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Background: Lack of standardization of outcome measures limits the usefulness of clinical trial evidence to inform health care decisions. This can be addressed by agreeing on a minimum core set of outcome measures per health condition, containing measures relevant to patients and decision makers. Since 1992, the Outcome Measures in Rheumatology (OMERACT) consensus initiative has successfully developed core sets for many rheumatologic conditions, actively involving patients since 2002. Its expanding scope required an explicit formulation of its underlying conceptual framework and process. Methods: Literature searches and iterative consensus process (surveys and group meetings) of stakeholders including patients, health professionals, and methodologists within and outside rheumatology. Results: To comprehensively sample patient-centered and intervention-specific outcomes, a framework emerged that comprises three core ''Areas,'' namely Death, Life Impact, and Pathophysiological Manifestations; and one strongly recommended Resource Use. Through literature review and consensus process, core set development for any specific health condition starts by identifying at least one core ''Domain'' within each of the Areas to formulate the ''Core Domain Set.'' Next, at least one applicable measurement instrument for each core Domain is identified to formulate a ''Core Outcome Measurement Set.'' Each instrument must prove to be truthful (valid), discriminative, and feasible. In 2012, 96% of the voting participants (n5125) at the OMERACT 11 consensus conference endorsed this model and process. Conclusion: The OMERACT Filter 2.0 explicitly describes a comprehensive conceptual framework and a recommended process to develop core outcome measurement sets for rheumatology likely to be useful as a template in other areas of health care. [ABSTRACT FROM AUTHOR]

The article offers information on a data collection methodology involving the Short Form-36 questionnaire (SF-36) in medical care and discusses an article published in the periodical which suggests using radar graphs also called spydergrams for plotting result of the questionnaire. It informs that spydergraph graphically depicts the data in two dimensions on a flat surface and analyzes its difficulties in quantitative interpretation.

Abstract: Background: In the setting of multiple remission and relapse periods of a chronic disease, simple endpoint analysis does not fully capture all relevant information, and we need methods to additionally describe both the duration of remission as well as the interruptions in this desired state. Probably the two-state continuous Markov process model comprises the best mathematical approach to data analysis. However, this approach is complex and not intuitive to clinicians. In this paper we propose a simple scoring system and a graph that can enhance the information about the remission experience in a trial or cohort study. Methods: The continuity rewarded (‘ConRew’) score sums up periods in remission, and rewards extended periods by placing more value on uninterrupted periods than on interrupted periods. The ‘patient vector graph’ attempts to plot each patient''s remission experience over time as a horizontal line (the ‘vector’) that is visible when the patient is in remission, but interrupted whenever relapse occurs. In this way a pattern is formed that conveys the number of patients experiencing remission, their individual total duration and interruptions, and time when these occur. Results: In a dataset of a randomized trial in early rheumatoid arthritis, the graph clearly showed both early and late benefit of one group over the other. The scoring system demonstrated the main benefit was in the number of remission periods, not in their ‘uninterruptedness’. Conclusion: Both approaches proved feasible and added extra information. [Copyright &y& Elsevier]

Abstract: Objective: To develop a simple system to assess benefit and harm of treatment on a single scale. Harm and benefit signals from trials need to be placed in the proper perspective to decide on the value of a treatment. Several systems have been developed for assessment, but few attempt to incorporate both benefit and risk in the same metric while retaining enough simplicity to aid patients and clinicians in their decision making. Study Design and Setting: We designed a very simple 3×3 table (Outcome Measures in Rheumatology [OMERACT] 3×3) that comprises three ranks for both beneficial and harm outcomes: for benefit, these are “none,” “substantial,” and “(near) remission”; for harm, these are “none,” “severe,” and “(near) death.” Patients are ranked both for benefit and harm and subsequently counted in a 3×3 table. Results: The system was feasible when applied to one trial dataset (patient-level information) and a meta-analysis. To become applicable as a tool, several issues need to be resolved in further development, especially the definitions and cutoffs for the ranks. Conclusion: A simple 3×3 table to rank both benefit and harm outcomes is feasible. For rheumatology this will be further developed in the context of the OMERACT initiative. [Copyright &y& Elsevier]

Conventional graphs often include error bars around the group means. Regardless of what these bars depict, they are uninformative as to whether a difference between the groups is statistically significant.This article suggests plotting the null bar or null zone: that is, the range or area in which the means of the two groups fall if the null hypothesis of no difference cannot be rejected. The bar and zone are simply derived from the confidence interval around the difference, obtained from the t-test. [Copyright &y& Elsevier]

Objective: To test the reliability of two radiologic scoring methods in rheumatoid arthritis (RA)—the Sharp/van der Heijde (SvH) and the Larsen/Scott (LS)—with generalizability analyses.Study design and setting: Films of 51 patients representing the spectrum of early RA were read by two raters for each method. The discriminative ability and responsiveness were expressed as: intraclass correlation coefficients (ICCs), two types of smallest detectable difference (SDD), and two types of smallest detectable change (SDC); reflecting measurement error when discriminating between or detecting changes within (1) individuals or (2) groups. They were calculated for (average) scores of one to three raters.Results: The discriminative capacity (0.85–0.97) and responsiveness (0.91–0.97) were good when expressed by ICC. On the group level the SDDs and SDCs ranged between 0.6–3.3% of the max. obtainable score. On the individual level, the scores showed better reliability measured with the SvH (SDDs 2.0–3.4%) than with the LS (SDDs 5.3–9.2%). The SvH also assessed changes in scores in individuals with less measurement error (SDCs 1.3–2.2%) than the LS (SDCs 2.3–3.9%).Conclusion: For early RA patients, the SvH seems preferable if analyses on individual level are included. [Copyright &y& Elsevier]

Abstract: Objective: To compare statistical models for the analysis of two-state disease processes. Study Design and Setting: A two-armed randomized trial of patients with early rheumatoid arthritis (RA) treated by either combination therapy (sulfasazaline, methotrextate, prednisolone) or monotherapy (sulfasazaline). Disease activity (remission or relapse) was analyzed with the logistic regression model, the proportional hazards regression model, and the continuous-time Markov process model for panel data. The dependence among the switching times was studied by (1) including correlated normal random patient effects for the relapse–remission and remission–relapse switching probabilities; (2) assuming the population to be a mixture of patients responsive and nonresponsive to therapy; (3) including separate parameters for the first and subsequent relapse–remission switch; and (4) combining (1) and (3). The four approaches were compared using parametric bootstrap checks. Results: The logistic regression model, the proportional hazards regression model, and the continuous-time Markov process model for panel data yielded similar combination therapy effects. The inclusion of random patient effects (approaches 1 and 4) gave the best fit to the observed disease activity pattern. Conclusion: Models with correlated random effects can provide a satisfactory fit to two-state disease patterns. [Copyright &y& Elsevier]

Abstract: Objective: Our purpose was to measure the agreement, reliability, construct validity, and feasibility of a measurement tool to assess systematic reviews (AMSTAR). Study Design and Setting: We randomly selected 30 systematic reviews from a database. Each was assessed by two reviewers using: (1) the enhanced quality assessment questionnaire (Overview of Quality Assessment Questionnaire [OQAQ]); (2) Sacks'' instrument; and (3) our newly developed measurement tool (AMSTAR). We report on reliability (interobserver kappas of the 11 AMSTAR items), intraclass correlation coefficients (ICCs) of the sum scores, construct validity (ICCs of the sum scores of AMSTAR compared with those of other instruments), and completion times. Results: The interrater agreement of the individual items of AMSTAR was substantial with a mean kappa of 0.70 (95% confidence interval [CI]: 0.57, 0.83) (range: 0.38–1.0). Kappas recorded for the other instruments were 0.63 (95% CI: 0.38, 0.78) for enhanced OQAQ and 0.40 (95% CI: 0.29, 0.50) for the Sacks'' instrument. The ICC of the total score for AMSTAR was 0.84 (95% CI: 0.65, 0.92) compared with 0.91 (95% CI: 0.82, 0.96) for OQAQ and 0.86 (95% CI: 0.71, 0.94) for the Sacks'' instrument. AMSTAR proved easy to apply, each review taking about 15 minutes to complete. Conclusions: AMSTAR has good agreement, reliability, construct validity, and feasibility. These findings need confirmation by a broader range of assessors and a more diverse range of reviews. [Copyright &y& Elsevier]

Abstract: Objective: To investigate areas of consensus and disagreement among Dutch physiatrists concerning prescription of therapeutic footwear for the neuropathic foot and to develop a research agenda. Study Design and Setting: Forty participants were physiatrists and experts in the field of orthopedic shoe techniques. Four postal Delphi rounds were followed by a final plenary session. Results: Forty of the 44 invited experts participated in all postal Delphi rounds, with an overall response of 100%. They achieved consensus on the following. 1. (Dutch) Terminology for two sets of domains and dimensions for the various features of the neuropathic foot and for the shoe characteristics. 2. Application of specific shoe components: insole, shaft, outsole, tongue, and heel. In most features of the neuropathic foot, shaft and outsole domains were linked in the flexibility dimension. 3. Shoe prescriptions for various features of the neuropathic foot in at least four technical domains. Experts disagreed on application of rocker bar and shaft height. In a final conference, 31 experts agreed on a prioritized research agenda. Conclusion: An intensive Delphi process yielded consensus on terminology, and determined areas of consensus and disagreement for future research for the various features of the neuropathic foot and the shoe characteristics. [Copyright &y& Elsevier]