A permutation method to assess heterogeneity in external validation for risk prediction models

PLoS ONE

Volumn 10, Issue 1, 2015, Pages

  Wang, Ling Yi ^b   Lee, Wen Chung ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b BUDDHIST TZU CHI GENERAL HOSPITAL   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

AREA UNDER THE CURVE; ARTICLE; BREAST CANCER; CONTROLLED STUDY; FEMALE; GENE EXPRESSION; HUMAN; MAJOR CLINICAL STUDY; MICROARRAY ANALYSIS; MONTE CARLO METHOD; PERMUTATION METHOD; PREDICTION; REPRODUCIBILITY; SUPPORT VECTOR MACHINE; BREAST NEOPLASMS; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETICS; RISK; STATISTICAL MODEL;

BREAST NEOPLASMS; FEMALE; GENE EXPRESSION PROFILING; HUMANS; MODELS, STATISTICAL; MONTE CARLO METHOD; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; RISK;

EID: 84921793715     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0116957     Document Type: Article

References (13)

1. Eagle KA, Lim MJ, Dabbous OH, Pieper KS, Goldberg RJ, et al. (2004) A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry. JAMA 291: 2727-2733. doi: 10.1001/jama.291.22.2727 PMID: 15187054
2. Barlow WE, White E, Balard-Barbash R, Vacek PM, Titus-Ernstoff L, et al. (2006) Prospective breast cancer risk prediction model for women undergoing screening mammography. J Natl Cancer Inst 98: 1204-1214. doi: 10.1093/jnci/djj331 PMID: 16954473
3. Moons KG, Kengne AP, Woodward M, Royston P, Vergouwe Y, et al. (2012) Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart 98: 683-690. doi: 10.1136/heartjnl-2011-301246 PMID: 22397945
4. Efron B, Tibshirani RJ (1994) An introduction to the bootstrap: CRC press.
5. Refaeilzadeh P, Tang L, Liu H (2009) Cross-validation. Encyclopedia of database systems: Springer. pp. 532-538.
6. Debray TP, Vergouwe Y, Koffijberg H, Nieboer D, Steyerberg EW, et al. (2014) A new framework to enhance the interpretation of external validation studies of clinical prediction models. J Clin Epidemiol (in press).
7. Vapnik VN (1999) An overview of statistical learning theory. IEEE Trans Neural Netw 10: 988-999. doi: 10.1109/72.788640 PMID: 18252602
8. Karatzoglou A, Meyer D, Hornik K (2005) Support vector machines in R.
9. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, et al. (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365: 671-679. doi: 10.1016/ S0140-6736(05)17947-1 PMID: 15721472
10. Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, et al. (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98: 262-272. doi: 10.1093/jnci/djj052 PMID: 16478745
11. Moons KG, Kengne AP, Grobbee DE, Royston P, Vergouwe Y, et al. (2012) Risk prediction models: II. External validation, model updating, and impact assessment. Heart 98: 691-698. doi: 10.1136/ heartjnl-2011-301247 PMID: 22397946
12. Toll DB, Janssen KJ, Vergouwe Y, Moons KG (2008) Validation, updating and impact of clinical prediction rules: a review. J Clin Epidemiol 61: 1085-1094. doi: 10.1016/j.jclinepi.2008.04.008 PMID: 19208371
13. Vergouwe Y, Moons KG, Steyerberg EW (2010) External validity of risk models: Use of benchmark values to disentangle a case-mix effect from incorrect coefficients. Am J Epidemiol 172: 971-980. doi: 10.1093/aje/kwq223 PMID: 20807737