C16050: A national, prospective, non-interventional study of using NINLARO® in real world clinical practice

Study type

• Study topic:
  Human medicinal product
• Study type:
  Non-interventional study
• Scope of the study:
  Effectiveness study (incl. comparative)

  Safety study (incl. comparative)

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Name of medicine:
  NINLARO
• Study drug International non-proprietary name (INN) or common name:
  IXAZOMIB CITRATE

  LENALIDOMIDE

  DEXAMETHASONE
• Anatomical Therapeutic Chemical (ATC) code:
  (L01XG03) ixazomib

  ixazomib
• Medical condition to be studied:
  Oncologic complication

Population studied

• Age groups:
  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:
  3000

Study design details

• Main study objective:
  The primary objective of the study is to evaluate the safety profile of NINLARO to fulfill the regulatory authority's requirement of intensive drug monitoring (IDM) in Chinese population.
• Outcomes:
  The primary outcomes will include assessment of the adverse events (AEs). ; The secondary outcomes will include assessment of the serious adverse events (SAEs), adverse drug reactions (ADRs), adverse event of special interests (AESI), dose adjustment, demographics, clinical and disease characteristics, and overall survival (OS).
• Data analysis plan:
  Descriptive statistics will be used. If necessary, Fisher's exact test, x^2 test, or t-test will be used to examine differences in AEs occurrence between subgroups. ; Disease and patient presentation, therapies, and clinical Outcome measures will be summarized descriptively by patient characteristics, disease characteristics, and predictors of treatment choice. ; Also, treatment patterns will be summarized according to subgroups based on clinically relevant factors. ; Kaplan-Meier survival analysis, Cox regression or Log-rank regression for drug efficiency may also be applied. Incidence of AEs, SAEs, ADRs, and AESI will be analyzed by 95% of confidence interval. Logistic regression models to identify critical factors may be used.