U. Can , A. Coskun , C. Canakci , B. Simsek , Y. Karaca , K. Sabuncu , O. Akca
{"title":"前列腺癌筛查的一个新指标：前列腺特异性抗原波动率","authors":"U. Can , A. Coskun , C. Canakci , B. Simsek , Y. Karaca , K. Sabuncu , O. Akca","doi":"10.1016/j.acuroe.2024.02.006","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>To evaluate whether PSA fluctuation can be used to predict the risk of prostate cancer.</p></div><div><h3>Materials and methods</h3><p>The study included 1244 patients who underwent prostate biopsy at Kartal Dr. Lutfi Kirdar City Hospital between 2013 and 2021 (848 in non-cancer; 396 in cancer). The patient's age, last two PSA values (PSA<sub>1</sub> and PSA<sub>2</sub>) within three months before the biopsy, the duration between two PSAs (days), prostate size (g) and PSA density (PSAD) were all recorded. PSA fluctuation rate (PSAfr) was defined as the change rate between two PSA values.</p></div><div><h3>Results</h3><p>PSAfr was significantly higher in the non-cancer group than in the prostate cancer group (15.2% (20.5) and 9.6% (14.4), <em>P</em> <!-->=<!--> <!-->.019). A Simple linear regression was used to examine the relationship between PSAfr and other factors such as age, PSA, PSAD, and prostate volume, but it was shown that these had no effect on PSA fluctuations. ROC analysis revealed a relatively low Area Under the Curve (AUC) for PSAfr (AUC, 0.584 (0.515–0.653)). However, the cut-off value of 12.35% was found to be significant, with a sensitivity of 58% and a specificity of 59% (<em>P</em>:.019, 95%CI). The odds ratio, adjusted for age, PSAD, and PSA2, was calculated as 0.545 (0.33−0.89) using logistic regression analysis to show the relationship between prostate cancer and PSAfr. As a result, those with high PSAfr were found to be 1.83 times less likely to be diagnosed with prostate cancer than those with low fluctuations.</p></div><div><h3>Conclusion</h3><p>PSAfr could be used in nomograms to predict prostate cancer risk and reduce the number of unnecessary biopsies.</p></div>","PeriodicalId":94291,"journal":{"name":"Actas urologicas espanolas","volume":"48 6","pages":"Pages 470-475"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new promising indicator in prostate cancer screening: Prostate-specific antigen fluctuation rate\",\"authors\":\"U. Can , A. Coskun , C. Canakci , B. Simsek , Y. Karaca , K. Sabuncu , O. Akca\",\"doi\":\"10.1016/j.acuroe.2024.02.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>To evaluate whether PSA fluctuation can be used to predict the risk of prostate cancer.</p></div><div><h3>Materials and methods</h3><p>The study included 1244 patients who underwent prostate biopsy at Kartal Dr. Lutfi Kirdar City Hospital between 2013 and 2021 (848 in non-cancer; 396 in cancer). The patient's age, last two PSA values (PSA<sub>1</sub> and PSA<sub>2</sub>) within three months before the biopsy, the duration between two PSAs (days), prostate size (g) and PSA density (PSAD) were all recorded. PSA fluctuation rate (PSAfr) was defined as the change rate between two PSA values.</p></div><div><h3>Results</h3><p>PSAfr was significantly higher in the non-cancer group than in the prostate cancer group (15.2% (20.5) and 9.6% (14.4), <em>P</em> <!-->=<!--> <!-->.019). A Simple linear regression was used to examine the relationship between PSAfr and other factors such as age, PSA, PSAD, and prostate volume, but it was shown that these had no effect on PSA fluctuations. ROC analysis revealed a relatively low Area Under the Curve (AUC) for PSAfr (AUC, 0.584 (0.515–0.653)). However, the cut-off value of 12.35% was found to be significant, with a sensitivity of 58% and a specificity of 59% (<em>P</em>:.019, 95%CI). The odds ratio, adjusted for age, PSAD, and PSA2, was calculated as 0.545 (0.33−0.89) using logistic regression analysis to show the relationship between prostate cancer and PSAfr. As a result, those with high PSAfr were found to be 1.83 times less likely to be diagnosed with prostate cancer than those with low fluctuations.</p></div><div><h3>Conclusion</h3><p>PSAfr could be used in nomograms to predict prostate cancer risk and reduce the number of unnecessary biopsies.</p></div>\",\"PeriodicalId\":94291,\"journal\":{\"name\":\"Actas urologicas espanolas\",\"volume\":\"48 6\",\"pages\":\"Pages 470-475\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Actas urologicas espanolas\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2173578624000131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Actas urologicas espanolas","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2173578624000131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new promising indicator in prostate cancer screening: Prostate-specific antigen fluctuation rate
Objectives
To evaluate whether PSA fluctuation can be used to predict the risk of prostate cancer.
Materials and methods
The study included 1244 patients who underwent prostate biopsy at Kartal Dr. Lutfi Kirdar City Hospital between 2013 and 2021 (848 in non-cancer; 396 in cancer). The patient's age, last two PSA values (PSA1 and PSA2) within three months before the biopsy, the duration between two PSAs (days), prostate size (g) and PSA density (PSAD) were all recorded. PSA fluctuation rate (PSAfr) was defined as the change rate between two PSA values.
Results
PSAfr was significantly higher in the non-cancer group than in the prostate cancer group (15.2% (20.5) and 9.6% (14.4), P = .019). A Simple linear regression was used to examine the relationship between PSAfr and other factors such as age, PSA, PSAD, and prostate volume, but it was shown that these had no effect on PSA fluctuations. ROC analysis revealed a relatively low Area Under the Curve (AUC) for PSAfr (AUC, 0.584 (0.515–0.653)). However, the cut-off value of 12.35% was found to be significant, with a sensitivity of 58% and a specificity of 59% (P:.019, 95%CI). The odds ratio, adjusted for age, PSAD, and PSA2, was calculated as 0.545 (0.33−0.89) using logistic regression analysis to show the relationship between prostate cancer and PSAfr. As a result, those with high PSAfr were found to be 1.83 times less likely to be diagnosed with prostate cancer than those with low fluctuations.
Conclusion
PSAfr could be used in nomograms to predict prostate cancer risk and reduce the number of unnecessary biopsies.
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