Target trial emulation
MSM, congenital heart disease, chronic lung disease, HTI
REGRESSION, CHRONIC LUNG DISEASE, APPENDIX
The emulated target trial protocol is detailed in Web Appendix 3 and Web Table 2. We define We are interested in the effect of any palivizumab prescription on RSV-related hospital admission in infants during their first RSV season of life. A full course of treatment by palivizumab requires up to 5 monthly doses during RSV season. As we could not determine adherence to treatment from the HTI data, we define a simplified exposure as a binary indicator of having been prescribed at least 1 dose of palivizumab in their first RSV season of life. Infants are identified in the first month of life for treatment, and it is typically administered in outpatient clinics, not when hospitalized for RSV. Our outcome is a binary indicator of having been hospitalized for an RSV-related condition during their first RSV season of life.Our target estimand is the ACE of palivizumab prescription on RSV-related hospital admission in To balance the confounders in the treated and untreated, we fitted a model for the propensity of receiving palivizumab, including gestational age, age at start of RSV season, Index of Multiple Deprivation quintiles, sex, ethnicity, year of birth, diagnosis of congenital heart disease or chronic lung disease (or both), and other comorbidities. The resultant propensity scores showed reasonable overlap in the treated and untreated (Web Figure 1). Mean differences between treated and untreated, adjusted for inverse probability of weighting by propensity score, were within 0.1, indicating good confounder balance.We fitted 2 different outcome models, a logistic regression model of hospital admission against treatment with inverse probability weight of being treated (IPTW), corresponding to a marginal structural model (MSM) (Continuous gestational age is imputed in the treated and untreated arms separately (to account for any interaction between gestational age and palivizumab) using a MNAR imputation model that includes all the variables of the propensity score model, plus the outcome and birth weight. Birth weight is not included in the outcome model due to collinearity with gestational age. There are thus 2 sensitivity parameters: Based on recommendations in Tompsett et al. (Missing birth weight, Index of Multiple Deprivation score, and ethnicity were imputed alongside gestational age using MICE. We report the results in Estimate of the Average Causal Effect for the Palivizumab Case Study Obtained Using Strategies 2 and 3, Using an Outcome Model Controlled for Confounders and Propensity ScoreAbbreviations: ACE, average causal effect; CI, confidence interval; N/A, not applicable; 
Estimated Average Causal Effect for the Palivizumab Case Study Obtained Using Strategies 2 and 3, Using an Inverse Probability Weighted Outcome ModelAbbreviations: ACE, average causal effect of treatment; CI, confidence interval; N/A, not applicable; 
