Aplicación del Grade en las recomendaciones de meta-análisis en red en la guía Colombiana de falla cardíaca
DOI:
https://doi.org/10.17533/udea.iatreia.26741Palabras clave:
guía, insuficiencia cardíaca, metaanálisisResumen
Introducción: los metaanálisis en red (MAR) permiten incorporar y analizar comparaciones indirectas entre intervenciones y son una ayuda para la elaboración de recomendaciones en las guías de práctica clínica. El objetivo de este artículo es resumir la revisión bibliográfica que realizó el grupo sobre MAR, las recomendaciones del grupo GRADE para evaluarlos y la forma como se elaboró la recomendación para esta pregunta de la la guía.
Metodología: para la pregunta sobre el uso de betabloqueadores (BB) en pacientes con síndrome de falla cardíaca clasificación C de la ACC/AHA se hizo una búsqueda sistemática. Se encontró un MAR, que resumía los hallazgos para responderla, con el cual se describe la aplicación de GRADE en este tipo de estudios.
Resultados: el resultado global del metaanálisis mostró una reducción significativa de la mortalidad con el uso de BB contra cualquier comparador; todas son comparaciones indirectas excepto el estudio de carvedilol contra metoprolol tartrato. Todos los BB mostraron reducción de la mortalidad, pero no hubo significancia estadística cuando se compararon entre ellos. Este MAR no publicó la probabilidad en el orden de tratamiento y el análisis de las características generales de los estudios incluidos en él no mostró intransitividad; además, la comparación entre metoprolol y carvedilol demostró coherencia de la comparación directa y la indirecta.
Conclusión: Los MAR son una forma de resumir la evidencia disponible incluyendo comparaciones indirectas, tienen una metodología particular y los criterios del grupo GRADE son prácticos y aplicables como mostramos se hizo en el desarrollo de esta guía de práctica clínica.
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(1.) Evidence-Based Medicine Working Group. Evidencebased medicine. A new approach to teaching the practice of medicine. JAMA. 1992 Nov;268(17):2420-5.
(2.) Karagianis J. Understanding and teaching key concepts and tools of evidence-based medicine: perspectives of a clinician-researcher pharmaceutical physician. Clin Ther. 2011 Dec;33(12):B3-10. DOI 10.1016/j.clinthera.2011.11.003.
(3.) Sackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS. Evidence based medicine: what it is and what it isn’t. BMJ. 1996 Jan;312(7023):71-2.
(4.) Masic I, Miokovic M, Muhamedagic B. Evidence based medicine - new approaches and challenges. Acta Inform Med. 2008;16(4):219-25. DOI 10.5455/aim.2008.16.219-225.
(5.) Grimes DA, Schulz KF. An overview of clinical research: the lay of the land. Lancet. 2002 Jan;359(9300):57-61.
(6.) Ho PM, Peterson PN, Masoudi FA. Evaluating the evidence: is there a rigid hierarchy? Circulation. 2008 Oct;118(16):1675-84. DOI 10.1161/CIRCULATIONAHA.107.721357.
(7.) Sibbald B, Roland M. Understanding controlled trials. Why are randomized controlled trials important? BMJ. 1998 Jan;316(7126):201.
(8.) Bigby M, Williams H. Appraising systematic reviews and meta-analyses. Arch Dermatol. 2003 Jun;139(6):795-8.
(9.) Villar J, Carroli G, Belizán JM. Predictive ability of meta-analyses of randomised controlled trials. Lancet. 1995 Mar;345(8952):772-6.
(10.) Garg AX, Hackam D, Tonelli M. Systematic review and meta-analysis: when one study is just not enough. Clin J Am Soc Nephrol. 2008 Jan;3(1):253-60. DOI 10.2215/CJN.01430307.
(11.) Cappelleri JC, Ioannidis JP, Schmid CH, de Ferranti SD, Aubert M, Chalmers TC, et al. Large trials vs metaanalysis of smaller trials: how do their results compare? JAMA. 1996 Oct0;276(16):1332-8.
(12.) LeLorier J, Grégoire G, Benhaddad A, Lapierre J, Derderian F. Discrepancies between meta-analyses and subsequent large randomized, controlled trials. N Engl J Med. 1997 Aug;337(8):536-42.
(13.) Pogue J, Yusuf S. Overcoming the limitations of current meta-analysis of randomised controlled trials. Lancet. 1998 Jan;351(9095):47-52.
(14.) Ferreira González I, Urrutia G, Alonso-Coello P. Revisione sitemáticas y meta-análisis: bases conceptuales e interpretaciones. Rev Esp Cardiol. 2011 Ago;64(8):688-96. DOI 10.1016/j.recesp.2011.03.029.
(15.) Bhandari M, Guyatt GH, Montori V, Devereaux PJ, Swiontkowski MF. User’s guide to the orthopaedic literature: how to use a systematic literature review. J Bone Joint Surg Am. 2002 Sep;84-A(9):1672-82.
(16.) Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med. 2009 Aug;151(4):W65-94.
(17.) Cornell JE. The PRISMA extension for network metaanalysis: bringing clarity and guidance to the reporting of systematic reviews incorporating network meta-analyses. Ann Intern Med. 2015 Jun;162(11):797-8. DOI 10.7326/M15-0930.
(18.) Clark GT, Mulligan R. Fifteen common mistakes encountered in clinical research. J Prosthodont Res. 2011 Jan;55(1):1-6. DOI 10.1016/j.jpor.2010.09.002.
(19.) Greco T, Zangrillo A, Biondi-Zoccai G, Landoni G. Meta-analysis: pitfalls and hints. Heart Lung Vessel. 2013;5(4):219-25.
(20.) McInnes MD, Bossuyt PM. Pitfalls of Systematic Reviews and Meta-Analyses in Imaging Research. Radiology. 2015 Oct;277(1):13-21. DOI 10.1148/radiol.2015142779.
(21.) Murad MH, Montori VM, Ioannidis JP, Jaeschke R, Devereaux PJ, Prasad K, et al. How to read a systematic review and meta-analysis and apply the results to patient care: users’ guides to the medical literature. JAMA. 2014 Jul;312(2):171-9. DOI 10.1001/jama.2014.5559.
(22.) Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Criticisms of Meta-Analysis. In: Introduction to Meta-Analysis. West Sussex UK: WILEY; 2009. p. 377-87.
(23.) Ioannidis JP, Patsopoulos NA, Rothstein HR. Reasons or excuses for avoiding meta-analysis in forest plots. BMJ. 2008 Jun;336(7658):1413-5. DOI 10.1136/bmj.a117.
(24.) Catalá-López F, Tobías A, Roqué M. Conceptos básicos del metaanálisis en red. Atención Primaria 2014 Dic;46(10):573-81. DOI 10.1016/j.aprim.2014.01.006.
(25.) Catalá-López F, Tobías A. Meta-análisis de ensayos clínicos aleatorizados, heterogeneidad e intervalos de predicción. Med Clin (Barc). 2014;142(6):270-4. DOI 10.1016/j.medcli.2013.06.013.
(26.) Mills EJ, Ioannidis JP, Thorlund K, Schünemann HJ, Puhan MA, Guyatt GH. How to use an article reporting a multiple treatment comparison meta-analysis. JAMA. 2012 Sep;308(12):1246-53.
(27.) Salanti G, Higgins JP, Ades AE, Ioannidis JP. Evaluation of networks of randomized trials. Stat Methods Med Res. 2008 Jun;17(3):279-301.
(28.) Melendez-Torres GJ, Bonell C, Thomas J. Emergent approaches to the meta-analysis of multiple heterogeneous complex interventions. BMC Med Res Methodol. 2015 Jun;15:47. DOI 10.1186/s12874-015-0040-z.
(29.) Puhan MA, Schünemann HJ, Murad MH, Li T, Brignardello-Petersen R, Singh JA, et al. A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. BMJ. 2014 Sep;349:g5630. DOI 10.1136/bmj.g5630. Erratum in: BMJ. 2015;350:h3326.
(30.) Hutton B, Salanti G, Caldwell DM, Chaimani A, Schmid CH, Cameron C, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med. 2015 Jun;162(11):777-84. DOI 10.7326/M14-2385.
(31.) Jansen JP, Trikalinos T, Cappelleri JC, Daw J, Andes S, Eldessouki R, et al. Indirect treatment comparison/network meta-analysis study questionnaire to assess relevance and credibility to inform health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report. Value Health. 2014 Mar;17(2):157-73. DOI 10.1016/j.jval.2014.01.004.Erratum in: Value Health. 2016 Jan;19(1):121.
(32.) Jansen JP, Fleurence R, Devine B, Itzler R, Barrett A, Hawkins N, et al. Interpreting indirect treatment comparisons and network meta-analysis for healthcare decision making: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 1. Value Health. 2011 Jun;14(4):417-28. DOI 10.1016/j.jval.2011.04.002.
(33.) Hoaglin DC, Hawkins N, Jansen JP, Scott DA, Itzler R, Cappelleri JC, et al. Conducting indirect-treatmentcomparison and network-meta-analysis studies: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 2. Value Health. 2011 Jun;14(4):429-37. DOI 10.1016/j.jval.2011.01.011.
(34.) Nikolakopoulou A, Chaimani A, Veroniki AA, Vasiliadis HS, Schmid CH, Salanti G. Characteristics of networks of interventions: a description of a database of 186 published networks. PLoS One. 2014 Jan;9(1):e86754. DOI 10.1371/journal.pone.0086754.
(35.) Hutton B, Salanti G, Chaimani A, Caldwell DM, Schmid C, Thorlund K, et al. The quality of reporting methods and results in network meta-analyses: an overview of reviews and suggestions for improvement. PLoS One. 2014 Mar;9(3):e92508. DOI 10.1371/journal.pone.0092508.
(36.) Bucher HC, Guyatt GH, Griffith LE, Walter SD. The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol. 1997 Jun;50(6):683-91.
(37.) Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med. 2002 Aug;21(16):2313-24.
(38.) Chaimani A, Higgins JP, Mavridis D, Spyridonos P, Salanti G. Graphical tools for network meta-analysis in STATA. PLoS One. 2013 Oct;8(10):e76654. DOI 10.1371/journal.pone.0076654.
(39.) Salanti G, Kavvoura FK, Ioannidis JP. Exploring the geometry of treatment networks. Ann Intern Med. 2008 Apr;148(7):544-53.
(40.) Neupane B, Richer D, Bonner AJ, Kibret T, Beyene J. Network meta-analysis using R: a review of currently available automated packages. PLoS One. 2014 Dec;9(12):e115065. DOI 10.1371/journal.pone.0115065. Erratum in: PLoS One. 2015;10(4):e0123364.
(41.) White IR, Barrett JK, Jackson D, Higgins JP. Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression. Res Synth Methods. 2012 Jun;3(2):111-25. DOI 10.1002/jrsm.1045.
(42.) Greco T, Landoni G, Biondi-Zoccai G, D’Ascenzo F, Zangrillo A. A Bayesian network meta-analysis for binary outcome: how to do it. Stat Methods Med Res. 2013;0(0):1-17 DOI: 10.1177/0962280213500185.
(43.) Yet B, Perkins ZB, Rasmussen TE, Tai NR, Marsh DW. Combining data and meta-analysis to build Bayesian networks for clinical decision support. J Biomed Inform. 2014 Dec;52:373-85. DOI 10.1016/j.jbi.2014.07.018.
(44.) Zhang J, Chu H, Hong H, Virnig BA, Carlin BP. Bayesian hierarchical models for network meta-analysis incorporating nonignorable missingness. Stat Methods Med Res. 2015 Jul 28. PII 0962280215596185.
(45.) Cipriani A, Higgins JP, Geddes JR, Salanti G. Conceptual and technical challenges in network metaanalysis. Ann Intern Med. 2013 Jul;159(2):130-7. DOI 10.7326/0003-4819-159-2-201307160-00008.
(46.) Dias S, Welton NJ, Sutton AJ, Caldwell DM, Lu G, Ades AE. Evidence synthesis for decision making 4: inconsistency in networks of evidence based on randomized controlled trials. Med Decis Making. 2013 Jul;33(5):641-56. DOI 10.1177/0272989X12455847.
(47.) Higgins JP, Jackson D, Barrett JK, Lu G, Ades AE, White IR. Consistency and inconsistency in network metaanalysis: concepts and models for multi-arm studies. Res Synth Methods. 2012 Jun;3(2):98-110. DOI 10.1002/jrsm.1044.
(48.) Jansen JP, Naci H. Is network meta-analysis as valid as standard pairwise meta-analysis? It all depends on the distribution of effect modifiers. BMC Med. 2013 Jul;11:159. DOI 10.1186/1741-7015-11-159.
(49.) Salanti G, Ades AE, Ioannidis JP. Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol. 2011 Feb;64(2):163-71. DOI 10.1016/j.jclinepi.2010.03.016.
(50.) Trinquart L, Attiche N, Bafeta A, Porcher R, Ravaud P. Uncertainty in Treatment Rankings: Reanalysis of Network Meta-analyses of Randomized Trials. Ann Intern Med. 2016 May;164(10):666-73. DOI 10.7326/M15-2521.
(51.) Salanti G, Del Giovane C, Chaimani A, Caldwell DM, Higgins JP. Evaluating the quality of evidence from a network meta-analysis. PLoS One. 2014 Jul;9(7):e99682. DOI 10.1371/journal.pone.0099682.
(52.) Chatterjee S, Biondi-Zoccai G, Abbate A, D’Ascenzo F, Castagno D, Van Tassell B, et al. Benefits of β blockers in patients with heart failure and reduced ejection fraction: network meta-analysis. BMJ. 2013 Jan;346:f55. DOI 10.1136/bmj.f55. Erratum in: BMJ. 2013;346:f596.
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