Objectives 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. Study Design and Setting 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). Results 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. Conclusions The lag-time approach can be a useful strategy to circumvent protopathic bias in observational studies.

Arfe, A., Corrao, G. (2016). The lag-time approach improved drug–outcome association estimates in presence of protopathic bias. JOURNAL OF CLINICAL EPIDEMIOLOGY, 78, 101-107 [10.1016/j.jclinepi.2016.03.003].

The lag-time approach improved drug–outcome association estimates in presence of protopathic bias

Arfe A.;Corrao G.
Ultimo
2016

Abstract

Objectives 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. Study Design and Setting 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). Results 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. Conclusions The lag-time approach can be a useful strategy to circumvent protopathic bias in observational studies.
Articolo in rivista - Articolo scientifico
Asthma exacerbations; Health care utilization database; Lag-time approach; Observational studies; Protophatic bias; Respiratory drugs;
Asthma exacerbations; Health care utilization database; Lag-time approach; Observational studies; Protophatic bias; Respiratory drugs; Adrenergic beta-Agonists; Adult; Anti-Asthmatic Agents; Asthma; Bias; Cross-Over Studies; Databases, Factual; Emergency Service, Hospital; Epidemiologic Studies; Female; Health Services; Hospitalization; Humans; Italy; Male; Observational Studies as Topic; Odds Ratio; Outcome Assessment, Health Care; Time Factors; Young Adult
English
2016
78
101
107
none
Arfe, A., Corrao, G. (2016). The lag-time approach improved drug–outcome association estimates in presence of protopathic bias. JOURNAL OF CLINICAL EPIDEMIOLOGY, 78, 101-107 [10.1016/j.jclinepi.2016.03.003].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/272175
Citazioni
  • Scopus 39
  • ???jsp.display-item.citation.isi??? 36
Social impact