Uncertain outcomes: adjusting for misclassification in antimalarial efficacy studies
Evaluation of antimalarial efficacy is difficult because recurrent parasitaemia can be due to recrudescence or re-infection. PCR is used to differentiate between recrudescences and re-infections by comparing parasite allelic variants before and after treatment. However, PCR-corrected results are sus...
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| Veröffentlicht in: | Epidemiology and infection 2011-04, Vol.139 (4), p.544-551 |
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| creator | PORTER, K. A. BURCH, C. L. POOLE, C. JULIANO, J. J. COLE, S. R. MESHNICK, S. R. |
| description | Evaluation of antimalarial efficacy is difficult because recurrent parasitaemia can be due to recrudescence or re-infection. PCR is used to differentiate between recrudescences and re-infections by comparing parasite allelic variants before and after treatment. However, PCR-corrected results are susceptible to misclassification: false positives, due to re-infection by the same variant present in the patient before treatment; and false negatives, due to variants that are present but too infrequent to be detected in the pre-treatment PCR, but are then detectable post-treatment. This paper aimed to explore factors affecting the probability of false positives and proposes a Monte Carlo uncertainty analysis to account for both types of misclassification. Higher levels of transmission intensity, increased multiplicity of infection, and limited allelic variation resulted in more false recrudescences. The uncertainty analysis exploits characteristics of study data to minimize bias in the estimate of efficacy and can be applied to areas of different transmission intensity. |
| doi_str_mv | 10.1017/S0950268810001652 |
| format | Article |
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A. ; BURCH, C. L. ; POOLE, C. ; JULIANO, J. J. ; COLE, S. R. ; MESHNICK, S. R.</creator><creatorcontrib>PORTER, K. A. ; BURCH, C. L. ; POOLE, C. ; JULIANO, J. J. ; COLE, S. R. ; MESHNICK, S. R.</creatorcontrib><description>Evaluation of antimalarial efficacy is difficult because recurrent parasitaemia can be due to recrudescence or re-infection. PCR is used to differentiate between recrudescences and re-infections by comparing parasite allelic variants before and after treatment. However, PCR-corrected results are susceptible to misclassification: false positives, due to re-infection by the same variant present in the patient before treatment; and false negatives, due to variants that are present but too infrequent to be detected in the pre-treatment PCR, but are then detectable post-treatment. This paper aimed to explore factors affecting the probability of false positives and proposes a Monte Carlo uncertainty analysis to account for both types of misclassification. Higher levels of transmission intensity, increased multiplicity of infection, and limited allelic variation resulted in more false recrudescences. The uncertainty analysis exploits characteristics of study data to minimize bias in the estimate of efficacy and can be applied to areas of different transmission intensity.</description><identifier>ISSN: 0950-2688</identifier><identifier>EISSN: 1469-4409</identifier><identifier>DOI: 10.1017/S0950268810001652</identifier><identifier>PMID: 20619072</identifier><identifier>CODEN: EPINEU</identifier><language>eng</language><publisher>Cambridge: Cambridge University Press</publisher><subject>Antimalarials ; Antimalarials - administration & dosage ; Antiparasitic agents ; Biological and medical sciences ; Biomedical Research - methods ; False negative errors ; False positive errors ; False Positive Reactions ; Fundamental and applied biological sciences. Psychology ; Humans ; Infections ; Infectious diseases ; Malaria ; Malaria - drug therapy ; Medical cures ; Microbiology ; Normal distribution ; Parasitology - methods ; Patients ; Polymerase chain reaction ; Polymerase Chain Reaction - methods ; Probabilities ; Probability ; Recurrence ; Relapse ; Sampling errors ; Treatment Outcome</subject><ispartof>Epidemiology and infection, 2011-04, Vol.139 (4), p.544-551</ispartof><rights>2011 Cambridge University Press</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © Cambridge University Press 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c509t-e3f249ef20fb1a8b7f61e3807e1c51ca8368fc229ea3e2ae9c02935a061412733</citedby><cites>FETCH-LOGICAL-c509t-e3f249ef20fb1a8b7f61e3807e1c51ca8368fc229ea3e2ae9c02935a061412733</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/27975624$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/27975624$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,315,728,781,785,804,886,27926,27927,53793,53795,58019,58252</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23952904$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20619072$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>PORTER, K. A.</creatorcontrib><creatorcontrib>BURCH, C. L.</creatorcontrib><creatorcontrib>POOLE, C.</creatorcontrib><creatorcontrib>JULIANO, J. J.</creatorcontrib><creatorcontrib>COLE, S. R.</creatorcontrib><creatorcontrib>MESHNICK, S. R.</creatorcontrib><title>Uncertain outcomes: adjusting for misclassification in antimalarial efficacy studies</title><title>Epidemiology and infection</title><addtitle>Epidemiol Infect</addtitle><description>Evaluation of antimalarial efficacy is difficult because recurrent parasitaemia can be due to recrudescence or re-infection. PCR is used to differentiate between recrudescences and re-infections by comparing parasite allelic variants before and after treatment. However, PCR-corrected results are susceptible to misclassification: false positives, due to re-infection by the same variant present in the patient before treatment; and false negatives, due to variants that are present but too infrequent to be detected in the pre-treatment PCR, but are then detectable post-treatment. This paper aimed to explore factors affecting the probability of false positives and proposes a Monte Carlo uncertainty analysis to account for both types of misclassification. Higher levels of transmission intensity, increased multiplicity of infection, and limited allelic variation resulted in more false recrudescences. The uncertainty analysis exploits characteristics of study data to minimize bias in the estimate of efficacy and can be applied to areas of different transmission intensity.</description><subject>Antimalarials</subject><subject>Antimalarials - administration & dosage</subject><subject>Antiparasitic agents</subject><subject>Biological and medical sciences</subject><subject>Biomedical Research - methods</subject><subject>False negative errors</subject><subject>False positive errors</subject><subject>False Positive Reactions</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Humans</subject><subject>Infections</subject><subject>Infectious diseases</subject><subject>Malaria</subject><subject>Malaria - drug therapy</subject><subject>Medical cures</subject><subject>Microbiology</subject><subject>Normal distribution</subject><subject>Parasitology - methods</subject><subject>Patients</subject><subject>Polymerase chain reaction</subject><subject>Polymerase Chain Reaction - methods</subject><subject>Probabilities</subject><subject>Probability</subject><subject>Recurrence</subject><subject>Relapse</subject><subject>Sampling errors</subject><subject>Treatment Outcome</subject><issn>0950-2688</issn><issn>1469-4409</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkctrVDEYxYModhz9A1woF0FcXc370YUgxRcUXNiuwzeZpGa4k9QkV-h_by4ztj4WrrI4v-9wTg5CTwl-TTBRb75iIzCVWhOMMZGC3kMrwqUZOcfmPlot8rjoJ-hRrbsOGarVQ3RCsSQGK7pCF5fJ-dIgpiHPzeW9r6cDbHdzbTFdDSGXYR-rm6DWGKKDFnMaOgypxT1MUCJMgw-L5G6G2uZt9PUxehBgqv7J8V2jyw_vL84-jedfPn4-e3c-OoFNGz0LlBsfKA4bAnqjgiSeaaw8cYI40Ezq4Cg1Hpin4I3D1DABPTwnVDG2Rm8PvtfzZu-3zqdWYLLXpUcrNzZDtH8qKX6zV_mH5Zr2-qobvDoalPx99rXZpayfJkg-z9VqaYRSSuj_k0JyLGXPt0Yv_iJ3eS6p_8MCEYK5kh0iB8iVXGvx4TY0wXbZ1v6zbb95_nvb24tfY3bg5RGA6mAKBZKL9Y5jRvTavHPPDtyutlzudGWUkJSzn7ZXtls</recordid><startdate>20110401</startdate><enddate>20110401</enddate><creator>PORTER, K. 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A.</au><au>BURCH, C. L.</au><au>POOLE, C.</au><au>JULIANO, J. J.</au><au>COLE, S. R.</au><au>MESHNICK, S. R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Uncertain outcomes: adjusting for misclassification in antimalarial efficacy studies</atitle><jtitle>Epidemiology and infection</jtitle><addtitle>Epidemiol Infect</addtitle><date>2011-04-01</date><risdate>2011</risdate><volume>139</volume><issue>4</issue><spage>544</spage><epage>551</epage><pages>544-551</pages><issn>0950-2688</issn><eissn>1469-4409</eissn><coden>EPINEU</coden><abstract>Evaluation of antimalarial efficacy is difficult because recurrent parasitaemia can be due to recrudescence or re-infection. PCR is used to differentiate between recrudescences and re-infections by comparing parasite allelic variants before and after treatment. 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The uncertainty analysis exploits characteristics of study data to minimize bias in the estimate of efficacy and can be applied to areas of different transmission intensity.</abstract><cop>Cambridge</cop><pub>Cambridge University Press</pub><pmid>20619072</pmid><doi>10.1017/S0950268810001652</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Epidemiology and infection, 2011-04, Vol.139 (4), p.544-551 |
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| subjects | Antimalarials Antimalarials - administration & dosage Antiparasitic agents Biological and medical sciences Biomedical Research - methods False negative errors False positive errors False Positive Reactions Fundamental and applied biological sciences. Psychology Humans Infections Infectious diseases Malaria Malaria - drug therapy Medical cures Microbiology Normal distribution Parasitology - methods Patients Polymerase chain reaction Polymerase Chain Reaction - methods Probabilities Probability Recurrence Relapse Sampling errors Treatment Outcome |
| title | Uncertain outcomes: adjusting for misclassification in antimalarial efficacy studies |
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