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Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement
Open accessAbstract
Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).
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Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Self-citationPreferred reporting items for systematic reviews and meta-analyses: The PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & the PRISMA Group* (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-151-4-200908180-00135 · Cited by 37,554
Self-citationvon Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020
Self-citationPreferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.06.005 · Cited by 19,575
Self-citation2013 ACCF/AHA Guideline for the Management of Heart Failure
Yancy, C. W., Jessup, M., Bozkurt, B., Butler, J., Casey, D. E., Drazner, M. H., Fonarow, G. C., Geraci, S. A., Horwich, T., Januzzi, J. L., et al. (2013) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.05.019 · Cited by 12,536
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147
Self-citation2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk
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) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.11.005 · Cited by 4,945
Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · BMJ · doi:10.1136/bmj.326.7379.41 · Cited by 3,215
Self-citationTowards Complete and Accurate Reporting of Studies of Diagnostic Accuracy: The STARD Initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · Radiology · doi:10.1148/radiol.2261021292 · Cited by 3,215
Self-citationVandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2007) · Epidemiology · doi:10.1097/ede.0b013e3181577511 · Cited by 2,779
Self-citation
Research works printed but not linked: 26
- Altman DG, McShane LM, Sauerbrei W, Taube SE (2012) Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration. BMC Med 10: 51. · DOI · Paper page
- Altman DG, Vergouwe Y, Royston P, Moons KGM (2009) Prognosis and prognostic research: Validating a prognostic model. BMJ 338: b605. · DOI · Paper page
- Anderson KM, Odell PM, Wilson PWF, Kannel WB (1991) Cardiovascular disease risk profiles. Am Heart J 121: 293–298. · DOI · Paper page
- Collins GS, Michaëlsson K (2012) Fracture risk assessment: state of the art, methodologically unsound, or poorly reported? Curr Osteoporos Rep 10: 199–207. · DOI · Paper page
- Collins GS, Omar O, Shanyinde M, Yu LM (2013) A systematic review finds prediction models for chronic kidney were poorly reported and often developed using inappropriate methods. J Clin Epidemiol 66: 268–277. · DOI · Paper page
- Haybittle JL, Blamey RW, Elston CW, Johnson J, Doyle PJ, Campbell FC, Nicholson RI, Griffiths K (1982) A prognostic index in primary breast cancer. Br J Cancer 45: 363–366. · DOI · Paper page
- Hayward RA, Kent DM, Vijan S, Hofer TP (2006) Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis. BMC Med Res Methodol 6: 18. · DOI · Paper page
- Hemingway H, Riley RD, Altman DG (2009) Ten steps towards improving prognosis research. BMJ 339: b4184. · DOI · Paper page
- Janssens AC, Ioannidis JP, Bedrosian S, Boffetta P, Dolan SM, Dowling N, Fortier I, Freedman AN, Grimshaw JM, Gulcher J, Gwinn M, Hlatky MA, Janes H, Kraft P, Melillo S, O'Donnell CJ, Pencina MJ, Ransohoff D, Schully SD, Seminara D, Winn DM, Wright CF, van Duijn CM, Little J, Khoury MJ (2011a) Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration. Eur J Clin Invest 41: 1010–1035. · DOI
- Järvinen TL, Jokihaara J, Guy P, Alonso-Coello P, Collins GS, Michaëlsson K, Sievänen H (2014) Conflicts at the heart of the FRAX tool. CMAJ 185: 165–167. · DOI · Paper page
- Justice AC, Covinsky KE, Berlin JA (1999) Assessing the generalizability of prognostic information. Ann Intern Med 130: 515–524. · DOI · Paper page
- Knottnerus JA (1995) Diagnostic prediction rules: principles, requirements and pitfalls. Prim Care 22: 341–363. · DOI · Paper page
- Laupacis A, Sekar N, Stiell IG (1997) Clinical prediction rules. A review and suggested modifications of methodological standards. JAMA 277: 488–494. · DOI · Paper page
- Le Gall JR, Loirat P, Alperovitch A, Glaser P, Granthil C, Mathieu D, Mercier P, Thomas R, Villers D (1984) A simplified acute physiology score for ICU patients. Crit Care Med 12: 975–977. · DOI · Paper page
- Moons KG, Kengne AP, Woodward M, Royston P, Vergouwe Y, Altman DG, Grobbee DE (2012b) Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart 98: 683–690. · DOI · Paper page
- Moons KGM, Altman DG, Vergouwe Y, Royston P (2009a) Prognosis and prognostic research: application and impact of prognostic models in clinical practice. BMJ 338: b606. · DOI · Paper page
- Moons KGM, Royston P, Vergouwe Y, Grobbee DE, Altman DG (2009b) Prognosis and prognostic research: what, why, and how? BMJ 338: b375. · DOI · Paper page
- Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R (1999) European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg 16: 9–13. · DOI · Paper page
- Reilly BM, Evans AT (2006) Translating clinical research into clinical practice: impact of using prediction rules to make decisions. Ann Intern Med 144: 201–209. · DOI · Paper page
- Steyerberg EW (2009) Clinical prediction models: a practical approach to development, validation, and updating. Springer: New York. · DOI · Paper page
- Steyerberg EW, Bleeker SE, Moll HA, Grobbee DE, Moons KGM (2003) Internal and external validation of predictive models: A simulation study of bias and precision in small samples. J Clin Epidemiol 56: 441–447. · DOI · Paper page
- Steyerberg EW, Harrell FE, Borsboom GJJM, Eijkemans MJC, Vergouwe Y, Habbema JDF (2001b) Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol 54: 774–781. · DOI · Paper page
- Stiell IG, Greenberg GH, McKnight RD, Nair RC, McDowell I, Worthington JR (1992) A study to develop clinical decision rules for the use of radiography in acute ankle injuries. Ann Emerg Med 21: 384–390. · DOI · Paper page
- Stiell IG, Wells GA, McKnight D, Brison R, Lesiuk H, Clement CM, Eisenhauer MA, Greenberg GH, MacPhail I, Reardon M, Worhington J, Verbeek R, Dreyer J, Cass D, Schull M, Morrison L, Rowe B, Holroyd B, Bandiera G, Laupacis A (2002a) Canadian C-Spine Rule study for alert and stable trauma patients: I. Background and rationale. CJEM 4: 84–90. · DOI
- Stiell IG, Wells GA, McKnight D, Brison R, Lesiuk H, Clement CM, Eisenhauer MA, Greenberg GH, MacPhail I, Reardon M, Worhington J, Verbeek R, Dreyer J, Cass D, Schull M, Morrison L, Rowe B, Holroyd B, Bandiera G, Laupacis A (2002b) Canadian C-Spine Rule study for alert and stable trauma patients: II. Study objectives and methodology. CJEM 4: 185–193. · DOI
- Wallace E, Smith SM, Perera-Salazar R, Vaucher P, McCowan C, Collins G, Verbakel J, Lakhanpaul M, Fahey T (2011) Framework for the impact analysis and implementation of Clinical Prediction Rules (CPRs). BMC Med Inform Decis Mak 11: 62. · DOI
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Radiomics: the bridge between medical imaging and personalized medicine
Lambin, P., Leijenaar, R. T. H., Deist, T. M., Peerlings, J., de Jong, E. E. C., van Timmeren, J., Sanduleanu, S., Larue, R. T. H. M., Even, A. J. G., Jochems, A., et al. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.141 · Cited by 5,688
Zwanenburg, A., Vallières, M., Abdalah, M. A., Aerts, H. J. W. L., Andrearczyk, V., Apte, A., Ashrafinia, S., Bakas, S., Beukinga, R. J., Boellaard, R., et al. (2020) · Radiology · doi:10.1148/radiol.2020191145 · Cited by 4,177
Seymour, C. W., Liu, V. X., Iwashyna, T. J., Brunkhorst, F. M., Rea, T. D., Scherag, A., Rubenfeld, G., Kahn, J. M., Shankar-Hari, M., Singer, M., et al. (2016) · JAMA · doi:10.1001/jama.2016.0288 · Cited by 3,939
STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L., Lijmer, J. G., Moher, D., Rennie, D., de Vet, H. C. W., et al. (2015) · BMJ · doi:10.1136/bmj.h5527 · Cited by 3,660
Self-citationPROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies
Wolff, R. F., Moons, K. G. M., Riley, R. D., Whiting, P. F., Westwood, M., Collins, G. S., Reitsma, J. B., Kleijnen, J., Mallett, S., & for the PROBAST Group† (2019) · Annals of Internal Medicine · doi:10.7326/m18-1376 · Cited by 2,984
Self-citation
Metadata
- Authors
- Collins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. G. M.
- Venue
- British Journal of Cancer
- Published
- 2015-01
- Volume
- 112
- Issue
- 2
- Pages
- 251-259
- ISSN
- 0007-0920 (ISSN-L)
- 1532-1827
- OpenAlex
- W2006940889
- Cited by
- 3,293
- References
- 34
- FWCI
- 127.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
- Licence
- creativecommons.org/licenses/by/4.0 (tdm)
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