Development of a Multivariable Model to Predict the Risk of Dose Delays following Chemotherapy

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Other
• If ‘other’, further details on the scope of the study:
  Risk prediction model development

Non-interventional study

• Non-interventional study design:
  Cohort

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)
• Special population of interest:
  Renal impaired

  Hepatic impaired
• Estimated number of subjects:
  3000

Study design details

• Main study objective:
  to develop and internally validate a risk prediction model to identify those patients that are at risk of dose delays.
• Data analysis plan:
  We will develop risk prediction equations using the whole cohort of patients to predict the risk of a patient receiving a dose delay at cycle 2.A Multivariable logistic regression model will be used for the analysis as an appropriate method where outcomes are binary and independent variables are continuous, categorical or a combination. Initially, we will fit a full multivariable model containing all variables. Backward elimination will then be used to successively remove non-significant factors with p values of greater than 0.2. Continuous candidate predictors will be retained in their continuous form to avoid statistical power loss.The performance of the developed model will be summarised in the development datasets using calibration and discrimination. Model calibration determines performance in terms of the agreement between predicted outcome risks and those actually observed. To quantify the degree of optimism, we will undertake in internal validation.