Suppr超能文献

下一代临床决策工具:针对不断演变的前列腺癌格局开发用于前列腺活检结果的实时预测工具。

The Next Generation of Clinical Decision Making Tools: Development of a Real-Time Prediction Tool for Outcome of Prostate Biopsy in Response to a Continuously Evolving Prostate Cancer Landscape.

作者信息

Strobl Andreas N, Thompson Ian M, Vickers Andrew J, Ankerst Donna P

机构信息

Department of Mathematics, Technical University Munich, Munich, Germany.

Department of Urology, University of Texas Health Science Center at San Antonio, San Antonio, Texas.

出版信息

J Urol. 2015 Jul;194(1):58-64. doi: 10.1016/j.juro.2015.01.092. Epub 2015 Jan 28.

Abstract

PURPOSE

We evaluate whether annual updating of the PCPT Risk Calculator would improve institutional validation compared to static use of the PCPT Risk Calculator alone.

MATERIALS AND METHODS

Data from 5 international cohorts including SABOR, Cleveland Clinic, ProtecT, Tyrol and Durham VA, comprising 18,400 biopsies, were used to evaluate an institution specific annual recalibration of the PCPT Risk Calculator. Using all prior years as a training set and the current year as the test set, annual recalibrations of the PCPT Risk Calculator were compared to static use of the PCPT Risk Calculator in terms of AUC and the Hosmer-Lemeshow goodness of fit statistic.

RESULTS

For predicting high grade disease the median AUC (higher is better) of the recalibrated PCPT Risk Calculator (static PCPT Risk Calculator) across all test years for the 5 cohorts was 67.3 (67.5), 65.0 (60.4), 73.4 (73.4), 73.9 (74.1) and 69.6 (67.2), respectively, and median Hosmer-Lemeshow goodness of fit statistics indicated better fit for recalibration compared to the static PCPT Risk Calculator for Cleveland Clinic, ProtecT and the Durham VA but not for SABOR and Tyrol. For predicting overall cancer median AUC was 63.5 (62.7), 61.0 (57.3), 62.1 (62.5), 66.9 (67.3) and 68.5 (65.5), respectively, and median Hosmer-Lemeshow goodness of fit statistics indicated a better fit for recalibration in all cohorts except for Tyrol.

CONCLUSIONS

A simple method has been provided to tailor the PCPT Risk Calculator to individual hospitals to optimize its accuracy for the patient population at hand.

摘要

目的

我们评估与单独静态使用前列腺癌预防试验(PCPT)风险计算器相比,每年更新该计算器是否会改善机构验证。

材料与方法

来自包括SABOR、克利夫兰诊所、前列腺癌检测与治疗试验(ProtecT)、蒂罗尔和达勒姆退伍军人事务部在内的5个国际队列的数据,共18400份活检样本,用于评估PCPT风险计算器的机构特定年度重新校准。以前所有年份的数据作为训练集,当前年份的数据作为测试集,将PCPT风险计算器的年度重新校准与静态使用该计算器在曲线下面积(AUC)和霍斯默-莱梅肖拟合优度统计方面进行比较。

结果

对于预测高级别疾病,在所有测试年份中,5个队列重新校准的PCPT风险计算器(静态PCPT风险计算器)的中位AUC(越高越好)分别为67.3(67.5)、65.0(60.4)、73.4(73.4)、73.9(74.1)和69.6(67.2),中位霍斯默-莱梅肖拟合优度统计表明,与静态PCPT风险计算器相比,克利夫兰诊所、ProtecT和达勒姆退伍军人事务部重新校准的拟合更好,但SABOR和蒂罗尔并非如此。对于预测总体癌症中位AUC分别为63.5(62.7)、61.0(57.3)、62.1(62.5)、66.9(67.3)和68.5(65.5),中位霍斯默-莱梅肖拟合优度统计表明,除蒂罗尔外,所有队列重新校准的拟合更好。

结论

已提供一种简单方法,可根据各个医院的情况调整PCPT风险计算器,以优化其针对手头患者群体的准确性。

相似文献

2
4
Evaluating the PCPT risk calculator in ten international biopsy cohorts: results from the Prostate Biopsy Collaborative Group.
World J Urol. 2012 Apr;30(2):181-7. doi: 10.1007/s00345-011-0818-5. Epub 2011 Dec 31.
6
Prostate Cancer Risk Calculator Apps in a Taiwanese Population Cohort: Validation Study.
J Med Internet Res. 2020 Dec 18;22(12):e16322. doi: 10.2196/16322.
7
Evaluation of Prostate Cancer Risk Calculators for Shared Decision Making Across Diverse Urology Practices in Michigan.
Urology. 2017 Jun;104:137-142. doi: 10.1016/j.urology.2017.01.039. Epub 2017 Feb 22.
8
A risk calculator to inform the need for a prostate biopsy: a rapid access clinic cohort.
BMC Med Inform Decis Mak. 2020 Jul 3;20(1):148. doi: 10.1186/s12911-020-01174-2.
9
Prostate cancer risk assessment tools in an unscreened population.
World J Urol. 2015 Jun;33(6):827-32. doi: 10.1007/s00345-014-1365-7. Epub 2014 Aug 5.

引用本文的文献

1
Integration of magnetic resonance imaging into prostate cancer nomograms.
Ther Adv Urol. 2022 May 13;14:17562872221096386. doi: 10.1177/17562872221096386. eCollection 2022 Jan-Dec.
2
A risk calculator to inform the need for a prostate biopsy: a rapid access clinic cohort.
BMC Med Inform Decis Mak. 2020 Jul 3;20(1):148. doi: 10.1186/s12911-020-01174-2.
3
Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools.
BMC Med Res Methodol. 2019 Oct 15;19(1):191. doi: 10.1186/s12874-019-0839-0.
4
Next-generation prostate cancer risk calculator for primary care physicians.
Can Urol Assoc J. 2018 Feb;12(2):E64-E70. doi: 10.5489/cuaj.4696. Epub 2017 Dec 1.

本文引用的文献

1
National trends in the management of low and intermediate risk prostate cancer in the United States.
J Urol. 2015 Jan;193(1):95-102. doi: 10.1016/j.juro.2014.07.111. Epub 2014 Aug 5.
3
Statins: new American guidelines for prevention of cardiovascular disease.
Lancet. 2013 Nov 30;382(9907):1762-5. doi: 10.1016/S0140-6736(13)62388-0. Epub 2013 Nov 20.
4
Simple dichotomous updating methods improved the validity of polytomous prediction models.
J Clin Epidemiol. 2013 Oct;66(10):1158-65. doi: 10.1016/j.jclinepi.2013.04.014. Epub 2013 Jul 9.
5
Recalibration and validation of a preoperative risk prediction model for mortality in major colorectal surgery.
Dis Colon Rectum. 2013 Jul;56(7):844-9. doi: 10.1097/DCR.0b013e31828343f2.
6
Mortality prediction models for pediatric intensive care: comparison of overall and subgroup specific performance.
Intensive Care Med. 2013 May;39(5):942-50. doi: 10.1007/s00134-013-2857-4. Epub 2013 Feb 22.
7
Real-time individual predictions of prostate cancer recurrence using joint models.
Biometrics. 2013 Mar;69(1):206-13. doi: 10.1111/j.1541-0420.2012.01823.x. Epub 2013 Feb 4.
9
Evaluating the PCPT risk calculator in ten international biopsy cohorts: results from the Prostate Biopsy Collaborative Group.
World J Urol. 2012 Apr;30(2):181-7. doi: 10.1007/s00345-011-0818-5. Epub 2011 Dec 31.
10
Effect of changes over time in the performance of a customized SAPS-II model on the quality of care assessment.
Intensive Care Med. 2012 Jan;38(1):40-6. doi: 10.1007/s00134-011-2390-2. Epub 2011 Oct 28.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验