Effect estimate comparison between the prescription sequence symmetry analysis (PSSA) and parallel group study designs: A systematic review

Idema, Demy L; Wang, Yuanyuan; Biehl, Michael; Horvatovich, Péter

doi:10.1371/journal.pone.0208389

Cited by 6 publications

(6 citation statements)

References 36 publications

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“…They will provide event rates for events resulting in hospital admissions (serious adverse reactions), or that may have therapeutic markers (such as the use of antidepressant drugs to identify depression) using prescription symmetry analysis [85][86][87].…”

Section: Exposure-based Methodsmentioning

confidence: 99%

Pharmacovigilance – The next chapter

et al. 2019

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Section: Exposure-based Methodsmentioning

confidence: 99%

Pharmacovigilance – The next chapter

et al. 2019

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“…Therefore, the influence of confounding might be mitigated with this design, resulting in estimates close to those of the recent meta‐analysis. However, it is also possible that the self‐controlled study design provide more‐conservative estimates than conventional comparator designs, as demonstrated by Idema et al 12 …”

Section: Discussionmentioning

confidence: 99%

“…However, few studies have explicitly compared the utility of the self-controlled study design for pharmacoepidemiological studies without an active comparator medication and that of non-user-comparator cohort study designs when based on a medical information database. 12 This study illustrates the utility of the self-controlled design in pharmacoepidemiological studies by comparing the results of a nonuser-comparator cohort study design and a self-controlled study design. As an example study, we assessed the cardiovascular risk posed by varenicline, a smoking cessation medication used in Japan, among current smokers.…”

Section: Introductionmentioning

confidence: 98%

The utility of the self‐controlled study design for pharmacoepidemiological studies without an active comparator medication using a medical information database: An application to assess the risk of varenicline on cardiovascular outcomes

Yokoyama

Takeuchi

Kumamaru

et al. 2023

Pharmacoepidemiology and Drug

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PurposeTo illustrate the utility of the self‐controlled study design for studies without an active comparator, we compared the results of a cohort design study with a non‐user comparator with those of a self‐controlled design study in evaluating the risk of varenicline on cardiovascular outcomes, using a Japanese medical claims database.MethodsThe participating smokers were identified from health‐screening results collected between May 2008 and April 2017. Using a non‐user‐comparator cohort study design, we estimated the hazard ratios (HRs) and 95% confidence intervals (CIs) of varenicline on initial hospitalization with cardiovascular outcomes using Cox's model adjusted for patients' sex, age, medical history, medication history, and health‐screening results. Using a self‐controlled study design, the within‐subject HR was estimated using a stratified Cox's model adjusted for medical history, medication history, and health‐screening results. The estimate from a recent meta‐analysis was considered the gold standard (risk ratio: 1.03).ResultsWe identified 460 464 smokers (398 694 males [86.6%]; mean (standard deviation) age: 42.9 [10.8] years) in the database. Of these, 11 561 had been dispensed varenicline at least once, and 4511 had experienced cardiovascular outcomes. The estimate of the non‐user‐comparator cohort study design exceeded the gold standard (HR [95% CI]: 2.04 [1.22–3.42]), whereas that of the self‐controlled study design was close to the gold standard (within‐subject HR [95% CI]: 1.12 [0.27–4.70]).ConclusionsThe self‐controlled study design is useful alternative to a non‐user‐comparator cohort design when evaluating the risk of medications relative to their non‐use, based on a medical information database.

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“…The performance of ARM was compared with that of SSA [ 18 , 19 ]. A proof-of-concept study on SSA was published in 1996, and since then the number of SSA-related articles published per year and the total number of articles are on the rise [ 38 , 39 ]. By using SSA, several ADRs associated with a wide array of organs have been identified [ 20 – 22 ].…”

Section: Methodsmentioning

confidence: 99%

Early Detection of Adverse Drug Reaction Signals by Association Rule Mining Using Large-Scale Administrative Claims Data

et al. 2023

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Introduction Adverse drug reactions (ADRs) are a leading cause of mortality worldwide and should be detected promptly to reduce health risks to patients. A data-mining approach using large-scale medical records might be a useful method for the early detection of ADRs. Many studies have analyzed medical records to detect ADRs; however, most of them have focused on a narrow range of ADRs, limiting their usefulness. Objective This study aimed to identify methods for the early detection of a wide range of ADR signals. Methods First, to evaluate the performance in signal detection of ADRs by data-mining, we attempted to create a gold standard based on clinical evidence. Second, association rule mining (ARM) was applied to patient symptoms and medications registered in claims data, followed by evaluating ADR signal detection performance. Results We created a new gold standard consisting of 92 positive and 88 negative controls. In the assessment of ARM using claims data, the areas under the receiver-operating characteristic curve and the precision-recall curve were 0.80 and 0.83, respectively. If the detection criteria were defined as lift > 1, conviction > 1, and p -value < 0.05, ARM could identify 156 signals, of which 90 were true positive controls (sensitivity: 0.98, specificity: 0.25). Evaluation of the capability of ARM with short periods of data revealed that ARM could detect a greater number of positive controls than the conventional analysis method. Conclusions ARM of claims data may be effective in the early detection of a wide range of ADR signals. Supplementary Information The online version contains supplementary material available at 10.1007/s40264-023-01278-4.

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Effect estimate comparison between the prescription sequence symmetry analysis (PSSA) and parallel group study designs: A systematic review

Cited by 6 publications

References 36 publications

Pharmacovigilance – The next chapter

Pharmacovigilance – The next chapter

The utility of the self‐controlled study design for pharmacoepidemiological studies without an active comparator medication using a medical information database: An application to assess the risk of varenicline on cardiovascular outcomes

Early Detection of Adverse Drug Reaction Signals by Association Rule Mining Using Large-Scale Administrative Claims Data

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