Stephenson Andrew J, Scardino Peter T, Eastham James A, Bianco Fernando J, Dotan Zohar A, DiBlasio Christopher J, Reuther Alwyn, Klein Eric A, Kattan Michael W
Department of Urology, Sidney Kimmel Center for Prostate and Urologic Cancers, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
J Clin Oncol. 2005 Oct 1;23(28):7005-12. doi: 10.1200/JCO.2005.01.867.
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.
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.
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.
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.
一项用于根治性前列腺切除术（RP）后前列腺癌复发的术后列线图已被独立验证具有准确性和鉴别力。我们通过将预测期延长至RP后10年对该列线图进行了更新，并使列线图预测能够根据患者在RP后维持的无病间隔进行调整。
采用Cox回归分析对1881例由两位高年资外科医生进行临床局限性前列腺癌RP手术的患者的临床信息进行建模。该模型分别在两个独立队列（分别为1782例患者和1357例患者）上进行外部验证。疾病进展定义为前列腺特异性抗原（PSA）水平升高、临床进展、术后12个月以上放疗或开始全身治疗。
建模集的10年无进展概率为79%（95%CI，75%至82%）。多变量模型中的显著变量包括PSA（P = 0.002）、主要（P < 0.0001）和次要Gleason分级（P = 0.0006）、包膜外扩展（P < 0.0001）、手术切缘阳性（P = 0.028）、精囊侵犯（P < 0.0001）、淋巴结受累（P = 0.030）、治疗年份（P = 0.008）和辅助放疗（P = 0.046）。应用于独立验证集时列线图的一致性指数分别为0.81和0.79。
我们已开发并验证了一种用于RP后前列腺癌复发的增强型术后列线图，作为一种强大的预测模型。该列线图预测的独特之处在于，可根据患者在RP后实现的无病间隔进行调整。
