Hepatocellular carcinoma screening practices among patients with chronic hepatitis B by Canadian gastroenterologists and hepatologists: An online survey
Bibliographic record
Abstract
BACKGROUND: Expert guidelines recommend hepatocellular carcinoma (HCC) surveillance among patients with high-risk chronic hepatitis B (CHB); however, physician screening practices are often variable. METHODS: An online survey of HCC screening practice was distributed to members of the Canadian Association for the Study of the Liver. Data were analyzed using appropriate statistical tests with p < .05 significance. RESULTS: Of 71 respondents, 86% ( n = 61) were gastroenterologists or hepatologists, and 72% ( n = 51) reported having been in clinical practice for more than 5 years. A significant number of survey respondents performed HCC screening without consideration of concomitant non-alcoholic fatty liver disease (50.7%); non-Asian, non-African ethnicity (46.4%); and family history of HCC (28.6%). Most (67.6%) performed screening with ultrasound (US) at the time of specialty clinic visits, 28.2% had an automatic recall system, and only 2.8% referred back to primary care physicians to organize screening. More than half (54.9%) included alpha-fetoprotein in screening. Obstacles to screening included lack of an automatic recall system (42.9%), patient non-compliance (30.0%), and limited US/MRI access (17.1%). CONCLUSIONS: HCC screening practices with hepatitis B patients vary widely among Canadian specialists, especially in unique populations with limited data to inform screening recommendations. Implementation of an automatic recall system could potentially increase HCC surveillance.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".