There is no such thing as a validated prediction model

Background Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context? Main body We argue to the cont...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	BMC medicine Ročník 21; číslo 1; s. 70 - 8
Hlavní autoři:	Van Calster, Ben, Steyerberg, Ewout W., Wynants, Laure, van Smeden, Maarten
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 24.02.2023 BioMed Central Ltd Springer Nature B.V BMC
Témata:	Biomarkers Biomedicine Calibration Clinical medicine Datasets Decision making Delirium Estimates External validation Fractures Health aspects Health risk assessment Heterogeneity Hospitals Internal validation Medicine Medicine & Public Health Methods Model performance Mortality Oncology Opinion Ovarian cancer Patients Populations Practice Prediction models Predictive analytics Pulmonary embolisms Risk prediction models Scanners Variables Netherlands Heterogeneity Model performance Discrimination External validation Risk prediction models Calibration Internal validation Predictive analytics
ISSN:	1741-7015, 1741-7015
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	Background Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context? Main body We argue to the contrary because (1) patient populations vary, (2) measurement procedures vary, and (3) populations and measurements change over time. Hence, we have to expect heterogeneity in model performance between locations and settings, and across time. It follows that prediction models are never truly validated. This does not imply that validation is not important. Rather, the current focus on developing new models should shift to a focus on more extensive, well-conducted, and well-reported validation studies of promising models. Conclusion Principled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making.
AbstractList	Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context? We argue to the contrary because (1) patient populations vary, (2) measurement procedures vary, and (3) populations and measurements change over time. Hence, we have to expect heterogeneity in model performance between locations and settings, and across time. It follows that prediction models are never truly validated. This does not imply that validation is not important. Rather, the current focus on developing new models should shift to a focus on more extensive, well-conducted, and well-reported validation studies of promising models. Principled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making. Background Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context? Main body We argue to the contrary because (1) patient populations vary, (2) measurement procedures vary, and (3) populations and measurements change over time. Hence, we have to expect heterogeneity in model performance between locations and settings, and across time. It follows that prediction models are never truly validated. This does not imply that validation is not important. Rather, the current focus on developing new models should shift to a focus on more extensive, well-conducted, and well-reported validation studies of promising models. Conclusion Principled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making. Keywords: Risk prediction models, Predictive analytics, Internal validation, External validation, Heterogeneity, Model performance, Calibration, Discrimination Abstract Background Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context? Main body We argue to the contrary because (1) patient populations vary, (2) measurement procedures vary, and (3) populations and measurements change over time. Hence, we have to expect heterogeneity in model performance between locations and settings, and across time. It follows that prediction models are never truly validated. This does not imply that validation is not important. Rather, the current focus on developing new models should shift to a focus on more extensive, well-conducted, and well-reported validation studies of promising models. Conclusion Principled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making. Background Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context? Main body We argue to the contrary because (1) patient populations vary, (2) measurement procedures vary, and (3) populations and measurements change over time. Hence, we have to expect heterogeneity in model performance between locations and settings, and across time. It follows that prediction models are never truly validated. This does not imply that validation is not important. Rather, the current focus on developing new models should shift to a focus on more extensive, well-conducted, and well-reported validation studies of promising models. Conclusion Principled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making. Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context?BACKGROUNDClinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context?We argue to the contrary because (1) patient populations vary, (2) measurement procedures vary, and (3) populations and measurements change over time. Hence, we have to expect heterogeneity in model performance between locations and settings, and across time. It follows that prediction models are never truly validated. This does not imply that validation is not important. Rather, the current focus on developing new models should shift to a focus on more extensive, well-conducted, and well-reported validation studies of promising models.MAIN BODYWe argue to the contrary because (1) patient populations vary, (2) measurement procedures vary, and (3) populations and measurements change over time. Hence, we have to expect heterogeneity in model performance between locations and settings, and across time. It follows that prediction models are never truly validated. This does not imply that validation is not important. Rather, the current focus on developing new models should shift to a focus on more extensive, well-conducted, and well-reported validation studies of promising models.Principled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making.CONCLUSIONPrincipled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making. Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context? Principled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making. BackgroundClinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external validation sufficient to claim that a prediction model works well in the intended clinical context?Main bodyWe argue to the contrary because (1) patient populations vary, (2) measurement procedures vary, and (3) populations and measurements change over time. Hence, we have to expect heterogeneity in model performance between locations and settings, and across time. It follows that prediction models are never truly validated. This does not imply that validation is not important. Rather, the current focus on developing new models should shift to a focus on more extensive, well-conducted, and well-reported validation studies of promising models.ConclusionPrincipled validation strategies are needed to understand and quantify heterogeneity, monitor performance over time, and update prediction models when appropriate. Such strategies will help to ensure that prediction models stay up-to-date and safe to support clinical decision-making.
ArticleNumber	70
Audience	Academic
Author	van Smeden, Maarten Van Calster, Ben Steyerberg, Ewout W. Wynants, Laure
Author_xml	– sequence: 1 givenname: Ben orcidid: 0000-0003-1613-7450 surname: Van Calster fullname: Van Calster, Ben organization: Department of Development and Regeneration, KU Leuven, EPI-Center, KU Leuven, Department of Biomedical Data Sciences, Leiden University Medical Center – sequence: 2 givenname: Ewout W. orcidid: 0000-0002-7787-0122 surname: Steyerberg fullname: Steyerberg, Ewout W. organization: Department of Development and Regeneration, KU Leuven – sequence: 3 givenname: Laure orcidid: 0000-0002-3037-122X surname: Wynants fullname: Wynants, Laure organization: Department of Development and Regeneration, KU Leuven, EPI-Center, KU Leuven, Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Maastricht University – sequence: 4 givenname: Maarten orcidid: 0000-0002-5529-1541 surname: van Smeden fullname: van Smeden, Maarten email: M.vanSmeden@umcutrecht.nl organization: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/36829188$$D View this record in MEDLINE/PubMed
BookMark	eNp9kstq3TAQhkVJaS7tC3RRDIXSjVPdLMnLEHoJBLpJ10KWRsc62NapZDfk7asTp7lRghASw_f_MxrNMTqY4gQIvSf4lBAlvmRCWyJqTFnZUrb19St0RCQntcSkOXh0P0THOW8xpo2U_A06ZEIVqVJHSFz1kKAKuZpilRfbV3Mfpk1lcmWqP2YIzszgql0CF-wc4lSN0cHwFr32Zsjw7u48Qb--fb06_1Ff_vx-cX52WdtGsbkWnlrSYNtgkNKCAmaoYdw1zBslDaWNosyTjnHZOqeMdxKgFRYTQQQTkp2gi9XXRbPVuxRGk250NEHfBmLaaJPmYAfQvjVCcNJJTxnv2rbtGqU4MCe8kNLz4vV59dql-HuBPOsxZAvDYCaIS9ZUKowlV4IV9OMzdBuXNJWX7inFJRcNfaA2puQPk49zMnZvqs8kU43CBKtCnf6HKsvBGGz5UR9K_Ing0yNBD2aY-xyHZd_9_BT8cFfl0o3g7tvz73cLQFfApphzAn-PEKz3I6TXEdJlhPTtCOnrIlLPRDbMZp-81B2Gl6VsleaSZ9pAemjbC6q_OZnVWA
CitedBy_id	crossref_primary_10_1186_s42466_024_00338_z crossref_primary_10_1186_s12911_024_02830_7 crossref_primary_10_1186_s12913_024_11715_4 crossref_primary_10_1097_JS9_0000000000002279 crossref_primary_10_1245_s10434_024_16698_4 crossref_primary_10_1016_j_jclinepi_2024_111636 crossref_primary_10_1371_journal_pone_0310712 crossref_primary_10_1016_j_bja_2024_09_003 crossref_primary_10_1016_j_jpi_2023_100347 crossref_primary_10_1007_s00210_024_03095_7 crossref_primary_10_1016_j_jpi_2023_100348 crossref_primary_10_1038_s41746_023_00832_9 crossref_primary_10_1227_neu_0000000000003275 crossref_primary_10_1186_s12916_023_03048_6 crossref_primary_10_1097_CCM_0000000000006441 crossref_primary_10_2196_51409 crossref_primary_10_1016_j_bpsc_2025_03_006 crossref_primary_10_1038_s41416_024_02578_x crossref_primary_10_1371_journal_pone_0314526 crossref_primary_10_1186_s13613_024_01330_1 crossref_primary_10_1371_journal_pone_0310321 crossref_primary_10_26833_ijeg_1710723 crossref_primary_10_1186_s41512_025_00199_3 crossref_primary_10_1093_jrsssc_qlae070 crossref_primary_10_1186_s12890_024_03233_0 crossref_primary_10_1007_s00068_023_02351_4 crossref_primary_10_1089_wound_2024_0069 crossref_primary_10_3348_kjr_2024_0144 crossref_primary_10_1111_eci_70002 crossref_primary_10_2196_65994 crossref_primary_10_1136_bmj_2023_078276 crossref_primary_10_1111_cdoe_12942 crossref_primary_10_1186_s12916_025_03994_3 crossref_primary_10_35401_2541_9897_2025_10_2_40_46 crossref_primary_10_1016_j_resplu_2023_100435 crossref_primary_10_1038_s41746_024_01037_4 crossref_primary_10_1002_sim_70011 crossref_primary_10_1093_ejendo_lvaf171 crossref_primary_10_1136_bmjebm_2025_113730 crossref_primary_10_1007_s10067_025_07328_9 crossref_primary_10_1186_s12544_024_00704_7 crossref_primary_10_1016_j_jvs_2023_12_023 crossref_primary_10_1093_eurheartj_ehad727 crossref_primary_10_1136_bmjopen_2022_070559 crossref_primary_10_1001_jamanetworkopen_2023_35377 crossref_primary_10_1136_bmjgh_2024_017582 crossref_primary_10_2196_57035 crossref_primary_10_1007_s00134_024_07738_4 crossref_primary_10_1007_s00068_023_02354_1 crossref_primary_10_1371_journal_pgph_0004606 crossref_primary_10_1016_j_ijmedinf_2024_105700 crossref_primary_10_1016_j_trre_2025_100934 crossref_primary_10_1186_s12959_024_00603_w crossref_primary_10_1093_jnci_djad202 crossref_primary_10_1136_bmj_2023_074819 crossref_primary_10_1093_humrep_deaf013 crossref_primary_10_1007_s10753_024_02185_1 crossref_primary_10_1038_s41746_025_01587_1 crossref_primary_10_3389_fped_2025_1636580 crossref_primary_10_3389_fonc_2023_1139902 crossref_primary_10_1016_j_landig_2025_100880 crossref_primary_10_1001_jamanetworkopen_2024_55475 crossref_primary_10_1186_s41512_024_00182_4 crossref_primary_10_1371_journal_pmed_1004540 crossref_primary_10_3748_wjg_v31_i18_106670 crossref_primary_10_1016_j_rpth_2024_102480 crossref_primary_10_1016_j_jclinepi_2024_111433 crossref_primary_10_1155_jdr_8830658 crossref_primary_10_1016_j_semperi_2025_152054 crossref_primary_10_1186_s12967_024_05005_0 crossref_primary_10_1016_j_compbiomed_2025_109710 crossref_primary_10_30944_20117582_2813 crossref_primary_10_1016_j_jcyt_2025_07_002 crossref_primary_10_1097_TA_0000000000004385 crossref_primary_10_1038_s41467_024_52618_6 crossref_primary_10_1007_s10461_025_04814_8 crossref_primary_10_1038_s41591_023_02540_z crossref_primary_10_1136_bmjmed_2023_000817 crossref_primary_10_7326_M23_0949 crossref_primary_10_1136_bmj_2023_074820 crossref_primary_10_1016_j_bas_2025_104208 crossref_primary_10_1093_humrep_dead165 crossref_primary_10_1016_j_jclinepi_2024_111387 crossref_primary_10_1186_s12877_024_05044_8 crossref_primary_10_1186_s12913_024_11936_7 crossref_primary_10_1213_ANE_0000000000007463 crossref_primary_10_1186_s12879_024_10319_x crossref_primary_10_1213_ANE_0000000000007464 crossref_primary_10_1093_eurjpc_zwae354 crossref_primary_10_1016_j_jdent_2025_105867 crossref_primary_10_1097_JS9_0000000000000979 crossref_primary_10_12968_hmed_2024_0781 crossref_primary_10_1186_s12874_024_02280_9 crossref_primary_10_1093_ndt_gfae050 crossref_primary_10_1016_j_ijrobp_2025_07_1445 crossref_primary_10_1186_s12933_024_02443_4 crossref_primary_10_1245_s10434_024_14997_4 crossref_primary_10_1007_s00420_025_02129_8 crossref_primary_10_3390_v15081735 crossref_primary_10_1038_s43856_025_00965_w crossref_primary_10_1186_s41512_025_00186_8 crossref_primary_10_1038_s41746_025_01479_4 crossref_primary_10_1016_j_ijmedinf_2024_105631 crossref_primary_10_1002_cam4_7253 crossref_primary_10_3233_CBM_230360 crossref_primary_10_1016_j_brat_2023_104443 crossref_primary_10_1016_j_spinee_2025_01_014 crossref_primary_10_1016_j_chiabu_2024_106799 crossref_primary_10_1093_ejendo_lvae166 crossref_primary_10_2196_47833 crossref_primary_10_1002_uog_27515 crossref_primary_10_1016_j_ebiom_2023_104823 crossref_primary_10_1016_j_compbiomed_2024_108014 crossref_primary_10_1093_eurjpc_zwae096 crossref_primary_10_1016_j_jtha_2025_06_026 crossref_primary_10_1016_j_ijmedinf_2025_105884 crossref_primary_10_1053_j_gastro_2025_05_012 crossref_primary_10_1016_j_blre_2024_101170 crossref_primary_10_1093_jamia_ocae036 crossref_primary_10_2112_JCOASTRES_D_24_00072_1 crossref_primary_10_1136_bmj_2023_078378 crossref_primary_10_1186_s12883_024_03546_x crossref_primary_10_1186_s41512_023_00161_1
Cites_doi	10.1186/1471-2288-13-128 10.1016/j.jclinepi.2019.11.001 10.1016/j.jclinepi.2014.11.010 10.1515/cclm-2015-1142 10.1093/jamia/ocz145 10.1016/j.jclinepi.2015.04.005 10.1136/bmjopen-2017-019223 10.1503/cmaj.091430 10.1016/S2589-7500(20)30186-2 10.1186/s12916-019-1466-7 10.1093/jamia/ocz130 10.1186/s41512-019-0046-9 10.1038/s41467-022-29437-8 10.1016/j.jhealeco.2014.11.003 10.1136/bmj-2022-071018 10.1093/qjmed/hcg027 10.1016/S0895-4356(01)00341-9 10.1177/0962280216668555 10.1136/bmj-2021-069881 10.1186/s41512-020-00077-0 10.1177/0962280218785504 10.7326/M14-0698 10.1136/bmj-2022-071058 10.1016/j.annemergmed.2011.01.020 10.1136/emermed-2021-212224 10.1136/bmj.m2614 10.1016/j.jclinepi.2015.12.005 10.1161/CIRCOUTCOMES.121.008487 10.1002/sim.9025 10.1136/bmj.i3140 10.1093/ejcts/ezs584 10.1186/s12874-022-01801-8 10.1016/S2352-3026(18)30220-5 10.1148/radiol.2020201940 10.1002/sim.6787 10.1016/j.jbi.2020.103611 10.1002/sim.5732 10.1016/S1474-4422(19)30232-7 10.1017/S1481803500013336 10.1136/bmj.b605 10.1002/(SICI)1097-0258(20000229)19:4<453::AID-SIM350>3.0.CO;2-5 10.1093/jamia/ocx030 10.7326/0003-4819-130-6-199903160-00016 10.1016/j.jclinepi.2016.05.007 10.1186/s41512-020-00090-3 10.1002/sim.8183 10.1055/s-0037-1613830 10.1186/s41512-017-0012-3 10.1038/s41746-019-0105-1 10.1002/sim.8296 10.1177/0272989X14547233 10.1016/j.jclinepi.2021.03.025 10.1136/bmj.k1479
ContentType	Journal Article
Copyright	The Author(s) 2023 2023. The Author(s). COPYRIGHT 2023 BioMed Central Ltd. 2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml	– notice: The Author(s) 2023 – notice: 2023. The Author(s). – notice: COPYRIGHT 2023 BioMed Central Ltd. – notice: 2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID	C6C AAYXX CITATION NPM 3V. 7QL 7U9 7X7 7XB 88E 8FI 8FJ 8FK ABUWG AFKRA AZQEC BENPR C1K CCPQU COVID DWQXO FYUFA GHDGH H94 K9. M0S M1P M7N PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQQKQ PQUKI PRINS 7X8 DOA
DOI	10.1186/s12916-023-02779-w
DatabaseName	Springer Nature OA Free Journals CrossRef PubMed ProQuest Central (Corporate) Bacteriology Abstracts (Microbiology B) Virology and AIDS Abstracts Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central Environmental Sciences and Pollution Management ProQuest One Coronavirus Research Database ProQuest Central Korea Proquest Health Research Premium Collection Health Research Premium Collection (Alumni) AIDS and Cancer Research Abstracts ProQuest Health & Medical Complete (Alumni) ProQuest Health & Medical Collection Medical Database Algology Mycology and Protozoology Abstracts (Microbiology C) ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic DOAJ Directory of Open Access Journals
DatabaseTitle	CrossRef PubMed Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Central China Environmental Sciences and Pollution Management ProQuest Central ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Health & Medical Research Collection AIDS and Cancer Research Abstracts ProQuest Central (New) ProQuest Medical Library (Alumni) Virology and AIDS Abstracts ProQuest One Academic Eastern Edition Coronavirus Research Database ProQuest Hospital Collection Health Research Premium Collection (Alumni) ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic
DatabaseTitleList	PubMed MEDLINE - Academic Publicly Available Content Database
Database_xml	– sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: PIMPY name: ProQuest Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Medicine
EISSN	1741-7015
EndPage	8
ExternalDocumentID	oai_doaj_org_article_f9a6641b7f234b999b5884e3d6f677f4 A738580108 36829188 10_1186_s12916_023_02779_w
Genre	Research Support, Non-U.S. Gov't Journal Article
GeographicLocations	Netherlands
GeographicLocations_xml	– name: Netherlands
GrantInformation_xml	– fundername: Fonds Wetenschappelijk Onderzoek grantid: G097322N funderid: http://dx.doi.org/10.13039/501100003130 – fundername: Fonds Wetenschappelijk Onderzoek grantid: G097322N
GroupedDBID	--- 0R~ 23N 2WC 4.4 53G 5GY 5VS 6J9 6PF 7X7 88E 8FI 8FJ AAFWJ AAJSJ AASML AAWTL ABDBF ABUWG ACGFO ACGFS ACIHN ACPRK ACUHS ADBBV ADRAZ ADUKV AEAQA AENEX AFKRA AFPKN AFRAH AHBYD AHMBA AHYZX ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS BAPOH BAWUL BCNDV BENPR BFQNJ BMC BPHCQ BVXVI C6C CCPQU CS3 DIK DU5 E3Z EAD EAP EAS EBD EBLON EBS EMB EMK EMOBN ESX F5P FYUFA GROUPED_DOAJ GX1 HMCUK HYE IAO IHR IHW INH INR ITC KQ8 M1P M48 MK0 M~E O5R O5S OK1 OVT P2P PGMZT PHGZM PHGZT PIMPY PJZUB PPXIY PQQKQ PROAC PSQYO PUEGO RBZ RNS ROL RPM RSV SMD SOJ SV3 TR2 TUS UKHRP WOQ WOW XSB AAYXX AFFHD CITATION ALIPV NPM 3V. 7QL 7U9 7XB 8FK AZQEC C1K COVID DWQXO H94 K9. M7N PKEHL PQEST PQUKI PRINS 7X8
ID	FETCH-LOGICAL-c583t-6f2c150c50e77ce8e3a2a34d53fa87a225823f1b3479dd8afd7ee96c016163673
IEDL.DBID	7X7
ISICitedReferencesCount	144
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000939497700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1741-7015
IngestDate	Tue Oct 14 18:52:38 EDT 2025 Thu Sep 04 19:03:19 EDT 2025 Wed Oct 08 14:11:02 EDT 2025 Tue Nov 11 10:03:39 EST 2025 Tue Nov 04 18:06:19 EST 2025 Thu May 22 21:24:23 EDT 2025 Mon Jul 21 05:54:00 EDT 2025 Sat Nov 29 04:08:29 EST 2025 Tue Nov 18 20:37:30 EST 2025 Sat Sep 06 07:24:53 EDT 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Heterogeneity Model performance Discrimination External validation Risk prediction models Calibration Internal validation Predictive analytics
Language	English
License	2023. The Author(s).
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c583t-6f2c150c50e77ce8e3a2a34d53fa87a225823f1b3479dd8afd7ee96c016163673
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ORCID	0000-0002-7787-0122 0000-0002-3037-122X 0000-0003-1613-7450 0000-0002-5529-1541
OpenAccessLink	https://www.proquest.com/docview/2788474652?pq-origsite=%requestingapplication%
PMID	36829188
PQID	2788474652
PQPubID	42775
PageCount	8
ParticipantIDs	doaj_primary_oai_doaj_org_article_f9a6641b7f234b999b5884e3d6f677f4 proquest_miscellaneous_2780074863 proquest_journals_2788474652 gale_infotracmisc_A738580108 gale_infotracacademiconefile_A738580108 gale_healthsolutions_A738580108 pubmed_primary_36829188 crossref_primary_10_1186_s12916_023_02779_w crossref_citationtrail_10_1186_s12916_023_02779_w springer_journals_10_1186_s12916_023_02779_w
PublicationCentury	2000
PublicationDate	2023-02-24
PublicationDateYYYYMMDD	2023-02-24
PublicationDate_xml	– month: 02 year: 2023 text: 2023-02-24 day: 24
PublicationDecade	2020
PublicationPlace	London
PublicationPlace_xml	– name: London – name: England
PublicationTitle	BMC medicine
PublicationTitleAbbrev	BMC Med
PublicationTitleAlternate	BMC Med
PublicationYear	2023
Publisher	BioMed Central BioMed Central Ltd Springer Nature B.V BMC
Publisher_xml	– name: BioMed Central – name: BioMed Central Ltd – name: Springer Nature B.V – name: BMC
References	EW Steyerberg (2779_CR39) 2019; 38 AC Justice (2779_CR5) 1999; 130 SE Davis (2779_CR35) 2017; 24 PC Austin (2779_CR43) 2016; 79 RD Riley (2779_CR48) 2021; 40 PC Austin (2779_CR44) 2017; 1 D Agniel (2779_CR18) 2018; 360 TPA Debray (2779_CR51) 2023; 380 EW Steyerberg (2779_CR8) 2019; 18 EW Steyerberg (2779_CR4) 2001; 54 T Takada (2779_CR46) 2021; 137 K Luijken (2779_CR19) 2019; 38 VMT De Jong (2779_CR14) 2022; 378 MAE Binuya (2779_CR53) 2022; 22 E White (2779_CR16) 2011; 163 KGM Moons (2779_CR50) 2015; 162 ER Berndt (2779_CR17) 2015; 40 C Reynard (2779_CR29) 2022 SE Davis (2779_CR31) 2020; 112 TPA Debray (2779_CR40) 2013; 32 PS Wells (2779_CR22) 2000; 83 TPA Debray (2779_CR41) 2019; 28 B Van Calster (2779_CR3) 2019; 26 S Iles (2779_CR24) 2003; 96 TPA Debray (2779_CR52) 2023; 380 L Wynants (2779_CR45) 2019; 3 B Van Calster (2779_CR55) 2016; 74 MC Lenert (2779_CR33) 2019; 26 H Lindroth (2779_CR25) 2018; 8 L Wynants (2779_CR42) 2018; 27 FM Fesmire (2779_CR23) 2011; 57 D Kim (2779_CR26) 2022; 13 MA Badgeley (2779_CR21) 2019; 2 GL Hickey (2779_CR36) 2013; 43 GS Collins (2779_CR49) 2015; 68 B Van Calster (2779_CR13) 2020; 370 DG Altman (2779_CR1) 2009; 338 RD Riley (2779_CR10) 2016; 353 G Cook (2779_CR37) 2019; 6 GS Collins (2779_CR54) 2016; 35 L Wynants (2779_CR27) 2013; 13 JH Min (2779_CR28) 2020; 297 EW Steyerberg (2779_CR2) 2016; 69 J Futoma (2779_CR7) 2020; 2 K Luijken (2779_CR20) 2020; 119 B Van Calster (2779_CR11) 2015; 35 G Gulati (2779_CR12) 2022; 15 B Nestor (2779_CR30) 2019; 106 S Ferraro (2779_CR15) 2016; 54 J Fan (2779_CR38) 2006; 8 DA Jenkins (2779_CR32) 2021; 5 DG Altman (2779_CR6) 2000; 19 IG Stiell (2779_CR47) 2010; 182 B Van Calster (2779_CR9) 2019; 17 RHH Groenwold (2779_CR34) 2020; 4
References_xml	– volume: 13 start-page: 128 year: 2013 ident: 2779_CR27 publication-title: BMC Med Res Methodol doi: 10.1186/1471-2288-13-128 – volume: 119 start-page: 7 year: 2020 ident: 2779_CR20 publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2019.11.001 – volume: 68 start-page: 134 year: 2015 ident: 2779_CR49 publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2014.11.010 – volume: 54 start-page: 1635 year: 2016 ident: 2779_CR15 publication-title: Clin Chem Lab Med doi: 10.1515/cclm-2015-1142 – volume: 26 start-page: 1645 year: 2019 ident: 2779_CR33 publication-title: J Am Med Inform Assoc. doi: 10.1093/jamia/ocz145 – volume: 69 start-page: 245 year: 2016 ident: 2779_CR2 publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2015.04.005 – volume: 8 start-page: e019223 year: 2018 ident: 2779_CR25 publication-title: BMJ Open doi: 10.1136/bmjopen-2017-019223 – volume: 182 start-page: 1173 year: 2010 ident: 2779_CR47 publication-title: CMAJ doi: 10.1503/cmaj.091430 – volume: 2 start-page: e489 year: 2020 ident: 2779_CR7 publication-title: Lancet Digit Health doi: 10.1016/S2589-7500(20)30186-2 – volume: 17 start-page: 230 year: 2019 ident: 2779_CR9 publication-title: BMC Med doi: 10.1186/s12916-019-1466-7 – volume: 26 start-page: 1651 year: 2019 ident: 2779_CR3 publication-title: J Am Med Inform Assoc. doi: 10.1093/jamia/ocz130 – volume: 3 start-page: 6 year: 2019 ident: 2779_CR45 publication-title: Diagn Progn Res doi: 10.1186/s41512-019-0046-9 – volume: 13 start-page: 1867 year: 2022 ident: 2779_CR26 publication-title: Nat Commun doi: 10.1038/s41467-022-29437-8 – volume: 40 start-page: 26 year: 2015 ident: 2779_CR17 publication-title: J Health Econ doi: 10.1016/j.jhealeco.2014.11.003 – volume: 380 start-page: e071018 year: 2023 ident: 2779_CR51 publication-title: BMJ doi: 10.1136/bmj-2022-071018 – volume: 96 start-page: 211 year: 2003 ident: 2779_CR24 publication-title: QJM doi: 10.1093/qjmed/hcg027 – volume: 54 start-page: 774 year: 2001 ident: 2779_CR4 publication-title: J Clin Epidemiol doi: 10.1016/S0895-4356(01)00341-9 – volume: 27 start-page: 1723 year: 2018 ident: 2779_CR42 publication-title: Stat Methods Med Res doi: 10.1177/0962280216668555 – volume: 378 start-page: e069881 year: 2022 ident: 2779_CR14 publication-title: BMJ doi: 10.1136/bmj-2021-069881 – volume: 4 start-page: 8 year: 2020 ident: 2779_CR34 publication-title: Diagn Progn Res doi: 10.1186/s41512-020-00077-0 – volume: 28 start-page: 2768 year: 2019 ident: 2779_CR41 publication-title: Stat Methods Med Res doi: 10.1177/0962280218785504 – volume: 162 start-page: W1 year: 2015 ident: 2779_CR50 publication-title: Ann Intern Med doi: 10.7326/M14-0698 – volume: 380 start-page: e071058 year: 2023 ident: 2779_CR52 publication-title: BMJ doi: 10.1136/bmj-2022-071058 – volume: 57 start-page: 628 year: 2011 ident: 2779_CR23 publication-title: Ann Emerg Med doi: 10.1016/j.annemergmed.2011.01.020 – year: 2022 ident: 2779_CR29 publication-title: Emerg Med J doi: 10.1136/emermed-2021-212224 – volume: 370 start-page: m2614 year: 2020 ident: 2779_CR13 publication-title: BMJ doi: 10.1136/bmj.m2614 – volume: 74 start-page: 167 year: 2016 ident: 2779_CR55 publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2015.12.005 – volume: 15 start-page: e008487 year: 2022 ident: 2779_CR12 publication-title: Circ Cardiovasc Qual Outcomes doi: 10.1161/CIRCOUTCOMES.121.008487 – volume: 40 start-page: 4230 year: 2021 ident: 2779_CR48 publication-title: Stat Med doi: 10.1002/sim.9025 – volume: 106 start-page: 1 year: 2019 ident: 2779_CR30 publication-title: Proc Mach Learn Res – volume: 353 start-page: i3140 year: 2016 ident: 2779_CR10 publication-title: BMJ doi: 10.1136/bmj.i3140 – volume: 43 start-page: 1146 year: 2013 ident: 2779_CR36 publication-title: Eur J Cardiothorac Surg doi: 10.1093/ejcts/ezs584 – volume: 22 start-page: 316 year: 2022 ident: 2779_CR53 publication-title: BMC Med Res Methodol doi: 10.1186/s12874-022-01801-8 – volume: 163 start-page: 143 year: 2011 ident: 2779_CR16 publication-title: IARC Sci Publ – volume: 6 start-page: e154 year: 2019 ident: 2779_CR37 publication-title: Lancet Haematol doi: 10.1016/S2352-3026(18)30220-5 – volume: 297 start-page: 573 year: 2020 ident: 2779_CR28 publication-title: Radiology doi: 10.1148/radiol.2020201940 – volume: 35 start-page: 214 year: 2016 ident: 2779_CR54 publication-title: Stat Med doi: 10.1002/sim.6787 – volume: 112 start-page: 103611 year: 2020 ident: 2779_CR31 publication-title: J Biomed Inform doi: 10.1016/j.jbi.2020.103611 – volume: 32 start-page: 3158 year: 2013 ident: 2779_CR40 publication-title: Stat Med doi: 10.1002/sim.5732 – volume: 18 start-page: 923 year: 2019 ident: 2779_CR8 publication-title: Lancet Neurol doi: 10.1016/S1474-4422(19)30232-7 – volume: 8 start-page: 19 year: 2006 ident: 2779_CR38 publication-title: CJEM doi: 10.1017/S1481803500013336 – volume: 338 start-page: b605 year: 2009 ident: 2779_CR1 publication-title: BMJ doi: 10.1136/bmj.b605 – volume: 19 start-page: 453 year: 2000 ident: 2779_CR6 publication-title: Stat Med doi: 10.1002/(SICI)1097-0258(20000229)19:4<453::AID-SIM350>3.0.CO;2-5 – volume: 24 start-page: 1052 year: 2017 ident: 2779_CR35 publication-title: J Am Med Inform Assoc doi: 10.1093/jamia/ocx030 – volume: 130 start-page: 515 year: 1999 ident: 2779_CR5 publication-title: Ann Intern Med doi: 10.7326/0003-4819-130-6-199903160-00016 – volume: 79 start-page: 76 year: 2016 ident: 2779_CR43 publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2016.05.007 – volume: 5 start-page: 1 year: 2021 ident: 2779_CR32 publication-title: Diagn Progn Res doi: 10.1186/s41512-020-00090-3 – volume: 38 start-page: 3444 year: 2019 ident: 2779_CR19 publication-title: Stat Med doi: 10.1002/sim.8183 – volume: 83 start-page: 416 year: 2000 ident: 2779_CR22 publication-title: Thromb Haemostat doi: 10.1055/s-0037-1613830 – volume: 1 start-page: 12 year: 2017 ident: 2779_CR44 publication-title: Diagn Progn Res doi: 10.1186/s41512-017-0012-3 – volume: 2 start-page: 31 year: 2019 ident: 2779_CR21 publication-title: npj Digit Med. doi: 10.1038/s41746-019-0105-1 – volume: 38 start-page: 4290 year: 2019 ident: 2779_CR39 publication-title: Stat Med doi: 10.1002/sim.8296 – volume: 35 start-page: 162 year: 2015 ident: 2779_CR11 publication-title: Med Decis Making doi: 10.1177/0272989X14547233 – volume: 137 start-page: 83 year: 2021 ident: 2779_CR46 publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2021.03.025 – volume: 360 start-page: k1479 year: 2018 ident: 2779_CR18 publication-title: BMJ doi: 10.1136/bmj.k1479
SSID	ssj0025774
Score	2.664989
Snippet	Background Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or... Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one external... Background Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or... BackgroundClinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal validation or one... Abstract Background Clinical prediction models should be validated before implementation in clinical practice. But is favorable performance at internal...
SourceID	doaj proquest gale pubmed crossref springer
SourceType	Open Website Aggregation Database Index Database Enrichment Source Publisher
StartPage	70
SubjectTerms	Biomarkers Biomedicine Calibration Clinical medicine Datasets Decision making Delirium Estimates External validation Fractures Health aspects Health risk assessment Heterogeneity Hospitals Internal validation Medicine Medicine & Public Health Methods Model performance Mortality Oncology Opinion Ovarian cancer Patients Populations Practice Prediction models Predictive analytics Pulmonary embolisms Risk prediction models Scanners Variables
SummonAdditionalLinks	– databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9QwEB6hqkJcUMszUMBISBzA6saOHzkWRMUBKg6AerNsxxYroWy12W3_Ph47CV0QcOEajy3nG09mJvZ8BnhRN84p5Sy1UbS0sVJTl_wMdV6EBbeiXeRC2q8f1NmZPj9vP1276gvPhBV64ALccWytlE3tVGS8cSmccVhaGXgno1QqZibQhWqnZGpMtUSKaqYSGS2Ph-TVajxsW_YsW3q144YyW__v3-RrTumXXdLsfE4P4PYYNZKTMttDuBH6O3Dz47gvfhdk0vY6kOVA-hUZtv4b2eCfJWIHYklaS0vM6ztyscYeqAqSb8C5B19O331--56ONyJQLzTfUBmZTxGcF4uglA86cMssbzrBo9XKJtvUjMfaYXlo12kbOxVCKz3GdZJLxe_DXr_qw0MgmiXd6VB7FgXC24bYIbmcwuLc2KoK6gkg40e6cLy14rvJaYOWpoBqEqgmg2quKng197koZBl_lX6DuM-SSHSdHyT1m1H95l_qr-AZas2UqtHZXM1JZulJyaau4GWWQINNL-DtWHeQYEDqqx3Jox3JZGh-t3laGWY09MEwlaajGilYBc_nZuyJh9f6sNpmGYzUtOQVPCgran5pLnXCRafBX09L7Ofgf8bu0f_A7jHcYsUkKGuOYG-z3oYnsO8vN8th_TQb1A_U1hzZ priority: 102 providerName: Directory of Open Access Journals – databaseName: SpringerLINK Contemporary 1997-Present dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR3LbtQwcAQFIS68oYECRkLiABYbO37kWBAVB6iQgKo3y3bsshLKVslu-_t4nAcsLwmu8YzlzMMz4_GMAZ6WlXNKOUttFDWtrNTUJTtDnRdhwa2oF7mQ9uidOjzUx8f1h7EorJ9uu08pybxTZ7XW8mWfLFOJF2aHvGNNzy_CJYHdZjBG_3g0h1kieTRTecxv8bZMUO7U_-t-_INB-ilDmg3PwfX_W_INuDY6mmR_kIybcCG0t-DK-zGVfhtkEpAukGVP2hXpN_4LWeNhFLE9sSSJ3xKPAhpy2iEGco_kR3PuwOeDN59ev6XjIwrUC83XVEbmk9PnxSIo5YMO3DLLq0bwaLWySZ0147F0WFHaNNrGRoVQS4-uoORS8buw067asAtEs8RuHUrPoqhKp-oQG-xHp7CeN9aqgHKiq_Fjh3F86OKryZGGlmYgiEkEMZkg5ryA5zPO6dBf46_Qr5BdMyT2xs4fVt2JGVXNxNpKieuLjFcuOcAOi3EDb2SUSsWqgMfIbDMUms4abvZzY58Un-oCnmUI1PH0A96OpQqJDNgtawtybwsy6abfHp4Eyox7Q2-YSstRlRSsgCfzMGLifbc2rDYZBp07LXkB9wZBnH-aS53ootPkLyap-z75n2l3_9_AH8BVNgguZdUe7Ky7TXgIl_3Zetl3j7LGfQNFTiJA priority: 102 providerName: Springer Nature
Title	There is no such thing as a validated prediction model
URI	https://link.springer.com/article/10.1186/s12916-023-02779-w https://www.ncbi.nlm.nih.gov/pubmed/36829188 https://www.proquest.com/docview/2788474652 https://www.proquest.com/docview/2780074863 https://doaj.org/article/f9a6641b7f234b999b5884e3d6f677f4
Volume	21
WOSCitedRecordID	wos000939497700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVADU databaseName: BioMed Central customDbUrl: eissn: 1741-7015 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0025774 issn: 1741-7015 databaseCode: RBZ dateStart: 20030101 isFulltext: true titleUrlDefault: https://www.biomedcentral.com/search/ providerName: BioMedCentral – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 1741-7015 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0025774 issn: 1741-7015 databaseCode: DOA dateStart: 20030101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 1741-7015 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0025774 issn: 1741-7015 databaseCode: M~E dateStart: 20030101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1741-7015 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0025774 issn: 1741-7015 databaseCode: 7X7 dateStart: 20090101 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1741-7015 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0025774 issn: 1741-7015 databaseCode: BENPR dateStart: 20090101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Publicly Available Content Database customDbUrl: eissn: 1741-7015 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0025774 issn: 1741-7015 databaseCode: PIMPY dateStart: 20090101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1741-7015 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0025774 issn: 1741-7015 databaseCode: RSV dateStart: 20031201 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3db9MwELdgQ2gvfH8ERjESEg9grbET23lCG9oEEquqAVN5shzHhkpTU5KW_fv4HCelIPbCS6Qk58jx_c53PvvuEHqZZmUpRKmJdnlBMs0lKb2eIaXJ7ZjpvBiHQNrzj2IykbNZMY0OtzYeq-znxDBRV7UBH_kB9Wu1TGQ8p2-XPwhUjYLd1VhC4zrahbLZgHMx2yy4cm_b9IEykh-0XrelcOS227ksyOWWMgo5-_-emX9TTX_slQYVdHL7fzt_B92Kxic-7NByF12zi3vo5mncXr-PuAdNY_G8xYsat2vzHa_AQYV1izX2kJyDe6DCywZaAEdxKKTzAH05Of787j2JhRWIySVbEe6o8YagycdWCGOlZZpqllU5c1oK7UVcUubSEqJMq0pqVwlrC27APOSMC_YQ7SzqhX2MsKQeAtKmhro8S0tRWFdBjjoBMb6uEAlK-xFWJmYdh-IXFyqsPiRXHVeU54oKXFGXCXo9tFl2OTeupD4Cxg2UkC87PKibbyqKn3KF5hz65yjLSm8UlxCga1nFHRfCZQl6DmxXXfDpIPXqMCT78WtWmaBXgQLk3v-A0TF8wQ8DZNDaotzfovTyarZf9xhRcb5o1QYgCXoxvIaWcAZuYet1oAGDT3KWoEcdJIefZlz6cZH-4296jG4-_u-xe3J1X56iPdpJC6HZPtpZNWv7DN0wP1fzthkFWQtXOUK7R8eT6dkouDT83fTD6fSrvzv7dP4LnfExmg
linkProvider	ProQuest
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LbxMxEB6VFAEX3o-FQo0E4gCrZu1d23tAqIVWrZpGFSqoN-P12hAJJSGbEPGn-I14vI8SEL31wHU9trz2Ny_bMwPwLEmLQohCx9pleZxqLuPC65m4MJntM53l_RBI-3EghkN5epofr8HPNhYGn1W2MjEI6nJi8Ix8i3pfLRUpz-ib6bcYq0bh7WpbQqOGxaH9sfQuW_X64J3f3-eU7u2evN2Pm6oCsckkm8fcUeOtIJP1rRDGSss01SwtM-a0FNrjW1LmkgJDLMtSalcKa3Nu0DbijAvmx70E6ynzc-nB-s7u8Ph95-Jl3ppqQ3Mk36q8Nk3wkW99V5rHyxX1F6oE_K0LflOGf9zOBqW3d-N_W66bcL0xr8l2zQ-3YM2Ob8OVo-YBwR3gni1mlowqMp6QamG-kDkewRFdEU08043wAKQk0xn2QMySUCroLny4kFnfg954MrYPgEjqQS5tYqjL0qQQuXUlZuETGMXschFB0u6oMk1edSzv8VUF_0pyVaNAeRSogAK1jOBl12daZxU5l3oHgdJRYkbw8GEy-6waAaNcrjnH-TnK0sKb_QWGIFtWcseFcGkEmwgzVYfXdnJNbYd0Rt4rlxG8CBQo2fwPGN0EaPhlwBxhK5QbK5ReIpnV5haTqpGIlToDZARPu2bsia_8xnayCDRo0krOIrhfs0D304xLvy7SD_6q5Ymzwf-9dg_Pn8smXN0_ORqowcHw8BFcozWnxjTdgN58trCP4bL5Ph9VsycNpxP4dNHc8gsENIjh
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwEB5BQVUvlFdLaKFGQuIAUTd2YjvH0rICUVYVj6o3y3FsWAllV0mW_n08zoMuLwlxjceWM57xzNjzjQGeJmlRCFHoWLssj1PNZVx4OxMXJrMTprN8EoC056diNpMXF_nZFRR_yHYfriQ7TANWaaraw2XpOhWX_LDxVirB5NnuDjKPL6_DjdRHMpjU9f7D-RhyZd67GaAyv-23Zo5C1f5f9-Yrxumn29JghKbb_z_923Crd0DJUScxd-Care7C5rv-iv0ecC84tSXzhlQL0qzMF9LiIRXRDdHEi-UcjwhKsqyxB64qCY_p3IdP01cfj1_H_eMKsckka2PuqPHOoMkmVghjpWWaapaWGXNaCu3VXFLmkgKRpmUptSuFtTk36CJyxgXbgY1qUdkHQCT1YiBtYqjL0qQQuXUl1qkTiPN1uYggGXisTF95HB_A-KpCBCK56hiiPENUYIi6jOD52GfZ1d34K_VLXLqREmtmhw-L-rPqVVC5XHOO83OUpYV3jAsE6VpWcseFcGkEB7jwqgOgjpqvjkLBHx-3ygieBQrUff8DRvcQBs8GrKK1Rrm_Rul11qw3D8Kl-j2jUVT46YiUZzSCJ2Mz9sQ8uMouVoEGnT7JWQS7nVCOP8249HyRfvAXgwT-GPzPvHv4b-QHsHl2MlWnb2Zv92CLdjIc03QfNtp6ZR_BTfOtnTf146CI3wHRoi4I
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=There+is+no+such+thing+as+a+validated+prediction+model&rft.jtitle=BMC+medicine&rft.au=Van+Calster%2C+Ben&rft.au=Steyerberg%2C+Ewout+W&rft.au=Wynants%2C+Laure&rft.au=van+Smeden%2C+Maarten&rft.date=2023-02-24&rft.pub=BioMed+Central+Ltd&rft.issn=1741-7015&rft.eissn=1741-7015&rft.volume=21&rft.issue=1&rft_id=info:doi/10.1186%2Fs12916-023-02779-w&rft.externalDocID=A738580108
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1741-7015&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1741-7015&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1741-7015&client=summon