Kent Matthew, Penson David F, Albertsen Peter C, Goodman Michael, Hamilton Ann S, Stanford Janet L, Stroup Antoinette M, Ehdaie Behfar, Scardino Peter T, Vickers Andrew J
Department of Epidemiology and Biostatistics, Health Outcomes Research Group, Memorial Sloan-Kettering Cancer Center, 485 Lexington Avenue, 2nd Floor, New York, NY, 10017, USA.
Department of Urologic Surgery, Vanderbilt University, Nashville, TN, USA.
BMC Med. 2016 Feb 9;14:25. doi: 10.1186/s12916-016-0572-z.
Although life expectancy estimation is vital to decision making for localized prostate cancer, there are few, if any, valid and usable tools. Our goal was to create and validate a prediction model for other cause mortality in localized prostate cancer patients that could aid clinician's initial treatment decisions at the point of care.
We combined an adjusted Social Security Administration table with a subset of comorbidities from a UK actuarial life expectancy model. Life tables were adjusted on the basis of survival data from a cohort of almost 10,000 radical prostatectomy patients treated at four major US academic institutions. Comorbidity-specific odds ratios were calculated and incorporated with baseline risk of mortality. We externally validated the model on 2898 patients from the Prostate Cancer Outcomes Study, which included men diagnosed with prostate cancer in six SEER cancer registries. These men had sufficient follow-up for our endpoints of 10- and 15-year mortality and also had self-reported comorbidity data.
Life expectancy for prostate cancer patients were close to that of a typical US man who was 3 years younger. On external validation, 10- and 15-year concordance indexes were 0.724 and 0.726, respectively. Our model exhibited excellent calibration. Taking into account differences between how comorbidities are used in the model versus how they were recorded in the validation cohort, calibration would improve for most patients, but there would be overestimation of the risk of death in the oldest and sickest patients.
We successfully created and externally validated a new life expectancy prediction model that, while imperfect, has clear advantages to any alternative. We urge consideration of its use in counseling patients with localized prostate cancer.
虽然预期寿命估计对于局限性前列腺癌的决策至关重要，但几乎没有有效的可用工具。我们的目标是创建并验证一个局限性前列腺癌患者其他原因死亡率的预测模型，以帮助临床医生在医疗点做出初始治疗决策。
我们将调整后的社会保障管理局表格与英国精算预期寿命模型中的一部分合并症相结合。根据美国四大学术机构治疗的近10000名接受根治性前列腺切除术患者队列的生存数据对寿命表进行调整。计算特定合并症的优势比，并将其与基线死亡风险相结合。我们在前列腺癌结局研究的2898名患者中对该模型进行了外部验证，该研究包括在六个监测、流行病学和最终结果（SEER）癌症登记处诊断为前列腺癌的男性。这些男性对我们10年和15年死亡率的终点有足够的随访，并且有自我报告的合并症数据。
前列腺癌患者的预期寿命接近比其年轻3岁的典型美国男性。在外部验证中，10年和15年的一致性指数分别为0.724和0.726。我们的模型显示出良好的校准。考虑到模型中合并症的使用方式与验证队列中记录方式的差异，大多数患者的校准会有所改善，但最年长和病情最严重的患者死亡风险会被高估。
我们成功创建并外部验证了一个新的预期寿命预测模型，该模型虽然不完美，但相对于任何其他模型都有明显优势。我们敦促考虑在为局限性前列腺癌患者提供咨询时使用该模型。
