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A brief introduction to propensity score for anesthesiologists.

ABSTRACT: Intergroup comparability is of paramount importance in clinical research since it is impossible to draw conclusions on a treatment if populations with different characteristics are compared. While an adequate randomization process in randomized controlled trials (RCTs) ensures a balanced distribution of subjects between groups, the distribution in observational prospective and retrospective studies may be influenced by many confounders.
Propensity score (PS) is a statistical technique that was developed more than 30 years ago with the purpose of estimating the probability to be assigned to a group. Once evaluated, the PS could be used to adjust and balance the groups using different methods such as matching, stratification, covariate adjustment, and weighting. The validity of PS is strictly related to the confounders used in the model, and confounders that are either not identified or not available will produce biases in the results. RCTs will therefore continue to provide the highest quality of evidence, but PS allows fine adjustments on otherwise unbalanced groups, which will increase the strength and quality of observational studies.

SUBMITTER: De Cassai A

PROVIDER: S-EPMC7403107 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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A brief introduction to propensity score for anesthesiologists.

De Cassai Alessandro A Andreatta Giulio G Boscolo Annalisa A Munari Marina M Navalesi Paolo P

Korean journal of anesthesiology 20200402 4

Intergroup comparability is of paramount importance in clinical research since it is impossible to draw conclusions on a treatment if populations with different characteristics are compared. While an adequate randomization process in randomized controlled trials (RCTs) ensures a balanced distribution of subjects between groups, the distribution in observational prospective and retrospective studies may be influenced by many confounders.<br/> Propensity score (PS) is a statistical technique that ...[more]

PMID: 32238789

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Project description:BackgroundThe diagnostic process is a key element of medicine but it is complex and prone to errors. Infectious diseases are one of the three categories of diseases in which diagnostic errors can be most harmful to patients. In this study we aimed to estimate the effect of initial misdiagnosis of the source of infection in patients with bacteraemia on 14 day mortality using propensity score methods to adjust for confounding.MethodsData from a previously described longitudinal cohort of patients diagnosed with monobacterial bloodstream infection (BSI) at the Leiden University Medical Centre (LUMC) between 2013 and 2015 were used. Propensity score matching and inversed probability of treatment weighting (IPTW) were applied to correct for confounding. The average treatment effect on the treated (ATT), which in this study was the average effect of initial misdiagnosis on the misdiagnosed (AEMM), was estimated. Methodological issues that were encountered when applying propensity score methods were addressed by performing additional sensitivity analyses. Sensitivity analyses consisted of varying caliper in propensity score matching and using different truncated weights in inversed probability of treatment weighting.ResultsData of 887 patients were included in the study. Propensity scores ranged between 0.015 and 0.999 and 80 patients (9.9%) had a propensity score > 0.95. In the matched analyses, 35 of the 171 misdiagnosed patients died within 14 days (20.5%), versus 10 of the 171 correctly diagnosed patients (5.8%), yielding a difference of 14.6% (7.6%; 21.6%). In the total group of patients, the observed percentage of patients with an incorrect initial diagnosis that died within 14 days was 19.8% while propensity score reweighting estimated that their probability of dying would have been 6.5%, if they had been correctly diagnosed (difference 13.3% (95% CI 6.9%;19.6%)). After adjustment for all variables that showed disbalance in the propensity score a difference of 13.7% (7.4%; 19.9%) was estimated. Sensitivity analyses yielded similar results. However, performing weighted analyses without truncation yielded unstable results.ConclusionThus, we observed a substantial increase of 14 day mortality in initially misdiagnosed patients. Furthermore, several patients received propensity scores extremely close to one and were almost sure to be initially misdiagnosed.

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A brief introduction to propensity score for anesthesiologists.

Publications

A brief introduction to propensity score for anesthesiologists.

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