{"id":"https://openalex.org/W2060706356","doi":"https://doi.org/10.1186/s12911-014-0099-1","title":"Optimum binary cut-off threshold of a diagnostic test: comparison of different methods using Monte Carlo technique","display_name":"Optimum binary cut-off threshold of a diagnostic test: comparison of different methods using Monte Carlo technique","publication_year":2014,"publication_date":"2014-11-24","ids":{"openalex":"https://openalex.org/W2060706356","doi":"https://doi.org/10.1186/s12911-014-0099-1","mag":"2060706356","pmid":"https://pubmed.ncbi.nlm.nih.gov/25421000"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-014-0099-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-014-0099-1","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-014-0099-1","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-014-0099-1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024654230","display_name":"Gilbert Reibnegger","orcid":"https://orcid.org/0000-0001-7202-2426"},"institutions":[{"id":"https://openalex.org/I202276237","display_name":"Medical University of Graz","ror":"https://ror.org/02n0bts35","country_code":"AT","type":"education","lineage":["https://openalex.org/I202276237"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Gilbert Reibnegger","raw_affiliation_strings":["Institute of Physiological Chemistry, Center of Physiological Medicine, Medical University of Graz, Graz, A-8010, Austria","Institute of Physiological Chemistry, Center of Physiological Medicine, Medical University of Graz, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Physiological Chemistry, Center of Physiological Medicine, Medical University of Graz, Graz, A-8010, Austria","institution_ids":["https://openalex.org/I202276237"]},{"raw_affiliation_string":"Institute of Physiological Chemistry, Center of Physiological Medicine, Medical University of Graz, Graz, Austria","institution_ids":["https://openalex.org/I202276237"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078027749","display_name":"Walter Schrabmair","orcid":"https://orcid.org/0000-0002-4196-2586"},"institutions":[{"id":"https://openalex.org/I202276237","display_name":"Medical University of Graz","ror":"https://ror.org/02n0bts35","country_code":"AT","type":"education","lineage":["https://openalex.org/I202276237"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Walter Schrabmair","raw_affiliation_strings":["Institute of Physiological Chemistry, Center of Physiological Medicine, Medical University of Graz, Graz, A-8010, Austria","Institute of Physiological Chemistry, Center of Physiological Medicine, Medical University of Graz, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Physiological Chemistry, Center of Physiological Medicine, Medical University of Graz, Graz, A-8010, Austria","institution_ids":["https://openalex.org/I202276237"]},{"raw_affiliation_string":"Institute of Physiological Chemistry, Center of Physiological Medicine, Medical University of Graz, Graz, Austria","institution_ids":["https://openalex.org/I202276237"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1570,"currency":"GBP","value_usd":1925},"apc_paid":{"value":1570,"currency":"GBP","value_usd":1925},"fwci":1.1823,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.83502357,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"14","issue":"1","first_page":"99","last_page":"99"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.16670000553131104,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.16670000553131104,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11314","display_name":"Clinical Laboratory Practices and Quality Control","score":0.07020000368356705,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.06750000268220901,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/youdens-j-statistic","display_name":"Youden's J statistic","score":0.8468204736709595},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.732433557510376},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6751809120178223},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6687541007995605},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6086028814315796},{"id":"https://openalex.org/keywords/binary-data","display_name":"Binary data","score":0.47242558002471924},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.47033295035362244},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4117581844329834},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.40753602981567383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2517470717430115},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.19838929176330566}],"concepts":[{"id":"https://openalex.org/C43346845","wikidata":"https://www.wikidata.org/wiki/Q8057732","display_name":"Youden's J statistic","level":3,"score":0.8468204736709595},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.732433557510376},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6751809120178223},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6687541007995605},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6086028814315796},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.47242558002471924},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.47033295035362244},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4117581844329834},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.40753602981567383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2517470717430115},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.19838929176330566},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000592","qualifier_name":"standards","is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000592","qualifier_name":"standards","is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000592","qualifier_name":"standards","is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D003955","descriptor_name":"Diagnostic Tests, Routine","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009010","descriptor_name":"Monte Carlo Method","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009010","descriptor_name":"Monte Carlo Method","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009010","descriptor_name":"Monte Carlo Method","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012016","descriptor_name":"Reference Values","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012016","descriptor_name":"Reference Values","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012016","descriptor_name":"Reference Values","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016013","descriptor_name":"Likelihood Functions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016013","descriptor_name":"Likelihood Functions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016013","descriptor_name":"Likelihood Functions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016015","descriptor_name":"Logistic Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016015","descriptor_name":"Logistic Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016015","descriptor_name":"Logistic Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1186/s12911-014-0099-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-014-0099-1","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-014-0099-1","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},{"id":"pmid:25421000","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25421000","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC medical informatics and decision making","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:4253606","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4253606","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Inform Decis Mak","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12911-014-0099-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-014-0099-1","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-014-0099-1","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2060706356.pdf","grobid_xml":"https://content.openalex.org/works/W2060706356.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1840658278","https://openalex.org/W1969430785","https://openalex.org/W1975357761","https://openalex.org/W1983321861","https://openalex.org/W2032189872","https://openalex.org/W2090142427","https://openalex.org/W2111570245","https://openalex.org/W2118555642","https://openalex.org/W2122231541","https://openalex.org/W2151700469","https://openalex.org/W2152330909","https://openalex.org/W2154832735","https://openalex.org/W2289847303","https://openalex.org/W2432590275","https://openalex.org/W4300653587"],"related_works":["https://openalex.org/W2034816881","https://openalex.org/W4233153962","https://openalex.org/W3094090087","https://openalex.org/W2060706356","https://openalex.org/W2048637055","https://openalex.org/W2553734051","https://openalex.org/W1986001860","https://openalex.org/W2130448352","https://openalex.org/W3088876697","https://openalex.org/W2195347453"],"abstract_inverted_index":{"BACKGROUND:":[0],"Using":[1],"Monte":[2],"Carlo":[3],"simulations,":[4],"we":[5],"compare":[6],"different":[7,75,108,304],"methods":[8],"(maximizing":[9],"Youden":[10,145,241,258],"index,":[11],"maximizing":[12],"mutual":[13,173],"information,":[14],"and":[15,40,83,117,128,147,222,239,260],"logistic":[16,148,296],"regression)":[17],"for":[18,27,80,121,135,156,198,246],"their":[19],"ability":[20],"to":[21,37,299],"determine":[22],"optimum":[23,101,113],"binary":[24,102],"cut-off":[25,103,114,142,176,208,249],"thresholds":[26],"a":[28,70,211,252],"ratio-scaled":[29,71],"diagnostic":[30,59,72,95,253,278,301],"test":[31,63,73],"variable.":[32,254],"Special":[33],"attention":[34],"is":[35,243,307],"given":[36],"the":[38,43,48,54,58,62,122,192,199,230,276,285,290],"stability":[39,238],"precision":[41],"of":[42,57,69,90,93,130,141,183,191,237,251,257,275,284,289],"results":[44,188,256],"in":[45,61],"dependence":[46],"on":[47,111],"distributional":[49,76,268],"characteristics":[50,77],"as":[51,53,270,272],"well":[52,271],"pre-test":[55,91,157,168,181,273,305],"probabilities":[56,92,158,169,274,306],"categories":[60],"population.":[64],"METHODS:":[65],"Fictitious":[66],"data":[67,99,124],"sets":[68],"with":[74,87,153,179,229,303],"are":[78,105,119,133,195,218,224,264],"generated":[79],"50,":[81],"100":[82],"200":[84],"fictitious":[85],"\"individuals\"":[86],"systematic":[88],"variation":[89],"two":[94,231,277],"categories.":[96,279],"For":[97],"each":[98],"set,":[100],"limits":[104,143,250],"determined":[106],"employing":[107],"methods.":[109,233],"Based":[110],"these":[112,131],"thresholds,":[115],"sensitivities":[116,223],"specificities":[118,217],"calculated":[120],"respective":[123],"sets.":[125],"Mean":[126],"values":[127,209],"SD":[129],"variables":[132],"computed":[134],"1000":[136],"repetitions":[137],"each.":[138],"RESULTS:":[139],"Optimizations":[140],"using":[144],"index":[146,242],"regression-derived":[149],"likelihood":[150,200,261,291],"ratio":[151,201,262,292],"functions":[152],"correct":[154],"adaption":[155],"both":[159],"yield":[160],"reasonably":[161],"stable":[162],"results,":[163],"being":[164],"nearly":[165],"independent":[166],"from":[167,295],"actually":[170],"used.":[171],"Maximizing":[172],"information":[174],"yields":[175],"levels":[177],"decreasing":[178],"increasing":[180],"probability":[182],"disease.":[184],"The":[185,255],"most":[186],"precise":[187],"(in":[189],"terms":[190,236],"smallest":[193],"SD)":[194],"usually":[196,219],"seen":[197],"method.":[202],"With":[203],"this":[204],"parametric":[205,286],"method,":[206],"however,":[207],"show":[210],"significant":[212],"positive":[213],"bias":[214],"and,":[215],"hence,":[216],"slightly":[220,226],"higher,":[221],"consequently":[225],"lower":[227],"than":[228],"non-parametric":[232],"CONCLUSIONS:":[234],"In":[235],"bias,":[240],"best":[244],"suited":[245],"determining":[247],"optimal":[248],"method":[259,263],"surprisingly":[265],"insensitive":[266],"against":[267],"differences":[269],"As":[280],"an":[281],"additional":[282],"bonus":[283],"procedure,":[287],"transfer":[288],"functions,":[293],"obtained":[294],"regression":[297],"analysis,":[298],"other":[300],"scenarios":[302],"straightforward.":[308]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
