Gender Difference in sidE eFfects of ImmuNotherapy: a possible clue to optimize cancEr tReatment (G-DEFINER)

Study type

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

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Medical condition to be studied:
  Breast cancer

  Malignant melanoma
• Additional medical condition(s):
  Melanoma, lung, head and neck, urogenital, breast cancer and, in addition, other solid tumors characterized by the presence of microsatellite instability (MSI-high), treated with immunocheckpoint inhibitors (ICI) irrespective of treatment schedule. It is possible to include patients treated with Immunotherapy in a compassionate use setting.

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:
  400

Study design details

• Main study objective:
  The study aim is to investigate the differences between sex and gender in the immune-related adverse events development associated with immune checkpoint inhibitors reatmtent.
• Outcomes:
  - To estimate and compare the immunorelated adverse events incidence in female and male patients, and estimate the incidence according to different clinical features and gender dimensions (behavioral and psychosocial differences associated with being female or male). - To estimate and compare the immunorelated adverse events incidence in pre- and postmenopausal women.
• Data analysis plan:
  The incidence of first severe irAEs of any type will be estimated in F and M as a proportion of patients developing the event respect to the total number of patients at risk. The main comparison F vs M will be performed by estimating the odds ratio (OR) in a univariable logistic model, F/M unbalance for different clinical and gender-related characteristics will be taken into account using the “matching weight” (MW) method (applying the propensity score methodology). IrAE incidence will also be estimated according to irAE type and grade, tumor site, ICI treatment, patients’ age and gender-based characteristics by sex groups. Logistic models using MW and including the interaction between sex and the different clinical features will be fitted to estimate OR according to different feature categories or values.