Suppr超能文献

在一个当代、多种族、有转诊需求的人群中对 Kaiser Permanente 前列腺癌风险计算器进行前瞻性验证。

Prospective validation of the Kaiser Permanente prostate cancer risk calculator in a contemporary, racially diverse, referral population.

机构信息

Department of Urology, Kaiser Permanente Northern California, Oakland, CA; Division of Research, Kaiser Permanente Northern California, Oakland, CA.

Division of Research, Kaiser Permanente Northern California, Oakland, CA.

出版信息

Urol Oncol. 2021 Nov;39(11):783.e11-783.e19. doi: 10.1016/j.urolonc.2021.03.023. Epub 2021 May 4.

Abstract

PURPOSE

To prospectively validate a new prostate cancer risk calculator in a racially diverse population.

MATERIALS AND METHODS

We recently developed, internally validated and published the Kaiser Permanente Prostate Cancer Risk Calculator. This study is a prospective validation of the calculator in a separate, referral population over a 21-month period. All patients were tested with a uniform PSA assay and a standardized systematic, ultrasound-guided biopsy scheme. We report on 3 calculator models: Model 1 included age, race, PSA, prior biopsy status, body mass index, and family history of prostate cancer; Model 2 added digital rectal exam to Model 1 variables; Model 3 added prostate volume to Model 2 variables. We considered three outcomes: high-grade disease (Gleason score ≥7), low-grade disease (Gleason score=6), and no cancer. Predictive discrimination and calibration were calculated. How each model might alter biopsy frequency and outcomes at various thresholds of risk was assessed. We compared the performance of our calculator with two other calculators.

RESULTS

In 4178 patients (16.2% Asian, 11.3% African American, 13.5% Hispanic), cancer was found in 53%; 62% were Gleason score ≥7. Using a high-grade risk threshold for biopsy of ≥10%, Model 2 predictions would result in 9% of men avoiding a biopsy, while only missing 2% of high-grade cancers. At the same threshold, Model 3 predictions would result in 26% of men avoiding a biopsy, while only missing 5% of high-grade cancers. The c-statistics for Models 1, 2, and 3 to predict high-grade disease vs. low-grade or no cancer were 0.76, 0.79 and 0.85, respectively. The c-statistics for Models 1, 2, and 3 to predict any prostate cancer vs. no cancer were 0.70, 0.72 and 0.80, respectively. All models were well calibrated for all outcomes. Our Model 3 calculator had superior discrimination for high grade disease (c-statistic=0.85, 0.84-0.86) and any cancer (0.80, 0.79-0.82) compared to the PBCG calculator [(0.79, 0.78-0.80); 0.72 (0.70-0.73)] and the PCPT calculator [(0.75, 0.74-0.77); 0.69 (0.67-0.70)], respectively. In the high-grade cancer predicted risk range of 0-30%, our Model 2 was better calibrated than the PCPT and PBCG calculators.

CONCLUSIONS

This validation of our calculator showed excellent performance characteristics.

摘要

目的

前瞻性验证一种新的前列腺癌风险计算器在种族多样化人群中的效果。

材料和方法

我们最近开发、内部验证并发表了 Kaiser Permanente 前列腺癌风险计算器。本研究是在 21 个月的时间内,对该计算器在另一个独立的转诊人群中的前瞻性验证。所有患者均采用统一的 PSA 检测方法和标准化的系统、超声引导活检方案进行检测。我们报告了 3 个计算器模型:模型 1 包括年龄、种族、PSA、既往活检状况、体重指数和前列腺癌家族史;模型 2 在模型 1 变量中加入了直肠指检;模型 3 在模型 2 变量中加入了前列腺体积。我们考虑了三种结果:高级别疾病(Gleason 评分≥7)、低级别疾病(Gleason 评分=6)和无癌症。计算了预测的区分度和校准度。评估了每个模型在不同风险阈值下如何改变活检频率和结果。我们将我们的计算器与另外两个计算器进行了比较。

结果

在 4178 名患者(16.2%为亚洲人,11.3%为非裔美国人,13.5%为西班牙裔)中,发现癌症占 53%;62%为 Gleason 评分≥7。使用高级别风险阈值≥10%进行活检,模型 2 的预测结果将使 9%的男性避免活检,而仅漏诊 2%的高级别癌症。在相同的阈值下,模型 3 的预测结果将使 26%的男性避免活检,而仅漏诊 5%的高级别癌症。模型 1、2 和 3 预测高级别疾病与低级别或无癌症的 c 统计值分别为 0.76、0.79 和 0.85。模型 1、2 和 3 预测任何前列腺癌与无癌症的 c 统计值分别为 0.70、0.72 和 0.80。所有模型在所有结果中均具有良好的校准度。我们的模型 3 计算器在预测高级别疾病(c 统计值=0.85、0.84-0.86)和任何癌症(0.80、0.79-0.82)方面的区分度优于 PBCG 计算器[(0.79、0.78-0.80);0.72(0.70-0.73)]和 PCPT 计算器[(0.75、0.74-0.77);0.69(0.67-0.70)]。在高级别癌症预测风险范围为 0-30%时,我们的模型 2 比 PCPT 和 PBCG 计算器具有更好的校准度。

结论

本计算器的验证结果表明其具有出色的性能特征。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验