A266 HEPATOCELLULAR CARCINOMA PREVALENCE IN NON-CIRRHOTIC HEPATITIS C PATIENTS
Bibliographic record
Abstract
According to WHO, HCC is the fifth most common tumor in men worldwide and the second most common cause of cancer related death. In adult women, it is the seventh most commonly diagnosed cancer and the sixth leading cause of cancer death. 1 Almost 80 percent of cases are due to underlying chronic hepatitis B and C virus infection. Previous studies showed incidence of HCC in non-cirrhotic HCV patients was ranging between 4.4–10.6 %. According to WHO, HCC is the fifth most common tumor in men worldwide and the second most common cause of cancer related death. In adult women, it is the seventh most commonly diagnosed cancer and the sixth leading cause of cancer death. 1 Almost 80 percent of cases are due to underlying chronic hepatitis B and C virus infection. Previous studies showed incidence of HCC in non-cirrhotic HCV patients was ranging between 4.4–10.6 %. The aim of our analysis is to determine the prevalence of HCC among liver transplant patients with hepatitis C virus in the absence of histologic cirrhosis. Secondary outcomes are to determine the characteristics of those patients and other possible contributing etiologies to developing HCC in the absence of cirrhosis We did a retrospective charts review of transplant patients in our center. We included all HCV patients who had HCC pre-liver transplant and excluded all patients younger than 18 or with other causes of cirrhosis. We reviewed the pathology reports of all explants to determine the fibrosis stage. We included 98 hepatitis C patients in our analysis. 91.1% were males with the mean age of the patients of 57.1 +/- 10 years. 99% of the patients were having a viral load of > 3 x 10/6 U/L. The most common HCV genotype was 1 (68%). Alcohol was the most common cofactor contributing to cirrhosis. Two patients (2%) were found to have fibrosis stage 2 and 3. First patient was a 50-years-old male with HCV infection (unknown genotype and viral load) and alcoholic hepatitis history and no other co-morbidities. His MELD and MELD-Na scores were 7 and 13, respectively. He had multi-focal HCC on both US and histopathology of the explant with a total tumor volume (TTV) of 45 and no lympho-vascular invasion. His fibrosis stage was F3. Second patient was a 65-years-old male with HCV infection genotype 1A and a pre-transplant viral load of 7.2 x 105. His BMI was 27.2. He had OSA being treated with C-PAP. His MELD and MELD-Na were 7 and 19. His multi-focal HCC and his TTV was 26. He underwent TACE pre-transplantation. He had no lympho-vascular invasion. His fibrosis stage was F2. Regression analysis of the factors contributing to this showed no significant correlation. Rate of HCC in non-cirrhotic HCV is still within the rate of previously reported studies. Although larger study including non-transplanted patients may revel higher incidence. None
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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 | 0.002 | 0.002 |
| 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) | 0.005 | 0.001 |
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".