A Multiparametric Serum Kallikrein Panel for Diagnosis of Non–Small Cell Lung Carcinoma
Bibliographic record
Abstract
PURPOSE: Human tissue kallikreins are a family of 15 secreted serine proteases. We have previously shown that the expression of several tissue kallikreins is significantly altered at the transcriptional level in lung cancer. Here, we examined the clinical value of 11 members of the tissue kallikrein family as potential biomarkers for lung cancer diagnosis. EXPERIMENTAL DESIGN: Serum specimens from 51 patients with non-small cell lung cancer (NSCLC) and from 50 healthy volunteers were collected. Samples were analyzed for 11 kallikreins (KLK1, KLK4-8, and KLK10-14) by specific ELISA. Data were statistically compared and receiver operating characteristic curves were constructed for each kallikrein and for various combinations. RESULTS: Compared with sera from normal subjects, sera of patients with NSCLC had lower levels of KLK5, KLK7, KLK8, KLK10, and KLK12, and higher levels of KLK11, KLK13, and KLK14. Expression of KLK11 and KLK12 was positively correlated with stage. With the exception of KLK5, expression of kallikreins was independent of smoking status and gender. KLK11, KLK12, KLK13, and KLK14 were associated with higher risk of NSCLC as determined by univariate analysis and confirmed by multivariate analysis. The receiver operating characteristic curve of KLK4, KLK8, KLK10, KLK11, KLK12, KLK13, and KLK14 combined exhibited an area under the curve of 0.90 (95% confidence interval, 0.87-0.97). CONCLUSIONS: We propose a multiparametric panel of kallikrein markers for lung cancer diagnosis with relatively good accuracy. This model requires validation with a larger series and may be further improved by addition of other biomarkers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 teacher head, 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".