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Table · dataset · 2026

Supporting Data and Code for Context-Dependent Pharmacovigilance Reporting Phenotypes Across Pulmonary Arterial Hypertension Therapies

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Description

<p dir="ltr"><b>This repository contains supporting derived data, machine-readable tables, analysis materials, and R code associated with the study “Quantifying context dependence of pharmacovigilance reporting phenotypes across pulmonary arterial hypertension therapies: an indication-matched FAERS study.”</b></p><p dir="ltr">The study analyzed publicly available U.S. FDA Adverse Event Reporting System (FAERS) reports accessed through the openFDA Drug Adverse Event resources, with a frozen data cut of 30 June 2026.

The analytic framework used an indication-matched pulmonary arterial hypertension (PAH) reporting universe and evaluated context dependence through conventional disproportionality analyses, sensitivity persistence, sequential persistence, treprostinil route localization, whole-profile reporting divergence, and selected regulatory-time analyses.</p><p dir="ltr">The repository includes derived analytical tables, figure-generation scripts, supplementary analysis scripts, locked inputs where available, quality-control files, manifests, and archived analysis packages used to support the reported results.

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Raw FAERS source records are not redistributed because they remain publicly available from the FDA/openFDA resources.</p><p dir="ltr">Key quantitative outputs include the three-universe sensitivity persistence score (SPS3), five-stage sequential persistence score (PPS5), route localization index (RLI), and reporting-profile divergence analyses across treprostinil administration routes and pharmacologic comparators.</p><p dir="ltr">The deposited materials are intended to facilitate transparency, reproducibility, and independent verification of the reported analyses.

Disproportionality statistics and reporting-profile measures in this repository characterize spontaneous-reporting patterns and should not be interpreted as estimates of incidence, comparative clinical risk, or causality.</p><p dir="ltr"><b>Data cut:</b> 30 June 2026<br><b>Source:</b> FDA Adverse Event Reporting System / openFDA<br><b>Corresponding authors:</b> Kaixun Zhao and Xueqiong Cheng</p>

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figshareoai:figshare.com:article/339548209 d agoJSON v1
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