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比较脊柱门诊中慢性下腰痛患者最佳管理的分层技术。

Comparison of stratification techniques for optimal management of patients with chronic low back pain in spine clinics.

机构信息

Center for Outcomes Research and Evaluation, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, JJ3-603, Cleveland, OH 44195, USA; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Ave, JJ3-603, Cleveland, OH 44195, USA.

Center for Outcomes Research and Evaluation, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, JJ3-603, Cleveland, OH 44195, USA; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Ave, JJ3-603, Cleveland, OH 44195, USA.

出版信息

Spine J. 2023 Sep;23(9):1334-1344. doi: 10.1016/j.spinee.2023.04.017. Epub 2023 May 5.

Abstract

BACKGROUND CONTEXT

Identifying optimal stratification techniques for subgrouping patients with low back pain (LBP) into treatment groups for the purpose of identifying optimal management and improving clinical outcomes is an important area for further research.

PURPOSE

Our study aimed to compare performance of the STarT Back Tool (SBT) and 3 stratification techniques involving PROMIS domain scores for use in patients presenting to a spine clinic for chronic LBP.

STUDY DESIGN

Retrospective cohort study.

PATIENT SAMPLE

Adult patients with chronic LBP seen in a spine center between November 14, 2018 and May 14, 2019 who completed patient-reported outcomes (PROs) as part of routine care, and were followed up with completed PROs 1 year later.

OUTCOME MEASURES

Four stratification techniques, including SBT, and 3 PROMIS-based techniques: the NIH Task Force recommended Impact Stratification Score (ISS), symptom clusters based on latent class analysis (LCA), and SPADE symptom clusters.

METHODS

The 4 stratification techniques were compared according to criterion validity, construct validity, and prognostic utility. For criterion validity, overlap in characterization of mild, moderate, and severe subgroups were compared to SBT, which was considered the gold standard, using quadratic weighted kappa statistic. Construct validity compared techniques' ability to differentiate across disability groups defined by modified Oswestry LBP Disability Questionnaire (MDQ), median days in the past month unable to complete activities of daily living (ADLs), and worker's compensation using standardized mean differences (SMD). Prognostic utility was compared based on the techniques' ability to predict long-term improvement in outcomes, defined as improvement in global health and MDQ at 1-year.

RESULTS

There were 2,246 adult patients with chronic LBP included in our study (mean age 61.0 [SD 14.0], 55.0% female, 83.4% white). All stratification techniques resulted in roughly a third of patients grouped into mild, moderate, and severe categories, with ISS and LCA demonstrating substantial agreement with SBT, while SPADE had moderate agreement. Construct validity was met for all techniques, with large effects demonstrated between mild and severe categories for differentiating MDQ, ADLs, and worker's compensation disability groups (SMD range 0.57-2.48). All stratification techniques demonstrated ability to detect improvement by 1-year, with severe groups experiencing the greatest improvement in multivariable logistic regression models.

CONCLUSIONS

All 4 stratification techniques demonstrated validity and prognostic utility for subgrouping patients with chronic LBP based on risk of long-term disability. ISS and LCA symptom clusters may be the optimal methods given the improved feasibility of including only a few relevant PROMIS domains. Future research should investigate multidisciplinary treatment approaches to target mild, moderate, and severe patients based on these techniques.

摘要

背景

为了确定最佳的管理方法并改善临床结果,将患有下腰痛(LBP)的患者分为治疗组进行亚组分析,以确定最佳的分层技术是一个重要的研究领域。

目的

我们的研究旨在比较 STAR 背部工具(SBT)和 3 种涉及 PROMIS 域评分的分层技术在因慢性 LBP 就诊于脊柱诊所的患者中的表现。

研究设计

回顾性队列研究。

患者样本

2018 年 11 月 14 日至 2019 年 5 月 14 日期间在脊柱中心就诊的患有慢性 LBP 的成年患者,他们完成了患者报告的结果(PROs)作为常规护理的一部分,并在 1 年后完成了 PROs 的随访。

结局测量

4 种分层技术,包括 SBT,以及 3 种基于 PROMIS 的技术:NIH 工作组推荐的影响分层评分(ISS)、基于潜在类别分析(LCA)的症状群和 SPADE 症状群。

方法

根据标准有效性、结构有效性和预后实用性比较 4 种分层技术。对于标准有效性,使用二次加权 kappa 统计量比较轻度、中度和重度亚组特征的重叠情况与 SBT 进行比较,SBT 被认为是金标准。结构有效性比较了技术在残疾组之间的差异能力,残疾组由改良 Oswestry LBP 残疾问卷(MDQ)定义,过去一个月无法完成日常生活活动(ADLs)的天数中位数,以及使用标准化均数差(SMD)的工人补偿。预后实用性基于技术预测长期结局改善的能力进行比较,定义为全球健康和 MDQ 在 1 年时的改善。

结果

我们的研究共纳入 2246 名患有慢性 LBP 的成年患者(平均年龄 61.0[14.0]岁,55.0%为女性,83.4%为白人)。所有分层技术均将大约三分之一的患者分为轻度、中度和重度组,ISS 和 LCA 与 SBT 具有显著一致性,而 SPADE 具有中度一致性。所有技术均符合结构有效性标准,在区分 MDQ、ADLs 和工人补偿残疾组方面,轻度和重度类别之间表现出较大的差异(SMD 范围为 0.57-2.48)。所有分层技术均显示出在 1 年内检测到改善的能力,严重组在多变量逻辑回归模型中经历了最大的改善。

结论

所有 4 种分层技术均显示出基于长期残疾风险对慢性 LBP 患者进行亚组分析的有效性和预后实用性。ISS 和 LCA 症状群可能是最佳方法,因为只包含几个相关的 PROMIS 域的可行性提高了。未来的研究应调查多学科治疗方法,根据这些技术针对轻度、中度和重度患者进行治疗。

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