Comments on ‘Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond’ by M. J. Pencina, R. B. D'Agostino Sr, R. B. D'Agostino Jr, R. S. Vasan, Statistics in Medicine (DOI: 10.1002/sim.2929)

C-Reactive Protein and Other Circulating Markers of Inflammation in the Prediction of Coronary Heart Disease

Danesh, J., Wheeler, J. G., Hirschfield, G. M., Eda, S., Eiriksdottir, G., Rumley, A., Lowe, G. D. O., Pepys, M. B., & Gudnason, V. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa032804 · Cited by 2,953

A general cardiovascular risk profile: The Framingham study

Kannel, W. B., McGee, D., & Gordon, T. (1976) · The American Journal of Cardiology · doi:10.1016/0002-9149(76)90061-8 · Cited by 1,189

General Cardiovascular Risk Profile for Use in Primary Care: The Framingham Heart Study

D’Agostino, R. B., Vasan, R. S., Pencina, M. J., Wolf, P. A., Cobain, M., Massaro, J. M., & Kannel, W. B. (2008) · Circulation · doi:10.1161/circulationaha.107.699579 · Cited by 7,491

Assessing the Performance of Prediction Models: A Framework for Traditional and Novel Measures

Steyerberg, E. W., Vickers, A. J., Cook, N. R., Gerds, T., Gonen, M., Obuchowski, N., Pencina, M. J., & Kattan, M. W. (2010) · Epidemiology · doi:10.1097/ede.0b013e3181c30fb2 · Cited by 5,170

Estimating glomerular filtration rate from serum creatinine and cystatin C

Inker, L. A., Schmid, C. H., Tighiouart, H., Eckfeldt, J. H., Feldman, H. I., Greene, T., Kusek, J. W., Manzi, J., Van Lente, F., Zhang, Y. L., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1114248 · Cited by 4,102

2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines

Goff, D. C., Lloyd-Jones, D. M., Bennett, G., Coady, S., D’Agostino, R. B., Gibbons, R., Greenland, P., Lackland, D. T., Levy, D., O’Donnell, C. J., et al. (2014) · Circulation · doi:10.1161/01.cir.0000437741.48606.98 · Cited by 3,697

Arterial Stiffness and Cardiovascular Events: The Framingham Heart Study

Mitchell, G. F., Hwang, S.-J., Vasan, R. S., Larson, M. G., Pencina, M. J., Hamburg, N. M., Vita, J. A., Levy, D., & Benjamin, E. J. (2010) · Circulation · doi:10.1161/circulationaha.109.886655 · Cited by 2,225

On the C‐statistics for evaluating overall adequacy of risk prediction procedures with censored survival data

Uno, H., Cai, T., Pencina, M. J., D'Agostino, R. B., & Wei, L. J. (2011) · Statistics in Medicine · doi:10.1002/sim.4154 · Cited by 1,535

Evaluation of risk stratification schemes for ischaemic stroke and bleeding in 182 678 patients with atrial fibrillation: the Swedish Atrial Fibrillation cohort study

Friberg, L., Rosenqvist, M., & Lip, G. Y. H. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehr488 · Cited by 1,192

Prognosis and prognostic research: Developing a prognostic model

Royston, P., Moons, K. G. M., Altman, D. G., & Vergouwe, Y. (2009) · BMJ · doi:10.1136/bmj.b604 · Cited by 1,172

A combined comorbidity score predicted mortality in elderly patients better than existing scores

Gagne, J. J., Glynn, R. J., Avorn, J., Levin, R., & Schneeweiss, S. (2011) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2010.10.004 · Cited by 995

Prognostic Value of Quantitative Contrast-Enhanced Cardiovascular Magnetic Resonance for the Evaluation of Sudden Death Risk in Patients With Hypertrophic Cardiomyopathy

Chan, R. H., Maron, B. J., Olivotto, I., Pencina, M. J., Assenza, G. E., Haas, T., Lesser, J. R., Gruner, C., Crean, A. M., Rakowski, H., et al. (2014) · Circulation · doi:10.1161/circulationaha.113.007094 · Cited by 962

Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker

Moons, K. G. M., Kengne, A. P., Woodward, M., Royston, P., Vergouwe, Y., Altman, D. G., & Grobbee, D. E. (2012) · Heart · doi:10.1136/heartjnl-2011-301246 · Cited by 889

C-Reactive Protein and Parental History Improve Global Cardiovascular Risk Prediction: The Reynolds Risk Score for Men

Ridker, P. M., Paynter, N. P., Rifai, N., Gaziano, J. M., & Cook, N. R. (2008) · Circulation · doi:10.1161/circulationaha.108.814251 · Cited by 841

Iron deficiency in chronic heart failure: an international pooled analysis

Klip, I. T., Comin-Colet, J., Voors, A. A., Ponikowski, P., Enjuanes, C., Banasiak, W., Lok, D. J., Rosentryt, P., Torrens, A., Polonski, L., et al. (2013) · American Heart Journal · doi:10.1016/j.ahj.2013.01.017 · Cited by 736

A 17-gene Assay to Predict Prostate Cancer Aggressiveness in the Context of Gleason Grade Heterogeneity, Tumor Multifocality, and Biopsy Undersampling

Klein, E. A., Cooperberg, M. R., Magi-Galluzzi, C., Simko, J. P., Falzarano, S. M., Maddala, T., Chan, J. M., Li, J., Cowan, J. E., Tsiatis, A. C., et al. (2014) · European Urology · doi:10.1016/j.eururo.2014.05.004 · Cited by 659

Calcium Density of Coronary Artery Plaque and Risk of Incident Cardiovascular Events

Criqui, M. H., Denenberg, J. O., Ix, J. H., McClelland, R. L., Wassel, C. L., Rifkin, D. E., Carr, J. J., Budoff, M. J., & Allison, M. A. (2014) · JAMA · doi:10.1001/jama.2013.282535 · Cited by 642

Red blood cell distribution width and the risk of death in middle-aged and older adults

Patel, K. V., Ferrucci, L., Ershler, W. B., Longo, D. L., & Guralnik, J. M. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.11 · Cited by 618

Net Reclassification Improvement: Computation, Interpretation, and Controversies: A Literature Review and Clinician's Guide

Leening, M. J. G., Vedder, M. M., Witteman, J. C. M., Pencina, M. J., & Steyerberg, E. W. (2014) · Annals of Internal Medicine · doi:10.7326/m13-1522 · Cited by 594

Optimizing ACS NSQIP Modeling for Evaluation of Surgical Quality and Risk: Patient Risk Adjustment, Procedure Mix Adjustment, Shrinkage Adjustment, and Surgical Focus

Cohen, M. E., Ko, C. Y., Bilimoria, K. Y., Zhou, L., Huffman, K., Wang, X., Liu, Y., Kraemer, K., Meng, X., Merkow, R., et al. (2013) · Journal of the American College of Surgeons · doi:10.1016/j.jamcollsurg.2013.02.027 · Cited by 583

A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses

Ripatti, S., Tikkanen, E., Orho-Melander, M., Havulinna, A. S., Silander, K., Sharma, A., Guiducci, C., Perola, M., Jula, A., Sinisalo, J., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(10)61267-6 · Cited by 562

Value and Limitations of Existing Scores for the Assessment of Cardiovascular Risk

Cooney, M. T., Dudina, A. L., & Graham, I. M. (2009) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2009.07.020 · Cited by 436

Inflammatory Biomarkers and Exacerbations in Chronic Obstructive Pulmonary Disease

Thomsen, M., Ingebrigtsen, T. S., Marott, J. L., Dahl, M., Lange, P., Vestbo, J., & Nordestgaard, B. G. (2013) · JAMA · doi:10.1001/jama.2013.5732 · Cited by 401

Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.

Pirracchio, R., Petersen, M. L., Carone, M., Rigon, M. R., Chevret, S., & van der Laan, M. J. (2015) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(14)70239-5 · Cited by 374

Association between a literature-based genetic risk score and cardiovascular events in women

Paynter, N. P. (2010) · JAMA · doi:10.1001/jama.2010.119 · Cited by 361

Use of Framingham risk score and new biomarkers to predict cardiovascular mortality in older people: population based observational cohort study

de Ruijter, W., Westendorp, R. G. J., Assendelft, W. J. J., den Elzen, W. P. J., de Craen, A. J. M., le Cessie, S., & Gussekloo, J. (2009) · BMJ · doi:10.1136/bmj.a3083 · Cited by 339

Frailty and Early Hospital Readmission After Kidney Transplantation

McAdams-DeMarco, M. A., Law, A., Salter, M. L., Chow, E., Grams, M., Walston, J., & Segev, D. L. (2013) · American Journal of Transplantation · doi:10.1111/ajt.12300 · Cited by 332

C-Reactive Protein and Reclassification of Cardiovascular Risk in the Framingham Heart Study

Wilson, P. W. F., Pencina, M., Jacques, P., Selhub, J., D'Agostino, R., & O'Donnell, C. J. (2008) · Circulation: Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.108.831198 · Cited by 299

Oxidative stress, inflammation, endothelial dysfunction and incidence of type 2 diabetes

Odegaard, A. O., Jacobs, D. R., Sanchez, O. A., Goff, D. C., Reiner, A. P., & Gross, M. D. (2016) · Cardiovascular Diabetology · doi:10.1186/s12933-016-0369-6 · Cited by 286

Fructosamine and glycated albumin for risk stratification and prediction of incident diabetes and microvascular complications: a prospective cohort analysis of the Atherosclerosis Risk in Communities (ARIC) study

Selvin, E., Rawlings, A. M., Grams, M., Klein, R., Sharrett, A. R., Steffes, M., & Coresh, J. (2014) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(13)70199-2 · Cited by 262

Disadvantages of Using the Area under the Receiver Operating Characteristic Curve to Assess Imaging Tests: A Discussion and Proposal for an Alternative Approach

Halligan, S., Altman, D. G., & Mallett, S. (2015) · European Radiology · doi:10.1007/s00330-014-3487-0 · Cited by 255

Cardiovascular Event Prediction and Risk Reclassification by Coronary, Aortic, and Valvular Calcification in the Framingham Heart Study

Hoffmann, U., Massaro, J. M., D'Agostino, R. B., Kathiresan, S., Fox, C. S., & O'Donnell, C. J. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.115.003144 · Cited by 239

Diagnostic and prognostic prediction models

Hendriksen, J. M. T., Geersing, G. J., Moons, K. G. M., & de Groot, J. A. H. (2013) · Journal of Thrombosis and Haemostasis · doi:10.1111/jth.12262 · Cited by 229

Cardiovascular Risk-Estimation Systems in Primary Prevention: Do They Differ? Do They Make a Difference? Can We See the Future?

Cooney, M. T., Dudina, A., D'Agostino, R., & Graham, I. M. (2010) · Circulation · doi:10.1161/circulationaha.109.852756 · Cited by 222

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

Steyerberg, E. W., Pencina, M. J., Lingsma, H. F., Kattan, M. W., Vickers, A. J., & Van Calster, B. (2012) · European Journal of Clinical Investigation · doi:10.1111/j.1365-2362.2011.02562.x · Cited by 219

A Genetic Risk Score Is Associated With Incident Cardiovascular Disease and Coronary Artery Calcium: The Framingham Heart Study

Thanassoulis, G., Peloso, G. M., Pencina, M. J., Hoffmann, U., Fox, C. S., Cupples, L. A., Levy, D., D'Agostino, R. B., Hwang, S.-J., & O'Donnell, C. J. (2012) · Circulation: Cardiovascular Genetics · doi:10.1161/circgenetics.111.961342 · Cited by 211

Reporting performance of prognostic models in cancer: a review.

Mallett, S., Royston, P., Waters, R., Dutton, S., & Altman, D. G. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-21 · Cited by 195

Updated genetic score based on 34 confirmed type 2 diabetes loci is associated with diabetes incidence and regression to normoglycemia in the Diabetes Prevention Program

Hivert, M.-F., Jablonski, K. A., Perreault, L., Saxena, R., McAteer, J. B., Franks, P. W., Hamman, R. F., Kahn, S. E., Haffner, S., the DIAGRAM Consortium, et al. (2011) · Diabetes · doi:10.2337/db10-1119 · Cited by 191

Cardiovascular disease: The rise of the genetic risk score

Knowles, J. W., & Ashley, E. A. (2018) · PLOS Medicine · doi:10.1371/journal.pmed.1002546 · Cited by 182

Advanced chronic kidney disease populations have elevated trimethylamine N-oxide levels associated with increased cardiovascular events

Kim, R. B., Morse, B. L., Djurdjev, O., Tang, M., Muirhead, N., Barrett, B., Holmes, D. T., Madore, F., Clase, C. M., Rigatto, C., et al. (2016) · Kidney International · doi:10.1016/j.kint.2016.01.014 · Cited by 179

Trimethylamine N ‐Oxide and Mortality Risk in Patients With Peripheral Artery Disease

Senthong, V., Wang, Z., Fan, Y., Wu, Y., Hazen, S. L., & Tang, W. H. W. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.116.004237 · Cited by 175

Associations among estimated glomerular filtration rate, proteinuria, and adverse cardiovascular outcomes

Bello, A. K., Hemmelgarn, B., Lloyd, A., James, M. T., Manns, B. J., Klarenbach, S., & Tonelli, M. (2011) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.09741110 · Cited by 151

Quantifying the Added Value of a Diagnostic Test or Marker

Moons, K. G. M., de Groot, J. A. H., Linnet, K., Reitsma, J. B., & Bossuyt, P. M. M. (2012) · Clinical Chemistry · doi:10.1373/clinchem.2012.182550 · Cited by 152

An Absolute Risk Model to Identify Individuals at Elevated Risk for Pancreatic Cancer in the General Population

Klein, A. P., Lindström, S., Mendelsohn, J. B., Steplowski, E., Arslan, A. A., Bueno-de-Mesquita, H. B., Fuchs, C. S., Gallinger, S., Gross, M., Helzlsouer, K., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072311 · Cited by 148

Predictors of remission in depression to individual and combined treatments (PReDICT): study protocol for a randomized controlled trial

Dunlop, B. W., Binder, E. B., Cubells, J. F., Goodman, M. M., Kelley, M. E., Kinkead, B., Kutner, M., Nemeroff, C. B., Newport, D. J., Owens, M. J., et al. (2012) · Trials · doi:10.1186/1745-6215-13-106 · Cited by 136

Longitudinal Algorithms to Estimate Cardiorespiratory Fitness

Artero, E. G., Jackson, A. S., Sui, X., Lee, D.-C., O’Connor, D. P., Lavie, C. J., Church, T. S., & Blair, S. N. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2014.03.008 · Cited by 128

Association of C-Reactive Protein With Cardiovascular Disease Mortality According to Diabetes Status

Kengne, A. P., Batty, G. D., Hamer, M., Stamatakis, E., & Czernichow, S. (2012) · Diabetes Care · doi:10.2337/dc11-1588 · Cited by 105

Metformin does not affect clinically relevant outcomes in patients with idiopathic pulmonary fibrosis

Spagnolo, P., Kreuter, M., Maher, T. M., Wuyts, W., Bonella, F., Corte, T. J., Kopf, S., Weycker, D., Kirchgaessler, K.-U., & Ryerson, C. J. (2018) · Respiration · doi:10.1159/000489668 · Cited by 61

Prediction of type 2 diabetes in women with a history of gestational diabetes using a genetic risk score

Kwak, S. H., Choi, S. H., Kim, K., Jung, H. S., Cho, Y. M., Lim, S., Cho, N. H., Kim, S. Y., Park, K. S., & Jang, H. C. (2013) · Diabetologia · doi:10.1007/s00125-013-3059-x · Cited by 56

Update of the German Diabetes Risk Score and external validation in the German MONICA/KORA study

Mühlenbruch, K., Ludwig, T., Jeppesen, C., Joost, H.-G., Rathmann, W., Meisinger, C., Peters, A., Boeing, H., Thorand, B., & Schulze, M. B. (2014) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2014.03.013 · Cited by 52

Association between Non-High-Density Lipoprotein Cholesterol Levels and the Incidence of Coronary Heart Disease among Japanese: The Circulatory Risk in Communities Study (CIRCS)

Kitamura, A., Noda, H., Nakamura, M., Kiyama, M., Okada, T., Imano, H., Ohira, T., Sato, S., Yamagishi, K., & Iso, H. (2011) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.7237 · Cited by 51

The Impact of C-Reactive Protein on Risk of Stroke, Stroke Subtypes, and Ischemic Heart Disease in Middle-Aged Japanese: the Japan Public Health Center-Based Study

Iso, H., Noda, H., Ikeda, A., Yamagishi, K., Inoue, M., Iwasaki, M., & Tsugane, S. (2012) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.11999 · Cited by 48

Population-Based Evidence that Survival in Amyotrophic Lateral Sclerosis Is Related to Weight Loss at Diagnosis

Marin, B., Arcuti, S., Jesus, P., Logroscino, G., Copetti, M., Fontana, A., Nicol, M., Raymondeau, M., Desport, J. C., Preux, P. M., et al. (2016) · Neurodegenerative Diseases · doi:10.1159/000442444 · Cited by 48

Serum activin A and B levels predict outcome in patients with acute respiratory failure: a prospective cohort study

de Kretser, D. M., Bensley, J. G., Pettilä, V., Linko, R., Hedger, M. P., Hayward, S., Allan, C. A., McLachlan, R. I., Ludlow, H., & Phillips, D. J. (2013) · Critical Care · doi:10.1186/cc13093 · Cited by 39

Chapter 12: Systematic Review of Prognostic Tests

Rector, T. S., Taylor, B. C., & Wilt, T. J. (2012) · Journal of General Internal Medicine · doi:10.1007/s11606-011-1899-y · Cited by 37

Strengthening the reporting of genetic risk prediction studies: the GRIPS statement

Janssens, A. C. J. W., Ioannidis, J. P. A., van Duijn, C. M., Little, J., Khoury, M. J., & for the GRIPS Group (2011) · European Journal of Clinical Investigation · doi:10.1111/j.1365-2362.2011.02494.x · Cited by 29

Predicting Prediabetes and Diabetes: Can We Do It? Is It Worth It?

Gillman, M. W. (2010) · Archives of Pediatrics & Adolescent Medicine · doi:10.1001/archpediatrics.2009.270 · Cited by 5