National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for Use of Tumor Markers in Liver, Bladder, Cervical, and Gastric Cancers
Bibliographic record
Abstract
BACKGROUND: Updated National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for the use of tumor markers in the clinic have been developed. METHODS: Published reports relevant to use of tumor markers for 4 cancer sites--liver, bladder, cervical, and gastric--were critically reviewed. RESULTS: Alpha-fetoprotein (AFP) may be used in conjunction with abdominal ultrasound for early detection of hepatocellular carcinoma (HCC) in patients with chronic hepatitis or cirrhosis associated with hepatitis B or C virus infection. AFP concentrations >200 microg/L in cirrhotic patients with typical hypervascular lesions >2 cm in size are consistent with HCC. After a diagnosis of HCC, posttreatment monitoring with AFP is recommended as an adjunct to imaging, especially in the absence of measurable disease. Although several urine markers have been proposed for bladder cancer, none at present can replace routine cystoscopy and cytology in the management of patients with this malignancy. Some may, however, be used as complementary adjuncts to direct more effective use of clinical procedures. Although carcinoembryonic antigen and CA 19-9 have been proposed for use gastric cancer and squamous cell carcinoma antigen for use in cervical cancer, none of these markers can currently be recommended for routine clinical use. CONCLUSIONS: Implementation of these recommendations should encourage optimal use of tumor markers for patients with liver, bladder, cervical, or gastric cancers.
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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 | 0.025 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".