Hydroxychloroquine and Phlebotomy for Treating Porphyria Cutanea Tarda

Study Design: Pragmatic Interventional study Primary Study Objective: To determine and compare time to remission with treatment with low-dose hydroxychloroquine or repeated phlebotomy in participants with PCT. Secondary Study Objective(s): 1. To assess the effects of susceptibility factors on responses to treatment of PCT by these methods. 2. To determine and compare rates of recurrence of PCT after treatment with low-dose hydroxychloroquine or phlebotomy. Study Population and Main Eligibility/ Exclusion Criteria: Treatment: Hydroxychloroquine 100 mg twice weekly for up to 24 months by mouth vs. phlebotomy 450 mL biweekly until target serum ferritin reached, or up to 24 months. Safety Issues- 1. Side effects of phlebotomy or hydroxychloroquine, which are the same as in clinical practice. Primary Outcome Measures: 1. Time to achievement of a normal plasma total porphyrin level. 2. Tolerability and safety of both treatments Secondary Outcome Measures: 1\. Time to 50% reduction in plasma porphyrin levels. 2. Time to 75% reduction in plasma porphyrin levels. 3. Time to normal urinary porphyrin levels 1. Time to disappearance of a plasma fluorescence peak at neutral pH. 2. Time to normalization of urinary total porphyrins. 3. Time to normalization of the urinary total porphyrin pattern by HPLC 4. Effects of susceptibility factors such as hepatitis C, inherited UROD deficiency, etc. on efficacy and safety of the two treatment methods. 5. Rates of recurrence after each type of treatment and the effects of susceptibility factors on recurrence rates. Statistical Considerations (sample size and analysis plan): Time to achieving biochemical endpoints will be determined from individual subject data. Outcome measures such as time to remission will be compared using Cox proportional models to study the effects of susceptibility factors on the hazard ratio to compare the two treatments. Additional modeling will assess factors affecting the frequency of recurrence and seasonality effects using logistic regression modeling and log-rank testing, respectively. Sponsors: National Institutes of Health (NIH)