• Medientyp: E-Artikel
  • Titel: Predictive value of Prostate Specific Antigen variations in the last week of salvage radiotherapy for biochemical recurrence of prostate cancer after surgery: A practical approach
  • Beteiligte: Vigna‐Taglianti, Riccardo; Boriano, Alberto; Gianello, Luca; Melano, Antonella; Bergesio, Fabrizio; Merlotti, Anna Maria; Reali, Alessia; Petrucci, Rachele; Russi, Elvio G.
  • Erschienen: Wiley, 2020
  • Erschienen in: Cancer Reports
  • Sprache: Englisch
  • DOI: 10.1002/cnr2.1285
  • ISSN: 2573-8348
  • Schlagwörter: Cancer Research ; Oncology
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>About a third of patients who underwent radical prostatectomy for prostate cancer (Pca) develop a biochemical failure (BF) within 10 years from surgery, and about a half of them receive salvage radiation therapy (SRT). Factors to predict risk to relapse after SRT are still lacking. Dynamic models, based on the assessment of changes in Prostate Specific Antigen (PSA) postsurgery seem to show good reliability.</jats:p></jats:sec><jats:sec><jats:title>Aims</jats:title><jats:p>The goal of the study was to identify a simple analytical method for the postsalvage radiation therapy biochemical failure (post‐SRTBF) prediction before the end of the SRT, regardless of the PSA value at the beginning of the treatment (PSA start), measuring the PSA values at the start and 1 week before the end of SRT.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>In a series of 83 patients treated with SRT for BF of Pca we measured PSA values at the first day and 1 week before the end of SRT. These values were used to define an analytical method for the post‐SRTBF prediction.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>PSA value in patients without post‐SRTBF show a significant difference in term of difference during the SRT with respect to patients with post‐SRTBF. Starting from this difference, we identified a simple and practical analytical method for the post‐SRTBF prediction before the end of the SRT. The data corresponds with the model and the analytical method is highly predictive (Sensitivity = 81%, Specificity = 85%, Accuracy = 83%).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This study offers a new tool to early predict Pca relapse overtime and to select patients who can benefit from an early additional systemic treatment.</jats:p></jats:sec>
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