From the Division of Rheumatology, Johns Hopkins University School of Medicine, Baltimore, Maryland; Division of Rheumatology, University of Utah, Salt Lake City, Utah; Department of Biostatistics, and Division of Rheumatology, University of Michigan, Ann Arbor Michigan, USA; Division of Rheumatology, University of Florence, Florence, Italy; Division of Rheumatology, Ghent University Hospital, Faculty of Internal Medicine, Ghent University, Ghent, Belgium; Rheumatology Unit, Royal Adelaide Hospital, Discipline of Medicine, University of Adelaide, Adelaide, Australia; Department of Medicine, and Division of Rheumatology, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania, USA.
Z.H. McMahan, Assistant Professor, MD, MHS, Division of Rheumatology, Johns Hopkins University School of Medicine; T. Frech, Associate Professor, MD, MS, Division of Rheumatology, University of Utah; V. Berrocal, Associate Professor, PhD, Department of Biostatistics, University of Michigan; D. Lim, PhD student, BS, Department of Biostatistics, University of Michigan; C. Bruni, Clinical Research Fellow, MD, Division of Rheumatology, University of Florence; M. Matucci-Cerinic, Professor, MD, PhD, Division of Rheumatology, University of Florence; V. Smith, Associate Professor, MD, PhD, Division of Rheumatology, Ghent University Hospital, Faculty of Internal Medicine, Ghent University; K. Melsens, MSc, PhD student, Division of Rheumatology, Ghent University Hospital, Faculty of Internal Medicine, Ghent University; S. Proudman, Associate Professor, MBBS, Rheumatology Unit, Royal Adelaide Hospital, Discipline of Medicine, University of Adelaide; J. Zhang, Gastroenterology Fellow, MD, Department of Medicine, Thomas Jefferson University Hospital; F. Mendoza, Assistant Professor, MD, Division of Rheumatology, Thomas Jefferson University Hospital; M. Woods, Department of Biostatistics, University of Michigan; D. Khanna, Professor, MD, MS, Division of Rheumatology, University of Michigan. Dr. Z.H. McMahan and Dr. T. Frech contributed equally to this work.
J Rheumatol. 2019 Jan;46(1):78-84. doi: 10.3899/jrheum.180004. Epub 2018 Nov 15.
Validated gastrointestinal (GI) symptoms scales are used in clinical practice to assess patient-reported GI involvement. We sought to determine whether University of California, Los Angeles (UCLA) GI Tract Questionnaire (GIT) 2.0 Reflux scale, Patient-Reported Outcomes Measurement Information System (PROMIS) Reflux scale, and the Quality of Life in Reflux and Dyspepsia questionnaire (QOLRAD) are sensitive to identifying changes in GI symptoms following therapeutic intervention in participants with systemic sclerosis (SSc) and gastroesophageal reflux disease (GERD).
Participants with active GERD were recruited during clinical visits at 6 international SSc centers. Patient-reported outcome surveys and the GI self-reported questionnaire were completed at baseline and again at 4 weeks following a single intervention, and patients were classified as "improved" or "not improved." Effect size (ES) was calculated to assess the sensitivity to change. ES was interpreted as 0.50-0.79 as moderate effect and ≥ 0.80 as large effect.
There were 116 participants with SSc and active GERD who enrolled. The average age was 53.8 years and mean disease duration was 12.0 years. The UCLA GIT 2.0 Reflux scale and PROMIS Reflux scale had a significant correlation at baseline (0.61, p < 0.0001), and both instruments correlated with the QOLRAD domains (-0.56 to -0.71). In participants who had the UCLA GIT 2.0, PROMIS Reflux scale, and QOLRAD administered over 2 timepoints (n = 57) and were classified as improved, the ES was large for the UCLA GIT 2.0 and PROMIS Reflux scale, and moderate to large across all QOLRAD domains.
The UCLA GIT 2.0 Reflux scale, PROMIS Reflux scale, and QOLRAD are sensitive to change and can be included in future clinical trials.
在临床实践中，经过验证的胃肠道（GI）症状量表用于评估患者报告的 GI 受累情况。我们旨在确定加利福尼亚大学洛杉矶分校（UCLA）GI 消化道问卷（GIT）2.0 反流量表、患者报告结局测量信息系统（PROMIS）反流量表和反流和消化不良生活质量问卷（QOLRAD）是否能够敏感地识别出系统性硬化症（SSc）和胃食管反流病（GERD）患者接受治疗干预后 GI 症状的变化。
在 6 个国际 SSc 中心的临床就诊期间，招募了有活动性 GERD 的参与者。在基线时和单一干预后 4 周再次完成患者报告的结果调查和 GI 自我报告问卷，患者被分类为“改善”或“未改善”。计算效应量（ES）以评估对变化的敏感性。ES 解释为 0.50-0.79 为中度效应，≥0.80 为大效应。
共有 116 名患有 SSc 和活动性 GERD 的参与者入组。平均年龄为 53.8 岁，平均病程为 12.0 年。UCLA GIT 2.0 反流量表和 PROMIS 反流量表在基线时具有显著相关性（0.61，p<0.0001），并且这两个工具均与 QOLRAD 各领域相关（-0.56 至-0.71）。在接受了 2 次 UCLA GIT 2.0、PROMIS 反流量表和 QOLRAD 测试且被分类为改善的 57 名参与者中，UCLA GIT 2.0 和 PROMIS 反流量表的 ES 较大，而所有 QOLRAD 领域的 ES 为中度至较大。
UCLA GIT 2.0 反流量表、PROMIS 反流量表和 QOLRAD 对变化敏感，可以包含在未来的临床试验中。
