자료유형  

 학위논문

Control Number  

0016932876

International Standard Book Number  

9798379867829

Dewey Decimal Classification Number  

600

Main Entry-Personal Name  

Chen, Xinyun.

Publication, Distribution, etc. (Imprint  

[S.l.] : University of Pittsburgh., 2022

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2022

Physical Description  

1 online resource(66 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

General Note  

Advisor: Kirisci, Levent;Kane-Gill, Sandra L.

Dissertation Note  

Thesis (M.Sc.)--University of Pittsburgh, 2022.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약The COVID-19 pandemic is one of the most serious health crises throughout the human history. With countless efforts of drug development and repurposing by the scientific community in a hope of finding safe and efficacious COVID-19 treatment, there is an emerging need for pharmacovigilance for these drugs indicated for COVID-19 treatment. For new drugs, clinical trials can only give limited knowledge about drug safety profiles which are not enough to guide the use of the drugs in large populations. Thus, potential risks of these drugs need to be quickly identified from data sources outside clinical trials. For repurposed drugs, change of indication may lead to unforeseeable risks even for drugs with well-established safety profiles. Thus, adverse events with elevated risks for repurposed drugs also need to be identified. This study set the aim of exploring the power of disproportionality analysis in extracting adverse drug reaction information from spontaneous reporting data to satisfy the pharmacovigilance need. For new drugs, the potential of identifying adverse reactions with limited report data was explored. For repurposed drugs, we focused on whether increase in disproportionality scores can be used to identify adverse drug events with elevated risks during the pandemic. The FDA Adverse Event Reporting System (FAERS) database was utilized, and the performance of two disproportionality scores ─ information component (IC) and reporting odds ratio (ROR) in signal detection and ranking were evaluated and compared. As a result, we found similar and seemingly plausible signal detection by both IC and ROR for a new drug Remdesivir. For repurposed drugs, we found that increase in IC and fold increase in ROR generally give plausible and comparable performance in signal detection and rankings especially for drug-adverse event combinations with large number of observations. This study explored the potentials of disproportionality analysis on identifying potential health risks for both new and repurposed drugs during the COVID-19 pandemic, which had lasting significance in case of a future public health crisis.

Subject Added Entry-Topical Term  

Infections.

Subject Added Entry-Topical Term  

COVID-19 vaccines.

Subject Added Entry-Topical Term  

Software packages.

Subject Added Entry-Topical Term  

Medical personnel.

Subject Added Entry-Topical Term  

Contingency tables.

Subject Added Entry-Topical Term  

Prescription drugs.

Subject Added Entry-Topical Term  

Pharmacovigilance.

Subject Added Entry-Topical Term  

Medical errors.

Subject Added Entry-Topical Term  

Drug dosages.

Subject Added Entry-Topical Term  

Sensitivity analysis.

Subject Added Entry-Topical Term  

Pandemics.

Subject Added Entry-Topical Term  

Clinical trials.

Subject Added Entry-Topical Term  

Severe acute respiratory syndrome.

Subject Added Entry-Topical Term  

Product safety.

Subject Added Entry-Topical Term  

Probability.

Subject Added Entry-Topical Term  

Coronaviruses.

Subject Added Entry-Topical Term  

Markov analysis.

Subject Added Entry-Topical Term  

Pharmaceutical sciences.

Added Entry-Corporate Name  

University of Pittsburgh.

Host Item Entry  

Dissertations Abstracts International. 85-01B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:641921