Opportunities for Standardizing Conversations about Curative Therapy for Sickle Cell Disease
Bibliographic record
Abstract
Background: Sickle cell disease (SCD) causes significant co-morbidities and early mortality secondary to vaso-occlusion and hemolysis. Despite medical advances, such as newborn screening and hydroxyurea, those with the disease continue to have a reduced life expectancy. The only available curative therapy for SCD has been stem cell transplant, which requires a human leukocyte antigen (HLA) matched donor, ideally a sibling. Gene therapy techniques have recently been approved, providing additional methods of curative and transformative therapy (CTT) without requiring an HLA matched donor, though equity in access to CTT for SCD remains an ongoing concern. Developing systematic approaches to the offering of and counseling regarding CTT options can reduce the risk of bias, promote uptake of CTT, and improve health literacy. This study's aim was to understand the varied programmatic components of institutions referring patients with SCD to CTT and to offer recommendations for standardizing the process to promote equitable access to CTT. Methods: We distributed an 18-question survey outlining current practices related to SCD and CTT discussions in pediatric hematology practices. The survey population included the Sickle Cell Transplant Advocacy and Research (STAR) Alliance, a consortium of 40 hematology and transplant programs in North America dedicated to improving access and outcomes of transplant for SCD. We received IRB-exemption determination from the Boston Children's Hospital IRB. REDCap was utilized as the survey tool, while Microsoft Excel and Microsoft Word were used for data analysis. For the open-ended survey questions, we utilized the Braun and Clarke reflexive thematic analysis framework. Results: Respondents from 32 institutions (80% completion rate) across the United States and Canada participating in the survey, with 59% of survey respondents being stem cell transplant physicians, 19% hematologists and 22% joint respondents. The median SCD patient census was between 200 - 500 individuals and median number of hematopoietic cell transplant (HCT) recipients with SCD in the past five years was 6 - 10. Regarding institutional practices, 91% of respondents reported that within the provider team, hematologists (as compared to stem cell transplant physicians) initiated the conversation surrounding HCT. Within the patient-provider relationship, 53% of institutions noted that patients typically initiated the HCT referral process. 69% of institutions had SCD-specific educational materials surrounding HCT available, while 19% of institutions had combined SCD/HCT clinics at the time of survey completion. When asked to report the primary barriers to performing HCT in patients with SCD, the most common responses were “patient concerns about risks” at 69%, “risks related to non-matched sibling donor” at 50%, and “patient/family resources” at 44%. Additional barriers included “transplant adherence feasibility” at 38%, “lack of open clinical trials” at 34%, “SCD team concern about risks” at 28%, and “transplant team capacity” at 25%. Common themes identified as areas for improving access to CTT fell into three domains: education, evaluation, and support. For education, many respondents advocated for more time during routine visits to better educate patients about curative therapies, having combined SCD/HCT clinics so that CTT can be discussed by the HCT team alongside a routine visit, and improved education materials for patients and families discussing CTT options. For evaluation, many respondents recommended evaluating all patients early in the patient-provider relationship, including the HCT team in evaluations, and to consider all CTT options formally.From a support standpoint, many institutions would benefit from increased financial and/or logistic support in the post-transplant period, establishing routine “survivorship” visits to surveil for late effects, and increased interdisciplinary emotional support in the post-transplant period. Discussion: This study provides insight on common practices surrounding CTT counseling in pediatric SCD clinics across the United States and Canada. Potential domains to target for improvement are: patient education materials, the HCT evaluation process, material resources, and psychosocial family support. Standardized HCT education and referral practices for patients with SCD can promote equitable access to CTT.
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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 | 0.032 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".