Research priorities in childhood-onset lupus: results of a multidisciplinary prioritization exercise
Bibliographic record
Abstract
BACKGROUND: Childhood-onset systemic erythematosus lupus (cSLE) is characterized by more severe disease, widespread organ involvement and higher mortality compared to adult-onset SLE. However, cSLE is largely underfunded to carry out necessary research to advance the field. Few commonly used SLE medications have been studied in children, and important knowledge gaps exist concerning epidemiology, genetics, pathophysiology and optimal treatments for cSLE. METHODS: In order to assess highest cSLE research priority areas, the Lupus Foundation of America (LFA) and Childhood Arthritis and Rheumatology Research Alliance (CARRA) administered a cSLE research prioritization survey to pediatric rheumatologists, dermatologists and nephrologists with expertise in lupus. Members of LFA and CARRA's SLE Committee identified a list of cSLE research domains and developed a 17-item tiered, web-based survey asking respondents to categorize the research domains into high, medium, or low priority areas. For domains identified as high priority, respondents ranked research topics within that category. For example, for the domain of nephritis, respondents ranked importance of: epidemiology, biomarkers, long-term outcomes, quality improvement, etc. The survey was distributed to members of CARRA, Midwestern Pediatric Nephrology Consortium (MWPNC) and Pediatric Dermatology Research Alliance (PeDRA) Connective Tissue Disease group. RESULTS: The overall response rate was 256/752 (34%). The highest prioritized research domains were: nephritis, clinical trials, biomarkers, neuropsychiatric disease and refractory skin disease. Notably, nephritis, clinical trials and biomarkers were ranked in the top five by all groups. Within each research domain, all groups showed agreement in identifying the following as important focus areas: determining best treatments, biomarkers/pathophysiology, drug discovery/novel treatments, understanding long term outcomes, and refining provider reported quality measures. CONCLUSION: This survey identified the highest cSLE research priorities among leading rheumatology, dermatology and nephrology clinicians and investigators engaged in care of children with lupus. There is a strong need for multidisciplinary collaboration moving forward, which was indicated as highly important among stakeholders involved in the survey. These survey results should be used as a roadmap to guide funding and specific research programs in cSLE to address urgent, unmet needs among this population.
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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 | 0.061 | 0.171 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".