Current clinical concerns for patients with hereditary hemochromatosis – a Delphi consensus study
Bibliographic record
Abstract
Abstract Introduction Hereditary hemochromatosis (HH) is caused by hepcidin dysregulation and is characterized by excessive iron accumulation in the liver, heart, and endocrine glands, leading to complications such as fatigue, joint pain, cirrhosis, hepatocellular carcinoma (HCC), and cardiac failure (Allen et al. 2008; Girelli et al. 2022). Standard-of-care treatment comprises phlebotomies (therapeutic venesection) and, less frequently, iron chelators. However, these treatments may have side effects, and impact quality of life, making them unsuitable for some patients (Pericleous et al. 2017; Brissot et al. 2010; EASL guidelines 2022). One study reported that only 33.1–43.2% of patients tolerate and adhere to regular phlebotomies, with these proportions decreasing over time (Hicken et al. 2003). Methods A Delphi consensus methodology following ACCORD, DELPHISTAR, and CREDES guidelines was used to gather professional perspectives on the prevalence of intolerance/refractoriness to phlebotomy in the HH population, define the patient subgroup overly burdened by phlebotomy, define phlebotomy success, limitations, and inappropriate response to front-line therapy, identify unmet needs in current therapy, and develop consensus recommendations for the management of HH, including intolerance and insufficient/suboptimal response. The survey was virtual and was sent in 3 rounds via SurveyMonkey. Results Thirty-two HH experts from Austria, Australia, Belgium, Canada, France, Germany, Italy, Norway, Spain, UK, and USA responded to the survey. Respondents agreed that lack of alternative therapies to phlebotomy (96.9% of respondents), symptoms that fail to resolve with current therapies (78.1%), and insufficient understanding of how transferrin saturation and non-transferrin-bound iron affect patient outcomes (100%) are the main unmet needs in HH. All respondents agreed that some patients experience a high phlebotomy treatment burden during induction, mostly due to session frequency (93.8%), severity of treatment-related adverse events (71.9%; mainly fatigue [96.9%] and arthralgia [84.4%]), and impact on daily activities (81.3%). Frequency and duration of phlebotomy treatment during induction were identified as significant limitations by 75.0% of respondents. Venipuncture site issues were anticipated as long-term complications from repeated phlebotomies by 80.0% of respondents. In the maintenance phase, 6 phlebotomies/year were considered the minimum number of sessions constituting high burden. Most (93.8%) respondents agreed that a failure to achieve treatment target despite a course of therapeutic phlebotomy should be defined as insufficient/suboptimal response. Overall, 90.6% of respondents agreed with the notion of intolerance to phlebotomy as the patient's inability to tolerate phlebotomy treatment due to adverse effects, comorbidities, or exacerbation of existing medical conditions. Most (81.3%) concurred that venous access, unpleasant reactions, and needle aversion are common reasons patients feel ‘unable to continue’ phlebotomy therapy. Patient-reported outcomes were considered of highest importance when assessing the impact of phlebotomy on a patient's life by 87.5% of respondents, who also agreed that this impact is not often measured. For optimal patient outcomes, respondents concurred that regular monitoring in the maintenance phase should include ferritin serum levels (96.7%), joint assessment (75.0%) every ≥12 months (88.0%), HCC surveillance in presence of advanced liver disease (100%) every 6 months (78.1%), liver function tests (72.9%), diabetes (71.9%), and, in selected patients, magnetic resonance liver iron concentration (96.9%). Additional monitoring of transferrin saturation was also considered appropriate in clinical practice (81.3%). Respondents (87.5%) agreed that hepcidin-ferroportin-targeted therapies +/- phlebotomy are the most promising HH treatment options and that patients experiencing high phlebotomy burden should be offered a second-line or alternative therapy. Conclusion The Delphi consensus survey identified several unmet needs in managing patients with HH, particularly the significant limitations of phlebotomy treatment, with respondents identifying a high unmet need for patients who cannot be managed with or do not tolerate this approach. It recommended routine assessments and suggested exploring alternative therapy options for patients who experience a high treatment burden or intolerance to phlebotomy.
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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 | 0.071 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".