Development and validation of multivariable machine learning algorithms to predict risk of cancer in symptomatic patients referred urgently from primary care: a diagnostic accuracy study.
Development and validation of multivariable machine learning algorithms to predict risk of cancer in symptomatic patients referred urgently from primary care: a diagnostic accuracy study.
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DOI：
10.1136/bmjopen-2021-053590
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发表时间：
2022-04-01
期刊：
影响因子：
2.9
通讯作者：
Hall G
中科院分区：
文献类型：
--
作者：
Savage R;Messenger M;Neal RD;Ferguson R;Johnston C;Lloyd KL;Neal MD;Sansom N;Selby P;Sharma N;Shinkins B;Skinner JR;Tully G;Duffy S;Hall G
开发和验证测试，以评估NHS紧急疑似癌症(2周等待，2WW)临床路径转介的患者的任何癌症风险。初级和二级保健，一个参与的区域中心。对2011-2019年利兹地区连续371,799例2WW转诊的数据进行了回顾分析。开发队列由2011年1月至2016年12月期间在利兹紧急转诊的224 669名疑似癌症患者组成。开发的诊断算法随后在一个类似的连续样本147 130名患者(2017年1月至2019年12月)上进行了外部验证。队列中包括所有18岁以上、有最低血细胞计数和生化测量数据的此类患者。灵敏度、特异度、阴性预测值、阳性预测值、受试者工作特征(ROC)曲线下面积(AUC)、校准曲线我们给出了两个临床应用案例的结果。在用例1中，算法识别了20%没有癌症的患者，他们可能不需要紧急的2WW转诊。在用例2中，他们确定了90%的癌症高概率病例，可以优先进行审查。结合一组广泛可用的血液标记物，可以为NHS 2WW患者提供有效的癌症血液测试。这些测试价格实惠，可以快速部署到任何NHS病理实验室，而不需要额外的硬件要求。
To develop and validate tests to assess the risk of any cancer for patients referred to the NHS Urgent Suspected Cancer (2-week wait, 2WW) clinical pathways. Primary and secondary care, one participating regional centre. Retrospective analysis of data from 371 799 consecutive 2WW referrals in the Leeds region from 2011 to 2019. The development cohort was composed of 224 669 consecutive patients with an urgent suspected cancer referral in Leeds between January 2011 and December 2016. The diagnostic algorithms developed were then externally validated on a similar consecutive sample of 147 130 patients (between January 2017 and December 2019). All such patients over the age of 18 with a minimum set of blood counts and biochemistry measurements available were included in the cohort. sensitivity, specificity, negative predictive value, positive predictive value, Receiver Operating Characteristic (ROC) curve Area Under Curve (AUC), calibration curves We present results for two clinical use-cases. In use-case 1, the algorithms identify 20% of patients who do not have cancer and may not need an urgent 2WW referral. In use-case 2, they identify 90% of cancer cases with a high probability of cancer that could be prioritised for review. Combining a panel of widely available blood markers produces effective blood tests for cancer for NHS 2WW patients. The tests are affordable, and can be deployed rapidly to any NHS pathology laboratory with no additional hardware requirements.
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DOI：
10.1016/j.annonc.2020.02.011
发表时间：
2020-06
期刊：
Annals of oncology : official journal of the European Society for Medical Oncology
影响因子：
--
作者：
Liu MC;Oxnard GR;Klein EA;Swanton C;Seiden MV;CCGA Consortium
通讯作者：
CCGA Consortium
影响因子：
16.6
作者：
Ulz, Peter;Perakis, Samantha;Speicher, Michael R.
通讯作者：
Speicher, Michael R.
DOI：
10.3399/bjgp22x718217
发表时间：
2022-01
期刊：
The British journal of general practice : the journal of the Royal College of General Practitioners
影响因子：
--
作者：
Smith L;Sansom N;Hemphill S;Bradley SH;Shinkins B;Wheatstone P;Hamilton W;Neal RD
通讯作者：
Neal RD
影响因子：
37.8
作者：
Collins, Gary S.;Reitsma, Johannes B.;Moons, Karel G. M.
通讯作者：
Moons, Karel G. M.
DOI：
10.1126/science.aar3247
发表时间：
2018-02-23
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Cohen JD;Li L;Wang Y;Thoburn C;Afsari B;Danilova L;Douville C;Javed AA;Wong F;Mattox A;Hruban RH;Wolfgang CL;Goggins MG;Dal Molin M;Wang TL;Roden R;Klein AP;Ptak J;Dobbyn L;Schaefer J;Silliman N;Popoli M;Vogelstein JT;Browne JD;Schoen RE;Brand RE;Tie J;Gibbs P;Wong HL;Mansfield AS;Jen J;Hanash SM;Falconi M;Allen PJ;Zhou S;Bettegowda C;Diaz LA Jr;Tomasetti C;Kinzler KW;Vogelstein B;Lennon AM;Papadopoulos N
通讯作者：
Papadopoulos N