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用于告知前列腺活检需求的风险计算器:快速通道诊所队列。

A risk calculator to inform the need for a prostate biopsy: a rapid access clinic cohort.

机构信息

Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.

UCD School of Medicine, University College Dublin, Dublin, Ireland.

出版信息

BMC Med Inform Decis Mak. 2020 Jul 3;20(1):148. doi: 10.1186/s12911-020-01174-2.

Abstract

BACKGROUND

Prostate cancer (PCa) represents a significant healthcare problem. The critical clinical question is the need for a biopsy. Accurate risk stratification of patients before a biopsy can allow for individualised risk stratification thus improving clinical decision making. This study aims to build a risk calculator to inform the need for a prostate biopsy.

METHODS

Using the clinical information of 4801 patients an Irish Prostate Cancer Risk Calculator (IPRC) for diagnosis of PCa and high grade (Gleason ≥7) was created using a binary regression model including age, digital rectal examination, family history of PCa, negative prior biopsy and Prostate-specific antigen (PSA) level as risk factors. The discrimination ability of the risk calculator is internally validated using cross validation to reduce overfitting, and its performance compared with PSA and the American risk calculator (PCPT), Prostate Biopsy Collaborative Group (PBCG) and European risk calculator (ERSPC) using various performance outcome summaries. In a subgroup of 2970 patients, prostate volume was included. Separate risk calculators including the prostate volume (IPRCv) for the diagnosis of PCa (and high-grade PCa) was created.

RESULTS

IPRC area under the curve (AUC) for the prediction of PCa and high-grade PCa was 0.6741 (95% CI, 0.6591 to 0.6890) and 0.7214 (95% CI, 0.7018 to 0.7409) respectively. This significantly outperforms the predictive ability of cancer detection for PSA (0.5948), PCPT (0.6304), PBCG (0.6528) and ERSPC (0.6502) risk calculators; and also, for detecting high-grade cancer for PSA (0.6623) and PCPT (0.6804) but there was no significant improvement for PBCG (0.7185) and ERSPC (0.7140). The inclusion of prostate volume into the risk calculator significantly improved the AUC for cancer detection (AUC = 0.7298; 95% CI, 0.7119 to 0.7478), but not for high-grade cancer (AUC = 0.7256; 95% CI, 0.7017 to 0.7495). The risk calculator also demonstrated an increased net benefit on decision curve analysis.

CONCLUSION

The risk calculator developed has advantages over prior risk stratification of prostate cancer patients before the biopsy. It will reduce the number of men requiring a biopsy and their exposure to its side effects. The interactive tools developed are beneficial to translate the risk calculator into practice and allows for clarity in the clinical recommendations.

摘要

背景

前列腺癌(PCa)是一个重大的医疗保健问题。关键的临床问题是是否需要进行活检。在活检前对患者进行准确的风险分层,可以进行个体化的风险分层,从而改善临床决策。本研究旨在建立一个风险计算器,以告知是否需要进行前列腺活检。

方法

使用 4801 名爱尔兰前列腺癌风险计算器(IPRC)患者的临床信息,使用包括年龄、直肠指检、前列腺癌家族史、阴性既往活检和前列腺特异性抗原(PSA)水平在内的二元回归模型,创建用于诊断 PCa 和高级别(Gleason≥7)的风险计算器。使用交叉验证对内部分类器的辨别能力进行内部验证,以减少过度拟合,并使用各种性能总结比较 PSA 和美国风险计算器(PCPT)、前列腺活检协作组(PBCG)和欧洲风险计算器(ERSPC)的性能。在 2970 名患者的亚组中,纳入了前列腺体积。创建了包括前列腺体积(IPRCv)的单独风险计算器,用于诊断 PCa(和高级别 PCa)。

结果

IPRC 预测 PCa 和高级别 PCa 的曲线下面积(AUC)分别为 0.6741(95%CI,0.6591 至 0.6890)和 0.7214(95%CI,0.7018 至 0.7409)。这显著优于 PSA(0.5948)、PCPT(0.6304)、PBCG(0.6528)和 ERSPC(0.6502)风险计算器对癌症检出的预测能力;也优于 PSA(0.6623)和 PCPT(0.6804)对高级别癌症的检出,但对 PBCG(0.7185)和 ERSPC(0.7140)没有显著改善。将前列腺体积纳入风险计算器显著提高了癌症检出的 AUC(AUC=0.7298;95%CI,0.7119 至 0.7478),但对高级别癌症的 AUC 没有提高(AUC=0.7256;95%CI,0.7017 至 0.7495)。决策曲线分析也显示出风险计算器具有增加的净效益。

结论

与之前的前列腺癌患者活检前风险分层相比,该风险计算器具有优势。它将减少需要进行活检的男性数量及其对其副作用的暴露。开发的交互工具有助于将风险计算器转化为实践,并使临床建议更加清晰。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03bb/7333322/731730e75752/12911_2020_1174_Fig1_HTML.jpg

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