Dynamic prediction of metastases after radical prostatectomy for prostate cancer
Study Type – Prognosis (retrospective cohort) Level of Evidence 2a What’s known on the subject? and What does the study add? One of two problems plagues virtually are existing post‐prostatectomy prediction tools: either (1) they predict PSA recurrences (which are of unclear importance) or (2) the pr...
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| Veröffentlicht in: | BJU international Jg. 108; H. 11; S. 1762 - 1768 |
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| Sprache: | Englisch |
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Oxford, UK
Blackwell Publishing Ltd
01.12.2011
Wiley-Blackwell Wiley Subscription Services, Inc |
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| ISSN: | 1464-4096, 1464-410X, 1464-410X |
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| Abstract | Study Type – Prognosis (retrospective cohort)
Level of Evidence 2a
What’s known on the subject? and What does the study add?
One of two problems plagues virtually are existing post‐prostatectomy prediction tools: either (1) they predict PSA recurrences (which are of unclear importance) or (2) the predictions they make are anchored at the date of surgery and are not updated based on how patients evolve over the postoperative years.
Our prediction tool is a significant improvement over existing prediction tools in that it predicts the development of metastases which is a very important clinical endpoint that indicates incurable prostate cancer. Additionally, our tool allows for updated predictions at any point following radical prostatectomy by considering commonly available postoperative information (postoperative serum PSA and use of adjuvant therapies) to modify its risk predictions. The net result is a dynamic tool that renders clinically relevant predictions that change as the patient’s clinical status changes throughout the postoperative course.
OBJECTIVE
• To develop a dynamic algorithm that predicts the risk of metastases from any time point after radical prostatectomy (RP).
PATIENTS AND METHODS
• The study cohort consisted of 5741 RP patients who were treated from 1990–99.
• Patients were grouped into one of four clinical states at follow‐up: State1, prostate‐specific antigen (PSA) undetectable; State2, PSA 0.15–0.39 ng/mL; State3, PSA ≥0.4 ng/mL; and State4, previous androgen deprivation or radiation therapy.
• Follow‐up epochs (alive and at risk of systemic progression) at 0, 2, 4 and 6 years post‐RP, cumulative incidence curves and multistate Cox models were used to assess the risk of metastases over the ensuing 5‐year interval.
• Gleason score, seminal vesicle and surgical margin involvement, and PSA variables were evaluated as predictors.
RESULTS
• Median follow‐up was 11.7 years, with 4411, 4256 and 3983 patients followed with PSA at 2, 4 and 6 years, respectively.
• In total, 287 metastatic events occurred and the 5‐year risk of metastasis was 0.4%, 2.1%, 8.7% and 12.6% for men in States 1, 2, 3 and 4, respectively.
• Independent predictors of metastasis by group included seminal vesicle involvement (all groups), Gleason score (groups 1, 3 and 4), current PSA (groups 3 and 4) and maximum past PSA (group 4).
CONCLUSIONS
• We present a web‐based prognostic tool for patients undergoing RP that is valid at many time points after surgery.
• Our tool predicts the development of metastases. |
|---|---|
| AbstractList | Study Type - Prognosis (retrospective cohort) Level of Evidence2a What's known on the subject? and What does the study add? One of two problems plagues virtually are existing post-prostatectomy prediction tools: either (1) they predict PSA recurrences (which are of unclear importance) or (2) the predictions they make are anchored at the date of surgery and are not updated based on how patients evolve over the postoperative years. Our prediction tool is a significant improvement over existing prediction tools in that it predicts the development of metastases which is a very important clinical endpoint that indicates incurable prostate cancer. Additionally, our tool allows for updated predictions at any point following radical prostatectomy by considering commonly available postoperative information (postoperative serum PSA and use of adjuvant therapies) to modify its risk predictions. The net result is a dynamic tool that renders clinically relevant predictions that change as the patient's clinical status changes throughout the postoperative course. OBJECTIVE *To develop a dynamic algorithm that predicts the risk of metastases from any time point after radical prostatectomy (RP). PATIENTS AND METHODS *The study cohort consisted of 5741 RP patients who were treated from 1990-99. *Patients were grouped into one of four clinical states at follow-up: State1, prostate-specific antigen (PSA) undetectable; State2, PSA 0.15-0.39 ng/mL; State3, PSA ≥0.4 ng/mL; and State4, previous androgen deprivation or radiation therapy. *Follow-up epochs (alive and at risk of systemic progression) at 0, 2, 4 and 6 years post-RP, cumulative incidence curves and multistate Cox models were used to assess the risk of metastases over the ensuing 5-year interval. *Gleason score, seminal vesicle and surgical margin involvement, and PSA variables were evaluated as predictors. RESULTS *Median follow-up was 11.7 years, with 4411, 4256 and 3983 patients followed with PSA at 2, 4 and 6 years, respectively. *In total, 287 metastatic events occurred and the 5-year risk of metastasis was 0.4%, 2.1%, 8.7% and 12.6% for men in States 1, 2, 3 and 4, respectively. *Independent predictors of metastasis by group included seminal vesicle involvement (all groups), Gleason score (groups 1, 3 and 4), current PSA (groups 3 and 4) and maximum past PSA (group 4). CONCLUSIONS *We present a web-based prognostic tool for patients undergoing RP that is valid at many time points after surgery. *Our tool predicts the development of metastases. [PUBLICATION ABSTRACT] What's known on the subject? and What does the study add? One of two problems plagues virtually are existing post-prostatectomy prediction tools: either (1) they predict PSA recurrences (which are of unclear importance) or (2) the predictions they make are anchored at the date of surgery and are not updated based on how patients evolve over the postoperative years. Our prediction tool is a significant improvement over existing prediction tools in that it predicts the development of metastases which is a very important clinical endpoint that indicates incurable prostate cancer. Additionally, our tool allows for updated predictions at any point following radical prostatectomy by considering commonly available postoperative information (postoperative serum PSA and use of adjuvant therapies) to modify its risk predictions. The net result is a dynamic tool that renders clinically relevant predictions that change as the patient's clinical status changes throughout the postoperative course.UNLABELLEDWhat's known on the subject? and What does the study add? One of two problems plagues virtually are existing post-prostatectomy prediction tools: either (1) they predict PSA recurrences (which are of unclear importance) or (2) the predictions they make are anchored at the date of surgery and are not updated based on how patients evolve over the postoperative years. Our prediction tool is a significant improvement over existing prediction tools in that it predicts the development of metastases which is a very important clinical endpoint that indicates incurable prostate cancer. Additionally, our tool allows for updated predictions at any point following radical prostatectomy by considering commonly available postoperative information (postoperative serum PSA and use of adjuvant therapies) to modify its risk predictions. The net result is a dynamic tool that renders clinically relevant predictions that change as the patient's clinical status changes throughout the postoperative course.• To develop a dynamic algorithm that predicts the risk of metastases from any time point after radical prostatectomy (RP).OBJECTIVE• To develop a dynamic algorithm that predicts the risk of metastases from any time point after radical prostatectomy (RP).• The study cohort consisted of 5741 RP patients who were treated from 1990-99. • Patients were grouped into one of four clinical states at follow-up: State(1) , prostate-specific antigen (PSA) undetectable; State(2), PSA 0.15-0.39 ng/mL; State(3), PSA ≥0.4 ng/mL; and State(4), previous androgen deprivation or radiation therapy. • Follow-up epochs (alive and at risk of systemic progression) at 0, 2, 4 and 6 years post-RP, cumulative incidence curves and multistate Cox models were used to assess the risk of metastases over the ensuing 5-year interval. • Gleason score, seminal vesicle and surgical margin involvement, and PSA variables were evaluated as predictors.PATIENTS AND METHODS• The study cohort consisted of 5741 RP patients who were treated from 1990-99. • Patients were grouped into one of four clinical states at follow-up: State(1) , prostate-specific antigen (PSA) undetectable; State(2), PSA 0.15-0.39 ng/mL; State(3), PSA ≥0.4 ng/mL; and State(4), previous androgen deprivation or radiation therapy. • Follow-up epochs (alive and at risk of systemic progression) at 0, 2, 4 and 6 years post-RP, cumulative incidence curves and multistate Cox models were used to assess the risk of metastases over the ensuing 5-year interval. • Gleason score, seminal vesicle and surgical margin involvement, and PSA variables were evaluated as predictors.• Median follow-up was 11.7 years, with 4411, 4256 and 3983 patients followed with PSA at 2, 4 and 6 years, respectively. • In total, 287 metastatic events occurred and the 5-year risk of metastasis was 0.4%, 2.1%, 8.7% and 12.6% for men in States 1, 2, 3 and 4, respectively. • Independent predictors of metastasis by group included seminal vesicle involvement (all groups), Gleason score (groups 1, 3 and 4), current PSA (groups 3 and 4) and maximum past PSA (group 4).RESULTS• Median follow-up was 11.7 years, with 4411, 4256 and 3983 patients followed with PSA at 2, 4 and 6 years, respectively. • In total, 287 metastatic events occurred and the 5-year risk of metastasis was 0.4%, 2.1%, 8.7% and 12.6% for men in States 1, 2, 3 and 4, respectively. • Independent predictors of metastasis by group included seminal vesicle involvement (all groups), Gleason score (groups 1, 3 and 4), current PSA (groups 3 and 4) and maximum past PSA (group 4).• We present a web-based prognostic tool for patients undergoing RP that is valid at many time points after surgery. • Our tool predicts the development of metastases.CONCLUSIONS• We present a web-based prognostic tool for patients undergoing RP that is valid at many time points after surgery. • Our tool predicts the development of metastases. What's known on the subject? and What does the study add? One of two problems plagues virtually are existing post-prostatectomy prediction tools: either (1) they predict PSA recurrences (which are of unclear importance) or (2) the predictions they make are anchored at the date of surgery and are not updated based on how patients evolve over the postoperative years. Our prediction tool is a significant improvement over existing prediction tools in that it predicts the development of metastases which is a very important clinical endpoint that indicates incurable prostate cancer. Additionally, our tool allows for updated predictions at any point following radical prostatectomy by considering commonly available postoperative information (postoperative serum PSA and use of adjuvant therapies) to modify its risk predictions. The net result is a dynamic tool that renders clinically relevant predictions that change as the patient's clinical status changes throughout the postoperative course. • To develop a dynamic algorithm that predicts the risk of metastases from any time point after radical prostatectomy (RP). • The study cohort consisted of 5741 RP patients who were treated from 1990-99. • Patients were grouped into one of four clinical states at follow-up: State(1) , prostate-specific antigen (PSA) undetectable; State(2), PSA 0.15-0.39 ng/mL; State(3), PSA ≥0.4 ng/mL; and State(4), previous androgen deprivation or radiation therapy. • Follow-up epochs (alive and at risk of systemic progression) at 0, 2, 4 and 6 years post-RP, cumulative incidence curves and multistate Cox models were used to assess the risk of metastases over the ensuing 5-year interval. • Gleason score, seminal vesicle and surgical margin involvement, and PSA variables were evaluated as predictors. • Median follow-up was 11.7 years, with 4411, 4256 and 3983 patients followed with PSA at 2, 4 and 6 years, respectively. • In total, 287 metastatic events occurred and the 5-year risk of metastasis was 0.4%, 2.1%, 8.7% and 12.6% for men in States 1, 2, 3 and 4, respectively. • Independent predictors of metastasis by group included seminal vesicle involvement (all groups), Gleason score (groups 1, 3 and 4), current PSA (groups 3 and 4) and maximum past PSA (group 4). • We present a web-based prognostic tool for patients undergoing RP that is valid at many time points after surgery. • Our tool predicts the development of metastases. Study Type – Prognosis (retrospective cohort) Level of Evidence 2a What’s known on the subject? and What does the study add? One of two problems plagues virtually are existing post‐prostatectomy prediction tools: either (1) they predict PSA recurrences (which are of unclear importance) or (2) the predictions they make are anchored at the date of surgery and are not updated based on how patients evolve over the postoperative years. Our prediction tool is a significant improvement over existing prediction tools in that it predicts the development of metastases which is a very important clinical endpoint that indicates incurable prostate cancer. Additionally, our tool allows for updated predictions at any point following radical prostatectomy by considering commonly available postoperative information (postoperative serum PSA and use of adjuvant therapies) to modify its risk predictions. The net result is a dynamic tool that renders clinically relevant predictions that change as the patient’s clinical status changes throughout the postoperative course. OBJECTIVE • To develop a dynamic algorithm that predicts the risk of metastases from any time point after radical prostatectomy (RP). PATIENTS AND METHODS • The study cohort consisted of 5741 RP patients who were treated from 1990–99. • Patients were grouped into one of four clinical states at follow‐up: State1, prostate‐specific antigen (PSA) undetectable; State2, PSA 0.15–0.39 ng/mL; State3, PSA ≥0.4 ng/mL; and State4, previous androgen deprivation or radiation therapy. • Follow‐up epochs (alive and at risk of systemic progression) at 0, 2, 4 and 6 years post‐RP, cumulative incidence curves and multistate Cox models were used to assess the risk of metastases over the ensuing 5‐year interval. • Gleason score, seminal vesicle and surgical margin involvement, and PSA variables were evaluated as predictors. RESULTS • Median follow‐up was 11.7 years, with 4411, 4256 and 3983 patients followed with PSA at 2, 4 and 6 years, respectively. • In total, 287 metastatic events occurred and the 5‐year risk of metastasis was 0.4%, 2.1%, 8.7% and 12.6% for men in States 1, 2, 3 and 4, respectively. • Independent predictors of metastasis by group included seminal vesicle involvement (all groups), Gleason score (groups 1, 3 and 4), current PSA (groups 3 and 4) and maximum past PSA (group 4). CONCLUSIONS • We present a web‐based prognostic tool for patients undergoing RP that is valid at many time points after surgery. • Our tool predicts the development of metastases. |
| Author | Blute, Michael L. Frank, Igor Karnes, R. Jeffrey Inman, Brant A. Bergstralh, Eric J. Boorjian, Stephen A. Akornor, Joseph W. Leibovich, Bradley C. |
| AuthorAffiliation | Department of Urology, Mayo Clinic College of Medicine, Rochester, MN, USA Division of Urology, Duke University Medical Center, Durham, NC, USA Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN, USA |
| AuthorAffiliation_xml | – name: Division of Urology, Duke University Medical Center, Durham, NC, USA – name: Department of Urology, Mayo Clinic College of Medicine, Rochester, MN, USA – name: Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN, USA |
| Author_xml | – sequence: 1 givenname: Brant A. surname: Inman fullname: Inman, Brant A. – sequence: 2 givenname: Igor surname: Frank fullname: Frank, Igor – sequence: 3 givenname: Stephen A. surname: Boorjian fullname: Boorjian, Stephen A. – sequence: 4 givenname: Joseph W. surname: Akornor fullname: Akornor, Joseph W. – sequence: 5 givenname: R. Jeffrey surname: Karnes fullname: Karnes, R. Jeffrey – sequence: 6 givenname: Bradley C. surname: Leibovich fullname: Leibovich, Bradley C. – sequence: 7 givenname: Michael L. surname: Blute fullname: Blute, Michael L. – sequence: 8 givenname: Eric J. surname: Bergstralh fullname: Bergstralh, Eric J. |
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| Cites_doi | 10.1016/j.eururo.2007.08.041 10.1002/9781118032985 10.1056/NEJM199810083391504 10.1016/S0022-5347(05)66452-X 10.1016/S0022-5347(01)63773-X 10.1002/cncr.10977 10.1016/S0022-5347(05)65761-8 10.1200/JCO.2005.04.0756 10.1200/JCO.1999.17.5.1499 10.1097/00005392-200101000-00030 10.1200/JCO.2005.01.867 10.1097/01.ju.0000158155.33890.e7 10.1056/NEJMoa040720 10.1016/S0022-5347(05)67457-5 |
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| Keywords | Nephrology Urinary system disease Prognosis Prostate disease Prediction Malignant tumor Metastasis clinical prediction Urology metastases Treatment Dynamics Surgery Prostatectomy outcome assessment Predictive factor Male genital diseases Prostate cancer Cancer |
| Language | English |
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| Snippet | Study Type – Prognosis (retrospective cohort)
Level of Evidence 2a
What’s known on the subject? and What does the study add?
One of two problems plagues... What's known on the subject? and What does the study add? One of two problems plagues virtually are existing post-prostatectomy prediction tools: either (1)... Study Type - Prognosis (retrospective cohort) Level of Evidence2a What's known on the subject? and What does the study add? One of two problems plagues... |
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| SubjectTerms | Aged Algorithms Biological and medical sciences clinical prediction Disease Progression Follow-Up Studies Gynecology. Andrology. Obstetrics Humans Male Male genital diseases Medical research Medical sciences metastases Middle Aged Neoplasm Invasiveness - diagnosis Neoplasm Metastasis Nephrology. Urinary tract diseases outcome assessment Postoperative Care Predictive Value of Tests Prognosis Prostate cancer Prostate-Specific Antigen - metabolism prostatectomy Prostatectomy - methods Prostatic Neoplasms - blood Prostatic Neoplasms - pathology Prostatic Neoplasms - surgery Risk Assessment Seminal Vesicles Tumors Tumors of the urinary system Urinary tract. Prostate gland |
| Title | Dynamic prediction of metastases after radical prostatectomy for prostate cancer |
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