Predicting the outcome of salvage radiation therapy for recurrent prostate cancer after radical prostatectomy.

By A. Stephenson, P. Scardino, M. Kattan, T. Pisansky, K. Slawin, E. Klein, M. Anscher, J. Michalski, H. Sandler, D. Lin and 10 more. Journal of Clinical Oncology, 2007

917 citations recorded by the source corpus.

PURPOSE An increasing serum prostate-specific antigen (PSA) level is the initial sign of recurrent prostate cancer among patients treated with radical prostatectomy. Salvage radiation therapy (SRT) may eradicate locally recurrent cancer, but studies to distinguish local from systemic recurrence lack adequate sensitivity and specificity. We developed a nomogram to predict the probability of cancer control at 6 years after SRT for PSA-defined recurrence. PATIENTS AND METHODS Using multivariable Cox regression analysis, we constructed a model to predict the probability of disease progression after SRT in a multi-institutional cohort of 1,540 patients. RESULTS The 6-year progression-free probability was 32% (95% CI, 28% to 35%) overall. Forty-eight percent (95% CI, 40% to 56%) of patients treated with SRT alone at PSA levels of 0.50 ng/mL or lower were disease free at 6 years, including 41% (95% CI, 31% to 51%) who also had a PSA doubling time of 10 months or less or poorly differentiated (Gleason grade 8 to 10) cancer. Significant variables in the model were PSA level before SRT (P < .001), prostatectomy Gleason grade (P < .001), PSA doubling time (P < .001), surgical margins (P < .001), androgen-deprivation therapy before or during SRT (P < .001), and lymph node metastasis (P = .019). The resultant nomogram was internally validated and had a concordance index of 0.69. CONCLUSION Nearly half of patients with recurrent prostate cancer after radical prostatectomy have a long-term PSA response to SRT when treatment is administered at the earliest sign of recurrence. The nomogram we developed predicts the outcome of SRT and should prove valuable for medical decision making for patients with a rising PSA level.

Subfields: Pulmonary and Respiratory Medicine, Rheumatology

View Paper: https://www.semanticscholar.org/paper/46090a7ba0f0b95b366f50345b8bddd27238e72f

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In Pulmonary and Respiratory Medicine

  1. A. Heidenreich
  2. Michel Bolla
  3. N. Mottet
  4. J. Bellmunt
  5. V. Matveev
  6. Steven Joniau
  7. F. Zattoni
  8. Thomas Wiegel

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