The risk of hepatocellular carcinoma decreases after the first 5 years of entecavir or tenofovir in Caucasians with chronic hepatitis B
Bibliographic record
Abstract
Whether there is a change of hepatocellular carcinoma (HCC) incidence in chronic hepatitis B patients under long-term therapy with potent nucleos(t)ide analogues is currently unclear. We therefore assessed the HCC incidence beyond year 5 of entecavir/tenofovir (ETV/TDF) therapy and tried to determine possible factors associated with late HCC occurrence. This European, 10-center, cohort study included 1,951 adult Caucasian chronic hepatitis B patients without HCC at baseline who received ETV/TDF for ≥1 year. Of them, 1,205 (62%) patients without HCC within the first 5 years of therapy have been followed for 5-10 (median, 6.8) years. HCCs have been diagnosed in 101/1,951 (5.2%) patients within the first 5 years and 17/1,205 (1.4%) patients within 5-10 years. The yearly HCC incidence rate was 1.22% within and 0.73% after the first 5 years (P = 0.050). The yearly HCC incidence rate did not differ within and after the first 5 years in patients without cirrhosis (0.49% versus 0.47%, P = 0.931), but it significantly declined in patients with cirrhosis (3.22% versus 1.57%, P = 0.039). All HCCs beyond year 5 developed in patients older than 50 years at ETV/TDF onset. Older age, lower platelets at baseline and year 5, and liver stiffness ≥12 kPa at year 5 were independently associated with more frequent HCC development beyond year 5 in multivariable analysis. No patient with low Platelets, Age, Gender-Hepatitis B score at baseline or year 5 developed HCC. CONCLUSION: The HCC risk decreases beyond year 5 of ETV/TDF therapy in Caucasian chronic hepatitis B patients, particularly in those with compensated cirrhosis; older age (especially ≥50 years), lower platelets, and liver stiffness ≥12 kPa at year 5 represent the main risk factors for late HCC development. (Hepatology 2017;66:1444-1453).
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| 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".