Time-window Bias in Case-control Studies

Suissa, Samy; Dell’Aniello, Sophie; Vahey, Sarah; Renoux, Christel

doi:10.1097/ede.0b013e3182093a0f

Cited by 93 publications

(103 citation statements)

References 12 publications

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“…The comparison of these two groups may introduce immortal time bias 17,22,23 . We conducted similar analyses in our data by classifying eligible individuals as initiators if they initiated statin therapy anytime during the first 6 months of follow-up and as non-initiators otherwise.…”

Section: Methodsmentioning

confidence: 99%

Examining Bias in Studies of Statin Treatment and Survival in Patients With Cancer

et al. 2018

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Importance Cancer patients who use statins appear to have a substantially better survival than non-users in observational studies. However, this inverse association between statin use and mortality in cancer patients may be due to selection bias and immortal time bias. Objective We used observational data to emulate a randomized trial of statin initiation that is free of selection bias and immortal time bias. Design We used data on 17,372 cancer patients from the SEER-Medicare 2007-2009 database with complete follow-up until 2011. Individuals were duplicated, with each replicate assigned to either the strategy “statin initiation within 6 months of diagnosis” or “no statin initiation”. Replicates were censored when they stopped following their assigned strategy, and the potential selection bias was adjusted for via inverse-probability weighting. Hazard ratios (HR), cumulative incidences, and risk differences were calculated for all-cause mortality and cancer-specific mortality. We then compared our estimates with those obtained using the same analytic approaches as in previous observational studies. Setting The SEER-Medicare data is a linkage between 17 American cancer registries and claims files from Medicare and Medicaid in 12 states. Participants We included individuals with a new diagnosis of colorectal, breast, prostate, and bladder cancer who had not been prescribed statins for at least 6 months before cancer. Exposure Statin initiation within 6 months from cancer diagnosis. Main outcome measure Cancer-specific and all-cause mortality. Results The adjusted HR (95% CI) comparing statin initiation vs. no initiation was 1.00 (0.88-1.15) for cancer-specific mortality and 1.07 (0.93-1.21) for overall mortality. Cumulative incidence curves for each group were almost overlapping. On the contrary, the methods used by prior studies resulted in a strong inverse association between statin use and mortality. Conclusion and relevance After using methods that are not susceptible to selection bias from prevalent users and to immortal time bias, initiation of statins within 6 months of cancer diagnosis did not appear to improve 3-year cancer-specific or overall survival.

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Section: Methodsmentioning

confidence: 99%

Examining Bias in Studies of Statin Treatment and Survival in Patients With Cancer

et al. 2018

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“…If this condition is not met, the 'time-window bias', an error that is still frequent in observational research, will usually result in a biased estimate of the exposure effect. 2 In clinical practice, medication non-adherence is one of the main factors that reduce the effectiveness of drug therapies; 1 therefore, the aim of this study was to evaluate the impact of the time-window bias when the exposure is a measure of medication adherence. In this setting, we found that this bias produces an underestimate of the beneficial effect of good medication adherence that conforms to clinical guidelines.…”

Section: Discussionmentioning

confidence: 99%

“…3 This method assigns the same length of observation to cases and to their matched controls to ensure equal time windows to measure exposure. 2 No studies have measured how the time-window bias affects assessments of the effect of medication adherence on health outcomes.…”

Section: Introductionmentioning

confidence: 99%

The impact of time-window bias on the assessment of the long-term effect of medication adherence: the case of secondary prevention after myocardial infarction

Martino¹,

Kirchmayer²,

Agabiti³

et al. 2015

BMJ Open

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ObjectivesTime-window bias was described in case–control studies and led to a biased estimate of drug effect. No studies have measured the impact of this bias on the assessment of the effect of medication adherence on health outcomes. Our goals were to estimate the association between adherence to drug therapies after myocardial infarction (MI) and the incidence of a new MI, and to quantify the error that would have been produced by a time-window bias.SettingThis is a population-based study. Data were obtained from the Regional Health Information Systems of the Lazio Region in Central Italy (around 5 million inhabitants).ParticipantsPatients discharged after MI in 2006–2007 were enrolled in the cohort and followed through 2009.Outcome measureThe study outcome was reinfarction: either mortality, or hospital admission for MI, whichever occurred first.DesignA nested case–control study was performed. Controls were selected using both time-dependent and time-independent sampling. Adherence to antiplatelets, β-blockers, ACE inhibitors/angiotensin receptor blockers (ACEI/ARBs) and statins was calculated using the proportion of days covered (PDC).ResultsA total of 6880 patients were enrolled in the cohort. Using time-dependent sampling, a protective effect was detected for all study drugs. Conversely, using time-independent sampling, the beneficial effect was attenuated, as in the case of antiplatelet agents and statins, or completely masked, as in the case of ACEI/ARBs and β-blockers. For ACEI/ARBs, the time-dependent approach produced ORs of 0.83 (95% CI 0.57 to 1.21) and 0.72 (0.55 to 0.95), respectively, for ‘0.50.75’ versus ‘0≤PDC≤0.5’. Using the time-independent approach, the ORs were 0.96 (0.65 to 1.43) and 1.00 (0.76 to 1.33), respectively.ConclusionsA time-independent definition of a time-dependent exposure introduces a bias when the length of follow-up varies with the outcome. The persistence of time-related biases in peer-reviewed papers strongly suggests the need for increased awareness of this methodological pitfall.

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“…Therefore, studies that compare long-acting insulin analogs to nonbasal insulin may introduce confounding by disease duration. Time-window bias occurs when the opportunity for exposure differs between case subjects and control subjects (29,43).…”

Section: Data Extraction and Quality Assessmentmentioning

confidence: 99%

Effect of Long-Acting Insulin Analogs on the Risk of Cancer: A Systematic Review of Observational Studies

Filion

Azoulay

et al. 2016

Diabetes Care

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OBJECTIVEObservational studies examining the association between long-acting insulin analogs and cancer incidence have produced inconsistent results. We conducted a systematic review of these studies, focusing on their methodological strengths and weaknesses. RESEARCH DESIGN AND METHODSWe systematically searched MEDLINE and EMBASE from 2000 to 2014 to identify all observational studies evaluating the relationship between the long-acting insulin analogs and the risk of any and site-specific cancers (breast, colorectal, prostate). We included cohort and case-control studies published in English on insulin glargine and detemir and any cancer incidence among patients with type 1 or 2 diabetes. The methodological assessment involved the inclusion of prevalent users, inclusion of lag periods, time-related biases, and duration of follow-up between insulin initiation and cancer incidence. RESULTSA total of 16 cohort and 3 case-control studies met our inclusion criteria. All studies evaluated insulin glargine, and four studies also examined insulin detemir. Follow-up ranged from 0.9 to 7.0 years. Thirteen of 15 studies reported no association between insulin glargine and detemir and any cancer. Four of 13 studies reported an increased risk of breast cancer with insulin glargine. In the quality assessment, 7 studies included prevalent users, 11 did not consider a lag period, 6 had time-related biases, and 16 had short (<5 years) follow-up. CONCLUSIONSThe observational studies examining the risk of cancer associated with long-acting insulin analogs have important methodological shortcomings that limit the conclusions that can be drawn. Thus, uncertainty remains, particularly for breast cancer risk.NPH insulin has been the mainstay treatment for type 1 diabetes and advanced type 2 diabetes since the 1950s. However, this insulin is associated with an increased risk of nocturnal hypoglycemia, and its relatively short half-life requires frequent administration (1,2). Consequently, structurally modified insulins, known as longacting insulin analogs (glargine and detemir), were developed in the 1990s to circumvent these limitations. However, there are concerns that long-acting insulin

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Time-window Bias in Case-control Studies

Cited by 93 publications

References 12 publications

Examining Bias in Studies of Statin Treatment and Survival in Patients With Cancer

Examining Bias in Studies of Statin Treatment and Survival in Patients With Cancer

The impact of time-window bias on the assessment of the long-term effect of medication adherence: the case of secondary prevention after myocardial infarction

Effect of Long-Acting Insulin Analogs on the Risk of Cancer: A Systematic Review of Observational Studies

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