Study type

Study topic

Disease /health condition

Study type

Non-interventional study

Scope of the study

Drug utilisation

Data collection methods

Secondary use of data
Non-interventional study

Non-interventional study design

Cohort
Study drug and medical condition

Medical condition to be studied

Idiopathic pulmonary fibrosis
Population studied

Short description of the study population

US population receiving healthcare in the ambulatory setting.
Patients were included in one of three study cohorts based on prescription history from October 1, 2014 to April 30, 2018, allowing for a 12-month pre-index period to describe patient demographic, clinical and treatment characteristics.

Age groups

  • Adult and elderly population (≥18 years)
    • Adults (18 to < 65 years)
      • Adults (46 to < 65 years)
    • Elderly (≥ 65 years)
      • Adults (65 to < 75 years)
      • Adults (75 to < 85 years)
      • Adults (85 years and over)

Special population of interest

Hepatic impaired
Immunocompromised
Pregnant women
Renal impaired

Estimated number of subjects

13300
Study design details

Main study objective

To understand characteristics of IPF patients treated with nintedanib and pirfenidone, as well as patients who do not receive a prescription for an antifibrotic treatment in the United States

Outcomes

The primary outcome will be the ASD and p-value comparing baseline patient characteristics between patients treated with nintedanib vs. pirfenidone, nintedanib vs. untreated and pirfenidone vs. untreated, The secondary outcomes are the adjusted odds ratios of receiving one treatment over another (or probability of receiving antifibrotic treatment) between the following cohorts:• Nintedanib vs. pirfenidone• Treated patients (i.e. nintedanib or pirfenidone) vs. untreated

Data analysis plan

For the primary objective, baseline patient characteristics will be described using descriptive analysis, i.e. described as counts and percentages for categorical variables and measures of central tendency (mean, median, SD, and min/max) for continuous variables. Differences between the cohorts will be assessed using ASD, where an ASD of at least 10% will be considered a meaningful difference. Patients with missing data will be reported as missing and excluded from the comparison for the missing variable. Bivariate statistical significance tests such as Chi-square test for categorical variables and Wilcoxon rank sum test or t-test for continuous variables (depending on distribution of data) will be performed to compare differences in baseline characteristics between the three cohorts. In addition to standardized differences, p-values will be reported. A multi-variable logistic regression model will be constructed for the secondary objective.