Derivation and assessment of risk prediction models using case-cohort data.
Derivation and assessment of risk prediction models using case-cohort data.
复制标题
DOI：
10.1186/1471-2288-13-113
复制
发表时间：
2013-09-13
影响因子：
4
通讯作者：
Pennells L
中科院分区：
文献类型：
--
作者：
Sanderson J;Thompson SG;White IR;Aspelund T;Pennells L
病例队列研究越来越多地用于量化新因素与疾病风险的关联。传统的预测能力的措施需要修改这种设计。我们展示了如何调整Harrell的C指数、Royston的D指数以及基于类别和连续版本的净重新分类指数（NRI）。我们模拟了全队列和病例-队列数据，样本分数范围从1%到90%，使用来自冠心病队列研究的协变量和两种发病率。然后，我们比较了所提出的风险预测指标的准确性和精度。C指数和D必须加权，以获得无偏的结果。NRI不需要修改，前提是从计算中排除相关的非子队列病例。模拟的经验标准误与C指数和D的分析标准误一致，但与NRI不一致。在我们的示例中观察到预测度量的良好相对效率，条件是C指数的采样分数高于40%，D指数的采样分数高于60%，NRI指数的采样分数高于30%。Stata代码可用。病例队列设计可用于提供C指数、D测量和NRI的无偏估计。
Case-cohort studies are increasingly used to quantify the association of novel factors with disease risk. Conventional measures of predictive ability need modification for this design. We show how Harrell’s C-index, Royston’s D, and the category-based and continuous versions of the net reclassification index (NRI) can be adapted. We simulated full cohort and case-cohort data, with sampling fractions ranging from 1% to 90%, using covariates from a cohort study of coronary heart disease, and two incidence rates. We then compared the accuracy and precision of the proposed risk prediction metrics. The C-index and D must be weighted in order to obtain unbiased results. The NRI does not need modification, provided that the relevant non-subcohort cases are excluded from the calculation. The empirical standard errors across simulations were consistent with analytical standard errors for the C-index and D but not for the NRI. Good relative efficiency of the prediction metrics was observed in our examples, provided the sampling fraction was above 40% for the C-index, 60% for D, or 30% for the NRI. Stata code is made available. Case-cohort designs can be used to provide unbiased estimates of the C-index, D measure and NRI.
登录
查看更多内容
影响因子：
2
作者：
Pencina, Michael J.;D'Agostino, Ralph B., Sr.;Steyerberg, Ewout W.
通讯作者：
Steyerberg, Ewout W.
影响因子：
5
作者：
Ganna, Andrea;Reilly, Marie;Ingelsson, Erik
通讯作者：
Ingelsson, Erik
DOI：
10.1056/nejmoa1107477
发表时间：
2012-10-04
期刊：
The New England journal of medicine
影响因子：
--
作者：
Emerging Risk Factors Collaboration;Kaptoge S;Di Angelantonio E;Pennells L;Wood AM;White IR;Gao P;Walker M;Thompson A;Sarwar N;Caslake M;Butterworth AS;Amouyel P;Assmann G;Bakker SJ;Barr EL;Barrett-Connor E;Benjamin EJ;Björkelund C;Brenner H;Brunner E;Clarke R;Cooper JA;Cremer P;Cushman M;Dagenais GR;D'Agostino RB Sr;Dankner R;Davey-Smith G;Deeg D;Dekker JM;Engström G;Folsom AR;Fowkes FG;Gallacher J;Gaziano JM;Giampaoli S;Gillum RF;Hofman A;Howard BV;Ingelsson E;Iso H;Jørgensen T;Kiechl S;Kitamura A;Kiyohara Y;Koenig W;Kromhout D;Kuller LH;Lawlor DA;Meade TW;Nissinen A;Nordestgaard BG;Onat A;Panagiotakos DB;Psaty BM;Rodriguez B;Rosengren A;Salomaa V;Kauhanen J;Salonen JT;Shaffer JA;Shea S;Ford I;Stehouwer CD;Strandberg TE;Tipping RW;Tosetto A;Wassertheil-Smoller S;Wennberg P;Westendorp RG;Whincup PH;Wilhelmsen L;Woodward M;Lowe GD;Wareham NJ;Khaw KT;Sattar N;Packard CJ;Gudnason V;Ridker PM;Pepys MB;Thompson SG;Danesh J
通讯作者：
Danesh J
影响因子：
7.2
作者：
Onland-Moret, N. Charlotte;van der A, Daphne L.;Peeters, Petra H. M.
通讯作者：
Peeters, Petra H. M.
影响因子：
3.7
作者：
Herder C;Baumert J;Zierer A;Roden M;Meisinger C;Karakas M;Chambless L;Rathmann W;Peters A;Koenig W;Thorand B
通讯作者：
Thorand B