Literature DB >> 32022247

Relapse or reinfection: Classification of malaria infection using transition likelihoods.

Feng-Chang Lin1, Quefeng Li1, Jessica T Lin2.   

Abstract

In patients with Plasmodium vivax malaria treated with effective blood-stage therapy, the recurrent illness may occur due to relapse from latent liver-stage infection or reinfection from a new mosquito bite. Classification of the recurrent infection as either relapse or reinfection is critical when evaluating the efficacy of an anti-relapse treatment. Although one can use whether a shared genetic variant exists between baseline and recurrence genotypes to classify the outcome, little has been suggested to use both sharing and nonsharing variants to improve the classification accuracy. In this paper, we develop a novel classification criterion that utilizes transition likelihoods to distinguish relapse from reinfection. When tested in extensive simulation experiments with known outcomes, our classifier has superior operating characteristics. A real data set from 78 Cambodian P. vivax malaria patients was analyzed to demonstrate the practical use of our proposed method.
© 2020 The International Biometric Society.

Entities:  

Keywords:  Plasmodium vivax; allelic variant; amplicon deep sequencing; malaria relapse; penalized maximum likelihood estimation

Mesh:

Year:  2020        PMID: 32022247      PMCID: PMC8711853          DOI: 10.1111/biom.13226

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  17 in total

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4.  Seasonal variation and high multiplicity of first Plasmodium falciparum infections in children from a holoendemic area in Ghana, West Africa.

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Journal:  Trop Med Int Health       Date:  2006-05       Impact factor: 2.622

5.  Using Amplicon Deep Sequencing to Detect Genetic Signatures of Plasmodium vivax Relapse.

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Journal:  J Infect Dis       Date:  2015-03-06       Impact factor: 5.226

6.  Misclassification of drug failure in Plasmodium falciparum clinical trials in southeast Asia.

Authors:  Jonathan J Juliano; Frederic Ariey; Rithy Sem; Noppadon Tangpukdee; Srivicha Krudsood; Carol Olson; Sornchai Looareesuwan; William O Rogers; Chansuda Wongsrichanalai; Steven R Meshnick
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7.  A general SNP-based molecular barcode for Plasmodium falciparum identification and tracking.

Authors:  Rachel Daniels; Sarah K Volkman; Danny A Milner; Nira Mahesh; Daniel E Neafsey; Daniel J Park; David Rosen; Elaine Angelino; Pardis C Sabeti; Dyann F Wirth; Roger C Wiegand
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8.  Differing patterns of selection and geospatial genetic diversity within two leading Plasmodium vivax candidate vaccine antigens.

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9.  Estimation of the Antirelapse Efficacy of Tafenoquine, Using Plasmodium vivax Genotyping.

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Journal:  J Infect Dis       Date:  2015-10-23       Impact factor: 5.226

10.  Genomic analysis of local variation and recent evolution in Plasmodium vivax.

Authors:  Roberto Amato; Sarah Auburn; Richard D Pearson; Olivo Miotto; Jacob Almagro-Garcia; Chanaki Amaratunga; Seila Suon; Sivanna Mao; Rintis Noviyanti; Hidayat Trimarsanto; Jutta Marfurt; Nicholas M Anstey; Timothy William; Maciej F Boni; Christiane Dolecek; Tinh Tran Hien; Nicholas J White; Pascal Michon; Peter Siba; Livingstone Tavul; Gabrielle Harrison; Alyssa Barry; Ivo Mueller; Marcelo U Ferreira; Nadira Karunaweera; Milijaona Randrianarivelojosia; Qi Gao; Christina Hubbart; Lee Hart; Ben Jeffery; Eleanor Drury; Daniel Mead; Mihir Kekre; Susana Campino; Magnus Manske; Victoria J Cornelius; Bronwyn MacInnis; Kirk A Rockett; Alistair Miles; Julian C Rayner; Rick M Fairhurst; Francois Nosten; Ric N Price; Dominic P Kwiatkowski
Journal:  Nat Genet       Date:  2016-06-27       Impact factor: 38.330

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  3 in total

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3.  COVID-19 diverse outcomes: Aggravated reinfection, type I interferons and antibodies.

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