric outpatient care delivery beyond blinatumomab.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".