Evidence map›Paper›PMID 42286536›Full record

ArticleBMC infectious diseases2026

Adverse events associated with candida infections in secukinumab treatment.

Chongli Yu, Tian Ma, Nan Wu, Chengxin Li, Rui Wang

Abstract read
In one paragraph

Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Chongli YuSchool of Medicine, Nankai University, Tianjin, 300071, China.
Tian MaDepartment of Dermatology, Fourth Medical Centre of Chinese PLA General Hospital, 51 Fucheng Rd, Beijing, 100089, China.
Nan WuDepartment of Dermatology, First Medical Centre of Chinese PLA General Hospital, 28 Fuxing Rd, Beijing, 100853, China.
Chengxin LiSchool of Medicine, Nankai University, Tianjin, 300071, China. chengxinderm@163.com.
Rui WangDepartment of Dermatology, First Medical Centre of Chinese PLA General Hospital, 28 Fuxing Rd, Beijing, 100853, China. wangruiderm@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSecukinumab, an interleukin-17 A inhibitor widely used in psoriasis and related disorders, has been linked to opportunistic infections. Candida infections are a key safety concern, yet their real-world clinical profiles, risk distribution, and onset patterns remain insufficiently characterized.

objectivesTo evaluate the clinical characteristics, severity, onset patterns, and risk factors of Candida infections associated with secukinumab, thereby informing risk stratification and patient management.

methodsA retrospective pharmacovigilance analysis was performed using the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) from Q1 2004 to Q1 2025. Secukinumab reports were retrieved, and Candida-related adverse events were identified using a predefined Candida-specific MedDRA Preferred Term dictionary. Disproportionality analyses were conducted using reporting odds ratios (RORs) with 95% confidence intervals (CIs). Event severity, subgroup characteristics, and time-to-onset were assessed, and Weibull shape parameter modeling was used to characterize risk patterns.

resultsWe identified 1,075 Candida events (0.8% of all secukinumab reports). Oral, esophageal, and vulvovaginal candidiasis predominated. All eight focal PTs showed significant disproportionality, with genital candidiasis yielding the strongest signal (ROR 19.85; 95% CI 12.91-30.53). Over half of events met criteria for serious outcomes. Stronger reporting signals were observed in females and adults aged 18-64 years. Median onset was 2-3 months, and Weibull β < 1 indicated an early-failure pattern, suggesting heightened risk shortly after treatment initiation.

conclusionsCandida infections during secukinumab therapy are uncommon but often severe, particularly in defined high-risk groups. Early onset highlights the importance of vigilant monitoring during initial treatment months. Real-world pharmacovigilance remains essential for optimizing biologic safety. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Antibodies, Monoclonal, HumanizedCandidiasisAdolescentAdultAdverse Drug Reaction Reporting SystemsAgedFemaleHumansMaleMiddle AgedPharmacovigilancePsoriasisRetrospective StudiesRisk FactorsUnited StatesYoung AdultAntibodies, Monoclonal, HumanizedsecukinumabBiologicsCandidaDisproportionalityFAERSPharmacovigilanceSecukinumabTime-to-onset

Identifiers

PMID42286536
PMCPMC13491659

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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.