Predictive Validity of the STarT Back Tool for Risk of Persistent Disabling Back Pain in a U.S. Primary Care Setting

Predictive validity of the STarT Back screening tool among older adults with back pain

BACKGROUND

The predictive validity of the STarT Back screening tool among older adults is uncertain. This study aimed to assess the predictive validity of the SBT among older adults in primary care.

METHODS

This prospective cohort study included 452 patients aged ≥55 years seeking Norwegian primary care with a new episode of back pain. A poor outcome (persistent disabling back pain) was defined as a score of ≥7/24 on the Roland-Morris Disability Questionnaire (RMDQ) at 3, 6 or 12 months of follow-up. The ability of the SBT risk groups to identify persistent disabling back pain was assessed with multivariable logistic regression, area under receiver operating characteristics curve (AUC), and with the accuracy measures sensitivity, specificity, predictive values and likelihood ratios.

RESULTS

The adjusted odds ratios (95% CI) for persistent disabling back pain were 2.40 (1.34-4.30) at 3 months, 3.42 (1.76-6.67) at 6 months and 2.81 (1.47-5.38) at 12 months for the medium-risk group (n = 118), and 8.90 (1.83-43.24), 2.66 (0.81-8.67) and 4.53 (1.24-16.46) for the high-risk group (n = 27), compared to the low-risk group (n = 282). There were no statistically significant differences in odds between the medium- and high-risk groups at any time point. AUC values (95% CI) were 0.65 (0.59-0.71), 0.67 (0.60-0.73) and 0.65 (0.58-0.71) at 3, 6 and 12 months. Accuracy measures were poor at all time points, with particularly poor sensitivity and negative likelihood ratio values.

CONCLUSION

The predictive validity of the SBT risk groups in predicting persistent disabling back pain in older adults was poor.

SIGNIFICANCE STATEMENT

This study found that the STarT Back screening tool had poor predictive validity among older adults and that it may need recalibration or extension before widespread implementation among older adults. Having valid tools for this population may aid clinicians with allocating scarce healthcare resources, which is especially important considering the rapidly ageing population and its expected challenge to the healthcare systems.

Stratified health care for low back pain using the STarT Back approach: Holy Grail or doomed to fail?

ABSTRACT

There have been at least 7 separate randomised controlled trials published between 2011 and 2023 that have examined primary care for nonspecific low back pain informed by the STarT Back approach to stratified care based on risk prediction, compared with care not informed by this approach. The results, across 4 countries, have been contrasting-some demonstrating effectiveness and/or efficiency of this approach, others finding no benefits over comparison interventions. This review considers possible explanations for the differences, particularly whether this is related to poor predictive performance of the STarT Back risk-prediction tool or to variable degrees of success in implementing the whole STarT Back approach (subgrouping and matching treatments to predicted risk of poor outcomes) in different healthcare systems. The review concludes that although there is room for improving and expanding the predictive value of the STarT Back tool, its performance in allocating individuals to their appropriate risk categories cannot alone explain the variation in results of the trials to date. Rather, the learning thus far suggests that challenges in implementing stratified care in clinical practice and in changing professional practice largely explain the contrasting trial results. The review makes recommendations for future research, including greater focus on studying facilitators of implementation of stratified care and developing better treatments for patients with nonspecific low back pain at high risk of poor outcomes.

Validation of the Keele STarT MSK Tool for Patients With Musculoskeletal Pain in United States-based Outpatient Physical Therapy Settings

The STarT MSK tool was developed to enable risk stratification of patients with common musculoskeletal (MSK) pain conditions and help identify individuals who may require more targeted interventions or closer monitoring in primary care settings, however, its validity in U.S.-based outpatient physical therapy settings has not been investigated. The 10-item Keele STarT MSK risk stratification tool was tested for construct (convergent and discriminant) and predictive validity using a multicenter, prospective cohort study design. Participants (n = 141) receiving physical therapy for MSK pain of the back, neck, shoulder, hip, knee, or multisite regions completed intake questionnaires including the Keele STarT MSK tool, Functional Comorbidity Index (FCI), Optimal Screening for Prediction of Referral and Outcome Review-of-Systems and Optimal Screening for Prediction of Referral and Outcome Yellow Flag tools. Pain intensity, pain interference, and health-related quality of life (Medical Outcomes Study 8-item Short-Form Health Survey (SF-8) physical [PCS] and mental [MCS] component summary scores) were measured at 2- and 6-month follow-up. Participants were classified as STarT MSK tool low (44%), medium (39%), and high (17%) risk. Follow-up rates were 70.2% (2 months) and 49.6% (6 months). For convergent validity, fair relationships were observed between the STarT MSK tool and FCI and SF-8 MCS (r = .35-.37) while moderate-to-good relationships (r = .51-.72) were observed for 7 other clinical measures. For discriminant validity, STarT MSK tool risk-dependent relationships were observed for Optimal Screening for Prediction of Referral and Outcome Review-of-Systems, Optimal Screening for Prediction of Referral and Outcome Yellow Flag, pain interference, and SF-8 PCS (low < medium < high; P < .01) and FCI, pain intensity, and SF-8 MCS (low < medium-or-high; P < .01). For predictive validity, intake STarT MSK tool scores explained additional variability in pain intensity (11.2%, 20.0%), pain interference (7.5%, 14.1%), and SF-8 PCS (8.2%, 12.8%) scores at 2 and 6 months, respectively. This study contributes to the existing literature by providing additional evidence of STarT MSK tool cross-sectional construct validity and longitudinal predictive validity. PERSPECTIVE: This study presents STarT MSK risk stratification tool validity findings from a U.S. outpatient physical therapy sample. The STarT MSK tool has the potential to help physical therapists identify individuals presenting with the most common MSK pain conditions who may require more targeted interventions or closer monitoring.

Predictors of response in PROMIS-global in a chronic low back pain specialty clinic: STarTBack and chronic overlapping pain conditions

BACKGROUND

Tools, such as the STarTBack Screening Tool (SBT), have been developed to identify risks of progressing to chronic disability in low back pain (LBP) patients in the primary care population. However, less is known about predictors of change in function after treatment in the specialty care population.

OBJECTIVE

We pursued a retrospective observational cohort study involving LBP patients seen in a multidisciplinary specialty clinic to assess which features can predict change in function at follow-up.

METHODS

The SBT was administered at initial visit, and a variety of patient characteristics were available in the chart including the presence of chronic overlapping pain conditions (COPCs). Patient Reported Outcomes Measurement Information System-10 (PROMIS-10) global physical health (PH) and global mental health (MH) were measured at baseline and at pragmatic time points during follow-up. Linear regression was used to estimate adjusted associations between available features and changes in PROMIS scores.

RESULTS

241 patients were followed for a mean of 17.0 ± 7.5 months. Mean baseline pain was 6.7 (SD 2.1), PROMIS-10 global MH score was 44.8 (SD 9.3), and PH score was 39.4 (SD 8.6). 29.7% were low-risk on the SBT, 41.8% were medium-risk, and 28.5% were high-risk. Mean change in MH and PH scores from baseline to the follow-up questionnaire were 0.86 (SD 8.11) and 2.39 (SD 7.52), respectively. Compared to low-risk patients, high-risk patients had a mean 4.35 points greater improvement in their MH score (p= 0.004) and a mean 3.54 points greater improvement in PH score (p= 0.006). Fewer COPCs also predicted greater improvement in MH and PH.

CONCLUSIONS

SBT and the presence of COPC, which can be assessed at initial presentation to a specialty clinic, can predict change in PROMIS following treatment. Effort is needed to identify other factors that can help predict change in function after treatment in the specialty care setting.

External validation and updating of prognostic prediction models for nonrecovery among older adults seeking primary care for back pain

ABSTRACT

Prognostic prediction models for 3 different definitions of nonrecovery were developed in the Back Complaints in the Elders study in the Netherlands. The models' performance was good (optimism-adjusted area under receiver operating characteristics [AUC] curve ≥0.77, R2 ≥0.3). This study aimed to assess the external validity of the 3 prognostic prediction models in the Norwegian Back Complaints in the Elders study. We conducted a prospective cohort study, including 452 patients aged ≥55 years, seeking primary care for a new episode of back pain. Nonrecovery was defined for 2 outcomes, combining 6- and 12-month follow-up data: Persistent back pain (≥3/10 on numeric rating scale) and persistent disability (≥4/24 on Roland-Morris Disability Questionnaire). We could not assess the third model (self-reported nonrecovery) because of substantial missing data (>50%). The models consisted of biopsychosocial prognostic factors. First, we assessed Nagelkerke R2 , discrimination (AUC) and calibration (calibration-in-the-large [CITL], slope, and calibration plot). Step 2 was to recalibrate the models based on CITL and slope. Step 3 was to reestimate the model coefficients and assess if this improved performance. The back pain model demonstrated acceptable discrimination (AUC 0.74, 95% confidence interval: 0.69-0.79), and R2 was 0.23. The disability model demonstrated excellent discrimination (AUC 0.81, 95% confidence interval: 0.76-0.85), and R2 was 0.35. Both models had poor calibration (CITL <0, slope <1). Recalibration yielded acceptable calibration for both models, according to the calibration plots. Step 3 did not improve performance substantially. The recalibrated models may need further external validation, and the models' clinical impact should be assessed.

A descriptive analysis of the contents of Care Response, an international data set of patient-reported outcomes for chiropractic patients

BACKGROUND

Databases have become an important tool in understanding trends and correlations in health care by collecting demographic and clinical information. Analysis of data collected from large cohorts of patients can have the potential to generate insights into factors identifying treatments and the characteristics of subgroups of patients who respond to certain types of care. The Care Response (CR) database was designed to capture patient-reported outcome measures (PROMs) for chiropractic patients internationally. Although several papers have been published analysing some of the data, its contents have not yet been comprehensively documented. The primary aim of this study was to describe the information in the CR database. The secondary aim was to determine whether there was suitable information available to better understand subgroups of chiropractic patients and responsiveness to care. This would be achieved by enabling correlations among patient demographics, diagnoses, and therapeutic interventions with machine learning approaches.

METHODS

Data in all available fields were requested with no date restriction. Data were collected on 12 April 2022. The output was manually scanned for scope and completeness. Tables were created with categories of information. Descriptive statistics were applied.

RESULTS

The CR database collects information from patients at the first clinical visit, 14, 30, and 90 days subsequently. There were 32,468 patient responses; 3210 patients completed all fields through the 90 day follow up period. 45% of respondents were male; 54% were female; the average age was 49. There was little demographic information, and no information on diagnoses or therapeutic interventions. We received StartBack, numerical pain scale, patient global impression of change, and Bournemouth questionnaire data, but no other PROMs.

CONCLUSIONS

The CR database is a large set of PROMs for chiropractic patients internationally. We found it unsuitable for machine learning analysis for our purposes; its utility is limited by a lack of demographic information, diagnoses, and therapeutic interventions. However, it can offer information about chiropractic care in general and patient satisfaction. It could form the basis for a useful clinical tool in the future, if reformed to be more accessible to researchers and expanded with more information collected.

Predictive performance of the STarT Back tool for poor outcomes in patients with low back pain: protocol for a systematic review and meta-analysis

INTRODUCTION

Subgroups for Targeted Treatment Back Tool (SBT) is a brief multiple-construct risk prediction tool for patients with low back pain (LBP). Thus far, the predictive ability of this tool has been inconsistent. Therefore, we aim to conduct a literature review on the predictive ability of the SBT to determine the outcomes of patients with LBP. The results of this review should improve the ability of the SBT to predict poor outcomes in patients with LBP.

METHODS AND ANALYSIS

Databases including PubMed, EMBASE, Cochrane Central, Web of Science, Chinese National Knowledge Infrastructure Databases, Chinese Science and Technology Journal Database, and Wanfang will be searched for studies on SBT and LBP from their inception until 31 March 2023. Longitudinal studies investigating the association between SBT subgroups and LBP outcomes, including pain, disability and quality of life, will be included. The identified studies will be independently screened for eligibility by two reviewers. A standardised sheet will be used to extract data. The Newcastle-Ottawa Scale will be used to assess the methodological quality of the included studies. Heterogeneity will be evaluated by the χ2 test with Cochran's Q statistic and quantified by the I2 statistic. The results will be synthesised qualitatively and presented as pooled risk ratios or beta coefficients quantitatively. The results will also be presented using their 95% confidence limits. Publication bias will be assessed using the method proposed by Egger and by visual inspection of funnel plots.

ETHICS AND DISSEMINATION

This study is a secondary analysis of original studies that received ethics approval. Therefore, prior ethical approval is not required for this study. The findings will be submitted to relevant peer-reviewed journals for publication and presented at profession-specific conferences.

TRIAL REGISTRATION NUMBER

PROSPERO registration numberCRD42022309189.

Risk Stratification in a Tertiary Care Spine Centre: Comparison Between STarTBack and OSPRO-YF Screening Tools

Purpose

STarT Back Screening Tool and OSPRO-YF scales have been reported to be accurate tools for estimating risk for the development of persistent pain or prolonged disability in primary care settings. We performed a comparison of construct convergent and known-group validity and ceiling floor effect (CFE) of these tools using a common sample of patients seen at a tertiary care spine centre.

Methods

This was a cross-sectional study of patients with and without a work-related back injury. The Hospital Anxiety and Depression Scale (HADS) was used as the reference outcome measure for convergent validity. For known-group validity, we examined the ability of the scales to differentiate between different levels of compensation, presence of non-organic signs, and work status. The CFE values were calculated.

Results

Fifty consecutive injured workers were included along with 50 patients without an active compensation claim related to their low back pain. STarTBack and OSPRO-YF had moderate to high associations with the depression component of the HADS (0.69 to 0.77 respectively) with a statistically significant difference in favour of the OSPRO-YF. STarTBack's risk stratification categories were able to differentiate patients with a compensable injury, non-organic signs, and inability to work (p values ranging from 0.002 to < 0.001). The physical activity and work fear-avoidance beliefs constructs of the OSPRO-YF consistently outperformed other yellow flag constructs (p values ranging from 0.008 to < 0.001). The psychological sub-score of STarTBack showed a ceiling effect. There was a floor effect for the negative affect domain of OSPRO-YF. Neither total score had a floor or ceiling effect.

Conclusions

STarTBack and OSPRO-YF are short screening tools with acceptable convergent and known-group construct validity and no floor or ceiling effect of their total score. Both tools could assist with the identification, evaluation, and management of psychological distress in patients presenting to tertiary care spine centres.

Management of Low Back Pain: Do Physiotherapists Know the Evidence-Based Guidelines?

BACKGROUND

Clinical practice guidelines promote bio-psychosocial management of patients suffering from low back pain (LBP). The objective of this study was to examine the current knowledge, attitudes and beliefs of physiotherapists about a guideline-adherent approach to LBP and to assess the ability of physiotherapists to recognise signs of a specific LBP in a clinical vignette.

METHODS

Physiotherapists were recruited to participate in an online study. They were asked to indicate whether they were familiar with evidence-based guidelines and then to fill in the Health Care Providers' Pain and Impairment Relationship Scale (HC-PAIRS), Back Pain Attitudes Questionnaire (Back-PAQ), Neurophysiology of Pain Questionnaire (NPQ), as well as questions related to two clinical vignettes.

RESULTS

In total, 527 physiotherapists participated in this study. Only 38% reported being familiar with guidelines for the management of LBP. Sixty-three percent of the physiotherapists gave guideline-inconsistent recommendations regarding work. Only half of the physiotherapists recognised the signs of a specific LBP.

CONCLUSIONS

The high proportion of physiotherapists unfamiliar with guidelines and demonstrating attitudes and beliefs not in line with evidence-based management of LBP is concerning. It is crucial to develop efficient strategies to enhance knowledge of guidelines among physiotherapists and increase their implementation in clinical practice.

Sequential and Comparative Evaluation of Pain Treatment Effectiveness Response (SCEPTER), a pragmatic trial for conservative chronic low back pain treatment

BACKGROUND

Chronic low back pain (cLBP) is a common and highly disabling problem world-wide. Although many treatment options exist, it is unclear how to best sequence the multitude of care options to provide the greatest benefit to patients.

METHODS

The Sequential and Comparative Evaluation of Pain Treatment Effectiveness Response (SCEPTER) trial uses a pragmatic, randomized, stepped design. Enrollment targets 2529 participants from 20 Veterans Affairs (VA) medical centers. Participants with chronic low back pain will first be randomized to one of three options: 1) an internet-based self-management program (Pain EASE); 2) a tailored physical therapy program (Enhanced PT); or 3) continued care with active monitoring (CCAM), a form of usual care. Participants not achieving a 30% or 2-point reduction on the study's primary outcome (Brief Pain Inventory Pain Interference (BPI-PI) subscale), 3 months after beginning treatment may undergo re-randomization in a second step to cognitive behavioral therapy for chronic pain, spinal manipulation therapy, or yoga. Secondary outcomes include pain intensity, back pain-related disability, depression, and others. Participants will be assessed every three months until 12 months after initiating their final trial therapy. Companion economic and implementation analyses are also planned.

RESULTS

The SCEPTER trial is currently recruiting and enrolling participants.

CONCLUSIONS

Trial results will inform treatment decisions for the stepped management of chronic low back pain - a common and disabling condition. Additional analyses will help tailor treatment selection to individual patient characteristics, promote efficient resource use, and identify implementation barriers of interventions.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT04142177.

Four Variables Were Sufficient for Low Back Pain: Determining Which Patient-Reported Tools Pain and Disability Improvements

OBJECTIVE: To predict 30- and 180-day improvements in disability and pain for patients seeking physical therapy care for low back pain (LBP). DESIGN: Longitudinal cohort. METHODS: Baseline assessment was completed by 259 patients with chief complaint of LBP, and the assessment includes psychosocial measures (Keele STarT Back Screening [SBST] and the Optimal Screening for Prediction of Referral and Outcome Yellow Flag [OSPRO-YF] tools), the Optimal Screening for Prediction of Referral and Outcome Review of Symptoms (OSPRO-ROS) and the Review of Symptoms Plus (OSPRO-ROS+) tools, the Charlson Comorbidity Index (CCI), the Area Deprivation Index (ADI), and the National Institute of Health Chronic Pain Criteria (NIH-CP). Using the Modified Low Back Disability Questionnaire (MDQ) and the Numeric Pain Rating Scale (NPRS) as primary outcomes, statistical analysis determined multiple sets of predictor variables with similar model performance. RESULTS: The parsimonious "best model" for prediction of the 180-day MDQ change included 3 predictors (Admit MDQ, NIH-CP, and OSPRO ROS+) because it had the lowest penalized goodness-of-fit statistic (BIC = -35.21) and the highest explained variance (R2 = 0.295). The parsimonious "best model" for 180-day NPRS change included 2 variables (Admit NPRS and OSPRO-ROS+) with the lowest penalized goodness-of-fit statistic (BIC = -18.2) and the highest explained variance (R2 = 0.190). CONCLUSION: There were many model options with similar statistical performance when using established measures to predict MDQ and NPRS outcomes. A potential variable set for a standard predictive model that balances statistical performance with pragmatic considerations included the OSPRO-ROS+, OSPRO-YF, NIH-CP definition, and admit MDQ and NPRS scores. J Orthop Sports Phys Ther 2022;52(10):685-693. Epub: 12 August 2022. doi:10.2519/jospt.2022.11018.

A Scoping Review of Chronic Low Back Pain Classification Schemes Based on Patient-Reported Outcomes

BACKGROUND

In 2014, the National Institutes of Health Pain Consortium Research Task Force recommended that patients with chronic low back pain (CLBP) be stratified by its impact on their lives. They proposed the Impact Stratification Score (ISS) to help guide therapy and facilitate study comparability. The ISS has been evaluated as a continuous measure, but not for use as a stratification or classification scheme.

OBJECTIVES

Identify the characteristics of successful schemes to inform the use of the ISS for stratification or classification.

STUDY DESIGN

Scoping review of the peer-reviewed literature.

METHODS

Search of PubMed, CINAHL, and APA PsycInfo to identify patient self-report-based classification schemes applicable to CLBP. Data were captured on the methods used for each scheme's development, the domains covered, their scoring criteria and what the classification has successfully measured. The study was reviewed and approved by the RAND Human Subjects Protection Committee (2019-0651-AM02).

RESULTS

The search identified 87 published articles about the development and testing of 5 classification schemes: 1) The Subgroups for Targeted Treatment (STarT) Back Screening Tool, 2) Multiaxial Assessment of Pain, 3) Graded Chronic Pain Scale, 4) Back Pain Classification Scale, and 5) Chronic Pain Risk Score. All have been shown to be predictive of future outcomes and the STarT Back has been found useful in identifying effective classification-specific treatment. Each scheme had a different classification scoring structure, was developed using different methods, and 3 included domains not found in the ISS.

LIMITATIONS

Expanding the search to other databases may have identified more classification schemes. Our minimum number of publications inclusion criterion eliminated dozens of cluster analyses, some of which may have eventually been replicated.

CONCLUSIONS

The methods used to develop these successful classification schemes, especially those that use straightforward scoring schemes, should be considered for use in the development of a scheme based on the ISS.

Healthcare utilization and related costs among older people seeking primary care due to back pain: findings from the BACE-N cohort study

OBJECTIVES

To describe healthcare utilization and estimate associated costs during 1 year of follow-up among older people seeking primary care due to a new episode back pain and to describe healthcare utilization across patients with different risk profiles stratified using the StarT Back Screening Tool (SBST).

DESIGN

Prospective cohort study.

PARTICIPANTS AND SETTING

A total of 452 people aged ≥55 years seeking Norwegian primary care with a new episode of back pain were included.

OUTCOME MEASURES

The primary outcome of this study was total cost of healthcare utilization aggregated for 1 year of follow-up. Secondary outcomes included components of healthcare utilization aggregated for 1 year of follow-up. Healthcare utilization was self-reported and included: primary care consultations, medications, examinations, hospitalisation, rehabilitation stay, and operations. Costs were estimated based on unit costs collected from national pricelists. Healthcare utilization across patients with different SBST risk profiles was compared using Kruskal-Wallis test, post hoc Mann-Whitney U tests and Bonferroni adjustment.

RESULTS

In total, 438 patients were included in the analysis. Mean (BCa 95% CI) total cost per patient over 1 year was €825 (682-976). Median (BCa 95% CI) total cost was €364 (307-440). The largest cost category was primary care consultations, accounting for 56% of total costs. Imaging rate was 34%. The most commonly used medication was paracetamol (27%-35% of patients). Medium- and high-risk patients had a significantly higher degree of healthcare utilization compared with low-risk patients (p<0.030).

CONCLUSION

This study estimated a 1 year mean and median cost of healthcare utilization of €825 and €364, respectively. Patients within the top 25th percentile accounted for 77% of all costs. Patients classified as medium risk and high risk had a significantly higher degree of healthcare utilization compared with patients classified as low risk.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov NCT04261309, results.

An interactive e-learning module to promote bio-psycho-social management of low back pain in healthcare professionals: a pilot study

Introduction: Low back pain (LBP) is ranked as the first musculoskeletal disorder considering years lived with disability worldwide. Despite numerous guidelines promoting a bio-psycho-social (BPS) approach in the management of patients with LBP, many health care professionals (HCPs) still manage LBP patients mainly from a biomedical point of view. Objective: The purpose of this pilot study was to evaluate the feasibility of implementing an interactive e-learning module on the management of LBP in HCPs. Methods: In total 22 HCPs evaluated the feasibility of the e-learning module with a questionnaire and open questions. Participants filled in the Back Pain Attitude Questionnaire (Back-PAQ) before and after completing the module to evaluate their attitudes and beliefs about LBP. Results: The module was structured and easy to complete (91%) and met the expectations of the participants (86%). A majority agreed that the module improved their knowledge (69%). Some participants (77%) identified specific topics that might be discussed in more detail in the module. HCPs knowledge, beliefs and attitudes about LBP significantly improved following module completion (t = -7.63, P < .001) with a very large effect size (d_s = -1.63). Conclusion: The module seems promising to change knowledge, attitudes and beliefs of the participants. There is an urgent need to develop and investigate the effect of educational interventions to favor best practice in LBP management and this type of e-learning support could promote the transition from a biomedical to a bio-psycho-social management of LBP in HCPs.

Cervical fusion for treatment of degenerative conditions: development of appropriate use criteria

BACKGROUND CONTEXT

High quality evidence is difficult to generate, leaving substantial knowledge gaps in the treatment of spinal conditions. Appropriate use criteria (AUC) are a means of determining appropriate recommendations when high quality evidence is lacking.

PURPOSE

Define appropriate use criteria (AUC) of cervical fusion for treatment of degenerative conditions of the cervical spine.

STUDY DESIGN/SETTING

Appropriate use criteria for cervical fusion were developed using the RAND/UCLA appropriateness methodology. Following development of clinical guidelines and scenario writing, a one-day workshop was held with a multidisciplinary group of 14 raters, all considered thought leaders in their respective fields, to determine final ratings for cervical fusion appropriateness for various clinical situations.

OUTCOME MEASURES

Final rating for cervical fusion recommendation as either "Appropriate," "Uncertain" or "Rarely Appropriate" based on the median final rating among the raters.

METHODS

Inclusion criteria for scenarios included patients aged 18 to 80 with degenerative conditions of the cervical spine. Key modifiers were defined and combined to develop a matrix of clinical scenarios. The median score among the raters was used to determine the final rating for each scenario. The final rating was compared between modifier levels. Spearman's rank correlation between each modifier and the final rating was determined. A multivariable ordinal regression model was fit to determine the adjusted odds of an "Appropriate" final rating while adjusting for radiographic diagnosis, number of levels and symptom type. Three decision trees were developed using decision tree classification models and variable importance for each tree was computed.

RESULTS

Of the 263 scenarios, 47 (17.9 %) were rated as rarely appropriate, 66 (25%) as uncertain and 150 (57%) were rated as appropriate. Symptom type was the modifier most strongly correlated with the final rating (adjusted ρ2 = 0.58, p<.01). A multivariable ordinal regression adjusting for symptom type, diagnosis, and number of levels and showed high discriminative ability (C statistic = 0.90) and the adjusted odds ratio (aOR) of receiving a final rating of "Appropriate" was highest for myelopathy (aOR, 7.1) and radiculopathy (aOR, 4.8). Three decision tree models showed that symptom type and radiographic diagnosis had the highest variable importance.

CONCLUSIONS

Appropriate use criteria for cervical fusion in the setting of cervical degenerative disorders were developed. Symptom type was most strongly correlated with final rating. Myelopathy or radiculopathy were most strongly associated with an "Appropriate" rating, while axial pain without stenosis was most associated with "Rarely Appropriate."

Pain Catastrophizing, Self-reported Disability, and Temporal Summation of Pain Predict Self-reported Pain in Low Back Pain Patients 12 Weeks After General Practitioner Consultation: A Prospective Cohort Study

OBJECTIVES

Patients with low back pain (LBP) often demonstrate pain sensitization, high degree of pain catastrophizing, and psychological distress. This study investigated whether pain sensitization mechanisms, the Pain Catastrophizing Scale (PCS), and Start Back Screening Tool were associated with pain in recurrent LBP patients 12 weeks after consulting their general practitioner (GP).

MATERIALS AND METHODS

In 45 LBP patients, pressure pain thresholds, temporal summation of pain (TSP), conditioned pain modulation (CPM), the Roland Morris Disability Questionnaire (RMDQ), and the PCS were assessed before consultation. Patients were classified into low to medium or high risk of poor prognosis on the basis of the Start Back Screening Tool. Worst pain within the last 24 hours was assessed on a visual analogue scale (VAS) at inclusion and 12 weeks after GP consultation.

RESULTS

VAS scores were reduced after 12 weeks in the low-to-medium (N=30, P<0.05), but not the high-risk group (N=15, P=0.40). RMDQ was reduced after 12 weeks (P<0.001), but with no difference between the groups. PCS was reduced in the low-to-medium and the high-risk group (P<0.05). TSP was significantly higher at follow-up in the high-risk group compared with the low-to-medium-risk group (P<0.05). A linear regression model explained 54.9% of the variance in VAS scores at follow-up utilizing baseline assessments of TSP, RMDQ, and PCS.

DISCUSSION

This study indicate that patients with LBP and high self-reported disability, high pain catastrophizing, and facilitated TSP assessed when consulting the GP might predictive poor pain progression 12 weeks after the consultation.

Developing clinical prediction models for nonrecovery in older patients seeking care for back pain: the back complaints in the elders prospective cohort study

ABSTRACT

Back pain is a leading cause of disability worldwide and is common in older adults. No clinical prediction models for poor long-term outcomes have been developed in older patients with back pain. This study aimed to develop and internally validate 3 clinical prediction models for nonrecovery in this population. A prospective cohort study in general practice was conducted (Back Complaints in the Elders, Netherlands), including 675 patients >55 years with a new episode of care for back pain. Three definitions of nonrecovery were used combining 6-month and 12-month follow-up data: (1) persistent back pain, (2) persistent disability, and (3) perceived nonrecovery. Sample size calculation resulted in a maximum of 14 candidate predictors that were selected from back pain prognostic literature and clinical experience. Multivariable logistic regression was used to develop the models (backward selection procedure). Models' performance was evaluated with explained variance (Nagelkerke's R2), calibration (Hosmer-Lemeshow test), and discrimination (area under the curve [AUC]) measures. The models were internally validated in 250 bootstrapped samples to correct for overoptimism. All 3 models displayed good overall performance during development and internal validation (ie, R2 > 30%; AUC > 0.77). The model predicting persistent disability performed best, showing good calibration, discrimination (AUC 0.86, 95% confidence interval 0.83-0.89; optimism-adjusted AUC 0.85), and explained variance (R2 49%, optimism-adjusted R2 46%). Common predictors in all models were: age, chronic duration, disability, a recent back pain episode, and patients' recovery expectations. Spinal morning stiffness and pain during spinal rotation were included in 2 of 3 models. These models should be externally validated before being used in a clinical primary care setting.

Predicting Persistent Disabling Low Back Pain in Veterans Affairs Primary Care Using the STarT Back Tool

BACKGROUND

The Subgrouping for Targeted Treatment (STarT Back) is a stratified care approach to low back pain (LBP) treatment. The predictive validity of STarT Back in Veterans Affairs (VA) primary care has not been demonstrated.

OBJECTIVE

To examine the validity of the STarT Back tool for predicting future persistent disabling LBP in VA primary care.

DESIGN

Cohort study.

SETTING

VA primary care in Washington State.

PARTICIPANTS

Veterans seeking care for LBP in VA primary care clinics.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

The STarT Back tool was used to classify Veterans according to their baseline risk group (low vs medium vs high). The primary study outcome, persistent disabling LBP, was defined as a Roland-Morris Disability Questionnaire (RMDQ) score ≥ 7 at 6-month follow-up. Analyses examined discrimination and calibration of the baseline STarT Back risk groups for prediction of persistent disabling LBP at 6-month follow-up.

RESULTS

Of the study sample, 9% were female and 80% reported longstanding LBP (>5 year duration). Among 538 participants, the baseline STarT Back risk groups were associated with future persistent disabling LBP at 6-month follow-up. Within each baseline STarT Back risk group, the proportions with future persistent disabling LBP at 6-month follow-up were 54% (low risk), 88% (medium risk), and 97% (high risk). The baseline STarT Back risk groups had useful discrimination (area under the curve [AUC] 0.79) for predicting future persistent disabling LBP, but the proportion of Veterans with persistent disabling LBP at 6-month follow-up was substantially higher than that observed in non-VA primary care settings.

CONCLUSIONS

The STarT Back risk groups had useful discrimination (AUC = 0.79) for future persistent disabling LBP, but calibration was poor, underestimating the risk of persistent disabling LBP. The STarT Back tool may require updating for use in VA primary care.

Adding Physical Impairment to Risk Stratification Improved Outcome Prediction in Low Back Pain

OBJECTIVE

Identifying subgroups of low back pain (LBP) has the potential to improve prediction of clinical outcomes. Risk stratification is one such strategy that identifies similar characteristics indicative of a common clinical outcome trajectory. The purpose of this study was to determine if an empirically derived subgrouping approach based on physical impairment measures improves information provided from the STarT Back Tool (SBT).

METHODS

At baseline in this secondary analysis of a cohort study, patients (N = 144) receiving physical therapy for LBP completed the SBT and tests (active lumbar flexion, extension, lateral bending, and passive straight-leg raise) from a validated physical impairment index. Clinical outcomes were assessed at 4 weeks and included the Numerical Pain Rating Scale and Oswestry Disability Index. Exploratory hierarchical agglomerative cluster analysis identified empirically derived subgroups based on physical impairment measures. Independent samples t testing and chi-square analysis were used to assess baseline subgroup differences in demographic and clinical measures. Spearman rho correlation coefficient was used to assess baseline SBT risk and impairment subgroup relationships, and a 3-way mixed-model ANOVA was used to assessed SBT risk and impairment subgroup relationships with clinical outcomes at 4 weeks.

RESULTS

Two physical impairment-based subgroups emerged from cluster analysis: (1) low-risk impairment (n = 119, 81.5%), characterized by greater lumbar mobility; and (2) high-risk impairment (n = 25, 17.1%), characterized by less lumbar mobility. A weak, positive relationship was observed between baseline SBT risk and impairment subgroups (rs = .170). An impairment-by-SBT risk-by-time interaction effect was observed for Oswestry Disability Index scores but not for Numerical Pain Rating Scale scores at 4 weeks.

CONCLUSIONS

Physical impairment subgroups were not redundant with SBT risk categories and could improve prediction of 4-week LBP disability outcomes. Physical impairment subgroups did not improve the prediction of 4-week pain intensity scores.

IMPACT

Subgroups based on physical impairment and psychosocial risk could lead to better prediction of LBP disability outcomes and eventually allow for treatment options tailored to physical and psychosocial risk.

Outcome of group physical therapy treatment for non-specific low back pain patients can be predicted with the cross-culturally adapted and validated Hungarian version STarT back screening tool

PURPOSE

The STarT Back Tool was developed to identify the specific modifiable prognostic factors for non-specific low back pain and to classify the patients into risk groups; low, medium and high risk of chronicity. Applied therapeutic approaches often involve group physical therapy. The aim of this study was the cross-cultural adaptation and validation of the Hungarian version of the STarT Back Tool and to investigate the predictive ability for global treatment outcome.

MATERIALS AND METHODS

A prospective cohort study (N = 133) was carried out involving non-specific low back pain patients. Internal consistency, construct validity, reliability and prognostic discriminative ability have been investigated. After 3 months of treatment global outcome was evaluated.

RESULTS

A 2-factor structure was found, with moderate internal consistency (Cronbach α = 0.89 for the total and psychosocial subscale 0.62). Between the Hungarian STarT Back Tool, the Oswestry Disability Index, leg pain, low back pain, Tampa Scale for Kinesiophobia, Fear Avoidance Beliefs Questionnaire and the physical subscale of the quality of life questionnaire, significant good to excellent- correlation was found (r > 0.41). The test-retest analysis showed excellent reliability (Intraclass Correlation Coefficient = 0.93) with standard error measurement being 0.49 (minimal detectable change = 1.37). The Area Under the Curve for baseline STarT Back Tool scores was 0.7 and 0.8 for global treatment outcome and distress, respectively. The Area Under the Curve for global treatment outcome versus STarT risk groups proved to be 0.76 representing adequate discriminative ability.

CONCLUSION

The successful cross-cultural adaptation was followed by the validity analysis and as a result the Hungarian version of the STarT Back Tool proved to be a reliable and valid tool in the identification of risk groups of chronicity for patients with low back pain. Patients allocated to the high-risk group were more likely experiencing poor outcome at 3 months follow up, thus it can be used to predict outcome if treated with group physical therapy.Implication for rehabilitationLow back pain is a multifactorial disease where physical and psychosocial risk factors play a role in the development and prognosis of the disease.The STarT-H can be considered as a reliable, valid measurement tool in the identification of risk groups of chronicity for patients with low back pain.Clinical relevance of the STarT-H is that it can be used to stratify patients into risk groups of chronicity in different Hungarian speaking healthcare settings.According to our findings the STarT-H can also be applied to predict global treatment outcome in low back pain patients if treated with group physical therapy.

Use of the STarT Back Screening Tool in patients with chronic low back pain receiving physical therapy interventions

BACKGROUND

The STarT Back Screening Tool (SBST) is used to stratify care. It is unclear if the SBST approach works as well for patients in low- and medium-income countries as for patients from high-income countries.

OBJECTIVES

(1) To investigate whether patients with chronic low back pain (LBP) stratified by the SBST are different at baseline; (2) to describe the clinical course for each SBST subgroup; (3) to investigate the SBST utility to predict clinical outcomes; and (4) to determine which SBST subgroup show greater clinical improvement.

DESIGN

This is a secondary analysis of data derived from a previously published clinical trial.

METHODS

148 patients with chronic nonspecific LBP were included. Pain intensity, disability, global perceived effect, and the SBST were assessed at baseline and at 5, 12, and 24 weeks after baseline. Descriptive data were provided and ANOVA, unadjusted and adjusted regression models, and linear mixed models were used for data analysis.

RESULTS

Duration of symptoms, use of medication, pain, disability, and global perceived effect were different between SBST subgroups. Clinical improvements over a 6-month period were consistently greater in patients classified as high risk. The SBST was able to predict disability but this predictability decreased when the analysis was adjusted for possible confounders.

CONCLUSION

Clinical outcomes were different between SBST subgroups over 6 months. Adjusting for confounders influenced the predictability of SBST. Patients classified as high risk presented higher improvements in terms of disability.

Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews

Artificial intelligence and machine learning (AI/ML) could enhance the ability to detect patterns of clinical characteristics in low-back pain (LBP) and guide treatment. We conducted three systematic reviews to address the following aims: (a) review the status of AI/ML research in LBP, (b) compare its status to that of two established LBP classification systems (STarT Back, McKenzie). AI/ML in LBP is in its infancy: 45 of 48 studies assessed sample sizes <1000 people, 19 of 48 studies used ≤5 parameters in models, 13 of 48 studies applied multiple models and attained high accuracy, 25 of 48 studies assessed the binary classification of LBP versus no-LBP only. Beyond the 48 studies using AI/ML for LBP classification, no studies examined use of AI/ML in prognosis prediction of specific sub-groups, and AI/ML techniques are yet to be implemented in guiding LBP treatment. In contrast, the STarT Back tool has been assessed for internal consistency, test-retest reliability, validity, pain and disability prognosis, and influence on pain and disability treatment outcomes. McKenzie has been assessed for inter- and intra-tester reliability, prognosis, and impact on pain and disability outcomes relative to other treatments. For AI/ML methods to contribute to the refinement of LBP (sub-)classification and guide treatment allocation, large data sets containing known and exploratory clinical features should be examined. There is also a need to establish reliability, validity, and prognostic capacity of AI/ML techniques in LBP as well as its ability to inform treatment allocation for improved patient outcomes and/or reduced healthcare costs.

STarT back tool retained its predicting abilities in patients with acute and sub-acute low back pain after a transcultural adaptation and validation to Hebrew

BACKGROUND

The STarT Back Screening Tool (SBT) distributes low back pain (LBP) patients into three prognostic groups for stratified care. This approach has demonstrated beneficial clinical and cost-effectiveness.

OBJECTIVES

To translate and validate the SBT by investigating its psychometric properties among Israelis with acute and sub-acute LBP, and to evaluate its ability to predict disability after three months.

DESIGN

Prospective study.

METHOD

The SBT was transcultural adapted into Hebrew using published guidelines. A total of 150 patients receiving physical therapy for acute or subacute LBP were administered the SBT. Clinical outcomes included the Roland-Morris Disability Questionnaire (RMDQ), the Hospital Anxiety and Depression Scale (HADS), the Fear-Avoidance Beliefs Questionnaire (FABQ) and a numerical pain rating scale (NPRS), collected by an independent interviewer by phone at the start of the physical therapy treatment and after three months.

RESULTS

The test-retest reliability of the SBT total score and psychosocial subscale were excellent (intraclass correlation coefficient 0.89 and 0.82). Spearman's correlation coefficient between SBT total score and RMDQ was 0.82, HADS (Anxiety 0.66, Depression 0.76), FABQ (exercise 0.53), NPRS (severe pain 0.48, average pain 0.53). The SBT baseline score showed excellent predictive abilities in discriminating poor disability after three months (ROC curve = 0.825, P < 0.001, 95% CI 0.756-0.894).

CONCLUSION

The Israeli translation and cross-cultural adaptation of the SBT is a valid and reliable instrument. The SBT discriminated low, medium and high-risk groups, and predicts disability after three months.

Feasibility and long-term efficacy of a proactive health program in the treatment of chronic back pain: a randomized controlled trial

BACKGROUND

To facilitate access to evidence-based care for back pain, a German private medical insurance offered a health program proactively to their members. Feasibility and long-term efficacy of this approach were evaluated.

METHODS

Using Zelen's design, adult members of the health insurance with chronic back pain according to billing data were randomized to the intervention (IG) or the control group (CG). Participants allocated to the IG were invited to participate in the comprehensive health program comprising medical exercise therapy and life style coaching, and those allocated to the CG to a longitudinal back pain survey. Primary outcomes were back pain severity (Korff's Chronic Pain Grade Questionnaire) as well as health-related quality of life (SF-12) assessed by identical online questionnaires at baseline and 2-year follow-up in both study arms. In addition to analyses of covariance, a subgroup analysis explored the heterogeneity of treatment effects among different risks of back pain chronification (STarT Back Tool).

RESULTS

Out of 3462 persons selected, randomized and thereafter contacted, 552 agreed to participate. At the 24-month follow-up, data on 189 of 258 (73.3%) of the IG were available, in the CG on 255 of 294 (86.7%). Significant, small beneficial effects were seen in primary outcomes: Compared to the CG, the IG reported less disability (1.6 vs 2.0; p = 0.025; d = 0.24) and scored better at the SF-12 physical health scale (43.3 vs 41.0; p < 0.007; d = 0.26). No effect was seen in back pain intensity and in the SF-12 mental health scale. Persons with medium or high risk of back pain chronification at baseline responded better to the health program in all primary outcomes than the subgroup with low risk at baseline.

CONCLUSIONS

After 2 years, the proactive health program resulted in small positive long-term improvements. Using risk screening prior to inclusion in the health program might increase the percentage of participants deriving benefits from it.

TRIAL REGISTRATION

The trial was registered at the German Clinical Trials Register under DRKS00015463 retrospectively (dated 4 Sept 2018).

The Evolving Case Supporting Individualised Physiotherapy for Low Back Pain

Low-back pain (LBP) is one of the most burdensome health problems in the world. Guidelines recommend simple treatments such as advice that may result in suboptimal outcomes, particularly when applied to people with complex biopsychosocial barriers to recovery. Individualised physiotherapy has the potential of being more effective for people with LBP; however, there is limited evidence supporting this approach. A series of studies supporting the mechanisms underpinning and effectiveness of the Specific Treatment of Problems of the Spine (STOPS) approach to individualised physiotherapy have been published. The clinical and research implications of these findings are presented and discussed. Treatment based on the STOPS approach should also be considered as an approach to individualised physiotherapy in people with LBP.

The use of STarT back screening tool to predict functional disability outcomes in patients receiving physical therapy for low back pain

BACKGROUND CONTEXT

The STarT Back Screening Tool (SBST) categorizes risk of future disability in patients with low back pain (LBP). Previous studies evaluating the use of SBST in physical therapy (PT) populations do not reflect the ethnic and socioeconomic diversity occurring in clinical practice and lack statistical power to evaluate factors associated with outcomes within each SBST risk category.

PURPOSE

The purpose of this study is to further refine SBST risk categorization for predicting improvements in functional disability with attention toward patient level factors that might guide SBST use in routine outpatient physical therapy practice.

STUDY DESIGN/SETTING

This was a retrospective cohort study that took place within a large academic, tertiary-care health system.

PATIENT SAMPLE

The study cohort consisted of 1,169 patients with LBP who completed a course of outpatient physical therapy from June 1, 2014 to May 31, 2015 and who completed the patient-reported SBST and modified low back pain disability questionnaire (MDQ) questionnaires as part of standard of care.

OUTCOME MEASURES

Improvement in functional disability defined as decrease in 10 or more points in the MDQ.

METHODS

Multivariable logistic regression was performed to evaluate independent predictors of improvement after PT, which included SBST risk category, baseline MDQ, a two-way interaction term between SBST category and baseline MDQ, prior level of function (independent vs. required assistance), demographic characteristics, number of completed PT visits, and duration of PT episode of care. In exploratory analyses, additional two-way interaction terms between SBST category and the significant predictors were added to the regression model.

RESULTS

Mean age of patients in the study cohort was 55.1 years (SD 16.1); 657 (56.2%) were female, 117 (10.0%) were black race, 127 (10.9%) had Medicaid insurance, and 353 (30.2%) had previously received PT for back pain. In all, 35.8% (n=419) patients categorized as low risk SBST category, 40.7% (n=476) medium risk SBST category, and 23.4% (n=274) high risk SBST category. There was an interaction between baseline MDQ and SBST risk category and improvement with PT. For all three SBST categories, higher baseline MDQ was associated with higher probability of improvement, but the effect was less pronounced as SBST risk category increased. Additional factors independently associated with reduced odds of improvement after PT included black race (odds ratio [OR] 0.44, 95% confidence interval [CI] 0.28-0.72), Medicaid insurance (OR=0.58, 95% CI 0.36-0.95), and prior PT (OR=0.48, 95% CI 0.34-0.67). In exploratory analyses, there was a significant interaction between insurance type and SBST risk category in predicting functional improvement after PT. Patients with Medicare and Medicaid insurance had similar rates of improvement in low and high risk SBST categories but different rates of improvement in the medium risk categories.

CONCLUSIONS

The SBST tool predicts outcomes of PT in a cohort of patients receiving outpatient PT for LBP. The odds of improvement varied according to baseline disability and SBST risk status. Race, insurance type, and history of previous PT influenced prediction independent of SBST risk status. Incorporating these variables and the interaction between SBST and baseline disability in outcome models has the potential to refine prediction of outcomes after PT.

Prognostic ability of the German version of the STarT Back tool: analysis of 12-month follow-up data from a randomized controlled trial

BACKGROUND

Stratified care is an up-to-date treatment approach suggested for patients with back pain in several guidelines. A comprehensively studied stratification instrument is the STarT Back Tool (SBT). It was developed to stratify patients with back pain into three subgroups, according to their risk of persistent disabling symptoms. The primary aim was to analyse the disability differences in patients with back pain 12 months after inclusion according to the subgroups determined at baseline using the German version of the SBT (STarT-G). Moreover, the potential to improve prognosis for disability by adding further predictor variables, an analysis for differences in pain intensity according to the STarT-Classification, and discriminative ability were investigated.

METHODS

Data from the control group of a randomized controlled trial were analysed. Trial participants were members of a private medical insurance with a minimum age of 18 and indicated as having persistent back pain. Measurements were made for the risk of back pain chronification using the STarT-G, disability (as primary outcome) and back pain intensity with the Chronic Pain Grade Scale (CPGS), health-related quality of life with the SF-12, psychological distress with the Patient Health Questionnaire-4 (PHQ-4) and physical activity. Analysis of variance (ANOVA), multiple linear regression, and area under the curve (AUC) analysis were conducted.

RESULTS

The mean age of the 294 participants was 53.5 (SD 8.7) years, and 38% were female. The ANOVA for disability and pain showed significant differences (p < 0.01) among the risk groups at 12 months. Post hoc Tukey tests revealed significant differences among all three risk groups for every comparison for both outcomes. AUC for STarT-G's ability to discriminate reference standard 'cases' for chronic pain status at 12 months was 0.79. A prognostic model including the STarT-Classification, the variables global health, and disability at baseline explained 45% of the variance in disability at 12 months.

CONCLUSIONS

Disability differences in patients with back pain after a period of 12 months are in accordance with the subgroups determined using the STarT-G at baseline. Results should be confirmed in a study developed with the primary aim to investigate those differences.

Effect of Low Back Pain Risk-Stratification Strategy on Patient Outcomes and Care Processes: the MATCH Randomized Trial in Primary Care

BACKGROUND

The STarT Back strategy for categorizing and treating patients with low back pain (LBP) improved patients' function while reducing costs in England.

OBJECTIVE

This trial evaluated the effect of implementing an adaptation of this approach in a US setting.

DESIGN

The Matching Appropriate Treatments to Consumer Healthcare needs (MATCH) trial was a pragmatic cluster randomized trial with a pre-intervention baseline period. Six primary care clinics were pair randomized, three to training in the STarT Back strategy and three to serve as controls.

PARTICIPANTS

Adults receiving primary care for non-specific LBP were invited to provide data 2 weeks after their primary care visit and follow-up data 2 and 6 months (primary endpoint) later.

INTERVENTIONS

The STarT Back risk-stratification strategy matches treatments for LBP to physical and psychosocial obstacles to recovery using patient-reported data (the STarT Back Tool) to categorize patients' risk of persistent disabling pain. Primary care clinicians in the intervention clinics attended six didactic sessions to improve their understanding LBP management and received in-person training in the use of the tool that had been incorporated into the electronic health record (EHR). Physical therapists received 5 days of intensive training. Control clinics received no training.

MAIN MEASURES

Primary outcomes were back-related physical function and pain severity. Intervention effects were estimated by comparing mean changes in patient outcomes after 2 and 6 months between intervention and control clinics. Differences in change scores by trial arm and time period were estimated using linear mixed effect models. Secondary outcomes included healthcare utilization.

KEY RESULTS

Although clinicians used the tool for about half of their patients, they did not change the treatments they recommended. The intervention had no significant effect on patient outcomes or healthcare use.

CONCLUSIONS

A resource-intensive intervention to support stratified care for LBP in a US healthcare setting had no effect on patient outcomes or healthcare use.

TRIAL REGISTRATION

National Clinical Trial Number NCT02286141.