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Items: 1 to 20 of 100

1.

Evaluating a new marker for risk prediction: decision analysis to the rescue.

Baker SG, Kramer BS.

Discov Med. 2012 Sep;14(76):181-8. Review.

2.

Evaluating a new marker for risk prediction using the test tradeoff: an update.

Baker SG, Van Calster B, Steyerberg EW.

Int J Biostat. 2012 Mar 22;8(1). pii: /j/ijb.2012.8.issue-1/1557-4679.1395/1557-4679.1395.xml. doi: 10.1515/1557-4679.1395.

PMID:
22499728
3.

Graphical assessment of incremental value of novel markers in prediction models: From statistical to decision analytical perspectives.

Steyerberg EW, Vedder MM, Leening MJ, Postmus D, D'Agostino RB Sr, Van Calster B, Pencina MJ.

Biom J. 2015 Jul;57(4):556-70. doi: 10.1002/bimj.201300260. Epub 2014 Jul 18.

PMID:
25042996
4.

Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond.

Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS.

Stat Med. 2008 Jan 30;27(2):157-72; discussion 207-12.

PMID:
17569110
5.

Sensitivity and specificity can change in opposite directions when new predictive markers are added to risk models.

Van Calster B, Steyerberg EW, D'Agostino RB Sr, Pencina MJ.

Med Decis Making. 2014 May;34(4):513-22. doi: 10.1177/0272989X13513654. Epub 2013 Dec 30.

PMID:
24378915
6.

[Performance measures for prediction models and markers: evaluation of predictions and classifications].

Steyerberg EW, Van Calster B, Pencina MJ.

Rev Esp Cardiol. 2011 Sep;64(9):788-94. doi: 10.1016/j.recesp.2011.04.017. Epub 2011 Jul 16. Spanish.

7.

Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers.

Vickers AJ, Cronin AM, Elkin EB, Gonen M.

BMC Med Inform Decis Mak. 2008 Nov 26;8:53. doi: 10.1186/1472-6947-8-53.

8.

[Discriminative ability, reclassification and net benefit: the predictive value of biomarkers].

Steyerberg EW, Pencina MJ, Van Calster B.

Ned Tijdschr Geneeskd. 2012;156(41):A5029. Review. Dutch.

PMID:
23062255
9.

Evaluation of markers and risk prediction models: overview of relationships between NRI and decision-analytic measures.

Van Calster B, Vickers AJ, Pencina MJ, Baker SG, Timmerman D, Steyerberg EW.

Med Decis Making. 2013 May;33(4):490-501. doi: 10.1177/0272989X12470757. Epub 2013 Jan 11. Review.

10.

Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics.

Romanens M, Ackermann F, Spence JD, Darioli R, Rodondi N, Corti R, Noll G, Schwenkglenks M, Pencina M.

Eur J Cardiovasc Prev Rehabil. 2010 Feb;17(1):18-23. doi: 10.1097/HJR.0b013e3283347059. Review.

PMID:
19952758
11.

[Prognostic value and clinical effectiveness of high sensitivity C-reactive protein as a marker in primary prevention of major cardiac events].

Schwarzer R, Schnell-Inderst P, Grabein K, Göhler A, Stollenwerk B, Grandi N, Klauss V, Wasem J, Siebert U.

Z Evid Fortbild Qual Gesundhwes. 2009;103(6):319-29. Review. German.

PMID:
19839204
12.

How to interpret a small increase in AUC with an additional risk prediction marker: decision analysis comes through.

Baker SG, Schuit E, Steyerberg EW, Pencina MJ, Vickers A, Moons KG, Mol BW, Lindeman KS.

Stat Med. 2014 Sep 28;33(22):3946-59. doi: 10.1002/sim.6195. Epub 2014 May 13. Erratum in: Stat Med. 2014 Feb 28;34(5):900. Vickers, Andew [corrected to Vickers, Andrew]. Stat Med. 2014 Sep 28;33(22)3960.

13.

Current concepts of tumor markers in bladder cancer.

Droller MJ.

Urol Clin North Am. 2002 Feb;29(1):229-34. Review.

PMID:
12109349
14.

Assessing the added value of breast tumor markers in genetic risk prediction model BRCAPRO.

Biswas S, Tankhiwale N, Blackford A, Barrera AM, Ready K, Lu K, Amos CI, Parmigiani G, Arun B.

Breast Cancer Res Treat. 2012 May;133(1):347-55. doi: 10.1007/s10549-012-1958-z. Epub 2012 Jan 21.

PMID:
22270937
15.

Calibration of risk prediction models: impact on decision-analytic performance.

Van Calster B, Vickers AJ.

Med Decis Making. 2015 Feb;35(2):162-9. doi: 10.1177/0272989X14547233. Epub 2014 Aug 25.

PMID:
25155798
16.

High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis.

Würtz P, Raiko JR, Magnussen CG, Soininen P, Kangas AJ, Tynkkynen T, Thomson R, Laatikainen R, Savolainen MJ, Laurikka J, Kuukasjärvi P, Tarkka M, Karhunen PJ, Jula A, Viikari JS, Kähönen M, Lehtimäki T, Juonala M, Ala-Korpela M, Raitakari OT.

Eur Heart J. 2012 Sep;33(18):2307-16. doi: 10.1093/eurheartj/ehs020. Epub 2012 Mar 26.

PMID:
22450427
17.

Tumor markers in breast cancer monitoring should be scheduled according to initial stage and follow-up time: a prospective study on 859 patients.

Gion M, Peloso L, Mione R, Vignati G, Fortunato A, Saracchini S, Biasioli R, Gulisano M, Cappelli G.

Cancer J. 2001 May-Jun;7(3):181-90.

PMID:
11419026
18.

Predicting risk of breast cancer in postmenopausal women by hormone receptor status.

Chlebowski RT, Anderson GL, Lane DS, Aragaki AK, Rohan T, Yasmeen S, Sarto G, Rosenberg CA, Hubbell FA; Women's Health Initiative Investigators.

J Natl Cancer Inst. 2007 Nov 21;99(22):1695-705. Epub 2007 Nov 13.

PMID:
18000216
19.

Prognostic value, clinical effectiveness and cost-effectiveness of high sensitivity C-reactive protein as a marker in primary prevention of major cardiac events.

Schnell-Inderst P, Schwarzer R, Göhler A, Grandi N, Grabein K, Stollenwerk B, Klauß V, Wasem J, Siebert U.

GMS Health Technol Assess. 2009 May 12;5:Doc06. doi: 10.3205/hta000068.

20.

Assessing the incremental value of diagnostic and prognostic markers: a review and illustration.

Steyerberg EW, Pencina MJ, Lingsma HF, Kattan MW, Vickers AJ, Van Calster B.

Eur J Clin Invest. 2012 Feb;42(2):216-28. doi: 10.1111/j.1365-2362.2011.02562.x. Epub 2011 Jul 5.

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