Research methods for subgrouping low back pain

Abstract

Background: There is considerable clinician and researcher interest in whether the outcomes for patients with low back pain, and the efficiency of the health systems that treat them, can be improved by 'subgrouping research'. Subgrouping research seeks to identify subgroups of people who have clinically important distinctions in their treatment needs or prognoses. Due to a proliferation of research methods and variability in how subgrouping results are interpreted, it is timely to open discussion regarding a conceptual framework for the research designs and statistical methods available for subgrouping studies (a method framework). The aims of this debate article are: (1) to present a method framework to inform the design and evaluation of subgrouping research in low back pain, (2) to describe method options when investigating prognostic effects or subgroup treatment effects, and (3) to discuss the strengths and limitations of research methods suitable for the hypothesis-setting phase of subgroup studies.

Discussion: The proposed method framework proposes six phases for studies of subgroups: studies of assessment methods, hypothesis-setting studies, hypothesis-testing studies, narrow validation studies, broad validation studies, and impact analysis studies. This framework extends and relabels a classification system previously proposed by McGinn et al (2000) as suitable for studies of clinical prediction rules. This extended classification, and its descriptive terms, explicitly anchor research findings to the type of evidence each provides. The inclusive nature of the framework invites appropriate consideration of the results of diverse research designs. Method pathways are described for studies designed to test and quantify prognostic effects or subgroup treatment effects, and examples are discussed. The proposed method framework is presented as a roadmap for conversation amongst researchers and clinicians who plan, stage and perform subgrouping research.

Summary: This article proposes a research method framework for studies of subgroups in low back pain. Research designs and statistical methods appropriate for sequential phases in this research are discussed, with an emphasis on those suitable for hypothesis-setting studies of subgroups of people seeking care.

Figure 1

Conceptual phases of research into subgroups

Figure 2

Flowchart for hypothesis-setting studies of subgroups based on opinion or based on physiological models

Figure 3

Flowchart for hypothesis-setting studies of subgroups based on 'data-driven' analysis

Figure 4

Example of the use of a 'supervised' statistical technique (logistic regression) on longitudinal data in a hypothesis-setting cohort study (single-group design).

Figure 5

Example of the use of 'supervised' statistical techniques (such as regression and ANOVA) on longitudinal data in a hypothesis-setting randomised controlled trial (two-group plus subgroup covariate design).

Figure 6

Example of the use of a 'supervised' statistical technique (cluster analysis) on cross-sectional data in a hypothesis-setting study.

Figure 7

Example of the use of 'clinimetric' statistical techniques (sensitivity and specificity) on cross-sectional data in a 'diagnostic' hypothesis-setting study.