Pre-operative prediction of extracapsular extension of prostate cancer: first external validation of the PRECE model on an independent dataset

Introduction The PRECE is a model predicting the risk of extracapsular extension (ECE) of prostate cancer: it has been developed on more than 6000 patients who underwent robotic radical prostatectomy (RARP) at the Global Robotic Institute, FL, USA. Up to now, it is the single tool predicting either...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International urology and nephrology 2023-01, Vol.55 (1), p.93-97
Hauptverfasser: Sighinolfi, Maria Chiara, Assumma, Simone, Cassani, Alessandra, Sarchi, Luca, Calcagnile, Tommaso, Terzoni, Stefano, Sandri, Marco, Micali, Salvatore, Noel, Jonathan, Moschovas, M. Covas, Seetharam, Bhat, Bozzini, Giorgio, Patel, Vipul, Rocco, Bernardo
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 97
container_issue 1
container_start_page 93
container_title International urology and nephrology
container_volume 55
creator Sighinolfi, Maria Chiara
Assumma, Simone
Cassani, Alessandra
Sarchi, Luca
Calcagnile, Tommaso
Terzoni, Stefano
Sandri, Marco
Micali, Salvatore
Noel, Jonathan
Moschovas, M. Covas
Seetharam, Bhat
Bozzini, Giorgio
Patel, Vipul
Rocco, Bernardo
description Introduction The PRECE is a model predicting the risk of extracapsular extension (ECE) of prostate cancer: it has been developed on more than 6000 patients who underwent robotic radical prostatectomy (RARP) at the Global Robotic Institute, FL, USA. Up to now, it is the single tool predicting either the side and the amount of ECE. The model has a free user-friendly interface and is made up from simple and available covariates, namely age, PSA, cT, GS and percent of positive core, the latter topographically distributed within the prostate gland. Despite the successful performance at internal validation, the model is still lacking an external validation (EV). The aim of the paper is to externally validate the PRECE model on an Italian cohort of patients elected to RARP. Methods 269 prostatic lobes from 141 patients represented the validation dataset. The EV was performed with the receiver operating characteristics (ROC) curves and calibration, to address the ability of PRECE to discriminate between patients with or without ECE. Results Overall, an ECE was found in 91 out of the 269 prostatic lobes (34%). Twenty-five patients out of pT3 had a bilateral ECE. The ROC curve showed an AUC of 0.80 (95% CI 0.74–0.85). Sensitivity and specificity were 77% and 69%, respectively. The model showed an acceptable calibration with tendency towards overestimation. Conclusions From the current EV, the PRECE displays a good predictive performance to discriminate between cases with and without ECE; despite preliminary, outcomes may support the generalizability of the model in dataset other than the development one.
doi_str_mv 10.1007/s11255-022-03365-4
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2720429434</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2760025062</sourcerecordid><originalsourceid>FETCH-LOGICAL-c375t-18ef885c595cf1ec3001d8c956652966097dea5aae9d13fd41e81a1ee21624a3</originalsourceid><addsrcrecordid>eNp9kctu1TAQhiMEojdegAWyxIZNYGzHjsMOHR0KUqVWVffWYE8gVY4TbKeCl-CZcXpOAbHoxrf5_Fvjr6pecnjLAdp3iXOhVA1C1CClVnXzpDrmqpW1UKZ5-s_6qDpJ6RYAOgPwvDqSmhuujDqufl1FqqeZIubhjtgcyQ8uD1NgU8_oR47ocE7LiHHdUUiH0hynlDETcxgcxfesH2LK90wMOLI7HAePD0H5G7Gr6-1my3aTp5GVUwxsCJ5mKkPIrLCYKJ9Vz3ocE704zKfVzcftzeZTfXF5_nnz4aJ2slW55oZ6Y5RTnXI9JycBuDeuU1or0WkNXesJFSJ1nsveN5wMR04kuBYNytPqzT62tPF9oZTtbkiOxhEDTUuyohXQiK6RTUFf_4feTsva4kppAKFAi0KJPeXKv6RIvZ3jsMP403Kwqyy7l2WLLHsvy67Rrw7Ry5cd-T9XHuwUQO6BVErhK8W_bz8S-xvIIKEa</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2760025062</pqid></control><display><type>article</type><title>Pre-operative prediction of extracapsular extension of prostate cancer: first external validation of the PRECE model on an independent dataset</title><source>MEDLINE</source><source>SpringerNature Journals</source><creator>Sighinolfi, Maria Chiara ; Assumma, Simone ; Cassani, Alessandra ; Sarchi, Luca ; Calcagnile, Tommaso ; Terzoni, Stefano ; Sandri, Marco ; Micali, Salvatore ; Noel, Jonathan ; Moschovas, M. Covas ; Seetharam, Bhat ; Bozzini, Giorgio ; Patel, Vipul ; Rocco, Bernardo</creator><creatorcontrib>Sighinolfi, Maria Chiara ; Assumma, Simone ; Cassani, Alessandra ; Sarchi, Luca ; Calcagnile, Tommaso ; Terzoni, Stefano ; Sandri, Marco ; Micali, Salvatore ; Noel, Jonathan ; Moschovas, M. Covas ; Seetharam, Bhat ; Bozzini, Giorgio ; Patel, Vipul ; Rocco, Bernardo</creatorcontrib><description>Introduction The PRECE is a model predicting the risk of extracapsular extension (ECE) of prostate cancer: it has been developed on more than 6000 patients who underwent robotic radical prostatectomy (RARP) at the Global Robotic Institute, FL, USA. Up to now, it is the single tool predicting either the side and the amount of ECE. The model has a free user-friendly interface and is made up from simple and available covariates, namely age, PSA, cT, GS and percent of positive core, the latter topographically distributed within the prostate gland. Despite the successful performance at internal validation, the model is still lacking an external validation (EV). The aim of the paper is to externally validate the PRECE model on an Italian cohort of patients elected to RARP. Methods 269 prostatic lobes from 141 patients represented the validation dataset. The EV was performed with the receiver operating characteristics (ROC) curves and calibration, to address the ability of PRECE to discriminate between patients with or without ECE. Results Overall, an ECE was found in 91 out of the 269 prostatic lobes (34%). Twenty-five patients out of pT3 had a bilateral ECE. The ROC curve showed an AUC of 0.80 (95% CI 0.74–0.85). Sensitivity and specificity were 77% and 69%, respectively. The model showed an acceptable calibration with tendency towards overestimation. Conclusions From the current EV, the PRECE displays a good predictive performance to discriminate between cases with and without ECE; despite preliminary, outcomes may support the generalizability of the model in dataset other than the development one.</description><identifier>ISSN: 1573-2584</identifier><identifier>ISSN: 0301-1623</identifier><identifier>EISSN: 1573-2584</identifier><identifier>DOI: 10.1007/s11255-022-03365-4</identifier><identifier>PMID: 36181585</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Cancer surgery ; Datasets ; Extranodal Extension ; Humans ; Male ; Medicine ; Medicine &amp; Public Health ; Neoplasm Staging ; Nephrology ; Prostate - pathology ; Prostate cancer ; Prostate-Specific Antigen ; Prostatectomy ; Prostatic Neoplasms - pathology ; Prostatic Neoplasms - surgery ; Retrospective Studies ; Robotic surgery ; Urological surgery ; Urology ; Urology - Original Paper</subject><ispartof>International urology and nephrology, 2023-01, Vol.55 (1), p.93-97</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2022. The Author(s), under exclusive licence to Springer Nature B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-18ef885c595cf1ec3001d8c956652966097dea5aae9d13fd41e81a1ee21624a3</citedby><cites>FETCH-LOGICAL-c375t-18ef885c595cf1ec3001d8c956652966097dea5aae9d13fd41e81a1ee21624a3</cites><orcidid>0000-0001-7211-0485</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11255-022-03365-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11255-022-03365-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36181585$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sighinolfi, Maria Chiara</creatorcontrib><creatorcontrib>Assumma, Simone</creatorcontrib><creatorcontrib>Cassani, Alessandra</creatorcontrib><creatorcontrib>Sarchi, Luca</creatorcontrib><creatorcontrib>Calcagnile, Tommaso</creatorcontrib><creatorcontrib>Terzoni, Stefano</creatorcontrib><creatorcontrib>Sandri, Marco</creatorcontrib><creatorcontrib>Micali, Salvatore</creatorcontrib><creatorcontrib>Noel, Jonathan</creatorcontrib><creatorcontrib>Moschovas, M. Covas</creatorcontrib><creatorcontrib>Seetharam, Bhat</creatorcontrib><creatorcontrib>Bozzini, Giorgio</creatorcontrib><creatorcontrib>Patel, Vipul</creatorcontrib><creatorcontrib>Rocco, Bernardo</creatorcontrib><title>Pre-operative prediction of extracapsular extension of prostate cancer: first external validation of the PRECE model on an independent dataset</title><title>International urology and nephrology</title><addtitle>Int Urol Nephrol</addtitle><addtitle>Int Urol Nephrol</addtitle><description>Introduction The PRECE is a model predicting the risk of extracapsular extension (ECE) of prostate cancer: it has been developed on more than 6000 patients who underwent robotic radical prostatectomy (RARP) at the Global Robotic Institute, FL, USA. Up to now, it is the single tool predicting either the side and the amount of ECE. The model has a free user-friendly interface and is made up from simple and available covariates, namely age, PSA, cT, GS and percent of positive core, the latter topographically distributed within the prostate gland. Despite the successful performance at internal validation, the model is still lacking an external validation (EV). The aim of the paper is to externally validate the PRECE model on an Italian cohort of patients elected to RARP. Methods 269 prostatic lobes from 141 patients represented the validation dataset. The EV was performed with the receiver operating characteristics (ROC) curves and calibration, to address the ability of PRECE to discriminate between patients with or without ECE. Results Overall, an ECE was found in 91 out of the 269 prostatic lobes (34%). Twenty-five patients out of pT3 had a bilateral ECE. The ROC curve showed an AUC of 0.80 (95% CI 0.74–0.85). Sensitivity and specificity were 77% and 69%, respectively. The model showed an acceptable calibration with tendency towards overestimation. Conclusions From the current EV, the PRECE displays a good predictive performance to discriminate between cases with and without ECE; despite preliminary, outcomes may support the generalizability of the model in dataset other than the development one.</description><subject>Cancer surgery</subject><subject>Datasets</subject><subject>Extranodal Extension</subject><subject>Humans</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>Neoplasm Staging</subject><subject>Nephrology</subject><subject>Prostate - pathology</subject><subject>Prostate cancer</subject><subject>Prostate-Specific Antigen</subject><subject>Prostatectomy</subject><subject>Prostatic Neoplasms - pathology</subject><subject>Prostatic Neoplasms - surgery</subject><subject>Retrospective Studies</subject><subject>Robotic surgery</subject><subject>Urological surgery</subject><subject>Urology</subject><subject>Urology - Original Paper</subject><issn>1573-2584</issn><issn>0301-1623</issn><issn>1573-2584</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp9kctu1TAQhiMEojdegAWyxIZNYGzHjsMOHR0KUqVWVffWYE8gVY4TbKeCl-CZcXpOAbHoxrf5_Fvjr6pecnjLAdp3iXOhVA1C1CClVnXzpDrmqpW1UKZ5-s_6qDpJ6RYAOgPwvDqSmhuujDqufl1FqqeZIubhjtgcyQ8uD1NgU8_oR47ocE7LiHHdUUiH0hynlDETcxgcxfesH2LK90wMOLI7HAePD0H5G7Gr6-1my3aTp5GVUwxsCJ5mKkPIrLCYKJ9Vz3ocE704zKfVzcftzeZTfXF5_nnz4aJ2slW55oZ6Y5RTnXI9JycBuDeuU1or0WkNXesJFSJ1nsveN5wMR04kuBYNytPqzT62tPF9oZTtbkiOxhEDTUuyohXQiK6RTUFf_4feTsva4kppAKFAi0KJPeXKv6RIvZ3jsMP403Kwqyy7l2WLLHsvy67Rrw7Ry5cd-T9XHuwUQO6BVErhK8W_bz8S-xvIIKEa</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Sighinolfi, Maria Chiara</creator><creator>Assumma, Simone</creator><creator>Cassani, Alessandra</creator><creator>Sarchi, Luca</creator><creator>Calcagnile, Tommaso</creator><creator>Terzoni, Stefano</creator><creator>Sandri, Marco</creator><creator>Micali, Salvatore</creator><creator>Noel, Jonathan</creator><creator>Moschovas, M. Covas</creator><creator>Seetharam, Bhat</creator><creator>Bozzini, Giorgio</creator><creator>Patel, Vipul</creator><creator>Rocco, Bernardo</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-7211-0485</orcidid></search><sort><creationdate>20230101</creationdate><title>Pre-operative prediction of extracapsular extension of prostate cancer: first external validation of the PRECE model on an independent dataset</title><author>Sighinolfi, Maria Chiara ; Assumma, Simone ; Cassani, Alessandra ; Sarchi, Luca ; Calcagnile, Tommaso ; Terzoni, Stefano ; Sandri, Marco ; Micali, Salvatore ; Noel, Jonathan ; Moschovas, M. Covas ; Seetharam, Bhat ; Bozzini, Giorgio ; Patel, Vipul ; Rocco, Bernardo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-18ef885c595cf1ec3001d8c956652966097dea5aae9d13fd41e81a1ee21624a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Cancer surgery</topic><topic>Datasets</topic><topic>Extranodal Extension</topic><topic>Humans</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine &amp; Public Health</topic><topic>Neoplasm Staging</topic><topic>Nephrology</topic><topic>Prostate - pathology</topic><topic>Prostate cancer</topic><topic>Prostate-Specific Antigen</topic><topic>Prostatectomy</topic><topic>Prostatic Neoplasms - pathology</topic><topic>Prostatic Neoplasms - surgery</topic><topic>Retrospective Studies</topic><topic>Robotic surgery</topic><topic>Urological surgery</topic><topic>Urology</topic><topic>Urology - Original Paper</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sighinolfi, Maria Chiara</creatorcontrib><creatorcontrib>Assumma, Simone</creatorcontrib><creatorcontrib>Cassani, Alessandra</creatorcontrib><creatorcontrib>Sarchi, Luca</creatorcontrib><creatorcontrib>Calcagnile, Tommaso</creatorcontrib><creatorcontrib>Terzoni, Stefano</creatorcontrib><creatorcontrib>Sandri, Marco</creatorcontrib><creatorcontrib>Micali, Salvatore</creatorcontrib><creatorcontrib>Noel, Jonathan</creatorcontrib><creatorcontrib>Moschovas, M. Covas</creatorcontrib><creatorcontrib>Seetharam, Bhat</creatorcontrib><creatorcontrib>Bozzini, Giorgio</creatorcontrib><creatorcontrib>Patel, Vipul</creatorcontrib><creatorcontrib>Rocco, Bernardo</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium &amp; Calcified Tissue Abstracts</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>International urology and nephrology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sighinolfi, Maria Chiara</au><au>Assumma, Simone</au><au>Cassani, Alessandra</au><au>Sarchi, Luca</au><au>Calcagnile, Tommaso</au><au>Terzoni, Stefano</au><au>Sandri, Marco</au><au>Micali, Salvatore</au><au>Noel, Jonathan</au><au>Moschovas, M. Covas</au><au>Seetharam, Bhat</au><au>Bozzini, Giorgio</au><au>Patel, Vipul</au><au>Rocco, Bernardo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pre-operative prediction of extracapsular extension of prostate cancer: first external validation of the PRECE model on an independent dataset</atitle><jtitle>International urology and nephrology</jtitle><stitle>Int Urol Nephrol</stitle><addtitle>Int Urol Nephrol</addtitle><date>2023-01-01</date><risdate>2023</risdate><volume>55</volume><issue>1</issue><spage>93</spage><epage>97</epage><pages>93-97</pages><issn>1573-2584</issn><issn>0301-1623</issn><eissn>1573-2584</eissn><abstract>Introduction The PRECE is a model predicting the risk of extracapsular extension (ECE) of prostate cancer: it has been developed on more than 6000 patients who underwent robotic radical prostatectomy (RARP) at the Global Robotic Institute, FL, USA. Up to now, it is the single tool predicting either the side and the amount of ECE. The model has a free user-friendly interface and is made up from simple and available covariates, namely age, PSA, cT, GS and percent of positive core, the latter topographically distributed within the prostate gland. Despite the successful performance at internal validation, the model is still lacking an external validation (EV). The aim of the paper is to externally validate the PRECE model on an Italian cohort of patients elected to RARP. Methods 269 prostatic lobes from 141 patients represented the validation dataset. The EV was performed with the receiver operating characteristics (ROC) curves and calibration, to address the ability of PRECE to discriminate between patients with or without ECE. Results Overall, an ECE was found in 91 out of the 269 prostatic lobes (34%). Twenty-five patients out of pT3 had a bilateral ECE. The ROC curve showed an AUC of 0.80 (95% CI 0.74–0.85). Sensitivity and specificity were 77% and 69%, respectively. The model showed an acceptable calibration with tendency towards overestimation. Conclusions From the current EV, the PRECE displays a good predictive performance to discriminate between cases with and without ECE; despite preliminary, outcomes may support the generalizability of the model in dataset other than the development one.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>36181585</pmid><doi>10.1007/s11255-022-03365-4</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0001-7211-0485</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1573-2584
ispartof International urology and nephrology, 2023-01, Vol.55 (1), p.93-97
issn 1573-2584
0301-1623
1573-2584
language eng
recordid cdi_proquest_miscellaneous_2720429434
source MEDLINE; SpringerNature Journals
subjects Cancer surgery
Datasets
Extranodal Extension
Humans
Male
Medicine
Medicine & Public Health
Neoplasm Staging
Nephrology
Prostate - pathology
Prostate cancer
Prostate-Specific Antigen
Prostatectomy
Prostatic Neoplasms - pathology
Prostatic Neoplasms - surgery
Retrospective Studies
Robotic surgery
Urological surgery
Urology
Urology - Original Paper
title Pre-operative prediction of extracapsular extension of prostate cancer: first external validation of the PRECE model on an independent dataset
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T21%3A32%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Pre-operative%20prediction%20of%20extracapsular%20extension%20of%20prostate%20cancer:%20first%20external%20validation%20of%20the%20PRECE%20model%20on%20an%20independent%20dataset&rft.jtitle=International%20urology%20and%20nephrology&rft.au=Sighinolfi,%20Maria%20Chiara&rft.date=2023-01-01&rft.volume=55&rft.issue=1&rft.spage=93&rft.epage=97&rft.pages=93-97&rft.issn=1573-2584&rft.eissn=1573-2584&rft_id=info:doi/10.1007/s11255-022-03365-4&rft_dat=%3Cproquest_cross%3E2760025062%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2760025062&rft_id=info:pmid/36181585&rfr_iscdi=true