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Limitation of inverse probability-of-censoring weights in estimating survival in the presence of strong selection bias.

ABSTRACT: In time-to-event analyses, artificial censoring with correction for induced selection bias using inverse probability-of-censoring weights can be used to 1) examine the natural history of a disease after effective interventions are widely available, 2) correct bias due to noncompliance with fixed or dynamic treatment regimens, and 3) estimate survival in the presence of competing risks. Artificial censoring entails censoring participants when they meet a predefined study criterion, such as exposure to an intervention, failure to comply, or the occurrence of a competing outcome. Inverse probability-of-censoring weights use measured common predictors of the artificial censoring mechanism and the outcome of interest to determine what the survival experience of the artificially censored participants would be had they never been exposed to the intervention, complied with their treatment regimen, or not developed the competing outcome. Even if all common predictors are appropriately measured and taken into account, in the context of small sample size and strong selection bias, inverse probability-of-censoring weights could fail because of violations in assumptions necessary to correct selection bias. The authors used an example from the Multicenter AIDS Cohort Study, 1984-2008, regarding estimation of long-term acquired immunodeficiency syndrome-free survival to demonstrate the impact of violations in necessary assumptions. Approaches to improve correction methods are discussed.

SUBMITTER: Howe CJ

PROVIDER: S-EPMC3105434 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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Limitation of inverse probability-of-censoring weights in estimating survival in the presence of strong selection bias.

Howe Chanelle J CJ Cole Stephen R SR Chmiel Joan S JS Muñoz Alvaro A

American journal of epidemiology 20110202 5

In time-to-event analyses, artificial censoring with correction for induced selection bias using inverse probability-of-censoring weights can be used to 1) examine the natural history of a disease after effective interventions are widely available, 2) correct bias due to noncompliance with fixed or dynamic treatment regimens, and 3) estimate survival in the presence of competing risks. Artificial censoring entails censoring participants when they meet a predefined study criterion, such as exposu ...[more]

PMID: 21289029

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Project description:The goal of this study was to examine what happens to established associations between attention deficit hyperactivity disorder (ADHD) symptoms and cortical surface and thickness regions once we apply inverse probability of censoring weighting (IPCW) to address potential selection bias. Moreover, we illustrate how different factors that predict participation contribute to potential selection bias. Participants were 9- to 11-year-old children from the Generation R study (N = 2707). Cortical area and thickness were measured with magnetic resonance imaging (MRI) and ADHD symptoms with the Child Behavior Checklist. We examined how associations between ADHD symptoms and brain morphology change when we weight our sample back to either follow-up (ages 9-11), baseline (cohort at birth), or eligible (population of Rotterdam at time of recruitment). Weights were derived using IPCW or raking and missing predictors of participation used to estimate weights were imputed. Weighting analyses to baseline and eligible increased beta coefficients for the middle temporal gyrus surface area, as well as fusiform gyrus cortical thickness. Alternatively, the beta coefficient for the rostral anterior cingulate decreased. Removing one group of variables used for estimating weights resulted in the weighted regression coefficient moving closer to the unweighted regression coefficient. In addition, we found considerably different beta coefficients for most surface area regions and all thickness measures when we did not impute missing covariate data. Our findings highlight the importance of using inverse probability weighting (IPW) in the neuroimaging field, especially in the context of mental health-related research. We found that including all variables related to exposure-outcome in the IPW model and combining IPW with multiple imputations can help reduce bias. We encourage future psychiatric neuroimaging studies to define their target population, collect information on eligible but not included participants and use inverse probability of censoring weighting (IPCW) to reduce selection bias.

Project description:BackgroundIn the LATITUDE study (ClinicalTrials.gov, NCT01715285), compared with placebos, abiraterone acetate plus prednisone (AAP) with androgen deprivation therapy (ADT) provided significant overall survival (OS) benefit in high-risk metastatic castration-sensitive prostate cancer (mCSPC) patients. It is controversial whether survival benefits would remain if all patients in the placebo group subsequently received life-extending therapies.ObjectiveTo estimate treatment effect in the case of all patients in the placebo group receiving life-extending subsequent therapies.Design setting and participantsA post hoc analysis of LATITUDE final-analysis data was carried out (setting and participants have been reported previously).InterventionAAP or placebos plus ADT.Outcome measurements and statistical analysisWe applied the inverse probability of censoring weighting (IPCW) method to represent the situation in which all patients in the placebo group would have received life-extending subsequent therapies. The OS hazard ratio (HR) of AAP versus placebos and associated 95% confidence interval (CI) were estimated using a Cox proportional hazards model.Results and limitationsOf the 581 eligible patients in the placebo group, 237 (40.8%) did not receive life-extending subsequent therapies. From the unadjusted intention-to-treat analysis, the HR for OS for AAP versus placebos was 0.661 (95% CI 0.564-0.775). Using IPCW to adjust for patients in the placebo group without life-extending subsequent therapies, the HR was 0.732 (95% CI 0.604-0.887). A limitation is a lack of proof that the Cox proportional hazards model for the absence of life-extending subsequent therapy is correctly specified for the IPCW method.ConclusionsTreatment with AAP exerts OS benefit over placebos in high-risk mCSPC patients, regardless of whether life-extending subsequent therapy is given.Patient summaryIn a previous study, high-risk metastatic castration-sensitive prostate cancer patients who received abiraterone acetate plus prednisone (AAP) with androgen deprivation therapy generally survived longer than those given placebos. The benefit of adding AAP continues regardless of whether life-extending subsequent therapy is given.

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Limitation of inverse probability-of-censoring weights in estimating survival in the presence of strong selection bias.

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Limitation of inverse probability-of-censoring weights in estimating survival in the presence of strong selection bias.

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