Paroxysmal Nocturnal Hemoglobinuria (PNH) Registry (M07-001)

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Assessment of risk minimisation measure implementation or effectiveness

  Disease epidemiology

  Effectiveness study (incl. comparative)

Non-interventional study

• Non-interventional study design:
  Other
• Non-interventional study design, other:
  Observational, non-interventional registry

Study drug and medical condition

• Medical condition to be studied:
  Paroxysmal nocturnal haemoglobinuria

Population studied

• Age groups:
  • Adolescents (12 to < 18 years)
  • Children (2 to < 12 years)
  • Infants and toddlers (28 days – 23 months)
  • Preterm newborn infants (0 – 27 days)
  • Term newborn infants (0 – 27 days)
  • Adults (18 to < 46 years)
  • Adults (46 to < 65 years)
  • Adults (65 to < 75 years)
  • Adults (75 to < 85 years)
  • Adults (85 years and over)
• Estimated number of subjects:
  6000

Study design details

• Main study objective:
  The PNH Registry will collect and evaluate safety data specific to the use of Soliris or Ultomiris in patients with PNH. The PNH registry will collect data to characterize the progression of PNH as well as clinical outcomes, mortality and morbidity in all enrolled patients.
• Data analysis plan:
  Primary analyses will assess safety endpoints, including occurrence and time to first event for pre-specified events. All SAEs will be collected for treated patients to characterize the long-term safety profile. Primary analysis will also describe treatment discontinuation, dose adjustments and clinical outcomes. Secondary analyses will describe patient population and health-related quality of life assessment. Analyses will be detailed in a Statistical Analysis Plan. Descriptive analyses will be reported for continuous variables, frequencies and percentages will be reported for categorical variables. The total number of events and total person-years during the period of interest will be determined. The predicted event rate will be calculated using Poisson regression with over-dispersion or generalized estimating equations with a log link, as is appropriate. Survival analysis will be used for time to event outcomes. Propensity scores may be used to reduce the bias.