GRADE Guidelines 28: Use of GRADE for the assessment of evidence about prognostic factors: rating certainty in identification of groups of patients with different absolute risks

Journal of Clinical Epidemiology

Volumn 121, Issue , 2020, Pages 62-70

  Foroutan, Farid ^a,b   Guyatt, Gordon ^a   Zuk, Victoria ^a   Vandvik, Per Olav ^c   Alba, Ana Carolina ^b   Mustafa, Reem ^d   Vernooij, Robin ^e   Arevalo Rodriguez, Ingrid ^f,g   Munn, Zachary ^h   Roshanov, Pavel ^a   Riley, Richard ⁱ   Schandelmaier, Stefan ^a   Kuijpers, Ton ^j   Siemieniuk, Reed ^a   Canelo Aybar, Carlos ^e   Schunemann, Holger ^a   Iorio, Alfonso ^a  

^a MCMASTER UNIVERSITY   (Canada)

^b TORONTO GENERAL HOSPITAL   (Canada)

^c INNLANDET HOSPITAL TRUST   (Norway)

^d UNIVERSITY OF KANSAS SCHOOL OF MEDICINE   (United States)

^e BIOMEDICAL RESEARCH INSTITUTE SANT PAU IIB SANT PAU   (Spain)

^f HOSPITAL RAMÓN Y CAJAL   (Spain)

^g School of Engineering Sciences and Industry   (Ecuador)

^h UNIVERSITY OF ADELAIDE   (Australia)

ⁱ UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^j DUTCH COLLEGE OF GENERAL PRACTITIONERS   (Netherlands)

more..

Author keywords

Certainty in evidence; GRADE; Guideline; Prognosis; Prognostic factor; Subgroup; Systematic review

Indexed keywords

ADULT; ARTICLE; CONSULTATION; DECISION MAKING; FEMALE; HUMAN; MALE; META ANALYSIS; OUTCOME ASSESSMENT; PRACTICE GUIDELINE; PROGNOSIS; PUBLICATION BIAS; RANDOMIZED CONTROLLED TRIAL (TOPIC); RISK ASSESSMENT; SYSTEMATIC REVIEW; FORECASTING; META ANALYSIS (TOPIC); OBSERVATIONAL STUDY; PROBABILITY; PUBLISHING; TREATMENT OUTCOME;

FORECASTING; GRADE APPROACH; HUMANS; META-ANALYSIS AS TOPIC; OBSERVATIONAL STUDIES AS TOPIC; PROBABILITY; PROGNOSIS; PUBLICATION BIAS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SYSTEMATIC REVIEWS AS TOPIC; TREATMENT OUTCOME;

EID: 85079626977     PISSN: 08954356     EISSN: 18785921     Source Type: Journal    
DOI: 10.1016/j.jclinepi.2019.12.023     Document Type: Article

References (26)

1. Riley, R.D., van der Windt, D.A., Croft, P., Moons, K.G., Prognosis research in health care: concepts, methods, and impact. 2019, Oxford University Press, Oxford, United Kingdom.
2. Riley, R.D., Hayden, J.A., Steyerberg, E.W., Moons, K.G., Abrams, K., Kyzas, P.A., et al. Prognosis Research Strategy (PROGRESS) 2: prognostic factor research. PLoS Med, 10(2), 2013, e1001380.
3. Hultcrantz, M., Rind, D., Akl, E.A., Treweek, S., Mustafa, R.A., Iorio, A., et al. The GRADE Working Group clarifies the construct of certainty of evidence. J Clin Epidemiol 87 (2017), 4–13.
4. Thompson, M., Vodicka, T.A., Blair, P.S., Buckley, D.I., Heneghan, C., Hay, A.D., et al. Duration of symptoms of respiratory tract infections in children: systematic review. BMJ, 347, 2013, f7027.
5. Iorio, A., Spencer, F.A., Falavigna, M., Alba, C., Lang, E., Burnand, B., et al. Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients. BMJ, 350, 2015, h870.
6. Hordijk-Trion, M., on behalf of the EHSCRI, Lenzen, M., Wijns, W., de Jaegere, P., Simoons, M.L., et al. Patients enrolled in coronary intervention trials are not representative of patients in clinical practice: results from the Euro Heart Survey on Coronary Revascularization. Eur Heart J 27 (2006), 671–678.
7. Hayden, J.A., van der Windt, D.A., Cartwright, J.L., Côté, P., Bombardier, C., Assessing bias in studies of prognostic factors. Ann Intern Med 158 (2013), 280–286.
8. Wolff, R.F., Moons, K.G.M., Riley, R.D., Whiting, P.F., Westwood, M., Collins, G.S., et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med 170 (2019), 51–58.
9. Reeves, B.C., Deeks, J.J., Higgins, J.P., Wells, G.A., Including non-randomized studies. Higgins, J.P., Green, S., (eds.) Cochrane Handbook for Systematic Reviews of Interventions, 2010, The Cochrane Collaboration, Hoboken, New Jersey, 391–432.
10. Cook, D.J., Fuller, H.D., Guyatt, G.H., Marshall, J.C., Leasa, D., Hall, R., et al. Risk factors for gastrointestinal bleeding in critically ill patients. N Engl J Med 330:6 (1994), 377–381.
11. Kucher, N., Kohler, H.P., Dornhofer, T., Wallmann, D., Lämmle, B., Accuracy of D-dimer/fibrinogen ratio to predict pulmonary embolism: a prospective diagnostic study. J Thromb Haemost 1 (2003), 708–713.
12. Perrier, A., Roy, P.M., Sanchez, O., Le Gal, G., Meyer, G., Gourdier, A.L., et al. Multidetector-row computed tomography in suspected pulmonary embolism. N Engl J Med 352 (2005), 1760–1768.
13. Wells, P.S., Anderson, D.R., Bormanis, J., Guy, F., Mitchell, M., Gray, L., et al. Value of assessment of pretest probability of deep-vein thrombosis in clinical management. Lancet 350 (1997), 1795–1798.
14. Sanchez, O., Trinquart, L., Colombet, I., Durieux, P., Huisman, M.V., Chatellier, G., et al. Prognostic value of right ventricular dysfunction in patients with haemodynamically stable pulmonary embolism: a systematic review. Eur Heart J 29 (2008), 1569–1577.
15. Cheng, Y.J., Liu, Z.H., Yao, F.J., Zeng, W.T., Zheng, D.D., Dong, Y.G., et al. Current and former smoking and risk for venous thromboembolism: a systematic review and meta-analysis. PLoS Med, 10(9), 2013, e1001515.
16. Witlox, J., Eurelings, L.S., de Jonghe, J.F., Kalisvaart, K.J., Eikelenboom, P., van Gool, W.A., Delirium in elderly patients and the risk of postdischarge mortality, institutionalization, and dementia: a meta-analysis. JAMA 304 (2010), 443–451.
17. Foroutan, F., Friesen, E.L., Clark, K.E., Motaghi, S., Zyla, R., Lee, Y., et al. Risk factors for one-year graft loss post-kidney transplantation. Clin J Am Soc Nephrol 14:11 (2019), 1642–1650.
18. Andre, F., McShane, L.M., Michiels, S., Ransohoff, D.F., Altman, D.G., Reis-Filho, J.S., et al. Biomarker studies: a call for a comprehensive biomarker study registry. Nat Rev Clin Oncol, 8, 2011, 171.
19. Kyzas, P.A., Denaxa-Kyza, D., Ioannidis, J.P.A., Almost all articles on cancer prognostic markers report statistically significant results. Eur J Cancer 43:17 (2007), 2559–2579.
20. Martin, B., Paesmans, M., Berghmans, T., Branle, F., Ghisdal, L., Mascaux, C., et al. Role of Bcl-2 as a prognostic factor for survival in lung cancer: a systematic review of the literature with meta-analysis. Br J Cancer, 89, 2003, 55.
21. McShane, L.M., Altman, D.G., Sauerbrei, W., Identification of clinically useful cancer prognostic factors: what are we missing?. J Natl Cancer Inst 97:14 (2005), 1023–1025.
22. Begg, C.B., Mazumdar, M., Operating characteristics of a rank correlation test for publication bias. Biometrics 50 (1994), 1088–1101.
23. Debray, T.P.A., Moons, K.G.M., Riley, R.D., Detecting small-study effects and funnel plot asymmetry in meta-analysis of survival data: a comparison of new and existing tests. Res Synth Methods 9:1 (2018), 41–50.
24. Peters, J.L., Sutton, A.J., Jones, D.R., Abrams, K.R., Rushton, L., Comparison of two methods to detect publication bias in meta-analysis. JAMA 295 (2006), 676–680.
25. Egger, M., Davey Smith, G., Schneider, M., Minder, C., Bias in meta-analysis detected by a simple, graphical test. BMJ 315 (1997), 629–634.
26. Vasilevska, M., Ross, S.A., Gesink, D., Fisman, D.N., Relative risk of cervical cancer in indigenous women in Australia, Canada, New Zealand, and the United States: a systematic review and meta-analysis. J Public Health Policy 33:2 (2012), 148–164.