A Case of Autoimmune Myelofibrosis Associated With Autoimmune Hepatitis
Bibliographic record
Abstract
Autoimmune myelofibrosis (AIMF) is a distinct, underrecognized, and rare cause of bone marrow fibrosis. It carries a favorable outcome and responds well to immunosuppression. Systemic lupus erythematosus is the most common association with AIMF, but there are other cases of associated autoimmune disorders defined in the literature. A 44-year-old female presented to hospital with a 1-month history of fatigue, malaise, and jaundice. She was found to be pancytopenic with elevated liver enzymes. Tests for Janus kinase 2, myeloproliferative leukemia, and calreticulin mutations were negative. Extensive investigations for hemolytic anemia including direct antiglobulin test, flow cytometry for paroxysmal nocturnal hemoglobinuria, testing for hereditary hemoglobinopathies, and hereditary red cell membrane disorders were non-contributory. Antinuclear antibody was positive at > 1,280, immunoglobulin G was 17.04 g/L, and anti-smooth muscle antibody (ASMA) was positive at 1:40. Characteristic features of AIMF on bone marrow biopsy led to the diagnosis of AIMF. The patient was started on prednisone 1 mg/kg with prolonged taper. Fibroscan and liver biopsy were consistent with cirrhosis and workups for other causes of liver dysfunction were unremarkable. She met criteria for diagnosis of autoimmune hepatitis (AIH). The pancytopenia and liver enzymes improved with prednisone. After 1 year of clinical stability, the patient had relapse of disease with pancytopenia, elevated liver enzymes, and similar fibrosis on repeat bone marrow biopsy. Prednisone was reinitiated at 1 mg/kg, and she was started on mycophenolate mofetil (MMF). Prednisone was tapered, and she continues to have an excellent response on MMF alone. We report a case of AIMF associated with AIH, complicated by non-immune hemolysis. AIMF is rare, and its association with AIH is described in only four other cases in the English-language literature. Overlapping biochemical features of AIH and non-immune hemolysis, which has not been well described in AIMF, lead to significant diagnostic complexity and delay. Despite this, a rapid response to corticosteroids was observed including reversal of profound transfusion dependence, normalization of hemoglobin, and reversal of biochemical evidence of hepatic inflammation. A shared pathogenesis of autoimmune fibrosis in both the bone marrow and liver is speculative but suggested by the temporal association in this case.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".