Evaluation of quantitative sputum cytology as an intermediate endpoint biomarker.
Bibliographic record
Abstract
A24 Lung cancer remains the leading cause of cancer death in North America. There is no widely accepted method to screen for this usually asymptomatic disease (particularly in it earlier more treatable stages). Recently the use of quantitative analysis of sputum cytology for lung cancer screening has been approved for lung cancer detection by Health Canada and LDSCT looks promising for peripheral disease detection although there still exists a substantial false positive nodule issue. Our group has focused on the systemic treatment of the early preinvasive stages of this disease through chemoprevention. While we have found that white light and fluorescence endoscopy with directed biopsies can establish the state of the central part of the bronchial tree at a specific time point, it is both some what invasive and only examines part of the organ at risk. In addition it modifies tissue at risk through sample removal. A similar strategy with LDSCT and needle biopsy is not feasible for the lung periphery. For these reasons we have examined quantitative sputum analysis as a biomarker of pre-invasive disease. In this study we present the correlation of a sputum score derived from the fully automated analysis of DNA-specific (Feulgen-Thionin) stained sputum samples mixing ploidy based classifiers and population based MAC (malignancy associated changes) classifiers in a single score, for more than 2200 cases. We correlated this biomarker with other know biomarkers (highest grade of biopsy confirmed dysplasia and/or biopsy morphometric index per subject, average grade of biopsy confirmed dysplasia and/or biopsy morphometric index per subject, cancer resection outcome in treated patients) as well as risk indicators such as age and smoking status and smoking history all stratified by sex. In all instances a correlation was observed independent of subject sex for which detailed results will be presented. A retrospective analysis of the performance of the sputum score on a previous lung cancer chemoprevention trial will also be presented. While the general correlation observed is not as strong as that for the directed invasively sampled biomarkers, the sample does potentially come from the entire organ at risk and may be a more comprehensive representation of the entire field instead of only that which is readily accessible. Supported by grant PO1-CA96964-04, NIH
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".