Tutorial: Strategies addressing detection bias were reviewed and implemented for investigating the statins–diabetes association

Advances in methodologies of negative controls: a scoping review

OBJECTIVES

Negative controls are considered an important tool to mitigate biases in observational studies. The aim of this scoping review was to summarize current methodologies of negative controls (both negative control exposure [NCE] and negative control outcome [NCO]).

STUDY DESIGN AND SETTING

We searched PubMed, Web of Science, Embase, and Cochrane Library (up to March 9, 2023) for articles on methodologies of negative controls. Two reviewers selected eligible studies and collected relevant data independently and in duplicate. We reported total numbers and percentages, and summarized methodologies narratively.

RESULTS

A total of 37 relevant methodological articles were included in our review. These publications covered NCE (n = 11, 29.8%), NCO (n = 13, 35.1%), or both (n = 13, 35.1%), with most focused on bias detection (n = 14, 37.8%), bias correction (n = 16, 43.3%), and P value or confidence interval (CI) calibration (n = 5, 13.5%). For the two remaining articles (5.4%), one discussed bias detection and P value or CI calibration and the other covered all the three functions. For bias detection, the existence of an association between the NCE (NCO) and outcome (exposure) variables of interest simply indicates that results may suffer from confounding bias, selection bias and/or information bias. For bias correction, however, the algorithms of negative control methods need more stringent assumptions such as rank preservation, monotonicity, and linearity.

CONCLUSION

Negative controls can be leveraged for bias detection, P value or CI calibration, and bias correction, among which bias correction has been the most studied methodologically. The current available methods need some stringent assumptions to detect or remove bias. More methodological research is needed to optimize the use of negative controls.

Association between prediagnostic prostate-specific antigen and prostate cancer probability in Black and non-Hispanic White men

BACKGROUND

Although Black men are more likely than non-Hispanic White men to develop and die from prostate cancer, limited data exist to guide prostate-specific antigen (PSA) screening protocols in Black men. This study investigated whether the risk for prostate cancer was higher than expected among self-identified Black than White veterans based on prebiopsy PSA level.

METHODS

Multivariable logistic regression models were estimated to predict the likelihood of prostate cancer diagnosis on first biopsy for 75,295 Black and 207,658 White male veterans. Self-identified race, age at first PSA test, prebiopsy PSA, age at first biopsy, smoking status, statin use, and socioeconomic factors were used as predictors. The adjusted predicted probabilities of cancer detection on first prostate biopsy from the logistic models at different PSA levels were calculated.

RESULTS

After controlling for PSA and other covariates, Black veterans were 50% more likely to receive a prostate cancer diagnosis on their first prostate biopsy than White veterans (odds ratio [OR], 1.50; 95% CI, 1.47-1.53; p < .001). At a PSA level of 4.0 ng/mL, the probability of prostate cancer for a Black man was 49% compared with 39% for a White man. This model indicated that Black veterans with a PSA of 4.0 ng/mL have an equivalent risk of prostate cancer as White veterans with a PSA of 13.4 ng/mL.

CONCLUSIONS

The findings indicate that, at any given PSA level, Black men are more likely to harbor prostate cancer than White men. Prospective studies are needed to better evaluate risks and benefits of PSA screening in Black men and other high-risk populations.

Diabetes Mellitus after SARS-CoV-2 Infection: An Epidemiological Review

Diabetes mellitus (DM) is among the major global public health issues. According to recent projections, a continued rise in DM prevalence is expected in the following decades. The research has shown that DM is associated with poorer outcomes of coronavirus disease 2019 (COVID-19). However, there is growing evidence suggesting that COVID-19 is associated with new-onset DM type 1 and type 2. This review aims to summarize the current knowledge about the new onset of DM following COVID-19. All identified studies were longitudinal, and they have predominantly shown a significantly increased risk for new-onset DM (both type 1 and type 2) following a SARS-CoV-2 infection. Increased risk of poorer COVID-19 outcomes (mechanical ventilation, death) was noted in persons with new-onset DM following SARS-CoV-2 infection. Studies investigating risk factors for new-onset DM in COVID-19 patients showed that severe disease, age, ethnicity, ventilation, and smoking habits were associated with DM occurrence. The information summarized in this review presents a valuable source of evidence for healthcare policymakers and healthcare workers in the effort of planning prevention measures for new-onset DM after SARS-CoV-2 infection and the timely identification and appropriate treatment of patients with COVID-19 who could be at greater risk for new-onset DM.

Prolonged Use of Proton Pump Inhibitors and Risk of Type 2 Diabetes: Results From a Large Population-Based Nested Case-Control Study

CONTEXT

It is still debated whether prolonged use of proton pump inhibitors (PPIs) might affect metabolic health.

OBJECTIVE

To investigate the relationship between prolonged use of PPIs and the risk of developing diabetes.

METHODS

We performed a case-control study nested into a cohort of 777 420 patients newly treated with PPIs between 2010 and 2015 in Lombardy, Italy. A total of 50 535 people diagnosed with diabetes until 2020 were matched with an equal number of controls that were randomly selected from the cohort members according to age, sex, and clinical status. Exposure to treatment with PPIs was assessed in case-control pairs based on time of therapy. A conditional logistic regression model was fitted to estimate the odds ratios and 95% CIs for the exposure-outcome association, after adjusting for several covariates. Sensitivity analyses were performed to evaluate the robustness of our findings.

RESULTS

Compared with patients who used PPIs for < 8 weeks, higher odds of diabetes of 19% (95% CI, 15-24), 43% (38-49), and 56% (49-64) were observed among those who used PPIs for between 8 weeks and 6 months, 6 months and 2 years, and > 2 years, respectively. The results were consistent when analyses were stratified according to age, sex, and clinical profile, with higher odds ratios being found in younger patients and those with worse clinical complexity. Sensitivity analyses revealed that the association was consistent and robust.

CONCLUSIONS

Regular and prolonged use of PPIs is associated with a higher risk of diabetes. Physicians should therefore avoid unnecessary prescription of this class of drugs, particularly for long-term use.

The Risk of Melanoma With Rasagiline Compared With Other Antiparkinsonian Medications: A Retrospective Cohort Study in the US Medicare Database

Purpose

Compare the risk of melanoma between initiators of rasagiline or other antiparkinsonian drugs (APDs) in a Parkinson's disease (PD) population.

Methods

A retrospective cohort study was conducted in the US Medicare claims research database (2006–2015) in adults aged ≥65 years with PD claims. Other APD initiators were randomly matched (4:1) to rasagiline initiators on age, sex, and cohort entry year. Cutaneous melanoma events were identified by a validated claims algorithm. Incidence rates (IRs), incidence rate ratios (IRRs), and Cox‐adjusted hazard ratios (HRs) for melanoma comparing rasagiline with other APD initiators were calculated and analyzed by duration of study medication use and cumulative dose of rasagiline. Potential indicators of surveillance bias were explored.

Results

Among 23 708 rasagiline initiators and 96 552 matched APD initiators, the crude IR of melanoma/100 000 person‐years was 334.3 (95% confidence interval [CI], 291.5–381.6) and 208.2 (95% CI, 190.1–227.5), respectively (crude IRR 1.61; 95% CI, 1.36–1.89). The adjusted HR was 1.37 (95% CI, 1.14–1.65) and increased with longer rasagiline exposure and higher cumulative rasagiline doses. Rasagiline initiators more frequently had dermatologist visits or skin biopsies before cohort entry than APD initiators and had a higher incidence of nonmelanoma skin cancer during follow‐up (crude IRR, 1.44; 95% CI, 1.35–1.54).

Conclusions

A small increased incidence of melanoma with exposure to rasagiline compared with other APDs was observed. Although the pattern with dose and duration is consistent with a hypothesized biologic effect, the increased skin cancer surveillance among rasagiline users suggests surveillance bias as a contributing explanation for the observed results.

On the Nature of Informative Presence Bias in Analyses of Electronic Health Records

Electronic health records (EHRs) offer unprecedented opportunities to answer epidemiologic questions. However, unlike in ordinary cohort studies or randomized trials, EHR data are collected somewhat idiosyncratically. In particular, patients who have more contact with the medical system have more opportunities to receive diagnoses, which are then recorded in their EHRs. The goal of this article is to shed light on the nature and scope of this phenomenon, known as informative presence, which can bias estimates of associations. We show how this can be characterized as an instance of misclassification bias. As a consequence, we show that informative presence bias can occur in a broader range of settings than previously thought, and that simple adjustment for the number of visits as a confounder may not fully correct for bias. Additionally, where previous work has considered only underdiagnosis, investigators are often concerned about overdiagnosis; we show how this changes the settings in which bias manifests. We report on a comprehensive series of simulations to shed light on when to expect informative presence bias, how it can be mitigated in some cases, and cases in which new methods need to be developed.

A Latent Disease Model to Reduce Detection Bias in Cancer Risk Prediction Studies

In studies of cancer risk, detection bias arises when risk factors are associated with screening patterns, affecting the likelihood and timing of diagnosis. To eliminate detection bias in a screened cohort, we propose modeling the latent onset of cancer and estimating the association between risk factors and onset rather than diagnosis. We apply this framework to estimate the increase in prostate cancer risk associated with black race and family history using data from the SELECT prostate cancer prevention trial, in which men were screened and biopsied according to community practices. A positive family history was associated with a hazard ratio (HR) of prostate cancer onset of 1.8, lower than the corresponding HR of prostate cancer diagnosis (HR = 2.2). This result comports with a finding that men in SELECT with a family history were more likely to be biopsied following a positive PSA test than men with no family history. For black race, the HRs for onset and diagnosis were similar, consistent with similar patterns of screening and biopsy by race. If individual screening and diagnosis histories are available, latent disease modeling can be used to decouple risk of disease from risk of disease diagnosis and reduce detection bias.

Better adherence with out-of-hospital healthcare improved long-term prognosis of acute coronary syndromes: Evidence from an Italian real-world investigation

BACKGROUND

Patients who experience a hospital admission for acute coronary syndromes (ACS) exhibit poor prognosis over the years. The purposes of this study were to evaluate the real-world patterns of out-of-hospital practice in the management of ACS patients and to assess their impact on the risk of selected outcomes.

METHODS

The cohort of 87,530 residents in the Lombardy Region (Italy) who were newly hospitalised for ACS during 2011-2015 was followed until 2018. Exposure to medical treatment including use of selected drugs, diagnostic procedures and laboratory tests was recorded. The main outcome of interest was re-hospitalisation for cardiovascular (CV) outcomes. Proportional hazards models were fitted to estimate hazard ratio, and 95% confidence intervals (CI), for the exposure-outcome association. Analyses were stratified according to the ACS type.

RESULTS

The cumulative incidence of re-hospitalisation for CV disease was 33%, 42% and 38% at 5 years after index discharge among STEMI, NSTEMI and unstable angina patients. Within one year from index discharge, between 70% and 80% of patients had at least a prescription of statins, beta-blockers and renin-angiotensin-system blocking agents, underwent ECG and lipid profile examination, and had a cardiologic examination. One patient in five underwent cardiac rehabilitation. Compared with patients who did not adhere to healthcare recommendations, the risk of CV hospital readmission was reduced from 10% (95% CI: 4%-10%) to 23% (12%-32%) among patients who underwent lipid profile examinations and who experienced cardiac rehabilitation.

CONCLUSION

Close out-of-hospital healthcare must be considered the cornerstone for improving the long-term prognosis of ACS patients.

Incidence, clinical presentation, and outcomes of Pneumocystis pneumonia when utilizing Polymerase Chain Reaction-based diagnosis in patients with Hodgkin lymphoma

A Polymerase Chain Reaction-based diagnosis of Pneumocystis Pneumonia (PCP) and the need for anti-Pneumocystis prophylaxis in Hodgkin lymphoma patients receiving chemotherapy requires further investigation. This retrospective, single-center, study evaluated 506 consecutive adult patients diagnosed with Hodgkin lymphoma receiving chemotherapy between January 2006 and August 2018. The cumulative incidence of PCP 1 year after start of chemotherapy was 6.2% (95% CI 3.8-8.5%). Mortality 30 days from PCP diagnosis was 8% (n = 2) with one death attributable to PCP. Bleomycin-containing combination chemotherapy regimen was not significantly associated with a higher risk for PCP when compared to other regimens (HR = 1.59, 95% CI 0.55-4.62 p = 0.40). Anti-Pneumocystis prophylaxis was not significantly associated with a decreased incidence of PCP (HR = 0.51, 95% CI 0.15-1.71, p = 0.28). As the overall incidence is above the commonly accepted 3.5% threshold, clinicians should consider the potential value of prophylaxis. The utility of universal vs. targeted anti-Pneumocystis prophylaxis requires prospective, randomized investigation.

Balancing cardiovascular benefit and diabetogenic harm of therapy with statins: Real-world evidence from Italy

AIM

To provide information on the balance between the cardiovascular (CV) benefit and the diabetogenic harm of statin therapy in the current clinical practice.

METHODS

All the 115,939 residents (older than 50 years) in the Italian Lombardy Region newly treated with statins between 2003 and 2005, were followed from the first statin prescription until 2012 to identify those experiencing a macrovascular complication and those with at least one sign suggestive of new onset diabetes. The proportion of days of follow-up covered by statin prescriptions measured adherence with statins. Hazard ratio, and relative 95% confidence interval (CI), for the two considered outcomes associated with statin adherence, were separately estimated (proportional hazard models). Number needed to treat (NNT) and number needed to harm (NNH), i.e., number of individuals who must be treated with statins in order to prevent a macrovascular complication, or to generate a new onset diabetes, respectively, were calculated to evaluate the balance between CV benefit and diabetogenic harm of statin therapy.

RESULTS

Compared to those at very low adherence with statins, patients at high adherence showed a significant reduction of macrovascular risk (28%, 95% CI: 23%-33%) and a greater risk of developing diabetic condition (67%, 50%-86%). In the whole cohort, the NNT was 26, whereas the NNH 65. NNT was lower than NNH also in all considered strata of age, gender, clinical profile.

CONCLUSIONS

This large cohort investigation provides real-world evidence that the balance between CV benefit and diabetogenic harm of statin therapy is largely favourable to treatment benefits.

Infection, antibiotic exposure, and risk of celiac disease: A systematic review and meta-analysis

BACKGROUND AND AIM

There is evidence of a relationship between infection (and the associated antibiotic exposure) and the risk of celiac disease (CD). This study performed a meta-analysis to investigate this relationship.

METHODS

To identify relevant studies, we conducted systematic searches of the PubMed, Embase, and Cochrane databases for articles published up to April 2019. Random effects models were used to determine overall pooled estimates and 95% confidence intervals (CIs).

RESULTS

The meta-analysis included 19 observational studies (15 on infection and six on antibiotic exposure). Our results showed that any infection was associated with an increased risk of CD later in life (odds ratio, 1.37; 95% CI: 1.2-1.56; P < 0.001). The I² was 94% (high heterogeneity among studies). Subgroup analyses suggested that the risk of CD is not affected by the type of infectious agent, timing of exposure, and site of infection. Exposure to antibiotics was also associated with new-onset CD (odds ratio, 1.2; 95% CI: 1.04-1.39; P < 0.001).

CONCLUSION

Exposure to early infection or antibiotic appears to increase the odds of developing CD, suggesting that intestinal immune or microbiota dysbiosis may play a role in the pathogenesis of CD. These findings may influence clinical management and primary prevention of CD. However, noncausal explanations for these positive associations cannot be excluded.

Association Between Health Maintenance Practices and Skin Cancer Risk as a Possible Source of Detection Bias

Importance

Detection bias may influence the results of epidemiologic studies of skin cancer risk. An individual's degree of contact with the health care system, and, specifically, undergoing routine screening practices, may be a source of such bias. More intensive screening practices may be associated with increased diagnoses of basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma.

Objective

To assess a possible association between health care screening practices and skin cancer risk.

Design, Setting, and Participants

The cohort of participants for this study was drawn from the Nurses' Health Study (121 700 women) and Health Professionals Follow-up Study (51 529 men). Participants in the Nurses' Health Study were followed up from June 1, 1990, to June 1, 2012, and participants in the Health Professionals Follow-up Study were followed up from January 1, 1990, to January 1, 2012. Statistical analysis was performed from April 4, 2017, to May 16, 2018.

Exposures

During cohort follow-up, Nurses' Health Study and Health Professionals Follow-up Study participants were asked whether they had undergone various health care screening practices including physical examination by a physician, sigmoidoscopy or colonoscopy, eye examination, serum cholesterol test, mammography, breast examination and pelvic examination, and prostate-specific antigen test and rectal examination.

Main Outcomes and Measures

Incident BCC, SCC, and invasive melanoma. Cases of SCC and melanoma were confirmed with histopathologic findings. Hazard ratios (HRs) with 95% CIs were calculated for the association between screening practices and the various types of skin cancer.

Results

This study included 77 736 women from the Nurses' Health Study (mean [SD] age at baseline, 56 [7] years) who were followed up for 1 388 523 person-years and 39 756 men from the Health Professionals Follow-up Study (mean [SD] age at baseline, 58 [10] years) who were followed up for 635 319 person-years. A total of 14 319 incident BCCs, 1517 SCCs, and 506 melanomas were identified in the Nurses' Health Study cohort and 8741 incident BCCs, 1191 SCCs, and 469 melanomas were identified in the Health Professionals Follow-up Study cohort. Positive associations were seen between various screening practices and diagnoses of BCC and SCC, with similar directions of associations seen with melanoma for some screening practices. In the Nurses' Health Study, the multivariable HR associated with undergoing a physical examination was 1.46 (95% CI, 1.30-1.64) for BCC, 2.32 (95% CI, 1.41-3.80) for SCC, and 1.66 (95% CI, 0.85-3.22) for melanoma. Similar results were seen in the Health Professionals Follow-up Study, with a multivariable HR associated with undergoing a physical examination of 1.43 (95% CI, 1.26-1.63) for BCC and 1.85 (95% CI, 1.17-2.92) for SCC, with an attenuated HR for melanoma of 1.04 (95% CI, 0.64-1.69).

Conclusions and Relevance

Undergoing health care screening practices increases the likelihood of being diagnosed with skin cancer. Researchers should be aware of this association and, where appropriate and possible, condition analyses of skin cancer risk on measures of health care use, including screening, to address confounding associated with detection bias.

Perils of Observational Data Analyses

See Article Ko et al.

Clinical significance of diabetes likely induced by statins: Evidence from a large population-based cohort

AIM

To provide information on the extent to which type 2 diabetes more likely induced by statins affects the risk of macrovascular complications compared to diabetes unlikely induced by statins.

METHODS

The 84,828 residents in the Italian Lombardy Region who were newly treated with statins between 2003 and 2005 were followed from the index statin prescription until 2009 (step-1 follow-up) to identify those starting antidiabetic therapy. The proportion of days of follow-up covered by statins measured adherence with statins. Cohort members who experienced diabetes were 1:3 matched with those who did not developed diabetes for gender, age and previous adherence with statin treatment. The 3321 diabetic - non-diabetic sets, were followed from the initial antidiabetic therapy until 2012 (step-2 follow-up) to estimate the hazard ratio (HR), and 95% Confidence Interval (CI), for macrovascular complications (proportional hazard models) associated with diabetes separately in each category of adherence with statins.

RESULTS

During the step-1 follow-up, the risk of new-onset diabetes increased progressively with increasing adherence with statins. During the step-2 follow-up, the risk of macrovascular complications associated with diabetes decreased progressively from 1.70 (1.18-2.44), 1.41 (1.17-1.70), 1.30 (1.07-1.57) until 1.10 (0.40-2.80) as adherence with statins during the step-1 follow-up increased.

CONCLUSIONS

Type 2 diabetes lost its association with increasing macrovascular risk when previous adherence with statins was very high, and thus the chance of its induction by the drug greater. Statin-dependent type 2 diabetes might be prognostically less adverse than diabetes unlikely induced by statins.

Statin use and risk of new-onset diabetes: A meta-analysis of observational studies

BACKGROUND AND AIMS

Meta-analyses of randomized control trials investigating the association between incident diabetes and statin use showed an increased risk of new-onset diabetes (NOD) from 9% to 13% associated with statins. However, short follow-up period, unpowered sample size, and lack of pre-specified diagnostic criteria for diabetes detection could be responsible of an underestimation of this risk. We conducted a meta-analysis of published observational studies to evaluate the association between statins use and risk of NOD.

METHODS AND RESULTS

PubMed, EMBASE and MEDLINE databases were searched from inception to June 30, 2016 for cohort and case-control studies with risk of NOD in users vs nonusers, on ≥1000 subjects followed-up for ≥1 year. Two review authors assessed study eligibility and risk of bias and undertook data extraction independently. Pooled estimates were calculated by a random-effects model and between-study heterogeneity was tested and measured by I² index. Furthermore, stratified analyses and the evaluation of publication bias were performed. Finally, the meta-analysis included 20 studies, 18 cohort and 2 case-control studies. Overall, NOD risk was higher in statin users than nonusers (RR 1.44; 95% CI 1.31-1.58). High between-study heterogeneity (I² = 97%) was found. Estimates for all single statins showed a class effect, from rosuvastatin (RR 1.61; 1.30-1.98) to simvastatin (RR 1.38; 1.19-1.61).

CONCLUSIONS

The present meta-analysis confirms and reinforces the evidence of a diabetogenic effect by statins utilization. These observations confirm the need of a rigorous monitoring of patients taking statins, in particular pre-diabetic patients or patients presenting with established risk factors for diabetes.

Evidence for Detection Bias by Medication Use in a Cohort Study of Breast Cancer Survivors

In previous studies, we found modestly decreased and increased risks of second breast cancer events with the use of statins and antibiotics, respectively, after adjustment for surveillance mammography. We evaluated detection bias by comparing receipt of surveillance mammography among users of these 2 disparate classes of medication. Adult women diagnosed with early-stage breast cancer during 1990-2008 (n = 3,965) while enrolled in an integrated health-care plan (Group Health Cooperative; Washington State) were followed for up to 10 years in the Commonly Used Medications and Breast Cancer Outcomes (COMBO) Study. Categories of antibiotic use included infrequent (1-3 dispensings/12 months) and frequent (≥4 dispensings/12 months) use, and categories of statin use included less adherent (1 dispensing/6 months) and adherent (≥2 dispensings/6 months). We examined associations between medication use and surveillance mammography using multivariable generalized estimating equations and evaluated the impact of adjusting for surveillance within Cox proportional hazard models. Frequent antibiotic users were less likely to receive surveillance mammography (odds ratio (OR) = 0.90, 95% confidence interval (CI): 0.82, 0.99) than were nonusers; no association was found among infrequent users (OR = 0.96, 95% CI: 0.90, 1.03). Adherent statin use was associated with more surveillance compared with nonuse (OR = 1.11, 95% CI: 1.01, 1.25), but less adherent statin use was not (OR = 1.03, 95% CI: 0.81, 1.31). No difference in associations between medications of interest and second breast cancer events was observed when surveillance was removed from otherwise adjusted models. The influence of detection bias by medication use warrants further exploration.

A probabilistic bias analysis for misclassified categorical exposures, with application to oral anti-hyperglycaemic drugs

PURPOSE

The effect of drug exposure misclassification generally receives little attention in pharmacoepidemiological research. In this paper, we illustrate a probabilistic bias analysis approach for misclassified categorical exposures and apply it in a database study of oral anti-hyperglycaemic drugs (OADs).

METHODS

A cohort study based on the Health Search Database general-practice database was carried out by including 12 640 adult (≥40 years) patients newly treated with OADs during 2003-2010. The proportion of days covered by OADs prescriptions during the first year of follow-up was evaluated for each individual, either by means of the prescribed daily dose or the defined daily dose. The effect of misclassification on hypothetical OAD-outcome association profiles was assessed through the proposed probabilistic bias analysis approach, taking advantage of available exposure validation data.

RESULTS

During the first year of follow-up, the average (SD) number of months with OADs available was 7 (4) months and 5 (3) months according to the prescribed daily dose and defined daily dose metrics, respectively. Probabilistic bias analysis results based on validation data suggest that the effect of misclassification is complex, as conventional exposure-outcome association estimates may be of greater or lower magnitude than their misclassification-adjusted values.

CONCLUSIONS

Misclassification should be taken into account in database studies on the safety of prescribed medications. To this aim, investigators should take advantage of external exposure validation data in sensitivity analysis approaches such as ours. Copyright © 2016 John Wiley & Sons, Ltd.

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

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.