The incidence of hepatocellular carcinoma is reduced in patients with chronic hepatitis B on long‐term nucleos(t)ide analogue therapy
Bibliographic record
Abstract
BACKGROUND: North American data are lacking on the effect of nucleos(t)ide analogues (NA) in preventing chronic hepatitis B (CHB)-related hepatocellular carcinoma (HCC). AIM: To determine the incidence of HCC in NA-treated patients and compare this risk with that predicted without treatment based on the REACH-B model. METHODS: In this retrospective study, the incidence of HCC was determined in CHB patients initiated on NA from 1999 to 2012. Pre-treatment data utilised in the REACH-B model were used to predict the annual HCC risk. The standardised incidence ratio (SIR) for HCC was calculated by comparing the observed to expected number of cases, and HCC risk factors determined by Cox proportional hazards regression. RESULTS: Five hundred and forty nine initiated NA (14% lamivudine, 5% adefovir, 1.5% telbivudine, 39% entecavir, 41% tenofovir). Over a median follow-up of 3.2 years (IQR 1.9-4.6), 11 (3.2%) were diagnosed with HCC. Among 322 with data to calculate the REACH-B model, the median age at treatment initiation was 46 years (IQR 38-55), 65% were male, 32% HBeAg positive and 20% had cirrhosis. The median pre-treatment ALT was 71 U/L (IQR 41-127) and HBV DNA was 6.48 log10 copies/mL (4.95-8.04). The observed annual HCC incidence (0.9%; 95% CI 0.5-1.7) was significantly lower than predicted without treatment by the REACH-B model (SIR 0.46; 95% CI 0.23-0.82); this risk was reduced after 4 years of therapy (SIR 0.49; 95% CI 0.2-1.00). CONCLUSIONS: In this Canadian study of nucleos(t)ide analogues-treated patients with chronic hepatitis B, the incidence of HCC was lower than expected, suggesting that NA reduce the risk of chronic hepatitis B-related HCC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".