Clinical Utility of AFP-L3% Measurement in North American Patients with HCV-Related Cirrhosis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3%) has been reported to be useful in the early detection of hepatocellular carcinoma (HCC) in Japan. The aim of this prospective study was to compare the clinical utility of AFP-L3% with that of total AFP in North American patients. METHODS: Patients with chronic hepatitis (CH) C virus-related cirrhosis from 7 clinical sites were prospectively followed every 3-6 months for 2 yr. RESULTS: Of the 372 patients evaluated, 40 had hepatitis C virus-related HCC at entry and 332 entered the prospective trial. Of the latter, 34 developed HCC and 298 remained free of HCC. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for AFP were 60.8%, 71.1%, 34.4%, and 88.0% with a cutoff of 20 ng/mL and 21.6%, 98.7%, 80.0%, and 83.5% with a cutoff of 200 ng/mL, compared to 36.5%, 91.6%, 51.9%, and 85.3% for AFP-L3% with a cutoff of 10%. In those with an elevated AFP (20-200 ng/mL), AFP-L3% had a specificity of 86.6% and an NPV of 80.7%. Multivariate analysis identified AFP, AFP-L3%, and age as independent predictors of HCC. Elevated AFP-L3% was associated with a lower cumulative HCC-free rate at 2 yr (58.9%) than was AFP (82.0%, P= 0.01). CONCLUSIONS: The incidence of HCC was significantly higher in patients with elevated AFP-L3% than in those with elevated AFP. The high specificity of AFP-L3% persisted among patients with elevated AFP (20-200 ng/mL) and suggests that AFP-L3% has clinical utility in HCV patients with AFP of 20-200 ng/mL.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".