Denosumab-Induced Immune Hepatitis
Bibliographic record
Abstract
Denosumab-Prolia®, Xgeva® (Amgen) is a fully human antibody to the receptor activator of the nuclear factor-K ligand (RANKL). Hepatotoxicity is extremely rare, with only one reported case of immune origin. We present a second case of hepatotoxicity resulting from an immune reaction to denosumab. A 43-year-old female was referred to the Endocrinology, Diabetes & Metabolism Department for treatment of low bone mineral density (BMD) following endocrine therapy with letrozole and lucrin because of breast cancer. She developed premature menopause at the age of 36 years when she underwent a left lumpectomy due to an infiltrating duct carcinoma of the breast (T1 NO MO) and was subsequently started on endocrine therapy. Denosumab was started to prevent osteoporosis. On the third year after starting on denosumab and one month after she received the last injection, she became ill. The routine biochemical analysis showed that the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) rose appreciatively to 10 times the upper limit of normal (ULN). The gamma-glutamyl transferase (GGT) level was elevated slightly to 67 U/L (0-38 U/L). The serum gamma-globulin level was elevated to 1.72 g/dL (0.7-1.6 gr/dl), while the total bilirubin (TB) and serum albumin levels were normal. A liver biopsy revealed a moderate to severe chronic inflammatory infiltrate containing MUM-1 positive plasma cells. In addition, numerous CD-3 positive small T lymphocytes and few CD-20 positive B lymphocytes and eosinophils were seen in the portal tracts. Moderate to severe interface hepatitis, bile duct proliferation and mild portal fibrosis were also identified. The results could be consistent with the diagnosis of drug-induced liver injury (DILI).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".