Characteristics and prognosis of hepatocellular carcinoma patients after direct-acting antiviral hepatitis C virus therapy in a single medical center in Egypt
Bibliographic record
Abstract
Objective: Hepatocellular carcinoma (HCC) incidence has increased dramatically over the previous two decades and is anticipated to rise further in some countries, notably the United States, by 2030. HCC is most widespread in Asia and Africa, where hepatitis B and C are ubiquitous and lead to the development of chronic liver disease and, finally, HCC. In this study, we examined changes in the characteristics and prognosis of HCC patients, as well as the risk of developing HCC after direct-acting antiviral (DAA) medication.Methods: The study enrolled all individuals who attended the Clinical Oncology and Nuclear Medicine Department, Suez Canal University Hospital, Ismailia, Egypt, with a proven diagnosis of HCC in the period between January 2020 and December 2021. HCC is diagnosed based on radiographic appearance (arterial enhancement phase and delayed washout phase) or compatible histology.Results: This retrospective cohort included 254 HCC patients, separated into three groups. Kaplan-Meier curves with log-rank analysis revealed that hepatitis C virus (HCV) treatment therapy considerably reduced the time to HCC development following hepatitis diagnosis (p < .001). HCV therapy had a substantial impact on progression-free survival and overall survival in HCC patients (p < .001).Conclusions: The emergence of DAA medication has greatly altered the management of HCV patients in the context of HCC. DAAs have been shown to be both safe and beneficial in these individuals, particularly in terms of lowering the risk of hepatic decompensation. DAAs have been reported to enhance overall survival in patients with cirrhotic HCV-related HCC, most likely due to decreased hepatic decompensation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".