Table 3 Proposed Methods of Analysis
Analysis | Hypothesis | Independent variable | Outcome variable | Method of analysis | |
|---|---|---|---|---|---|
Name | Variable type | ||||
Primary | Presence of one or more prothrombotic defect/s increase the risk of TE | Presence of one or more prothrombotic defect | Symptomatic TE | Binary | Fisher’s Exact Test Analysis performed for overall prevalence of at least one prothrombotic defect and for individual defect. |
Secondary | |||||
Aim 1. | 1.a Older age increases the risk of TE, especially in presence of one or more prothrombotic defect | Age of the patient (age < 10 years, age ≥ 10 years) | Symptomatic TE | Binary | Logistic regression |
1.b HR/VHR ALL increases the risk of TE, especially in presence of one or more prothrombotic defect | Risk categorization of ALL (HR/VHR ALL, SR ALL) | ||||
1.c PEG ASP therapy increases the risk of TE, especially in presence of one or more prothrombotic defect | Type of ASP (E. coli ASP, PEG ASP) | ||||
Aim 2 | A mathematical model can be used to determine the risk of symptomatic TE | Clinical Variables: age of the patient, risk categorization of ALL presence or absence of prothrombotic defect, Therapy variable: type of ASP used | Symptomatic TE | Binary | Regression analysis will be used to predict the risk of TE |
Aim 3 | The overall (presence of at least one tested) prevalence of one or more prothrombotic defect is at least 20% | Â | Prevalence of one or more prothrombotic defect/s | Categorical | Prevalence of individual and overall prothrombotic defect will be expressed as percentage of affected patients with 95% CI |