Are liver function tests relevant for early detection of liver metastasis of uveal melanoma?
Bibliographic record
Abstract
Abstract Purpose The liver is the main target for screening for uveal melanoma metastasis, which could be achieved by liver function tests (LFTs). The aim of our study is to analyze the relevance of LFTs for detection of metastatic disease in term of prognostic value and cost evaluation Methods Patients (n=88, who developed metastasis while undergoing semi‐annual follow‐up with LFTs including aspartate‐aminotransferase (AST), alanine‐aminotransferase (ALT), gammagutamylransferase (γGT), lactodeshydrogenase (LDH), and phosphatase alkaline (PA) were included. For assessing the level of LFTs for metastasis only the one preceding screening LFTs before the diagnostic by imaging was recorded. Consecutive patients (n=174) with uveal melanoma were chosen as control from patients who did not develop metastasis Results We were able to detect metastasis after LFTs abnormality in 40 (45%) patients. However, at the time of the one preceding screening LFTs before the metastasis diagnosis, 51(58%) patients had at least one abnormal LFT. The metastasis diagnosis was missed in 11 patients (13%). The overall sensitivity of LFTs ranged from 12.5 to 58.0% and the predictive positive value ranged from 9.4 to 38.6%. Interestingly we observed false positives in 20.3% with the variable “at least one abnormal LFT”. Using financial approach, we calculated the semi‐annual screening by LFTs. Conclusion Using the most important retrospective series analyzing semi‐annually all LFTs, we demonstrate that LFTs screening (AST, ALT, γGT, LDH and PA) is not relevant for detection of early metastasis even if the over cost induced by imaging requested for false positive is low
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".