Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

BMC Medicine

Karel GM Moons²  Douglas G Altman¹  Johannes B Reitsma²  Gary S Collins¹ 

[1]Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, Centre for Statistics in Medicine, University of Oxford, Oxford OX3 7LD, UK

[2]Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, 3508, GA, the Netherlands

关键词: Reporting;    Transparency;    Validation;    Model development;    Diagnostic;    Prognostic;    Prediction models;   

Others  :  1109878
DOI  :  10.1186/s12916-014-0241-z

 received in 2014-11-13, accepted in 2014-11-14,  发布年份 2015

【 摘 要 】

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 webcite).

Editors’ note: In order to encourage dissemination of the TRIPOD Statement, this article is freely accessible on the Annals of Internal Medicine Web site (www.annals.org webcite) and will be also published in BJOG, British Journal of Cancer, British Journal of Surgery, BMC Medicine, British Medical Journal, Circulation, Diabetic Medicine, European Journal of Clinical Investigation, European Urology, and Journal of Clinical Epidemiology. The authors jointly hold the copyright of this article. An accompanying Explanation and Elaboration article is freely available only on www.annals.org webcite; Annals of Internal Medicine holds copyright for that article.

【 授权许可】

   
2015 Collins et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

【 参考文献 】

• [1]Moons KG, Royston P, Vergouwe Y, Grobbee DE, Altman DG: Prognosis and prognostic research: what, why, and how? BMJ 2009, 338:b375. PMID: 19237405
• [2]Steyerberg EW: Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. Springer, New York; 2009.
• [3]Dorresteijn JA, Visseren FL, Ridker PM, Wassink AM, Paynter NP, Steyerberg EW, van der Graaf Y, Cook NR: Estimating treatment effects for individual patients based on the results of randomised clinical trials. BMJ 2011, 343:d5888. PMID: 21968126
• [4]Hayward RA, Kent DM, Vijan S, Hofer TP: Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis. BMC Med Res Methodol 2006, 6:18. PMID: 16613605 BioMed Central Full Text
• [5]Riley RD, Hayden JA, Steyerberg EW, Moons KG, Abrams K, Kyzas PA, Malats N, Briggs A, Schroter S, Altman DG, Hemingway H: Prognosis Research Strategy (PROGRESS) 2: prognostic factor research. PLoS Med 2013, 10:e1001380. PMID: 23393429
• [6]Steyerberg EW, Moons KG, van der Windt DA, Hayden JA, Perel P, Schroter S, Riley RD, Hemingway H, Altman DG: Prognosis Research Strategy (PROGRESS) 3: prognostic model research. PLoS Med 2013, 10:e1001381. PMID: 23393430
• [7]Anderson KM, Odell PM, Wilson PW, Kannel WB: Cardiovascular disease risk profiles. Am Heart J 1991, 121:293-298. PMID: 1985385
• [8]Stiell IG, Greenberg GH, McKnight RD, Nair RC, McDowell I, Worthington JR: A study to develop clinical decision rules for the use of radiography in acute ankle injuries. Ann Emerg Med 1992, 21:384-390. PMID: 1554175
• [9]Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R: European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg 1999, 16:9-13. PMID: 10456395
• [10]Haybittle JL, Blamey RW, Elston CW, Johnson J, Doyle PJ, Campbell FC, Nicholson RI, Griffiths K: A prognostic index in primary breast cancer. Br J Cancer 1982, 45:361-366. PMID: 7073932
• [11]Le Gall JR, Loirat P, Alperovitch A, Glaser P, Granthil C, Mathueu D, Mercier P, Thomas R, Villers D: A simplified acute physiology score for ICU patients. Crit Care Med 1984, 12:975-977. PMID: 6499483
• [12]Royston P, Moons KG, Altman DG, Vergouwe Y: Prognosis and prognostic research: developing a prognostic model. BMJ 2009, 338:b604. PMID: 19336487
• [13]Moons KG, Kengne AP, Grobbee DE, Royston P, Vergouwe Y, Altman DG, Woodward M: Risk prediction models: II. External validation, model updating, and impact assessment. Heart 2012, 98:691-698. PMID: 22397946
• [14]Altman DG, Vergouwe Y, Royston P, Moons KG: Prognosis and prognostic research: validating a prognostic model. BMJ 2009, 338:b605. PMID: 19477892
• [15]Moons KG, Kengne AP, Woodward M, Royston P, Vergouwe Y, Altman DG, Grobbee DE: Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart 2012, 98:683-690. PMID: 22397945
• [16]Steyerberg EW, Harrell FE, Borsboom GJJM, Eijkemans MJC, Vergouwe Y, Habbema JDF: Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol 2001, 54:774-781. PMID: 11470385
• [17]Justice AC, Covinsky KE, Berlin JA: Assessing the generalizability of prognostic information. Ann Intern Med 1999, 130:515-524. PMID: 10075620
• [18]Steyerberg EW, Pencina MJ, Lingsma HF, Kattan MW, Vickers AJ, Van Calster B: Assessing the incremental value of diagnostic and prognostic markers: a review and illustration. Eur J Clin Invest 2012, 42:216-228. PMID: 21726217
• [19]Steyerberg EW, Bleeker SE, Moll HA, Grobbee DE, Moons KG: Internal and external validation of predictive models: a simulation study of bias and precision in small samples. J Clin Epidemiol 2003, 56:441-447. PMID: 12812818
• [20]Steyerberg EW, Eijkemans MJ, Habbema JD: Application of shrinkage techniques in logistic regression analysis: a case study. Statistica Neerlandica 2001, 55:76-88.
• [21]Reilly BM, Evans AT: Translating clinical research into clinical practice: impact of using prediction rules to make decisions. Ann Intern Med 2006, 144:201-209. PMID: 16461965
• [22]Wallace E, Smith SM, Perera-Salazar R, Vaucher P, McCowan C, Collins G, Verbakel J, Lakhanpaul M, Fahey T: Framework for the impact analysis and implementation of clinical prediction rules (CPRs). BMC Med Inform Decis Mak 2011, 11:62. PMID: 21999201 BioMed Central Full Text
• [23]Bouwmeester W, Zuithoff NP, Mallett S, Geerlings MI, Vergouwe Y, Steyerberg EW, Altman DG, Moons KG: Reporting and methods in clinical prediction research: a systematic review. PLoS Med 2012, 9:1-12. PMID: 22629234
• [24]Collins GS, Mallett S, Omar O, Yu LM: Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting. BMC Med 2011, 9:103. PMID: 21902820 BioMed Central Full Text
• [25]Collins GS, Omar O, Shanyinde M, Yu LM: A systematic review finds prediction models for chronic kidney were poorly reported and often developed using inappropriate methods. J Clin Epidemiol 2013, 66:268-277. PMID: 23116690
• [26]Mallett S, Royston P, Dutton S, Waters R, Altman DG: Reporting methods in studies developing prognostic models in cancer: a review. BMC Med 2010, 8:20. PMID: 20353578 BioMed Central Full Text
• [27]Laupacis A, Sekar N, Stiell IG: Clinical prediction rules. A review and suggested modifications of methodological standards. JAMA 1997, 277:488-494. PMID: 9020274
• [28]Collins GS, de Groot JA, Dutton S, Omar O, Shanyinde M, Tajar A, Voysey M, Wharton R, Yu LM, Moons KG, Altman DG: External validation of multivariable prediction models: a systematic review of methodological conduct and reporting. BMC Med Res Methodol 2014, 14:40. PMID: 24645774 BioMed Central Full Text
• [29]Ettema RG, Peelen LM, Schuurmans MJ, Nierich AP, Kalkman CJ, Moons KG: Prediction models for prolonged intensive care unit stay after cardiac surgery: systematic review and validation study. Circulation 2010, 122:682-689. PMID: 20679549
• [30]Goff DC, Lloyd-Jones DM, Bennett G, Coady S, D’Agostino RB, Gibbons R, Greenland P, Lackland DT, Levy D, O'Donnell CJ, Robinson JG, Schwartz JS, Shero ST, Smith SC Jr, Sorlie P, Stone NJ, Wilson PW, Jordan HS, Nevo L, Wnek J, Anderson JL, Halperin JL, Albert NM, Bozkurt B, Brindis RG, Curtis LH, DeMets D, Hochman JS, Kovacs RJ, Ohman EM, et al.: 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. Circulation 2014, 129:S49-S73. PMID: 24222018
• [31]Rabar S, Lau R, O’Flynn N, Li L, Barry P: Guideline Development Group: Risk assessment of fragility fractures: summary of NICE guidance. BMJ 2012, 345:e3698. PMID: 22875946
• [32]Laine C, Goodman SN, Griswold ME, Sox HC: Reproducible research: moving toward research the public can really trust. Ann Intern Med 2007, 146:450-453. PMID: 17339612
• [33]Siontis GC, Tzoulaki I, Siontis KC, Ioannidis JP: Comparisons of established risk prediction models for cardiovascular disease: systematic review. BMJ 2012, 344:e3318. PMID: 22628003
• [34]Seel RT, Steyerberg EW, Malec JF, Sherer M, Macciocchi SN: Developing and evaluating prediction models in rehabilitation populations. Arch Phys Med Rehabil 2012, 93:S138-S153. PMID: 22840880
• [35]Collins GS, Moons KG: Comparing risk prediction models. BMJ 2012, 344:e3186. PMID: 22628131
• [36]Knottnerus JA: Diagnostic prediction rules: principles, requirements and pitfalls. Prim Care 1995, 22:341-363. PMID: 7617791
• [37]McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM: Statistics Subcommittee of the NCI-EORTC Working Group on Cancer Diagnostics: Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst 2005, 97:1180-1184. PMID: 16106022
• [38]Moons KG, Altman DG, Vergouwe Y, Royston P: Prognosis and prognostic research: application and impact of prognostic models in clinical practice. BMJ 2009, 338:b606. PMID: 19502216
• [39]von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP: STROBE Initiative: Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 2007, 335:806-808. PMID: 17947786
• [40]Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM, Lijmer JG, Moher D, Rennie D, de Vet HC: Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD Initiative. Radiology 2003, 226:24-28. PMID: 12511664
• [41]Janssens AC, Ioannidis JP, van Duijn CM, Little J, Khoury MJ: GRIPS Group: Strengthening the reporting of genetic risk prediction studies: the GRIPS statement. Eur J Clin Invest 2011, 41:1004-1009. PMID: 21434891
• [42]Tzoulaki I, Liberopoulos G, Ioannidis JP: Use of reclassification for assessment of improved prediction: an empirical evaluation. Int J Epidemiol 2011, 40:1094-1105. PMID: 21325392
• [43]Moons KGM, Altman DG, Reitsma JB, Ioannidis JPA, Macaskill P, Steyerberg EW, Vickers AJ, Ransohoff DF, Collins GS: Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med 2015, 162:W1-W73.
• [44]Moher D, Schulz KF, Simera I, Altman DG: Guidance for developers of health research reporting guidelines. PLoS Med 2010, 16:e1000217. PMID: 20169112
• [45]Little J, Higgins JP, Ioannidis JP, Moher D, Gagnon F, von Elm E, Khoury MJ, Cohen B, Davey-Smith G, Grimshaw J, Scheet P, Gwinn M, Williamson RE, Zou GY, Hutchings K, Johnson CY, Tait V, Wiens M, Golding J, van Duijn C, McLaughlin J, Paterson A, Wells G, Fortier I, Freedman M, Zecevic M, King R, Infante-Rivard C, Stewart A, Birkett N: STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement. PLoS Med 2009, 6:e22. PMID: 19192942
• [46]Moher D, Liberati A, Tetzlaff J, Altman DG: PRISMA Group: Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 2009, 151:264-269. PMID: 19622511
• [47]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: Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration. Eur J Clin Invest 2011, 41:1010-1035. PMID: 21434890
• [48]Altman DG, McShane LM, Sauerbrei W, Taube SE: Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration. BMC Med 2012, 10:51. PMID: 22642691 BioMed Central Full Text
• [49]Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, Poole C, Schlesselman JJ, Egger M: Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Epidemiology 2007, 18:805-835. PMID: 18049195
• [50]Collins GS, Michaëlsson K: Fracture risk assessment: state of the art, methodologically unsound, or poorly reported? Curr Osteoporos Rep 2012, 10:199-207. PMID: 22688862
• [51]Järvinen TL, Jokihaara J, Guy P, Alonso-Coello P, Collins GS, Michaëlsson K, Sievänen H: Conflicts at the heart of the FRAX tool. CMAJ 2014, 186:165-167. PMID: 24366895
• [52]Moons KG, de Groot JA, Bouwmeester W, Vergouwe Y, Mallett S, Altman DG, Reitsma JB, Collins GS: Critical appraisal and data extraction for the systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med 2014, 11:e1001744. PMID: 25314315
• [53]Williams RJ, Tse T, Harlan WR, Zarin DA: Registration of observational studies: is it time? CMAJ 2010, 182:1638-1642. PMID: 20643833
• [54]Hemingway H, Riley RD, Altman DG: Ten steps towards improving prognosis research. BMJ 2009, 339:b4184. PMID: 20042483
• [55]Canadian CT Head and C-Spine (CCC) Study Group: Canadian C-Spine Rule study for alert and stable trauma patients: I. Background and rationale CJEM 2002, 4:84-90. PMID: 17612425
• [56]Canadian CT Head and C-Spine (CCC) Study Group: Canadian C-Spine Rule study for alert and stable trauma patients: II. Study objectives and methodology CJEM 2002, 4:185-193. PMID: 17609004
• [57]TRIPOD.www.tripod-statement.org
• [58]EQUATOR.www.equator-network.org