A253 MEASUREMENT OF NATURAL KILLER CELL ACTIVITY (NKA) IN SUBJECTS UNDERGOING COLONOSCOPY:TEST PERFORMANCE OF A NEW BLOOD TEST AT DIFFERENT CUT-OFFS FOR THE DETECTION OF COLORECTAL CANCER (CRC)
Bibliographic record
Abstract
Low NKA has been linked to a higher risk of cancer and has been reported in CRC patients.A novel simple blood test in vitro diagnostic device (IVDD) which measures NKA in a small volume of whole blood is now available. Tha aim of the study is to evaluate the test performance metrics of the IVDD at different cut-offs in subjects with CRC and adenomatous polyps (AP). This study measured NKA in 1081 subjects presenting for screening or prescribed colonoscopies using a biological assay performed as per the manufacturer’s directions. In the 872 evaluable subjects,statistically significant differences were found between the NKA of subjects positive for CRC (n=23), and that of subjects negative for CRC (n=849) [CRC mean 317.1 pg/ml (DS:845.5),CRC-negative mean 745.7 pg/ml (SD:1028.5),p=0.001; CRC median 86.0 pg/ml (IQR:43.3–151.0),CRC-negative median 298.1 pg/ml (IQR:100.4–920.2),p<0.001]. The prevalence of CRC was 2.6% and of AP >10 mm was 14.6%. Receiver Operator Characterisitcs (ROC) analysis show an optimum cut-off for detection of CRC at 181 pg/ml,with an area under the curve of 73% (p<0.0001). At cut-offs of 200 pg/ml, high sensitivity and negative predictive values for detection of CRC were seen. At cut-offs of 300 and 500 pg/ml, a slight improvement in the test performance was seen in the sensitivity for AP>10 mm. The odds ratio for the NKA IVDD for the detection of cancer at a cut-off of 200 pg/ml was 10.3 (95% CI 3.03–34.9). The clinical results in the present study using new simple blood test for measurement of NKA confirm that there are limited benefits of using different cut-offs other than the optimal cut-off (220 pg/ml) for this new IVDD as determined by ROC analysis for detection of CRC None
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".