Evaluation of a point of care prostate-specific antigen blood test on a mobile outreach service
Bibliographic record
Abstract
BackgroundPoint of care (POC) tests may improve accessibility and reduce costs of blood tests including in prostate cancer. The Man Van project was a pilot designed to address health inequalities that affect prostate cancer with novel community-based targeting of high-risk groups on a mobile clinical unit.MethodsThe i-CHROMA-II™ POC machine is a quantitative assay for the measurement of total prostate specific antigen (PSA) from capillary blood using fluorescence immunoassay technology. Laboratory based Serum PSA testing was compared with capillary blood POC testing using the i-CHROMA-II™ to determine its accuracy and impact on clinical decision making on the Man Van.Results28 men participated. The median age was 53 years (range 45-74). One POC test result was invalid. Nine POCT samples gave a result of <0.5 μg/L and were not included in the analysis. Of the remaining results (N = 18) the median PSA was 1.97 μg/L (range 0.54-31.22 μg/L). Using Lin's Concordance Correlation Coefficient of Absolute Agreement gave a value of 0.392 (N = 17). A Bland-Altman plot showed a mean difference of 0.377 μg/L.ConclusionsWe report the first testing of PSA using the i-Chroma-II™ machine, and the first real-world mobile testing using any POC PSA test. Our study did not show correlation between the laboratory and i-Chroma-II™, although it did replicate the positive bias seen in previous studies. Further testing and refinement of POC tests may help to achieve the goal to developing reliable POC PSA tests.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".