Risk Stratification Case Study Examples

1. Cook NR, Buring JE, Ridker PM. The effect of including C-reactive protein in cardiovascular risk prediction models for women. Annals of Internal Medicine. 2006;145:21–9.[PubMed]

2. Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation. 2007;115:928–35.[PubMed]

3. Tice JA, Cummings SR, Smith-Bindman R, Ichikawa L, Barlow WE, Kerlikowske K. Using clinical factors and mammographic breast density to estimate breast cancer risk: Development and validation of a new predictive model. Annals of Internal Medicine. 2008;148:337–47.[PMC free article][PubMed]

4. Lauer MS, Pothier CE, Magid DJ, Smith SS, Kattan MW. An externally validated model for predicting long-term survival after exercise treadmill testing in patients with suspected coronary artery disease and a normal electrocardiogram. Annals of Internal Medicine. 2007;147:821–8.[PubMed]

5. van der Steeg WA, Boekholdt M, Stein EA, El-archaoui K, Stroes ESG, Sandhu MS, Wareham NJ, Jukema JW, Luben R, Zwinderman AH, Kastelein JJP, Khaw K-T. Role of the apolipoprotein B – apolipoprotein A-1 ratio in cardiovascular risk assessment: A case-control analysis in EPIC-Norfolk. Annals of Internal Medicine. 2007;146:640–8.[PubMed]

6. Parikh NI, Pencina MJ, Wang TJ, Benjamin EJ, Lanier KJ, Levy D, D’Agostino RB, Kannel WB, Vasan RS. A risk score for predicting near-term incidence of hypertension: The Framingham heart study. Annals of Internal Medicine. 2008;148:102–10.[PubMed]

7. Wang TJ, Gona P, Larson MG, Tofler GH, Levy D, Newton-Cheh C, Jacques PF, Rifai N, Selhub J, Robins SJ, Benjamin EJ, D’Agostino RB, Vasan RS. Multiple biomarkers for the prediction of first major cardiovascular events and death. New England Journal of Medicine. 2006;355:2631–39.[PubMed]

8. Chlebowski RT, Collyar DE, Somerfield MR, Pfister DG. American Society of Clinical Oncology technology assessment on breast cancer risk reduction strategies: Tamoxifen and raloxifene. Journal of Clinical Oncology. 1999;17:1939–55.[PubMed]

9. Levine M, Moutquin JM, Walton R, Feightner J. Chemoprevention of breast cancer. A joint guideline from the Canadian Task Force on preventive health care and the Canadian Breast Cancer Initiative’s steering committee on clinical practice guidelines for the care and treatment of breast cancer. Canadian Medical Association Journal. 2001;164:1681–90.[PMC free article][PubMed]

10. Harrell FE. Regression Modelling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. Springer-Verlag; New York: 2001.

11. Hosmer DW, Lemeshow S. Applied Logistic Regression. John Wiley and Sons; New York: 1989. Section 5.2.2.

12. Cook NR. Comments on ‘Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond’ by MJ Pencina et al. Statistics in Medicine. 2008;27:191–5.[PubMed]

13. Cook NR. Statistical evaluation of prognostic versus diagnostic models: Beyond the ROC curve. Clinical Chemistry. 2008;54:17–23.[PubMed]

14. Pencina MJ, Vasan RS, D’Agostino RB. Algorithms for assessing cardiovascular risk in women. Journal of the American Medical Association. 2007;298:176–7.[PubMed]

15. Pencina MJ, D’Agostino RB, Sr, D’Agostino RB, Jr, Vasan RS. Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond. Statistics in Medicine. 2008;27(2):157–72.[PubMed]

16. Pepe MS, Feng Z, Huang Y, Longton G, Prentice R, Thompson IM, Zheng Y. Integrating the predictiveness of a marker with its performance as a classifier. American Journal of Epidemiology. 2008;167(3):362–8.[PMC free article][PubMed]

17. Prentice RL, Pyke R. Logistic disease incidence models and case-control studies. Biometrika. 1979;66:403–11.

18. Borgan O, Langholz B. Non-parametric estimation of relative mortality from nested case-control studies. Biometrics. 1993;49:593–602.[PubMed]

19. Benichou J, Gail MH. Methods of inference for estimates of absolute risk derived from population-based case-control studies. Biometrics. 1995;51:182–94.[PubMed]

20. Langholz B, Borgan O. Methods of inference for estimates of absolute risk derived from population-based case-control studies. Biometrics. 1997;53:767–74.[PubMed]

21. Huang Y, Pepe MS. A Parametric ROC Model Based Approach for Evaluating the Predictiveness of Continuous Markers in Case-control Studies. UW Biostatistics Working Paper Series. Workig Paper 318. http://www.bepress.com/uwbiostat/paper318. [PMC free article][PubMed]

22. Huang Y, Pepe MS. Semiparametric methods for evaluating the covariate-specific predictiveness of continuous markers in matched case-control studies. UW Biostatistics Working Paper Series. Working Paper 329. http://www.bepress.com/uwbiostat/paper329. [PMC free article][PubMed]

23. Pauker SG, Kassirer JP. Therapeutic decision making: A cost-benefit analysis. N Engl J Med. 1975;293(5):229–34.[PubMed]

24. Pepe MS. Invited discussion of “The skill plot: a graphical technique for evaluating diagnostic tests” Biometrics. 2008;64:256–258.

25. Huang Y, Pepe MS, Feng Z. Evaluating the predictiveness of a continuous marker. Biometrics. 2007;63:1181–8.[PMC free article][PubMed]

26. Copas JB. Regression, prediction, and shrinkage. Journal of the Royal Statistical Society, Series B. 1983;45:311–54.

27. Chatfield C. Model uncertainty, data mining, and statistical inference. Journal of the Royal Statistical Society, Series A. 1995;158(part 3):419–66.

28. Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Statistics in Medicine. 1996;15:361–87.[PubMed]

1. Stewart GD, O’Mahony FC, Powles T, Riddick ACP, Harrison DJ, Faratian D. What can molecular pathology contribute to the management of renal cell carcinoma? Nat Rev Urol. 2011;8:255–65. doi: 10.1038/nrurol.2011.43.[PubMed][Cross Ref]

2. Sun M, Thuret R, Abdollah F, Lughezzani G, Schmitges J, Tian Z, et al. Age-adjusted incidence, mortality, and survival rates of stage-specific renal cell carcinoma in North America: a trend analysis. Eur Urol. 2011;59:135–41. doi: 10.1016/j.eururo.2010.10.029.[PubMed][Cross Ref]

3. Heng DY, Xie W, Regan MM, Harshman LC, Bjarnason GA, Vaishampayan UN, et al. External validation and comparison with other models of the International Metastatic Renal-Cell Carcinoma Database Consortium prognostic model: a population-based study. Lancet Oncol. 2013;14:141–8. doi: 10.1016/S1470-2045(12)70559-4.[PMC free article][PubMed][Cross Ref]

4. Motzer RJ, Bacik J, Murphy BA, Russo P, Mazumdar M. Interferon-alfa as a comparative treatment for clinical trials of new therapies against advanced renal cell carcinoma. J Clin Oncol. 2002;20:289–96. doi: 10.1200/JCO.2002.20.1.289.[PubMed][Cross Ref]

5. Kim HL, Seligson D, Liu X, Janzen N, Bui MHT, Yu H, et al. Using protein expressions to predict survival in clear cell renal carcinoma. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2004;10:5464–71 [PubMed]

6. Galsky MD. A prognostic model for metastatic renal-cell carcinoma. Lancet Oncol. 2013;14:102–3. doi: 10.1016/S1470-2045(12)70581-8.[PubMed][Cross Ref]

7. Ljungberg B, Bensalah K, Canfield S, Dabestani S, Hofmann F, Hora M, et al. EAU guidelines on renal cell carcinoma: 2014 Update. Eur Urol. 2015;67:913–24. doi: 10.1016/j.eururo.2015.01.005.[PubMed][Cross Ref]

8. Kern SE. Why your new cancer biomarker may never work: recurrent patterns and remarkable diversity in biomarker failures. Cancer Res. 2012;72:6097–101. doi: 10.1158/0008-5472.CAN-12-3232.[PMC free article][PubMed][Cross Ref]

9. Motzer RJ, Hutson TE, Tomczak P, Michaelson MD, Bukowski RM, Oudard S, et al. Overall survival and updated results for sunitinib compared with interferon alfa in patients with metastatic renal cell carcinoma. J Clin Oncol. 2009;27:3584–90. doi: 10.1200/JCO.2008.20.1293.[PMC free article][PubMed][Cross Ref]

10. Motzer RJ, Hutson TE, Tomczak P, Michaelson MD, Bukowski RM, Rixe O, et al. Sunitinib versus interferon alfa in metastatic renal-cell carcinoma. N Engl J Med. 2007;356:115–24. doi: 10.1056/NEJMoa065044.[PubMed][Cross Ref]

11. Mendel DB, Laird AD, Xin X, Louie SG, Christensen JG, Li G, et al. In vivo antitumor activity of SU11248, a novel tyrosine kinase inhibitor targeting vascular endothelial growth factor and platelet-derived growth factor receptors: determination of a pharmacokinetic/pharmacodynamic relationship. Clin Cancer Res. 2003;9:327–37.[PubMed]

12. Vázquez S, León L, Fernández O, Lázaro M, Grande E, Aparicio L. Sunitinib: the first to arrive at first-line metastatic renal cell carcinoma. Adv Ther. 2012;29:202–17. doi: 10.1007/s12325-011-0099-9.[PubMed][Cross Ref]

13. Weinstock M, McDermott D. Targeting PD-1/PD-L1 in the treatment of metastatic renal cell carcinoma. Ther. Adv. Urol. 2015;7:365. doi: 10.1177/1756287215597647.[PMC free article][PubMed][Cross Ref]

14. Heppner G. Tumor heterogeneity. Cancer Res. 1984;44:2259–65.[PubMed]

15. Gerlinger M, Horswell S, Larkin J, Rowan AJ, Salm MP, Varela I, et al. Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing. Nat Genet. 2014;46:225–33. doi: 10.1038/ng.2891.[PMC free article][PubMed][Cross Ref]

16. Marusyk A, Almendro V, Polyak K. Intra-tumour heterogeneity: a looking glass for cancer? Nat Rev Cancer. 2012;12:323–34. doi: 10.1038/nrc3261.[PubMed][Cross Ref]

17. Abel EJ, Culp SH, Matin SF, Tamboli P, Wallace MJ, Jonasch E, et al. Percutaneous biopsy of primary tumor in metastatic renal cell carcinoma to predict high risk pathological features: comparison with nephrectomy assessment. J Urol. 2010;184:1877–81. doi: 10.1016/j.juro.2010.06.105.[PMC free article][PubMed][Cross Ref]

18. Powles T, Blank C, Chowdhury S, Horenblas S, Peters J, Shamash J, et al. The outcome of patients treated with sunitinib prior to planned nephrectomy in metastatic clear cell renal cancer. Eur Urol. 2011;60:448–54. doi: 10.1016/j.eururo.2011.05.028.[PubMed][Cross Ref]

19. Stewart GD, Riddick ACP, Rae F, Marshall C, MacLeod L, O’Mahony FC, et al. Translational research will fail without surgical leadership: SCOTRRCC a successful surgeon-led Nationwide translational research infrastructure in renal cancer. Surgeon. 2015;13:181–6. doi: 10.1016/j.surge.2015.03.001.[PubMed][Cross Ref]

20. Stewart GD, O’Mahony FC, Laird A, Rashid S, Martin SA, Eory L, et al. Carbonic anhydrase 9 expression increases with vascular endothelial growth factor-targeted therapy and is predictive of outcome in metastatic clear cell renal cancer. Eur Urol. 2014;66:956–63. doi: 10.1016/j.eururo.2014.04.007.[PMC free article][PubMed][Cross Ref]

21. Benjamini Y, Yekutieli D. The control of the false discovery rate in multiple testing under dependency. Ann. Stat. 2001;29:1165–88. doi: 10.1214/aos/1013699998.[Cross Ref]

22. Pencina MJ, Steyerberg EW, D’Agostino RB. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med. 2011;30:11–21. doi: 10.1002/sim.4085.[PMC free article][PubMed][Cross Ref]

23. Kerr KF, Wang Z, Janes H, McClelland RL, Psaty BM, Pepe MS. Net reclassification indices for evaluating risk prediction instruments: a critical review. Epidemiology. 2014;25:114–21. doi: 10.1097/EDE.0000000000000018.[PMC free article][PubMed][Cross Ref]

24. O’Mahony FC, Nanda J, Laird A, Mullen P, Caldwell H, Overton IM, et al. The use of reverse phase protein arrays (RPPA) to explore protein expression variation within individual renal cell cancers. J Vis Exp. 2013;22. doi: 10.3791/50221 [PMC free article][PubMed]

25. Stewart GD, O’Mahony FC, Laird A, Eory L, Lubbock ALR, Mackay A, et al. Sunitinib treatment exacerbates intratumoral heterogeneity in metastatic renal cancer. Clin Cancer Res. 2015;21:4212–23. doi: 10.1158/1078-0432.CCR-15-0207.[PubMed][Cross Ref]

26. Cox D. Regression models and life tables. J R Stat Soc B. 1972;34:187–220.

27. Kohavi R, John GH. Wrappers for feature subset selection. Artif Intell. 1997;97:273–324. doi: 10.1016/S0004-3702(97)00043-X.[Cross Ref]

28. Venables WN, Ripley BD. Modern applied statistics with S. New York: Springer; 2010.

29. Press WH, Teukolsky SA. Quasi (that is, sub) random numbers. Comput Phys. 1989;3:76–9. doi: 10.1063/1.4822879.[Cross Ref]

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