Imunogenisitas, Keamanan, dan Efikasi Vaksin Malaria: Tinjauan Sistematis dan Network Meta-Analysis dari Uji Klinis Acak Terkontrol

Malaria remains a major global health issue, with challenges in existing control methods like insecticide resistance and artemisinin-based therapy failures. Vaccines offer a promising solution to reduce transmission, build herd immunity, and decrease morbidity and mortality, especially in vulnerable populations. This study conducts a network meta-analysis of malaria vaccines to compare their immunogenicity, safety, and efficacy. A systematic review following PRISMA-NMA guidelines was performed using four databases—PubMed, Cochrane Library, ScienceDirect, and Google Scholar—assessing study quality with the Cochrane Risk of Bias 2.0 tool. The analysis, which included over 33,000 participants from 57 clinical trials, revealed that RTS,S/AS01 and RTS,S/AS02 significantly increased antibody titers despite heterogeneity. Safety outcomes showed RTS,S/AS02 and FMP1/AS02 were linked to increased injection site pain, and RTS,S vaccines had a higher risk of fever. R21/Matrix-M showed the highest efficacy in preventing clinical malaria episodes, though data on it were limited. Vaccines like PfSPZ and PvCS had fewer side effects but weaker antibody responses. Overall, RTS,S vaccines were highly immunogenic and effective, though safety profiles varied, and the limited data on certain vaccines like R21/Matrix-M underscored the need for further research to validate their long-term effects.

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Publication Details

Journal
ASPIRATOR - Journal of Vector-borne Disease Studies
Published
2025-06-30
DOI
https://doi.org/10.58623/aspirator.v16i1.114
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Imunogenisitas, Keamanan, dan Efikasi Vaksin Malaria: Tinjauan Sistematis dan Network Meta-Analysis dari Uji Klinis Acak Terkontrol

Bagus Hermansyah, Dini Agustina, Fitranda Kusiyanto Taslim, Vania Yuli Rahmantia
ASPIRATOR - Journal of Vector-borne Disease Studies
Computational Drug Discovery Methods
article

Imunogenisitas, Keamanan, dan Efikasi Vaksin Malaria: Tinjauan Sistematis dan Network Meta-Analysis dari Uji Klinis Acak Terkontrol

Bagus Hermansyah, Dini Agustina, Fitranda Kusiyanto Taslim, Vania Yuli Rahmantia
article en

Abstract

Malaria remains a major global health issue, with challenges in existing control methods like insecticide resistance and artemisinin-based therapy failures. Vaccines offer a promising solution to reduce transmission, build herd immunity, and decrease morbidity and mortality, especially in vulnerable populations. This study conducts a network meta-analysis of malaria vaccines to compare their immunogenicity, safety, and efficacy. A systematic review following PRISMA-NMA guidelines was performed using four databases—PubMed, Cochrane Library, ScienceDirect, and Google Scholar—assessing study quality with the Cochrane Risk of Bias 2.0 tool. The analysis, which included over 33,000 participants from 57 clinical trials, revealed that RTS,S/AS01 and RTS,S/AS02 significantly increased antibody titers despite heterogeneity. Safety outcomes showed RTS,S/AS02 and FMP1/AS02 were linked to increased injection site pain, and RTS,S vaccines had a higher risk of fever. R21/Matrix-M showed the highest efficacy in preventing clinical malaria episodes, though data on it were limited. Vaccines like PfSPZ and PvCS had fewer side effects but weaker antibody responses. Overall, RTS,S vaccines were highly immunogenic and effective, though safety profiles varied, and the limited data on certain vaccines like R21/Matrix-M underscored the need for further research to validate their long-term effects.

ASPIRATOR - Journal of Vector-borne Disease StudiesVol. 16(1)
Universitas Jember (ID)
Openalex Percentile: Top 80%
Computational Drug Discovery Methods
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Imunogenisitas, Keamanan, dan Efikasi Vaksin Malaria: Tinjauan Sistematis dan Network Meta-Analysis dari Uji Klinis Acak Terkontrol — Bagus Hermansyah, Dini Agustina, et al. · ASPIRATOR - Journal of Vector-borne Disease Studies (2025) | TGRS Research Map | TGRS