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Background: To add context to the impact of medical conditions, it is important to interpret and compare health outcomes across studies and populations. We aimed to determine Dutch reference values for the Patient-Reported Outcomes Measurement Information System Scale v1.2 - Global Health (PROMIS-GH). Methods: The PROMIS-GH, also referred to as PROMIS-10, was completed by 4370 Dutch persons, representative for the 2016 Dutch population. T-scores for the mental health (GMH) and physical health (GPH) subscales, and their shorter two-item subscales, were calculated for the entire population, age groups and gender. T-scores for GMH and GPH were compared to the US reference population, representative for the 2000 US general population. Interpretability thresholds for poor, fair, good, very good and excellent GPH and GMH were calculated based on T-scores of participants, which were categorized into five groups based on their response to item Global01. For each group the mean GPH and GMH T-score was calculated and the midpoint between two adjacent means was identified, resulting in thresholds. Thresholds based on the Dutch data were compared to US thresholds. Results: The Dutch population had a GMH T-score of 44.7 and a GPH T-score of 45.2, both substantially worse than the US reference population T-score of 50. Lower T-scores were also found for age-range and gender subpopulations. Dutch GMH and GPH interpretability thresholds were mostly not substantially different compared to the US thresholds, although the Dutch threshold between fair and poor mental health was considerably higher (29 vs. 38). Conclusions: This study reports reference values for the PROMIS-GH scale for the Dutch general population, including age-range and gender subpopulations. These reference values provide an important tool for healthcare professionals and researchers to better evaluate and interpret patient-reported mental health and physical health. Scores are notably worse than the US reference values. The exact reason for this remains subject for further research, although possibilities for the differences are discussed, including the presence of differential item functioning and the representativeness and recentness of the data. [ABSTRACT FROM AUTHOR]

To standardize outcome reporting in clinical trials of patients with nonspecific low back pain, an international multidisciplinary panel recommended physical functioning, pain intensity, and health-related quality of life (HRQoL) as core outcome domains. Given the lack of a consensus on measurement instruments for these 3 domains in patients with low back pain, this study aimed to generate such consensus. The measurement properties of 17 patient-reported outcome measures for physical functioning, 3 for pain intensity, and 5 for HRQoL were appraised in 3 systematic reviews following the COSMIN methodology. Researchers, clinicians, and patients (n = 207) were invited in a 2-round Delphi survey to generate consensus (≥67% agreement among participants) on which instruments to endorse. Response rates were 44% and 41%, respectively. In round 1, consensus was achieved on the Oswestry Disability Index version 2.1a for physical functioning (78% agreement) and the Numeric Rating Scale (NRS) for pain intensity (75% agreement). No consensus was achieved on any HRQoL instrument, although the Short Form 12 (SF12) approached the consensus threshold (64% agreement). In round 2, a consensus was reached on an NRS version with a 1-week recall period (96% agreement). Various participants requested 1 free-to-use instrument per domain. Considering all issues together, recommendations on core instruments were formulated: Oswestry Disability Index version 2.1a or 24-item Roland-Morris Disability Questionnaire for physical functioning, NRS for pain intensity, and SF12 or 10-item PROMIS Global Health form for HRQoL. Further studies need to fill the evidence gaps on the measurement properties of these and other instruments. [ABSTRACT FROM AUTHOR]

Background: In cooperation with the Core Outcome Measures in Effectiveness Trials (COMET) initiative, the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative aimed to develop a guideline on how to select outcome measurement instruments for outcomes (i.e., constructs or domains) included in a "Core Outcome Set" (COS). A COS is an agreed minimum set of outcomes that should be measured and reported in all clinical trials of a specific disease or trial population.Methods: Informed by a literature review to identify potentially relevant tasks on outcome measurement instrument selection, a Delphi study was performed among a panel of international experts, representing diverse stakeholders. In three consecutive rounds, panelists were asked to rate the importance of different tasks in the selection of outcome measurement instruments, to justify their choices, and to add other relevant tasks. Consensus was defined as being achieved when 70 % or more of the panelists agreed and when fewer than 15 % of the panelists disagreed.Results: Of the 481 invited experts, 120 agreed to participate of whom 95 (79 %) completed the first Delphi questionnaire. We reached consensus on four main steps in the selection of outcome measurement instruments for COS: Step 1, conceptual considerations; Step 2, finding existing outcome measurement instruments, by means of a systematic review and/or a literature search; Step 3, quality assessment of outcome measurement instruments, by means of the evaluation of the measurement properties and feasibility aspects of outcome measurement instruments; and Step 4, generic recommendations on the selection of outcome measurement instruments for outcomes included in a COS (consensus ranged from 70 to 99 %).Conclusions: This study resulted in a consensus-based guideline on the methods for selecting outcome measurement instruments for outcomes included in a COS. This guideline can be used by COS developers in defining how to measure core outcomes. [ABSTRACT FROM AUTHOR]

Objective To compare rates of sustained low and minimal disease activity and remission according to the American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) criteria during 3-year followup in rheumatoid arthritis (RA) patients treated with etanercept and adalimumab in routine care. Methods Four hundred seven RA patients previously unexposed to tumor necrosis factor antagonists were treated with etanercept (n = 203) or adalimumab (n = 204) and assessed at 3- and later 6-month intervals. Treatment allocation was at the discretion of the treating rheumatologist. Clinical parameters were measured at each time point, as were anti-adalimumab antibodies in adalimumab-treated patients. Achievement of clinical outcome was defined as the occurrence of sustained (at least 12 consecutive months) low disease activity (28-joint Disease Activity Score [DAS28] <3.2), minimal disease activity (DAS28 <2.6), or ACR/EULAR remission based on the Simplified Disease Activity Index (SDAI). Non-overlapping response rates were calculated. Results Among the adalimumab group, 13% reached sustained low disease activity but not sustained minimal disease activity, 15% reached sustained minimal disease activity but not sustained remission according to the SDAI, and 16% reached sustained ACR/EULAR remission. In the etanercept group the corresponding rates were 16%, 11%, and 12%, respectively ( P = 0.42, overall test for linear trend). Adalimumab-treated patients without anti-adalimumab antibodies (n = 150 [74%]) had the best outcomes, and adalimumab-treated patients with anti-adalimumab antibodies the worst, with outcomes in etanercept-treated patients in between ( P < 0.0001). Differences were most apparent in the sustained SDAI remission and sustained minimal disease activity categories. For example, 40% of anti-adalimumab antibody-negative patients, 23% of etanercept-treated patients, and 4% of anti-adalimumab antibody-positive patients achieved at least sustained minimal disease activity. Conclusion Overall, etanercept and adalimumab treatment appear similar in inducing a good long-term clinical outcome. However, in the case of adalimumab this is strongly dependent on the presence or absence of anti-adalimumab antibodies. [ABSTRACT FROM AUTHOR]