Association between previous biologic therapy exposure and incidence of life-threatening infections in patients with rheumatoid arthritis and psoriasis. A population-based cohort study.

Study type

• Study topic:
  Disease /health condition

  Human medicinal product
• Study type:
  Non-interventional study
• Scope of the study:
  Safety study (incl. comparative)
• Data collection methods:
  Secondary use of data

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Name of medicine, other:
  Biologic therapies

Population studied

• Short description of the study population:
  Adult patients diagnosed with rheumatoid arthritis and/or psoriasis treated with biologic and non-biologic therapies in Catalonia, Spain.
• Age groups:
  Adult and elderly population (≥18 years)

  Adults (18 to < 65 years)

  Adults (18 to < 46 years)

  Adults (46 to < 65 years)

  Elderly (≥ 65 years)

  Adults (65 to < 75 years)

  Adults (75 to < 85 years)

  Adults (85 years and over)
• Estimated number of subjects:
  25000

Study design details

• Study design:
  Population-based cohort study
• Main study objective:
  This study aims to evaluate the association between biologic exposure and the incidence of serious infections, including COVID-19, influenza, pneumonia, and/or septicaemia, in patients diagnosed with rheumatoid arthritis and/or psoriasis in the general population of Catalonia.
• Setting:
  Primary Care and Outpatients Specialized Care in Catalonia, Spain
• Comparators:
  Biologic vs non-biologic therapies
• Outcomes:
  The infections will be classified as potentially severe if they are associated with hospitalization or mortality: any infection that requires hospitalization or is associated with mortality, including pneumonia, influenza, septicaemia, and COVID-19.
• Data analysis plan:
  The study population will be described overall and stratified by exposure status (exposed vs. unexposed individuals). Quantitative variables will be summarized using means with standard deviations (SD) or medians with interquartile ranges (IQR), depending on the distribution of the variable. Categorical variables will be presented as absolute and relative frequencies. Bivariate comparisons between groups will be conducted using Student's t-tests, Wilcoxon rank-sum tests, or Chi-square tests, as appropriate.; For the primary outcome, marginal structural models (MSMs) will be employed to estimate the risk of treatment exposure while addressing confounding. Inverse probability of treatment weights (IPTWs) will be derived from propensity scores calculated using age, sex, socioeconomic deprivation score, previous life-threatening infections, and other relevant clinical factors. If necessary, weights will be truncated at the 1st percentile to stabilize estimates. Covariate balance before and after weighting will be evaluated using the standardized mean difference (SMD). Variables with SMD > 0.1 after weighting will be included in the MSM as additional covariates to achieve double robustness.; IPTWs will then be applied in logistic regression models to estimate risk ratios (RRs) with 95% confidence intervals (CIs), using robust standard errors (SEs) to account for variability. Statistical significance will be determined using the Wald test at a 0.05 level. When assessing the association between prior biologic exposure and severity outcomes, patients will be assigned to the worst outcome observed (all-cause death > hospitalization > disease presence) to ensure a mutually exclusive classification.