Phase <scp>II</scp> clinical trial of phlebotomy for non‐alcoholic fatty liver disease
Bibliographic record
Abstract
BACKGROUND: Elevated iron indices are described in non-alcoholic fatty liver disease and iron reduction has been suggested as a potential therapy. AIM: To determine whether phlebotomy is an effective therapy for non-alcoholic fatty liver disease. METHODS: Patients with biopsy proven non-alcoholic fatty liver disease underwent baseline evaluation to determine severity of metabolic and liver disease. A Phase II trial of phlebotomy was carried out to achieve near-iron depletion (serum ferritin ≤50 μg/L or haemoglobin 100 g/L). Repeat liver biopsy, anthropometric and biochemical measurements were performed 6 months following the end of treatment. Primary outcome was improvement in liver histology, assessed using the non-alcoholic fatty liver disease activity score. RESULTS: Thirty-one patients completed follow-up. Iron reduction resulted in a significant improvement in the non-alcoholic fatty liver disease activity score (-0.74 ± 1.83, P = 0.019). Reductions in individual histological features of lobular inflammation (-0.29 ± 1.07, P = 0.182), steatosis (-0.26 ± 0.82, P = 0.134), hepatocyte ballooning (-0.19 ± 0.70, P = 0.213) did not achieve significance nor did the score for fibrosis (-0.32 ± 0.94, P = 0.099). CONCLUSIONS: This prospective Phase II study of phlebotomy with paired liver biopsies evaluating phlebotomy therapy in non-alcoholic fatty liver disease patients suggests that iron reduction may improve liver histology. However, the effect size of phlebotomy raises questions of whether treatment could have sufficient clinical significance to justify a definitive Phase III trial. This trial has been registered with the US National Institute of Health (clinicaltrials.gov, Identifier NCT 00641524).
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".