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Nair R, Aggarwal R, Khanna D. Methods of formal consensus in classification/diagnostic criteria and guideline development. Semin Arthritis Rheum 2011; 41:95-105. [PMID: 21420149 DOI: 10.1016/j.semarthrit.2010.12.001] [Citation(s) in RCA: 264] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2010] [Revised: 11/20/2010] [Accepted: 12/05/2010] [Indexed: 11/29/2022]
Abstract
Guidelines or diagnostic criteria in clinical practice assist physicians in their clinical decision-making and improve health outcomes for patients. Diagnostic and classification criteria should be based on evidence from rigorously conducted controlled studies. Formal group consensus methods have been developed to organize subjective judgments and to synthesize them with the available evidence. This review discusses 4 types of formal consensus methods used in the health field and their applications in rheumatology: the Delphi method, Nominal Group Technique, RAND/UCLA Appropriateness Method, and National Institutes of Health consensus development conference.
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Affiliation(s)
- Raj Nair
- Department of Medicine, Washington Hospital Center, Washington, DC, USA
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de Bandt M, Fautrel B, Maillefert JF, Berthelot JM, Combe B, Flipo RM, Lioté F, Meyer O, Saraux A, Wendling D, Le Loët X, Guillemin F. Determining a low disease activity threshold for decision to maintain disease-modifying antirheumatic drug treatment unchanged in rheumatoid arthritis patients. Arthritis Res Ther 2009; 11:R157. [PMID: 19849865 PMCID: PMC2787280 DOI: 10.1186/ar2836] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2009] [Revised: 08/24/2009] [Accepted: 10/23/2009] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION The aim of this study was to determine a low disease activity threshold--a 28-joint disease activity score (DAS28) value--for the decision to maintain unchanged disease-modifying antirheumatic drug (DMARD) treatment in rheumatoid arthritis patients, based on expert opinion. METHODS Nine hundred and sixty-seven case scenarios with various levels for each component of the DAS28 (resulting in a disease activity score between 2 and 3.2) were presented to 44 panelists. For each scenario, panelists had to decide whether or not DMARD treatment (excluding steroids) could be maintained unchanged. In each scenario, for decision, the participants were given the DAS28 parameters, without knowledge of the resultant DAS28. The relationship between panelists' decision, DAS28 value, and components of the score were analysed by multiple logistic regression analysis. Each panelist analysed 160 randomised scenarios. Intra-rater and inter-rater reproducibility were assessed. RESULTS Forty-four panelists participated in the study. Inter-panelist agreement was good (kappa = 0.63; 95% confidence interval = 0.61 to 0.65). Intra-panelist agreement was excellent (kappa = 0.87; 95% confidence interval = 0.82 to 0.92). Quasi-perfect agreement was observed for DAS28 < or = 2.4, less pronounced between 2.5 and 2.9, and almost no agreement for DAS28 > 3.0. For values below 2.5, panelists agreed to maintain unchanged DMARDs; for values above 2.5, discrepancies occurred more frequently as the DAS28 value increased. Multivariate analysis confirmed the relationship between panelist's decision, DAS28 value and components of the DAS28. Between DAS28 of 2.4 and 3.2, a major determinant for panelists' decision was swollen joint count. Female and public practice physicians decided more often to maintain treatment unchanged. CONCLUSIONS As a conclusion, panelists suggested that in clinical practice there is no need to change DMARD treatment in rheumatoid arthritis patients with DAS28 < or = 2.4.
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Affiliation(s)
- Michel de Bandt
- Centre hospitalier d'Aulnay sous Bois, Service de Rhumatologie, Boulevard Ballanger, Aulnay sous Bois F-93600, France
| | - Bruno Fautrel
- APHP-GH Pitié Salpêtrière, Service de Rhumatologie, UFR de Médecine, Université Paris VI - Pierre et Marie Curie, 83 boulevard de l'Hôpital, 75651 Paris cedex 13, France
| | - Jean Francis Maillefert
- Centre Hospitalo-Universitaire du Dijon, Hôpital du Bocage, Service de Rhumatologie, 3 rue du faubourg Raynes, Dijon F-21000, France
| | - Jean Marie Berthelot
- INSERM ERI 7 (EA 3822), Centre Hospitalo-Universitaire de Nantes, Hotel-Dieu, Service de Rhumatologie, 1 Place Alexis Ricordeau, Nantes F-44000, France
| | - Bernard Combe
- Centre Hospitalo-Universitaire du Montpellier, Hôpital Lapeyronie, Service de Rhumatologie, 371 avenue du Doyen Gaston Giraud, Montpellier F-34000, France
| | - René-Marc Flipo
- Centre Régional Hospitalo-Universitaire de Lille, Service de Rhumatologie, Rue du Pr E Laine, Lille F-59000, France
| | - Frédéric Lioté
- Hôpital Lariboisière, Centre Viggo-Petersen, Service de Rhumatologie, 2 rue A Paré, Paris F-75010, France
| | - Olivier Meyer
- UFR de Médecine - Bichat Lariboisière, Université Paris 7, APHP, Groupe hospitalier Bichat - Claude Bernard, Service de Rhumatologie, 46 rue H Huchard, Paris F-75018, France
| | - Alain Saraux
- Centre Hospitalo-Universitaire de Brest, Hôpital de la Cavale Blanche, Service de Rhumatologie, rue T Prigent, Brest F-29000, France
| | - Daniel Wendling
- EA3186 - Agents pathogènes et Inflammation, Université de Franche-Comté, Centre Hospitalo - Universitaire de Besançon, Hôpital Jean Minjoz, Service de Rhumatologie, 1 Bd Fleming, Besançon F-25000, France
| | - Xavier Le Loët
- Department of Rheumatology, Rouen University Hospital & Inserm U905 (IFRMP 23), University of Rouen, 1 rue de Germont, Rouen F-76230, France
| | - Francis Guillemin
- INSERM CIC-EC, CHU de Nancy - Hôpital Marin, 92 av Mal de Lattre de Tassigny, 54035 Nancy cedex, France
- Université Henri Poincaré Nancy I, EA4003, Ecole de Santé Publique, Faculté de Médecine de Nancy, Nancy F-54000, France
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Abstract
Rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are associated with increased mortality, largely as a consequence of cardiovascular disease. Increased cardiovascular morbidity and mortality in patients with RA and SLE cannot be entirely explained by traditional risk factors, suggesting that the systemic inflammation that characterizes these diseases may accelerate atherosclerosis. We used carotid ultrasonography to investigate the prevalence and correlates to preclinical atherosclerosis in patients with RA and SLE. Because atherosclerosis is a systemic disease, assessment of carotid plaque by ultrasonography provides a robust, direct measure of systemic atherosclerosis. We observed a substantially increased prevalence of carotid plaque in RA and SLE patients compared with age- and sex-matched controls, which remained after adjustment for traditional risk factors. The presence of carotid atherosclerosis was associated with disease duration in both RA and SLE and damage in SLE. These data support the hypothesis that inflammation associated with RA and SLE contributes to accelerated atherosclerosis and argue that RA and SLE disease activity should be more aggressively managed.
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