Evidence map›Paper›PMID 41510438›Full record

ArticleCureus2025

Comparative Real-World Safety Profiles of Six Selective Serotonin Reuptake Inhibitors: A Global Pharmacovigilance Analysis.

Adrian Chin Yan Chan

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Adrian Chin Yan ChanGlobal Safety, Bayer Pharmaceuticals, Beijing, CHN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Selective serotonin reuptake inhibitors (SSRIs) represent the cornerstone of modern antidepressant therapy, yet critical knowledge gaps persist regarding their comparative real-world safety profiles. This evidence deficit has profound implications for clinical decision-making and patient outcomes. Methods We conducted a comprehensive pharmacovigilance analysis utilizing VigiBase, the WHO global database of individual case safety reports, encompassing over 342,000 reports for six major SSRIs (sertraline, fluoxetine, paroxetine, citalopram, escitalopram, and fluvoxamine). Disproportionality analysis using information component (IC) values was performed across seven clinically relevant safety domains: anticholinergic effects, sexual dysfunction, metabolic effects, extrapyramidal symptoms, sleep disturbances, withdrawal syndrome, and cardiac conduction abnormalities. Results Significant heterogeneity in safety profiles was observed among SSRIs, with clear correlations between pharmacodynamic properties and adverse event patterns. Paroxetine demonstrated the highest rates of anticholinergic effects, sexual dysfunction, weight gain, and withdrawal syndrome, correlating with its high muscarinic M1 receptor binding affinity (Ki = 108 nM). Citalopram showed elevated cardiac conduction abnormalities, while fluoxetine exhibited increased extrapyramidal symptoms. A strong inverse relationship was observed between SSRI half-life and withdrawal syndrome reporting. Conclusions This analysis reveals that SSRIs exhibit distinct safety profiles that correlate with their pharmacodynamic properties, challenging the traditional view of these medications as a homogeneous therapeutic class. These findings support precision prescribing approaches based on individual patient risk factors and provide mechanistic insights for evidence-based SSRI selection.

Indexed as

adverse drug reactionspharmacodynamicspharmacovigilanceprecision medicineselective serotonin reuptake inhibitors

Identifiers

PMID41510438
PMCPMC12775886

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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.