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Postoperative Nomogram Predicting the 10-Year Probability of Prostate Cancer Recurrence After Radical Prostatectomy
Open accessAbstract
Purpose: A postoperative nomogram for prostate cancer recurrence after radical prostatectomy (RP) has been independently validated as accurate and discriminating. We have updated the nomogram by extending the predictions to 10 years after RP and have enabled the nomogram predictions to be adjusted for the disease-free interval that a patient has maintained after RP. Methods: Cox regression analysis was used to model the clinical information for 1,881 patients who underwent RP for clinically-localized prostate cancer by two high-volume surgeons. The model was externally validated separately on two independent cohorts of 1,782 patients and 1,357 patients, respectively. Disease progression was defined as a rising prostate-specific antigen (PSA) level, clinical progression, radiotherapy more than 12 months postoperatively, or initiation of systemic therapy. Results: The 10-year progression-free probability for the modeling set was 79% (95% CI, 75% to 82%). Significant variables in the multivariable model included PSA (P = .002), primary (P < .0001) and secondary Gleason grade (P = .0006), extracapsular extension (P < .0001), positive surgical margins (P = .028), seminal vesicle invasion (P < .0001), lymph node involvement (P = .030), treatment year (P = .008), and adjuvant radiotherapy (P = .046). The concordance index of the nomogram when applied to the independent validation sets was 0.81 and 0.79. Conclusion: We have developed and validated as a robust predictive model an enhanced postoperative nomogram for prostate cancer recurrence after RP. Unique to predictive models, the nomogram predictions can be adjusted for the disease-free interval that a patient has achieved after RP.
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Nonparametric Estimation from Incomplete Observations
Kaplan, E. L., & Meier, P. (1958) · Journal of the American Statistical Association · doi:10.1080/01621459.1958.10501452 · Cited by 39,158
Modeling Survival Data: Extending the Cox Model
Therneau, T. M., & Grambsch, P. M. (2000) · Statistics for Biology and Health · doi:10.1007/978-1-4757-3294-8 · Cited by 8,674
Cited by
Vergis, R., Corbishley, C. M., Norman, A. R., Bartlett, J., Jhavar, S., Borre, M., Heeboll, S., Horwich, A., Huddart, R., Khoo, V., et al. (2008) · The Lancet Oncology · doi:10.1016/s1470-2045(08)70076-7 · Cited by 282
Reporting methods in studies developing prognostic models in cancer: a review
Mallett, S., Royston, P., Dutton, S., Waters, R., & Altman, D. G. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-20 · Cited by 206
“Our search string selected 2,076 articles from 681,530 articles with subject MeSH heading of neoplasm published in 2005, of which 47 met inclusion criteria for this study (Figure 1) [13-59].”
BackgroundMethodReporting performance of prognostic models in cancer: a review.
Mallett, S., Royston, P., Waters, R., Dutton, S., & Altman, D. G. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-21 · Cited by 195
Jelovsek, J. E., Chagin, K., Lukacz, E. S., Nolen, T. L., Shepherd, J. P., Barber, M. D., Sung, V., Brubaker, L., Norton, P. A., Rahn, D. D., et al. (2018) · Obstetrics & Gynecology · doi:10.1097/aog.0000000000002750 · Cited by 36
Self-citationPrognostic Genomic Tissue-Based Biomarkers in the Treatment of Localized Prostate Cancer
Ingrosso, G., Alì, E., Marani, S., Saldi, S., Bellavita, R., & Aristei, C. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12010065 · Cited by 9
Metadata
- Authors
- Stephenson, A. J., Scardino, P. T., Eastham, J. A., Bianco, F. J., Dotan, Z. A., DiBlasio, C. J., Reuther, A., Klein, E. A., & Kattan, M. W.
- Venue
- Journal of Clinical Oncology
- Published
- 2005-10-01
- Volume
- 23
- Issue
- 28
- Pages
- 7005-7012
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2149696900
- Cited by
- 663
- References
- 2
- FWCI
- 27.38
- Type
- journal article
- Language
- en
- Open access
- green
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- Stephenson, A. J., Scardino, P. T., Eastham, J. A., Bianco, F. J., Dotan, Z. A., DiBlasio, C. J., Reuther, A., Klein, E. A., & Kattan, M. W. (2005). Postoperative Nomogram Predicting the 10-Year Probability of Prostate Cancer Recurrence After Radical Prostatectomy. Journal of Clinical Oncology. https://doi.org/10.1200/jco.2005.01.867
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