The relationship between the Keele STarT back screening tool, the short form of central sensitivity inventory and health-related quality of life in patients with low back pain

ABSTRACT

Introduction

It has been reported that the scores of the Keele STarT Back Screening Tool (SBST) and the short form of Central Sensitization Inventory (CSI-9) are associated with Health-Related Quality of Life (HRQoL) in patients with low back pain (LBP). However, it is unclear which screening tool is more associated with HRQoL in patients with LBP.

Objective

To identify which SBST and CSI-9 are more related to HRQoL and investigate the association between SBST and CSI-9 scores.

Study design

Cross-sectional study.

Method

A multiple regression analysis was conducted to examine the factors associated with the HRQoL using age, pain intensity, disability, SBST score, and CSI-9 score as independent variables. Spearman’s rank correlation coefficient was also conducted to determine the association between SBST and CSI-9 score.

Results

Multiple regression analysis revealed that the Oswestry Disability Index (ODI) score (p < 0.01, β = −0.62, VIF = 1.70) and SBST score (p < 0.01, β = −0.32, VIF = 1.86) were significant associated variables. A significant association was found between SBST and CSI-9 scores (p < 0.01, ρ = 0.47).

Conclusion

The results showed that in patients with LBP the association of HRQoL with SBST was more substantial than with CSI-9.

Introduction

Low back pain (LBP) is a common problem over the world, and it tends to recur in 44%–78% of patients, and is chronic in 5%–10% of patients, thereby detracting from the quality of life (QoL) [1]. In a cross-sectional telephone survey of 17,249 community-dwelling individuals, the HRQoL of subjects with chronic LBP(CLBP) was reported to be significantly lower than the HRQoL of subjects without CLBP [2]. In addition, a longitudinal study of 1,110 community residents reported that baseline pain intensity and the degree of LBP-related disability were significantly negatively correlated with HRQoL at six months follow-up [3].

Therefore, the assessment of QoL in those with LBP is essential for treatment planning and goals of care and for evaluating changes in pain and outcomes of treatment [4]. The HRQoL in patients with CLBP has been described as a multifaceted concept affected by various factors, including physical and psychological status, social relationships, and functional capacity [5]. For instance, factors associated with HRQoL in patients with LBP included age, pain intensity, and disability [3,6,7]. Furthermore, psychosocial factors such as anxiety, fear of movement, depression and relationships with others have been reported as factors contributing to the reduction of HRQoL [8–10]. In addition, the degree of Central Sensitization-related symptoms (CSSs) has been reported to be associated with HRQoL in patients with LBP [11,12]. CSSs are physical and emotional health-related symptoms that are associated with central sensitization (CS) [13]. CS is defined as ‘increased responsiveness of nociceptive neurons in the central nervous system to their normal or subthreshold afferent input’ [14]. In patients with LBP, the presence of CSSs has been associated with pain intensity and functional disability of LBP [15]. The degree of CSSs was more severe in subjects with CLBP than in those without CLBP, and CSSs have been implicated in the pathogenesis of CLBP [11].

Recently, screening tools have been developed that include assessing psychosocial factors and CSSs. The Keele STarT Back Screening Tool (SBST) is a screening form for patients with LBP, comprising physical and psychosocial items. It classifies the patients into three groups based on the risk of chronicity [16]. The SBST total score and psychosocial sub-score have been reported to negatively correlate with HRQoL in patients with LBP [17]. Interventions based on this classification model can improve patient outcomes and longitudinal HRQoL [18,19]. The short form of the Central Sensitivity Inventory (CSI-9) is another questionnaire for screening CSSs [20]. In a prospective study of patients with LBP, it was reported that patients with higher baseline CSI scores had significantly higher pain-related functional disability at three months than those with lower scores, suggesting that CSI scores may have the ability to predict disability [21]. In addition, it was also found that CSI scores improved in patients with chronic spinal pain disorder through an interdisciplinary biopsychosocial treatment approach, suggesting that CSI scores may be useful as an outcome measure and a screener in patients with chronic spinal pain disorder [22]. Furthermore, in spinal fusion patients, preoperative CSI scores have been reported to have a significant negative correlation with the severity of postoperative functional disability caused by pain and HRQoL [23]. In several other cross-sectional studies, CSI scores have been reported to have significant negative associations with HRQoL in patients with CLBP [12] and musculoskeletal pain [21,24].

It has been previously described that SBST and CSI-9 were associated with HRQoL in LBP, respectively [11,12,17–19,21,24]. However, it is unclear which screening tool is more associated with HRQoL in patients with LBP. Furthermore, the direct relationship between the two screening tools is not clear. The purpose of this study was to investigate which of the two tools was more related to factors associated with HRQoL in LBP patients and to examine the relationship between SBST and CSI-9. We hypothesized that both screening tool scores are associated with HRQoL and a significant association between the two screening tools.

Methods

Study design

This cross-sectional study was conducted from August 2019 to January 2021, at a private orthopedic clinic in Mitaka city, Japan. Physical therapists evaluated the participants at the first physical therapy session as part of the treatment, and the patient information was not blinded. The number of patients at the institution was about 150 per day. Four physical therapists evaluated patients who had been diagnosed with LBP and prescribed physical therapy by their doctors. The study was conducted in compliance with the Declaration of Helsinki, and we obtained written informed consent from all participants.The study was approved by the research ethic committee of the Faculty of Health Sciences, Kyorin University (No.2019–51).

Participants

LBP was defined as ‘pain that occurs posteriorly in the region between the lower rib margin and the proximal thighs’ [25]. We classified LBP persisting for less than 6 weeks as acute LBP, LBP persisting between 6 and 12 weeks as sub-acute LBP, and LBP persisting for more than 12 weeks as CLBP [26]. We defined recurrent LBP as two or more episodes of LBP lasting more than 24 hours in the past year, with a pain-free period of at least 30 days between each episode” in reference to a previous study [27].

Patients were eligible for inclusion if they met all of the following inclusion criteria: (1) diagnosed from a doctor in any stage (acute, sub-acute, chronic and recurrent) of LBP with or without leg pain between August 2019 to January 2021; and (2) males and females over 18 years old. Exclusion criteria were: (1)known or suspected serious pathology (nerve root compromise, cauda equina syndromes, infection, fracture, and tumor); and (2) Japanese speaker to allow response to the questionnaires and communication with the physical therapists; and (3) previous spinal surgery or scheduled for surgery within 6 months; and (4) pregnancy; and (5) neurological disease; and (6) dementia.

For recruitment, patients who met the inclusion criteria were verbally offered the opportunity to participate in the study by their physical therapist.

Measures

Demographics

Demographic characteristics, including gender, age, and body mass index (BMI) were evaluated. BMI was calculated by the researcher (H.N) height and weight based on self-reported.

Pain intensity

Patients rated the maximum pain they felt during activities of daily living within a week. Pain intensity was assessed by using the Numerical Pain Rating Scale (NPRS), which is an 11-point numeric scale [28], with 0 being no pain at all and 10 being the worst pain that could be imagined [29]. In this study, we assessed the maximum pain intensity in the past week, referring to previous studies [30–33].

Disability

The Japanese version of the Oswestry Disability Index (ODI) [34] was used to evaluate the disability within a week caused by LBP. The Japanese version of the ODI was developed based on the English version of the ODI version 2.0 [34]. The ODI assesses how pain influences daily life and is composed of the following 10 items [35]: 1-pain intensity, 2-personal care, 3-lifting, 4-walking, 5-sitting, 6-standing, 7-sleeping, 8-sex life (if applicable), 9-social life, and 10-traveling. Each item is scored between 0 and 5, and the total score is calculated as a percentage; a high score represents severe disability.

The Keele STarT Back Screening Tool (SBST)

The SBST can classify patients with LBP into one of three risk of chronicity groups [16]. The SBST comprises four items related to physical factors and five distress subscale items (fear, anxiety, catastrophizing, depression, and bothersomeness). Items 1 to 8 have a two-selection option; ‘disagree’ or agree”. Only Item 9 has a five-point Likert scale; ‘Not at all’, ‘Slightly’, ‘Moderately’, ‘Very much’ and ‘Extremely’. The last two responses are scored as one point, and the others are zero. Patients who achieve a total score of 0–3 are classified into the low-risk group; those with a total score of ≥4 and a subscale score of <3 are categorized into the medium-risk group; those with a subscale score of ≥3 are classified into the high-risk subgroup. The SBST was translated into the Japanese version, whose validity and constantly has been reported [17]. The total score of SBST is positively associated with psychosocial problems [17,36]. We used the total score of the Japanese version of the SBST in this study.

The short form of the Central Sensitization Inventory (CSI-9)

We used the Japanese version of the short form of the Central Sensitization Inventory (CSI-9) to assess CSSs [20]. The CSI-9 includes 9 items, comprising the following areas: emotional distress (1 item); urological (1 item), general (1 item), muscular (2 items), and headache/jaw (1 item) symptoms; sleep disturbance (2 items); and not loading (1 item) [11]. Each item is scored on a five-point scale; total scores of 20 or more suggest that patients have CSSs related to functional disabilities and psychosocial impairments [37]. For patients with musculoskeletal, acceptable sensitivity and specificity of the usage of CSI-9 have been reported [37]. We used the CSI-9 because the short version is often used in clinical situations to reduce the burden on the patients [20,37]. The cutoff score of the CSI-9 was 20 points [37], and in this study, those with a CSI-9 score of 20 points or higher were considered CSSs positive.

Health-Related Quality of Life (HRQoL)

The European QoL questionnaire five dimensions five levels (EQ-5D-5L) is a questionnaire, which has been translated into Japanese, used to assess the HRQoL [38,39]. It consists of the following five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension has five grades that are used to create a single index value; values range from 0 (dead) to 1 (full health).

Statistical analysis

First, we conducted a normal distribution curve to examine the participants’ demographics and analyzed it using the Kolmogorov-Smirnov test. Spearman’s rank correlation coefficient was used to examine the association between EQ-5D-5L and age, NPRS, ODI score, SBST score, and CSI-9 score. In addition, we performed a multiple regression analysis to find the factors associated with the EQ-5D-5L. In the multiple regression analysis, the EQ-5D-5L was assigned to the dependent variable and age, NPRS, ODI score, SBST score, and CSI-9 score were set as the independent variables. Multiple regression analysis was only tested in models with age, NRPS score, ODI score, the total score of SBST, and CSI-9 as dependent variables using the forced imputation method. Also, we calculated Spearman’s rank correlation coefficient to analyze the association between the total score of SBST and CSI-9. Another co-researcher (H.M) performed the statistical analysis with the blinding. We analyzed it by setting the significance level at 0.05 and by using BellCurve for Excel (Social Survey Research Information Co. Ltd.)

Results

Participants characterization

A total of 52 patients (male = 20) participated in this study. Table 1 shows the characteristics of patients and each measurement item. In this study, 17.3% (9/52) of the participants were positive for CSS. In the SBST risk group, 25 (48.0%) were assigned to the low-risk group, 21 (40.0%) to the medium-risk group, and 6 (12.0%) to the high-risk group.

Table 1.

Participants Characteristics (n = 52).

	n (%) or mean	SD or IQR	min-max
Gender male female	20 (38.4) 32 (61.6)
Age, mean <45 years 45–64 ≧65 years	53.46 (16.08) 19 (36.5) 17 (32.7) 16 (30.8)	16.08	22–84
BMI	23.69	4.83	-
Duration of LBP acute (<6 weeks) sub-acute (6–12 weeks) chronic (≧12 weeks)	17 (34.0) 9 (16.0) 26 (50.0)	-	-
Recurrent LBP	18 (34.6)	-	-
Having refereed leg pain	3 (5.7)	-	-
Taking pain medication	27 (51.9)	-	-
NPRS*	6	4–8	1–10
SBST total score	3.67	2.40	0–9
SBST group Low risk Medium risk High risk	25 (48.0) 21 (40.0) 6 (12.0)	-	-
ODI (%)	26.84	14.36	2–62
CSI-9	12.5	8–17	2–28
CSI-9≧20	9 (17.3)	-	-
EQ-5D-5L	0.66	0.13	0.37–1

*NPRS was assessed as maximum pain intensity in the last week.

n, total number; BMI, body mass index; LBP, low back pain; NPRS, numerical pain rating scale; SBST, Keel STarT Back Screening Tool; ODI, Oswestry disability index; CSI-9, short form of central sensitization inventory; EQ-5D-5L, European Quality of Life questionnaire five dimensions five levels; SD, standard deviation; IQR, interquartile range.

Factors associated with EQ-5D-5L

Spearman’s rank correlation coefficient showed that EQ-5D-5L was significantly negatively associated with ODI (ρ = −0.77), SBST (ρ = −0.68), CSI-9 (ρ = −0.40) and NPRS (ρ = −0.31) (all p < 0.01). Table 2 represents the results of multiple regression analysis. It revealed that the ODI score (p < 0.01, β = −0.62, VIF = 1.70) and the SBST score (p < 0.01, β = −0.32, VIF = 1.86) were significant independent variables. The result of the analysis of variance in the multiple regression analysis was significant (p < 0.01). The degree of freedom-adjusted coefficient of determination was 0.66. The Coefficient of Determination (R²) was 0.70. In the post hoc test, the power (1-β) in the correlation analysis was 0.96, and the effect size in the multiple regression analysis was 1.64, with a power of 1.0.

Table 2.

Result of multiple regression analysis.

	SC	F	β	t value	p value	VIF	95% CI for β
Age	0.12	1.82	0.1176	1.35	0.18	0.20	−0.00	0.00
NPRS*	−0.01	0.03	−0.0150	−0.17	0.86	−0.03	−0.01	0.01
SBST	−0.32	8.26	−0.3181	−2.87	*0.01	−0.40	−0.03	−0.00
ODI	−0.62	34.59	−0.6233	−5.88	*0.00	−0.66	−0.01	−0.00
CSI-9	−0.01	0.00	−0.0064	−0.07	0.95	−0.01	−0.00	0.00

*NPRS was assessed as maximum pain intensity in the last week. The Coefficient of Determination (R²) = 0.70.

SC, Standardized Coefficients; VIF, variance inflation factor; 95% CI for β, 95% Confidence Interval for β; NPRS, numerical pain rating scale; SBST, Keel STarT Back Screening Tool; ODI, Oswestry disability index; CSI-9, short form of central sensitization inventory.

Association between SBST and CSI-9

A significant association was found between the SBST and CSI-9 scores (p < 0.01, ρ = 0.47) (Figure 1).

Figure 1.

Result of correlation analysis between the score of SBST and CSI-9.

Discussion

We investigated whether SBST or CSI-9 was more associated with HRQoL in patients with LBP and the relationship between the SBST and CSI-9 score. We hypothesized that CSI-9 and SBST associate factors of the HRQOL measured by EQ-5D-5L and were associated with each other. As a result of our study, we found that the SBST score and ODI were independently and significantly associated with the HRQoL, although the CSI-9 score was not. We also found a positive association between the SBST and CSI-9 scores.

The total score of SBST was associated with a better EQ-5D-5L. Both the total and psychosocial SBST scores were negatively associated with the HRQoL in the previous study [17]. The SBST has been considered a validated measure for recognizing patients with a poor long-term HRQoL in a population with LBP [18,19]. In addition, the total score of SBST was positively associated with psychosocial factors such as Fear-avoidance belief, Catastrophizing, depression, and anxiety [17,36]. The results of the multiple regression analysis of this study were similar to those of previous studies. Therefore, we believe that the total SBST score was extracted as a significant dependent variable of HRQoL. In contrast, it was not a significant dependent variable, although CSI-9 scores had a significant negative association with HRQoL. Also, the positive rate of CSSs in this study was 17%. Previous studies in patients with LBP have reported CSSs positivity rates of 13.0% [40] and 14.1% [11]. The CSSs positive rate in the current study participants was comparable to previous studies. In addition, previous studies have indicated a negative association between HRQoL and CSI scores in musculoskeletal pain patients, including those with LBP [11,12,20,37]. Although the results of multiple regression analysis showed that CSI-9 scores were less associated with HRQoL than disability and total SBST scores, based on the results of this study and previous studies, it is necessary to focus on multifaceted factors such as the risk of chronicity, CSSs, and psychosocial factors to assess HRQoL in LBP patients.

We also found a positive association between the SBST and CSI-9 scores. This was the first study to examine the relationship between the score of SBST and CSI or CSI-9. Previous studies have reported that the SBST score was associated with psychosocial problems [16,17,36]. On the other hand, some studies reported that there was an association between CSI and some psychosocial factors [17,18,21,36,41]. Another systematic review revealed that CSI includes psychological properties [42]. As described above, both SBST and CSI have a relationship with psychosocial factors, which might explain the association found between them in this study.

Limitations

There are several limitations in this study. First, we recruited subjects from only one medical institution, which may have caused selection bias. Therefore, we did not set an upper limit on the age of the participants to include subjects of a wide age range. As a result, the mean age of the participant was 53.46 ± 16.08 years, which is consistent with previous studies on patients with LBP [12,21,34]. Furthermore, previous systematic reviews have shown that the prevalence of LBP is more significant in females than in males [43,44]. The present study also showed a similar trend (females: 61.6%). Therefore, the basic demographics of the participants in this study can be said to be similar to those of previous studies. In light of this, the influence of bias on the research results is considered small. Additionally, this study surveyed patients who received physical therapy, and therefore, the clinical significance of this study is practical when used by physical therapists in actual clinical situations.

Secondly, since this is a cross-sectional study, the long-term association of ODI and SBST scores on patients’ HRQoL are unknown, and the causal relationship has not been verified. Thus, it is necessary to examine whether the HRQoL of patients with LBP changes with alterations in ODI and SBST scores in the long term. As a result of multiple regression analysis, ODI and SBST were regarded as factors associating with HRQoL. Although the standard regression coefficient of SBST was −0.32, indicating that the effect of changes in the SBST score on HRQoL was limited; the degree of the Coefficient of Determination (R²) was 0.70, showing that the prediction accuracy of the regression equation was high. Besides that, the number of cases was sufficient for the power test. The association between SBST and CSI and their association with HRQoL in patients with LBP has not been reported so far, and the actual situation remains unclear. Based on the results of this study, long-term validation with an increase in the number of cases is recommended in the future.

Finally, in this study, patients with acute LBP and patients with CLBP were examined together. Unlike acute pain, the pathogenesis of chronic pain is thought to be a combination of psychological factors, such as depression and anxiety, sleep disturbance, and activity limitation, in addition to the pain itself [45–48]. Differences in the pathophysiology at different stages of the disease may affect the results of this study, and it is necessary to examine each stage of the disease in the future.

Conclusion

We investigated the extent of the relationship between SBST, CSI-9 and HRQoL of LBP patients and the relationship between these two screening tools. This study showed that in patients with LBP the association of HRQoL with SBST was more substantial than with CSI-9. We also found an association between SBST and CSI-9 although the association was weak. Since this was a cross-sectional study with a small effect, it may be useful to use SBST, ODI or CSI-9, respectively, at this stage in clinical practice, although we suggest that these three scores were somehow related with HRQoL. On the other hand, however, improvement in the score of SBST may impact the improvement of HRQoL. Therefore, future studies may need to investigate how changes in SBST and CSI-9 scores affect HRQoL.

Biographies

Hiraku Nagahori, PT, MSc is a clinical researcher working at Mitaka Clinic in Japan. His clinical research focuses on therapeutic exercise and manual therapy for musculoskeletal disorders.

Takahiro Miki, PT, MSc is a clinical researcher working at Sapporo Maruyama Orthopedic Hospital. He has a Master's degree in Health Science from Hokkaido University. His research field is the management of musculoskeletal diseases based on biopsychosocial models.

Hiroshi Momma, PT, Ph.D is a researcher in the Department of Physical Therapy at Kyorin University. He has a wide range of research, including post-return rehabilitation of astronauts, motor imagery and mental practices, and professional education using active learning.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Funding Statement

The author(s) reported there is no funding associated with the work featured in this article.

Ethics approval

the study was approved by the research ethic committee of the Faculty of Health Sciences, Kyorin University (No.2019-51).

Data availability statement

The data that support the findings of this study are available from the corresponding author up reasonable request.

Disclosure statement

No potential conflict of interest was reported by the author(s).