Evidence map›Paper›PMID 35789689›Full record

ArticleClinical epidemiology2022

A Real-World Disproportionality Analysis of Olaparib: Data Mining of the Public Version of FDA Adverse Event Reporting System.

Yamin Shu, Xucheng He, Yanxin Liu, Pan Wu, Qilin Zhang

Open access · goldAbstract read
In one paragraph

Article in Clinical epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 2 pooled it
14.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

93 citing papers in PubMed, 2 syntheses or guidelines pooled it, 150 citations in OpenAlex.

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  4. Disproportionality analysis of adverse events associated with degarelix: a real-world study from the FDA Adverse Event Reporting System (FAERS) database.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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33 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 5 institutions in 1 country.

Yamin ShuDepartment of Pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.ORCID 0000-0002-1532-8135
Xucheng HeDepartment of Pharmacy, Pengzhou Second People's Hospital, Pengzhou, People's Republic of China.
Yanxin LiuDepartment of Pharmacy, Pengzhou People's Hospital, Pengzhou, People's Republic of China.
Pan WuDepartment of Pharmacy, Qionglai Maternal & Child Health and Family Planning Service Center, Qionglai, People's Republic of China.
Qilin ZhangDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Health and Family Planning Commission of Sichuan Province · CNPeople's Hospital of Cangzhou · CNTaizhou Second People's Hospital · CNTongji Hospital · CNUnion Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Olaparib, the world's first poly ADP-ribose polymerase (PARP) inhibitor (PARPi), has been approved for treatment of ovarian cancer, breast cancer, pancreatic cancer and prostate cancer by FDA. The current study was to assess olaparib-related adverse events (AEs) of real-world through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN) and the multi-item gamma Poisson shrinker (MGPS) algorithms were employed to quantify the signals of olaparib-associated AEs. Results: Out of 8,450,009 reports collected from the FAERS database, 6402 reports of olaparib-associated AEs were identified. A total of 118 significant disproportionality preferred terms (PTs) conforming to the four algorithms simultaneously were retained. The most common AEs included anemia, thrombocytopenia, nausea, decreased appetite, blood creatinine increased and dermatomyositis, which were corresponding to those reported in the specification and clinical trials. Unexpected significant AEs as interstitial lung disease, Conclusion: Results of our study were consistent with clinical observations, and we also found potential new and unexpected AEs signals for olaparib, suggesting prospective clinical studies were needed to confirm these results and illustrate their relationship. Our results could provide valuable evidence for further safety studies of olaparib.

Indexed as

data miningFAERSolaparibPARP inhibitorpharmacovigilance

Identifiers

PMID35789689
PMCPMC9250344
OpenAlexW4283662007

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.