Addressing Knowledge Gaps in the Early Detection of Bronchiolitis Obliterans Syndrome after Hematopoietic Cell Transplantation: An Official American Thoracic Society Research Statement
Bibliographic record
Abstract
Abstract Background Bronchiolitis obliterans syndrome (BOS) is a late-onset noninfectious pulmonary complication of allogeneic hematopoietic cell transplant (HCT) that is often diagnosed at an advanced stage with severe lung impairment. Increasing use of HCT for the treatment of hematologic diseases worldwide translates to an increasing burden of BOS, particularly for the community pulmonologist. Early recognition of BOS, which offers the best opportunity to mitigate morbidity and mortality, is hampered by incomplete knowledge of the clinical course and disease process. The goal of this research statement is to survey our current understanding of BOS and to define the research agenda for the early detection of BOS. Methods We convened a multidisciplinary panel that included community representatives for an in-depth survey of the published literature followed by an online workshop. Results Major knowledge gaps were identified within interrelated themes of natural history and pathogenesis, risk factors, and the clinical diagnostic approach. Conclusions This statement reflects the detailed assessment of identified knowledge gaps with associated key research questions, as well as a proposed research road map to stimulate cross-disciplinary collaborations from preclinical to clinical investigations.
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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 | 0.174 | 0.234 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".