title: The lag-time approach improved drug-outcome association estimates in presence of protopathic bias.
abstract: Protopathic bias is a systematic error which occurs when measured exposure status may be affected by the latent onset of the target outcome. In this article, we aimed to discuss the benefits and drawbacks of the lag-time approach to address this type of bias.
  
  
  
  The lag-time approach consists in excluding from exposure assessment the period immediately preceding the outcome detection date. With the help of simple causal diagrams, we illustrate the rationale and limitations of such strategy. The lag-time approach was illustrated in a case-crossover study, based on the health care utilization databases of the Italian Lombardy Region, on the real-world effectiveness of some respiratory drugs (exposure) in preventing asthma exacerbations (outcome).
  
  
  
  A total of 7,300 of patients who were admitted to an emergency department (ED) for asthma during 2010-2012 (cases) were included. Use (vs. nonuse) of short-acting beta-agonists (SABAs, an asthma reliever medication) during the 90 days before the ED admission date was associated with an increased risk of the outcome [odds ratio (OR): 1.95; 95% confidence interval (CI): 1.72, 2.22]. This paradoxical finding may be explained by protopathic bias, as SABA use prior the ED admission may be affected by preceding respiratory distress. Indeed, when a 120-day period preceding the ED admission was ignored from drug exposure assessment (lag time), SABAs were found to be associated with a reduced risk of the outcome (OR: 0.81; 95% CI: 0.84, 0.92), as expected.
  
  
  
  The lag-time approach can be a useful strategy to circumvent protopathic bias in observational studies.
authors.affiliation: Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Piazza dell'Ateneo Nuovo 1, Milan 20126, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Arfè
authors.affiliation: Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Piazza dell'Ateneo Nuovo 1, Milan 20126, Italy. Electronic address: giovanni.corrao@unimib.it.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Corrao
mesh_terms: D000318:Adrenergic beta-Agonists / Q000627:therapeutic use*; D000328:Adult; D018927:Anti-Asthmatic Agents / Q000627:therapeutic use*; D001249:Asthma / Q000188:drug therapy*; D015982:Bias; D018592:Cross-Over Studies; D016208:Databases, Factual / Q000706:statistics & numerical data; D004636:Emergency Service, Hospital; D016021:Epidemiologic Studies; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data*; D006760:Hospitalization; D006801:Humans; D007558:Italy; D008297:Male; D064887:Observational Studies as Topic; D016017:Odds Ratio; D017063:Outcome Assessment, Health Care / Q000379:methods* / Q000706:statistics & numerical data*; D013997:Time Factors; D055815:Young Adult
chemical_list: D000318:Adrenergic beta-Agonists; D018927:Anti-Asthmatic Agents
keywords: Asthma exacerbations; Health care utilization database; Lag-time approach; Observational studies; Protophatic bias; Respiratory drugs