A192 GRADE OF ACTIVITY AND FIBROSIS IS SIMILAR IN EAG- AND EAG+ IMMUNE ACTIVE HBV-INFECTED LIVER BIOPSIES
Bibliographic record
Abstract
Immune checkpoints are negative regulatory receptors present on T cells that have been implicated in T cell exhaustion allowing chronic infection with hepatitis B virus (HBV). There is increasing interest in the role of checkpoint inhibitors to reverse T cell exhaustion in chronic HBV and other chronic viral infections, which could lead to effective viral clearance. As part of a larger study involving characterization of checkpoint and their ligands in HBV-infected liver biopsies, here we review the characteristics of HBV infected liver biopsies by disease phase, prior to staining for checkpoints and their ligands. Using the Toronto Centre for Liver Disease (TCLD) database, patients who had a diagnosis of HBV and had a liver biopsy between 2006 and 2017 at the University Health Network were identified. Patients were included if the pre-defined criteria of typical HBV phase were met and were divided into the following groups: immune active (IA) (subdivided by eAg status), immune tolerance (IT), inactive without treatment, and patients on treatment. Patients with coexistent liver disease were excluded. Of 633 liver biopsies (from 588 patients), 128 were included. Of the excluded biopsies, 42% did not meet the exact definitions of disease phase, 30% did not have corresponding blood work close to the time of biopsy and 14% had HCV. Of the included biopsies, 68.8% were from male patients; 4 patients had more than one biopsy included. 15 biopsies had some degree of steatosis. 88 biopsies were included in the IA group (38 eAg- and 50 eAg+), 18 in the IT group, 10 in the inactive group and 12 in the treatment group. The median age was higher in the eAg- IA compared to the eAg+ IA subgroup (43.5 vs. 33 years respectively, p<0.001). Median ALT did not differ, nor did median activity and fibrosis grades (p=NS). Not surprisingly, biopsies from the IT group had lower fibrosis compared to the IA group (Laennec fibrosis grade 1/4 vs. 2/4 respectively, p<0.001). The qualitative analysis revealed that pattern of activity was similar between IT, inactive and treatment groups, but that fibrosis was higher in the treatment group. The degree of activity and fibrosis is similar between eAg+ and eAg- immune active biopsies, although age was higher in the eAg- group. These findings can in part be explained by the fact that eAg- patients with advanced fibrosis are usually on treatment. Further characterization of checkpoint and their ligands will help better understand the different behaviors of disease phases. In particular, whether or not there are true differences in checkpoint prevalence depending on eAg status will be of interest. 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".