Evidence map›Paper›PMID 38099939›Full record

ArticleEuropean journal of clinical pharmacology2024

Safety analysis of therapeutic drugs for breast cancer patients and construction of a predictive model for serious adverse drug reactions.

Shuzhi Lin, Shuang Lei, Wei Liu, Xiaoying Zhu, Biqi Ren, Bianling Feng

Abstract read
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In one paragraph

Article in European journal of clinical pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
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

6 authors at 1 institution in 1 country.

Shuzhi LinThe Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Shuang LeiThe Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Wei LiuThe Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Xiaoying ZhuThe Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Biqi RenThe Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Bianling FengThe Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, China. fengbianling@163.com.ORCID http://orcid.org/0000-0003-1937-7951
Xi'an Jiaotong University · CN

Funding

National Social Science Foundation of China 18XGL019
6 · The paper itself

Abstract

objectivesTo explore the characteristics of the occurrence of antineoplastic drug adverse reactions (ADRs) in breast cancer and to utilize a computerized tool to identify early warning indicators of potentially serious ADRs.

methodsWe conducted descriptive statistical analyses of the demographic features, medication use characteristics, and clinical manifestations of suspected ADRs in ADR-exposed patients using data from the Shaanxi Provincial Adverse Drug Reaction Monitoring Center, China, from 2017 to 2021. Using disproportionality methods (reporting odds ratio, proportional reporting ratio, and comprehensive standard method), the relationship between drugs and ADRs was measured. Finally, a web-based clinical prediction model for serious ADRs based on binary logistic regression was developed to estimate individual event probabilities numerically.

resultsWe developed a new computer-mineable breast cancer-ADR system. In total, 1119 ADR reports were received between 2017 and 2021, with an increasing trend in the number. Antineoplastic medications of natural sources made up the greatest portion of the drug category (530, 38.10%) while targeted drugs' part increased with time. The medicine with the greatest number of ADR cases was docetaxel. Bone marrow failure was the most reported ADR. The disproportionality methods produced 19 signals of disproportionate reporting, two signals of disproportionate reporting were unknown ADRs. The occurrence of serious ADRs was shown to be substantially correlated with gender, platinum drugs, and blood and lymphatic system disorders. The clinical prediction model for serious ADRs had above-moderate discriminatory power (C-index was 0.775).

conclusionsThe number of ADRs to breast cancer antineoplastic drugs was constantly increasing, with docetaxel ranking first, with the majority of ADRs presenting as bone marrow suppression, nausea, and vomiting. Data mining identified 19 signals of disproportionate reporting.

Indexed as

Antineoplastic AgentsBreast NeoplasmsDrug-Related Side Effects and Adverse ReactionsAdverse Drug Reaction Reporting SystemsDocetaxelFemaleHumansModels, StatisticalPharmacovigilancePrognosisAntineoplastic AgentsDocetaxelAdverse drug reactionsA prediction modelBreast cancerDrug safetyPharmacovigilance

Identifiers

PMID38099939
OpenAlexW4389794049

What OpenQuestion holds

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Registered trials

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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.