File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Genetic polymorphisms at 19q13.33 are associated with [−2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer

TitleGenetic polymorphisms at 19q13.33 are associated with [−2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer
Authors
KeywordsNRI
p2PSA
prostate cancer
prostate health index
SNP
Issue Date2021
Citation
Prostate, 2021, v. 81, n. 13, p. 971-982 How to Cite?
AbstractBackground: Prostate health index (phi), a derivative of [−2]proPSA (p2PSA), has shown better accuracy than prostate-specific antigen (PSA) in prostate cancer (PCa) detection. The present study was to investigate whether previously identified PSA-associated single nucleotide polymorphisms (SNPs) influence p2PSA or phi levels and lead to potential clinical utility. Methods: We conducted an observational prospective study with 2268 consecutive patients who underwent prostate biopsy in three tertiary medical centers from August 2013 to March 2019. Genotyping data of the 46 candidate genes with a ± 100 kb window were tested for association with p2PSA and phi levels using linear regression. Multivariable logistic regression models were performed and internally validated using repeated tenfold cross-validation. We further calculated personalized phi cutoff values based on the significant genotypes. Discriminative performance was assessed using decision curve analysis and net reclassification improvement (NRI) index. Results: We detected 11 significant variants at 19q13.33 which were p2PSA-associated independent of PCa. The most significant SNP, rs198978 in KLK2 (Pcombined = 5.73 × 10−9), was also associated with phi values (Pcombined = 3.20 × 10−6). Compared to the two commonly used phi cutoffs of 27.0 and 36.0, the personalized phi cutoffs had a significant NRI for PCa ranged from 5.23% to 9.70% among men carrying variant types (all p <.01). Conclusion: Rs198978, is independently associated with p2PSA values, and can improve the diagnostic ability of phi for PCa using personalized cutoff values.
Persistent Identifierhttp://hdl.handle.net/10722/314411
ISSN
2023 Impact Factor: 2.6
2023 SCImago Journal Rankings: 1.032
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHuang, Da-
dc.contributor.authorRuan, Xiaohao-
dc.contributor.authorWu, Yishuo-
dc.contributor.authorLin, Xiaoling-
dc.contributor.authorHuang, Jingyi-
dc.contributor.authorYe, Dingwei-
dc.contributor.authorGao, Yi-
dc.contributor.authorDing, Qiang-
dc.contributor.authorXu, Danfeng-
dc.contributor.authorNa, Rong-
dc.date.accessioned2022-07-20T12:03:59Z-
dc.date.available2022-07-20T12:03:59Z-
dc.date.issued2021-
dc.identifier.citationProstate, 2021, v. 81, n. 13, p. 971-982-
dc.identifier.issn0270-4137-
dc.identifier.urihttp://hdl.handle.net/10722/314411-
dc.description.abstractBackground: Prostate health index (phi), a derivative of [−2]proPSA (p2PSA), has shown better accuracy than prostate-specific antigen (PSA) in prostate cancer (PCa) detection. The present study was to investigate whether previously identified PSA-associated single nucleotide polymorphisms (SNPs) influence p2PSA or phi levels and lead to potential clinical utility. Methods: We conducted an observational prospective study with 2268 consecutive patients who underwent prostate biopsy in three tertiary medical centers from August 2013 to March 2019. Genotyping data of the 46 candidate genes with a ± 100 kb window were tested for association with p2PSA and phi levels using linear regression. Multivariable logistic regression models were performed and internally validated using repeated tenfold cross-validation. We further calculated personalized phi cutoff values based on the significant genotypes. Discriminative performance was assessed using decision curve analysis and net reclassification improvement (NRI) index. Results: We detected 11 significant variants at 19q13.33 which were p2PSA-associated independent of PCa. The most significant SNP, rs198978 in KLK2 (Pcombined = 5.73 × 10−9), was also associated with phi values (Pcombined = 3.20 × 10−6). Compared to the two commonly used phi cutoffs of 27.0 and 36.0, the personalized phi cutoffs had a significant NRI for PCa ranged from 5.23% to 9.70% among men carrying variant types (all p <.01). Conclusion: Rs198978, is independently associated with p2PSA values, and can improve the diagnostic ability of phi for PCa using personalized cutoff values.-
dc.languageeng-
dc.relation.ispartofProstate-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectNRI-
dc.subjectp2PSA-
dc.subjectprostate cancer-
dc.subjectprostate health index-
dc.subjectSNP-
dc.titleGenetic polymorphisms at 19q13.33 are associated with [−2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1002/pros.24192-
dc.identifier.pmid34254325-
dc.identifier.pmcidPMC8456816-
dc.identifier.scopuseid_2-s2.0-85110598177-
dc.identifier.volume81-
dc.identifier.issue13-
dc.identifier.spage971-
dc.identifier.epage982-
dc.identifier.eissn1097-0045-
dc.identifier.isiWOS:000672224000001-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats