Cargando…

Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer

PURPOSE: Determining the frequency and distribution of pathogenic germline variants (PGVs) in Austrian prostate cancer (PCa) patients and to assess the accuracy of different clinical risk scores to correctly predict PGVs. METHODS: This cross-sectional study included 313 men with advanced PCa. A comp...

Descripción completa

Detalles Bibliográficos
Autores principales: Rebhan, Katharina, Stelzer, Philipp D., Pradere, Benjamin, Rajwa, Pawel, Kramer, Gero, Hofmann, Bernd, Resch, Irene, Yurdakul, Ozan, Laccone, Franco A., Bujalkova, Maria Gerykova, Smogavec, Mateja, Tan, Yen Y., Ristl, Robin, Shariat, Shahrokh F., Egger, Gerda, Hassler, Melanie R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415416/
https://www.ncbi.nlm.nih.gov/pubmed/37528288
http://dx.doi.org/10.1007/s00345-023-04535-4
_version_ 1785087534508802048
author Rebhan, Katharina
Stelzer, Philipp D.
Pradere, Benjamin
Rajwa, Pawel
Kramer, Gero
Hofmann, Bernd
Resch, Irene
Yurdakul, Ozan
Laccone, Franco A.
Bujalkova, Maria Gerykova
Smogavec, Mateja
Tan, Yen Y.
Ristl, Robin
Shariat, Shahrokh F.
Egger, Gerda
Hassler, Melanie R.
author_facet Rebhan, Katharina
Stelzer, Philipp D.
Pradere, Benjamin
Rajwa, Pawel
Kramer, Gero
Hofmann, Bernd
Resch, Irene
Yurdakul, Ozan
Laccone, Franco A.
Bujalkova, Maria Gerykova
Smogavec, Mateja
Tan, Yen Y.
Ristl, Robin
Shariat, Shahrokh F.
Egger, Gerda
Hassler, Melanie R.
author_sort Rebhan, Katharina
collection PubMed
description PURPOSE: Determining the frequency and distribution of pathogenic germline variants (PGVs) in Austrian prostate cancer (PCa) patients and to assess the accuracy of different clinical risk scores to correctly predict PGVs. METHODS: This cross-sectional study included 313 men with advanced PCa. A comprehensive personal and family history was obtained based on predefined questionnaires. Germline DNA sequencing was performed between 2019 and 2021 irrespective of family history, metastatic or castration status or age at diagnosis. Clinical risk scores for hereditary cancer syndromes were evaluated and a PCa-specific score was developed to assess the presence of PGVs. RESULTS: PGV presence was associated with metastasis (p = 0.047) and castration resistance (p = 0.011), but not with personal cancer history or with relatives with any type of cancer. Clinical risk scores (Manchester score, PREMM5 score, Amsterdam II criteria or Johns Hopkins criteria) showed low sensitivities (3.3–20%) for assessing the probability of PGV presence. A score specifically designed for PCa patients stratifying patients into low- or high-risk regarding PGV probability, correctly classified all PGV carriers as high-risk, whereas a third of PCa patients without PGVs was classified as low risk of the presence of PGVs. CONCLUSION: Application of common clinical risk scores based on family history are not suitable to identify PCa patients with high PGV probabilities. A PCa-specific score stratified PCa patients into low- or high-risk of PGV presence with sufficient accuracy, and germline DNA sequencing may be omitted in patients with a low score. Further studies are needed to evaluate the score. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00345-023-04535-4.
format Online
Article
Text
id pubmed-10415416
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-104154162023-08-12 Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer Rebhan, Katharina Stelzer, Philipp D. Pradere, Benjamin Rajwa, Pawel Kramer, Gero Hofmann, Bernd Resch, Irene Yurdakul, Ozan Laccone, Franco A. Bujalkova, Maria Gerykova Smogavec, Mateja Tan, Yen Y. Ristl, Robin Shariat, Shahrokh F. Egger, Gerda Hassler, Melanie R. World J Urol Topic Paper PURPOSE: Determining the frequency and distribution of pathogenic germline variants (PGVs) in Austrian prostate cancer (PCa) patients and to assess the accuracy of different clinical risk scores to correctly predict PGVs. METHODS: This cross-sectional study included 313 men with advanced PCa. A comprehensive personal and family history was obtained based on predefined questionnaires. Germline DNA sequencing was performed between 2019 and 2021 irrespective of family history, metastatic or castration status or age at diagnosis. Clinical risk scores for hereditary cancer syndromes were evaluated and a PCa-specific score was developed to assess the presence of PGVs. RESULTS: PGV presence was associated with metastasis (p = 0.047) and castration resistance (p = 0.011), but not with personal cancer history or with relatives with any type of cancer. Clinical risk scores (Manchester score, PREMM5 score, Amsterdam II criteria or Johns Hopkins criteria) showed low sensitivities (3.3–20%) for assessing the probability of PGV presence. A score specifically designed for PCa patients stratifying patients into low- or high-risk regarding PGV probability, correctly classified all PGV carriers as high-risk, whereas a third of PCa patients without PGVs was classified as low risk of the presence of PGVs. CONCLUSION: Application of common clinical risk scores based on family history are not suitable to identify PCa patients with high PGV probabilities. A PCa-specific score stratified PCa patients into low- or high-risk of PGV presence with sufficient accuracy, and germline DNA sequencing may be omitted in patients with a low score. Further studies are needed to evaluate the score. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00345-023-04535-4. Springer Berlin Heidelberg 2023-08-01 2023 /pmc/articles/PMC10415416/ /pubmed/37528288 http://dx.doi.org/10.1007/s00345-023-04535-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Topic Paper
Rebhan, Katharina
Stelzer, Philipp D.
Pradere, Benjamin
Rajwa, Pawel
Kramer, Gero
Hofmann, Bernd
Resch, Irene
Yurdakul, Ozan
Laccone, Franco A.
Bujalkova, Maria Gerykova
Smogavec, Mateja
Tan, Yen Y.
Ristl, Robin
Shariat, Shahrokh F.
Egger, Gerda
Hassler, Melanie R.
Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer
title Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer
title_full Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer
title_fullStr Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer
title_full_unstemmed Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer
title_short Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer
title_sort performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer
topic Topic Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415416/
https://www.ncbi.nlm.nih.gov/pubmed/37528288
http://dx.doi.org/10.1007/s00345-023-04535-4
work_keys_str_mv AT rebhankatharina performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT stelzerphilippd performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT praderebenjamin performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT rajwapawel performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT kramergero performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT hofmannbernd performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT reschirene performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT yurdakulozan performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT lacconefrancoa performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT bujalkovamariagerykova performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT smogavecmateja performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT tanyeny performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT ristlrobin performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT shariatshahrokhf performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT eggergerda performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer
AT hasslermelanier performanceofclinicalriskscoresandpredictionmodelstoidentifypathogenicgermlinevariantsinpatientswithadvancedprostatecancer