Patterns of Hepatocellular Carcinoma After Direct Antiviral Agents and Pegylated-Interferon Therapy
Bibliographic record
Abstract
INTRODUCTION: The impact of direct-acting antiviral agents (DAAs) on the development of hepatocellular carcinoma (HCC) is controversial and a part of the scientific community believes it as a biased interpretation of data. Many studies have reported an aggressive pattern of HCC after DAA use. In this study, we attempted to assess the changes in the pattern of HCC after treatment with DAAs or PI (PEG, pegylated-interferon). METHODS: A total of 37 HCC patients after DAA treatment and 21 HCC patients after PI treatment were included. The diagnosis of HCC was made and information about demographics, HCC infiltrative pattern, portal vein thrombosis (PVT), time at initial presentation, Child-Turcotte-Pugh (CTP) score, and Barcelona Clinic Liver Cancer (BCLC) stage were compared in the two groups. RESULTS: The total number of male patients in the DAA group was 62% while either gender was almost equal in PI. The age group of 40-60 was more prevalent in the DAA group while the PI group comprised more patients who were above 60 years. Patients in the DAA group presented after 3.35 years on average while patients in the PI group presented after about seven years. Most of the patients presented with the CTP stage of A. That is true for both groups. For BCLC staging, most of the patients had stage C, which means multiple lesions. At the initial presentation, most of the patients presented with multifocal lesions. CONCLUSION: Our study found no significant difference in the initial presentation between both groups. However, HCC patients with prior DAA therapy presented early than those with PI therapy.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".