Serum Krebs Von Den Lungen-6 as a Biomarker for Early Detection of Bronchiolitis Obliterans Syndrome in Children Undergoing Allogeneic Stem Cell Transplantation
Bibliographic record
Abstract
Bronchiolitis obliterans syndrome (BOS) is a devastating complication after allogeneic stem cell transplantation (allo-SCT). Early identification of high-risk patients is pivotal for success. Lung proteins, KL-6, CCSP, SP-A, and SP-D, measured in the serum may identify high-risk patients for BOS earlier than pulmonary function tests (PFTs) can identify changes or clinical symptoms. Lung proteins were measured in patients' serum at baseline and at 1, 3, 6, 9, 12, 18, and 24 months after transplantation along with history, clinical examination, and PFTs. Serum levels of lung proteins were also measured in healthy control subjects. The primary endpoint was the development of BOS confirmed by pathological biopsy or National Institutes of Health criteria. Between September 2009 and September 2011, 39 patients were enrolled. Six children developed BOS at a median time of 200 days (range, 94 to 282). KL-6 levels were low in control subjects, at a median of .1 U/mL (range, .1 to 1.5). Pre-SCT and 1-month KL-6 levels were significantly higher in surviving patients who developed BOS (n = 6) versus those who did not (n = 18) (pre-SCT: mean, 32.6 U/mL [IQR, 9.7 to 89.3] versus 5.8 U/mL [IQR, 2.1 to 12.6], P = .03; at 1 month: mean, 52.5 U/mL [IQR, 20.2 to 121.3] versus 11.4 U/mL [IQR, 5.7 to 36.0], P = .04). Three- and 6-month KL-6 levels continued to be higher in BOS group but were not statistically significant. CCSP, SP-A, and SP-D were not predictive. KL-6 measured in the serum of children receiving allo-SCT may identify patients at high risk for the development of BOS. These patients will benefit from intensive surveillance protocol and early therapy before irreversible lung damage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".