Estimating the lifetime risk of a false positive screening test result
False positive results in screening tests have potentially severe psychological, medical, and financial consequences for the recipient. However, there have been few efforts to quantify how the risk of a false positive accumulates over time. We seek to fill this gap by estimating the probability that...
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description | False positive results in screening tests have potentially severe psychological, medical, and financial consequences for the recipient. However, there have been few efforts to quantify how the risk of a false positive accumulates over time. We seek to fill this gap by estimating the probability that an individual who adheres to the U.S. Preventive Services Task Force (USPSTF) screening guidelines will receive at least one false positive in a lifetime. To do so, we assembled a data set of 116 studies cited by the USPSTF that report the number of true positives, false negatives, true negatives, and false positives for the primary screening procedure for one of five cancers or six sexually transmitted diseases. We use these data to estimate the probability that an individual in one of 14 demographic subpopulations will receive at least one false positive for one of these eleven diseases in a lifetime. We specify a suitable statistical model to account for the hierarchical structure of the data, and we use the parametric bootstrap to quantify the uncertainty surrounding our estimates. The estimated probability of receiving at least one false positive in a lifetime is 85.5% (±0.9%) and 38.9% (±3.6%) for baseline groups of women and men, respectively. It is higher for subpopulations recommended to screen more frequently than the baseline, including more vulnerable groups such as pregnant women and men who have sex with men. Since screening technology is imperfect, false positives remain inevitable. The high lifetime risk of a false positive reveals the importance of educating patients about this phenomenon. |
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However, there have been few efforts to quantify how the risk of a false positive accumulates over time. We seek to fill this gap by estimating the probability that an individual who adheres to the U.S. Preventive Services Task Force (USPSTF) screening guidelines will receive at least one false positive in a lifetime. To do so, we assembled a data set of 116 studies cited by the USPSTF that report the number of true positives, false negatives, true negatives, and false positives for the primary screening procedure for one of five cancers or six sexually transmitted diseases. We use these data to estimate the probability that an individual in one of 14 demographic subpopulations will receive at least one false positive for one of these eleven diseases in a lifetime. We specify a suitable statistical model to account for the hierarchical structure of the data, and we use the parametric bootstrap to quantify the uncertainty surrounding our estimates. The estimated probability of receiving at least one false positive in a lifetime is 85.5% (±0.9%) and 38.9% (±3.6%) for baseline groups of women and men, respectively. It is higher for subpopulations recommended to screen more frequently than the baseline, including more vulnerable groups such as pregnant women and men who have sex with men. Since screening technology is imperfect, false positives remain inevitable. The high lifetime risk of a false positive reveals the importance of educating patients about this phenomenon.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0281153</identifier><identifier>PMID: 36791062</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Biology and Life Sciences ; Breast cancer ; Cancer ; Data collection ; Diagnosis ; Disease transmission ; Evaluation ; False Positive Reactions ; Female ; Gays & lesbians ; Hepatitis ; Homosexuality, Male ; Humans ; Male ; Males ; Mass Screening - methods ; Mathematical models ; Medical screening ; Medical tests ; Medicine and Health Sciences ; Medicine, Preventive ; Men ; Mens health ; Methods ; Neoplasms ; Patient education ; People and Places ; Pregnancy ; Preventive health services ; Probability ; Prostate ; Prostate cancer ; Risk ; Sexual and Gender Minorities ; Sexually transmitted diseases ; Statistical analysis ; Statistical models ; STD ; Subpopulations ; Syphilis ; Women</subject><ispartof>PloS one, 2023-02, Vol.18 (2), p.e0281153-e0281153</ispartof><rights>Copyright: © 2023 White, Algeri. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 White, Algeri. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 White, Algeri 2023 White, Algeri</rights><rights>2023 White, Algeri. 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However, there have been few efforts to quantify how the risk of a false positive accumulates over time. We seek to fill this gap by estimating the probability that an individual who adheres to the U.S. Preventive Services Task Force (USPSTF) screening guidelines will receive at least one false positive in a lifetime. To do so, we assembled a data set of 116 studies cited by the USPSTF that report the number of true positives, false negatives, true negatives, and false positives for the primary screening procedure for one of five cancers or six sexually transmitted diseases. We use these data to estimate the probability that an individual in one of 14 demographic subpopulations will receive at least one false positive for one of these eleven diseases in a lifetime. We specify a suitable statistical model to account for the hierarchical structure of the data, and we use the parametric bootstrap to quantify the uncertainty surrounding our estimates. 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One</addtitle><date>2023-02-15</date><risdate>2023</risdate><volume>18</volume><issue>2</issue><spage>e0281153</spage><epage>e0281153</epage><pages>e0281153-e0281153</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>False positive results in screening tests have potentially severe psychological, medical, and financial consequences for the recipient. However, there have been few efforts to quantify how the risk of a false positive accumulates over time. We seek to fill this gap by estimating the probability that an individual who adheres to the U.S. Preventive Services Task Force (USPSTF) screening guidelines will receive at least one false positive in a lifetime. To do so, we assembled a data set of 116 studies cited by the USPSTF that report the number of true positives, false negatives, true negatives, and false positives for the primary screening procedure for one of five cancers or six sexually transmitted diseases. We use these data to estimate the probability that an individual in one of 14 demographic subpopulations will receive at least one false positive for one of these eleven diseases in a lifetime. We specify a suitable statistical model to account for the hierarchical structure of the data, and we use the parametric bootstrap to quantify the uncertainty surrounding our estimates. The estimated probability of receiving at least one false positive in a lifetime is 85.5% (±0.9%) and 38.9% (±3.6%) for baseline groups of women and men, respectively. It is higher for subpopulations recommended to screen more frequently than the baseline, including more vulnerable groups such as pregnant women and men who have sex with men. Since screening technology is imperfect, false positives remain inevitable. The high lifetime risk of a false positive reveals the importance of educating patients about this phenomenon.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>36791062</pmid><doi>10.1371/journal.pone.0281153</doi><tpages>e0281153</tpages><orcidid>https://orcid.org/0000-0001-5535-0452</orcidid><orcidid>https://orcid.org/0000-0001-7366-3866</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Biology and Life Sciences Breast cancer Cancer Data collection Diagnosis Disease transmission Evaluation False Positive Reactions Female Gays & lesbians Hepatitis Homosexuality, Male Humans Male Males Mass Screening - methods Mathematical models Medical screening Medical tests Medicine and Health Sciences Medicine, Preventive Men Mens health Methods Neoplasms Patient education People and Places Pregnancy Preventive health services Probability Prostate Prostate cancer Risk Sexual and Gender Minorities Sexually transmitted diseases Statistical analysis Statistical models STD Subpopulations Syphilis Women |
title | Estimating the lifetime risk of a false positive screening test result |
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