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Implications of the Propensity Score Matching Paradox in Pharmacoepidemiology.

ABSTRACT: Recent work has demonstrated that propensity score matching may lead to increased covariate imbalance, even with the corresponding decrease in propensity score distance between matched units. The extent to which this paradoxical phenomenon might harm causal inference in real epidemiologic studies has not been explored. We evaluated the effect of this phenomenon using insurance claims data from the Pharmaceutical Assistance Contract for the Elderly (1999-2002) and Medicaid Analytic eXtract (2000-2007) databases in the United States. For each data set, we created several 1:1 propensity-score-matched data sets by manipulating the size of the covariate set used to generate propensity scores, the index exposure prevalence in the prematched data set, and the matching algorithm. We matched all index units, then progressively pruned matched sets in order of decreasing propensity score distance, calculating covariate imbalance after each pruning. Although covariate imbalance sometimes increased after progressive pruning of matched sets, the application of commonly used propensity score calipers for defining an acceptable match stopped pruning near the lowest region of the imbalance trend and resulted in an improvement over the imbalance in the prematched data set. Thus, propensity score matching does not appear to induce increased covariate imbalance when standard propensity score calipers are applied in these types of pharmacoepidemiologic studies.

SUBMITTER: Ripollone JE

PROVIDER: S-EPMC6118075 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Implications of the Propensity Score Matching Paradox in Pharmacoepidemiology.

Ripollone John E JE Huybrechts Krista F KF Rothman Kenneth J KJ Ferguson Ryan E RE Franklin Jessica M JM

American journal of epidemiology 20180901 9

Recent work has demonstrated that propensity score matching may lead to increased covariate imbalance, even with the corresponding decrease in propensity score distance between matched units. The extent to which this paradoxical phenomenon might harm causal inference in real epidemiologic studies has not been explored. We evaluated the effect of this phenomenon using insurance claims data from the Pharmaceutical Assistance Contract for the Elderly (1999-2002) and Medicaid Analytic eXtract (2000- ...[more]

PMID: 29750409

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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.

Project description:BackgroundLoneliness and unemployment are each detrimental to health and well-being. Recent evidence suggests a potential bidirectional relationship between loneliness and unemployment in working age individuals. As most existing research focuses on the outcomes of unemployment, this paper seeks to understand the impact of loneliness on unemployment, potential interaction with physical health, and assess bidirectionality in the working age population.MethodsThis study utilised data from waves 9 (2017-19) and 10 (2018-2020) of the Understanding Society UK Household Longitudinal Study. Nearest-neighbour probit propensity score matching with at least one match was used to infer causality by mimicking randomisation. Analysis was conducted in three steps: propensity score estimation; matching; and stratification. Propensity scores were estimated controlling for age, gender, ethnicity, education, marital status, household composition, number of own children in household and region. Findings were confirmed in panel data random effect models, and heterogeneous treatment effects assessed by the matching-smoothing method.ResultsExperience of loneliness in at least one wave increased the probability of being unemployed in wave 10 by 17.5 [95%CI: 14.8, 20.2] percentage points. Subgroup analysis revealed a greater effect from sustained than transitory loneliness. Further exploratory analysis identified a positive average treatment effect, of smaller magnitude, for unemployment on loneliness suggesting bidirectionality in the relationship. The impact of loneliness on unemployment was further exacerbated by interaction with physical health.ConclusionsThis is the first study to directly consider the potentially bidirectional relationship between loneliness and unemployment through analysis of longitudinal data from a representative sample of the working age population. Findings reinforce the need for greater recognition of wider societal impacts of loneliness. Given the persisting and potentially scarring effects of both loneliness and unemployment on health and the economy, prevention of both experiences is key. Decreased loneliness could mitigate unemployment, and employment abate loneliness, which may in turn relate positively to other factors including health and quality of life. Thus, particular attention should be paid to loneliness with additional support from employers and government to improve health and well-being.

Dataset Information

Implications of the Propensity Score Matching Paradox in Pharmacoepidemiology.

Publications

Implications of the Propensity Score Matching Paradox in Pharmacoepidemiology.

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