鍼治療の効果を予測するためのSTarT Back Screening Toolの有用性 —腰部疼痛強度visual analog scaleの変化に着目したリスク分類の評価
STarT Back Screening Tool（以下，SBST）は，腰痛の慢性・難治化リスクを簡便に評価するための確立された臨床評価ツールである．本研究では，鍼治療を受けている腰痛患者において，SBSTの有用性について検討した．2019年から2022年までに筑波技術大学保健科学部附属東西医学統合医療センター鍼灸外来を受診した腰痛患者71人を，腰痛の原因を問わず対象とした．調査項目はSBST，腰部疼痛強度visual analogue scale（以下，VAS）とし，基本属性と鍼治療内容の情報はカルテより収集した．治療開始から4週間後のVASの値を臨床転帰の指標とし，反復測定分散分析と階...
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| Published in | 日本温泉気候物理医学会雑誌 Vol. 87; no. 2; pp. 56 - 65 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
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一般社団法人 日本温泉気候物理医学会
31.05.2024
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| Abstract | STarT Back Screening Tool（以下，SBST）は，腰痛の慢性・難治化リスクを簡便に評価するための確立された臨床評価ツールである．本研究では，鍼治療を受けている腰痛患者において，SBSTの有用性について検討した．2019年から2022年までに筑波技術大学保健科学部附属東西医学統合医療センター鍼灸外来を受診した腰痛患者71人を，腰痛の原因を問わず対象とした．調査項目はSBST，腰部疼痛強度visual analogue scale（以下，VAS）とし，基本属性と鍼治療内容の情報はカルテより収集した．治療開始から4週間後のVASの値を臨床転帰の指標とし，反復測定分散分析と階層的重回帰分析により解析した．初診時のSBSTによる分類は，low risk群36人，medium risk群30人，high risk群15人であった．反復測定分散分析では，4週間の前後（P<0.01），初診時の3群分類（P<0.01），および交互作用（P<0.05）に統計学的有意差が認められた．4週間後のVAS値は，high risk群の値が他の2群と比較し有意に高かった（いずれもP<0.01）．4週間後のVASを従属変数とした階層的重回帰分析では，SBSTとの交互作用項，属性項目および治療に関する項目を調整したいずれのモデルにおいてもSBSTの回帰係数には統計学的有意差が認められた．また，回帰式の単純傾斜分析では，下肢症状を有する場合は有さない場合と比較し，初診時high risk群の4週後のVASの値が，他の2群に比べ高くなる傾向がより明確であった．以上から，SBSTは鍼治療における臨床転記の予測に関して，簡便かつ有用なツールとなり得ることが示唆された． |
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| AbstractList | STarT Back Screening Tool（以下，SBST）は，腰痛の慢性・難治化リスクを簡便に評価するための確立された臨床評価ツールである．本研究では，鍼治療を受けている腰痛患者において，SBSTの有用性について検討した．2019年から2022年までに筑波技術大学保健科学部附属東西医学統合医療センター鍼灸外来を受診した腰痛患者71人を，腰痛の原因を問わず対象とした．調査項目はSBST，腰部疼痛強度visual analogue scale（以下，VAS）とし，基本属性と鍼治療内容の情報はカルテより収集した．治療開始から4週間後のVASの値を臨床転帰の指標とし，反復測定分散分析と階層的重回帰分析により解析した．初診時のSBSTによる分類は，low risk群36人，medium risk群30人，high risk群15人であった．反復測定分散分析では，4週間の前後（P<0.01），初診時の3群分類（P<0.01），および交互作用（P<0.05）に統計学的有意差が認められた．4週間後のVAS値は，high risk群の値が他の2群と比較し有意に高かった（いずれもP<0.01）．4週間後のVASを従属変数とした階層的重回帰分析では，SBSTとの交互作用項，属性項目および治療に関する項目を調整したいずれのモデルにおいてもSBSTの回帰係数には統計学的有意差が認められた．また，回帰式の単純傾斜分析では，下肢症状を有する場合は有さない場合と比較し，初診時high risk群の4週後のVASの値が，他の2群に比べ高くなる傾向がより明確であった．以上から，SBSTは鍼治療における臨床転記の予測に関して，簡便かつ有用なツールとなり得ることが示唆された． |
| Author | 松田, えりか 近藤, 宏 |
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| References | 14) Dionne CE, Dunn KM, Croft PR, et al: A consensus approach toward the standardization of back pain definitions for use in prevalence studies. Spine (Phila Pa 1976) 2008; 33(1): 95-103. 24) Altman DG: In relation between several variables. In: Practical Statistics for Medical Research, Chapman & Hall, London, 1999; p325-364. 21) Vickers AJ, Cronin AM, Maschino AC, et al: Acupuncture for chronic pain: individual patient data meta-analysis. Arch Intern Med 2012; 172(19): 1444-1453. 29) Kalauokalani D, Cherkin DC, Sherman KJ, et al: Lessons from a trial of acupuncture and massage for low back pain: patient expectations and treatment effects. Spine 2001; 26(13): 1418-1424. 3) Sherman KJ, Cherkin DC, Ichikawa L, et al: Characteristics of patients with chronic back pain who benefit from acupuncture. BMC Musculoskelet Disord 2009; 21(10): 114. 15) Matsudaira K, Kikuchi N, Kawaguchi M, et al: Nihongoban STarT (Subgroupin for Targeted Treatment) Back sukuri-ningu tu-ru no kaihatsu: gengoteki datousei wo tanposhita nihongoban no sakusei [Development of the Japanese version of the STarT Back Tool: creation of a translation version ensuring linguistic validity]. J Musculoskelet Pain Res 2013; 5(1): 11-19 (in Japanese). 5) Hill JC, Dunn KM, Lewis M, et al: A primary care back pain screening tool: identifying patient subgroups for initial treatment. Arthritis Rheum 2008; 59(5): 632-641. 27) Cherkin DC, Deyo RA, Sherman KJ, et al: Characteristics of visits to licensed acupuncturists, chiropractors, massage therapists, and naturopathic physicians. J Am Board Fam Pract 2002; 15(6): 463-472. 2) Cherkin DC, Eisenberg D, Sherman KJ, et al: Randomized trial comparing traditional Chinese medical acupuncture, therapeutic massage, and self-care education for chronic low back pain. Arch Intern Med 2001; 161(8): 1081-1088. 16) Whisman M, McClelland GH: Designing, testing, and interpreting interactions and moderator effects in family research. J Fam Psychol 2005; 19(1): 111-120. 30) Nilay S, Yavuz V, Gul D, et al: Comparison among pain, depression, and quality of life in cases with failed back surgery syndrome and non-specific chronic back pain. J Phys Ther Sci 2017; 29(5): 891-895. 11) Katzan IL, Thompson NR, George SZ, et al: The use of STarT back screening tool to predict functional disability outcomes in patients receiving physical therapy for low back pain. Spine J 2019; 19(4): 645-654. 7) Storm L, Rousing R, Andersen MO, et al: Usefulness of the STarT Back Screening Tool to predict pain problems after lumbar spine surgery. Dan Med J 2018; 65(12): A5517. 17) Tsuda S, Inagaki H, Sugiyama M, et al: Living alone, cognitive function, and well-being of Japanese older men and women: a cross-sectional study. Health Soc Care Community 2023; Article ID 7183821, 8 pages (Early Online Publication). 12) Matsuda E, Kondo H, Kinoshita H, et al: Effects of psychosocial factors on acupuncture in patients with chronic low back pain: exploratory analysis and logistic regression analysis based on the results of immediate effect. J Jpn Soc Balneol Climatol Phys Med 2020; 83(3): 122-130 (in Japanese). 23) Dawson JF: Moderation in management research: What, why, when, and how. J Bus Psychol 2014; 29(1): 1-19. 4) Witt CM, Jena S, Selim D, et al: Pragmatic randomized trial evaluating the clinical and economic effectiveness of acupuncture for chronic low back pain. Am J Epidemiol 2006; 164(5): 487-496. 22) Bishop FL, Yardley L, Cooper C, et al: Predicting adherence to acupuncture appointments for low back pain: a prospective observational study. BMC Complement Altern Med 2017; 17(1): 5. 28) Linde K, Witt CM, Streng A, et al: The impact of patient expectations on outcomes in four randomized controlled trials of acupuncture in patients with chronic pain. Pain 2007; 128(3): 264-271. 8) Suri P, Delaney K, Rundell SD, et al: Predictive validity of the STarT Back Tool for risk of persistent disabling back pain in a U.S primary care setting. Arch Phys Med Rehabil 2018; 99(8): 1533-1539. 9) Beneciuk JM, Bishop MD, Fritz JM, et al: The STarT Back Screening Tool and individual psychological measures: evaluation of prognostic capabilities for low back pain clinical outcomes in outpatient physical therapy settings. Phys Ther 2013; 93(3): 321-333. 26) Raykov T, Katerina M, Marcoulides M: Evaluation of variance inflation factors in regression models using Latent variable modeling methods. Educ Psychol Meas 2018; 79(1): 874-882. 20) Sherman KJ, Cherkin DC, Ichikawa L, et al: Treatment expectations and preferences as predictors of outcome of acupuncture for chronic back pain. Spine 2010; 35(15): 1471-1477. 25) Kline RB: Introduction to pass analysis. In: Principles and Practice of Structural Equation Modeling, 2nd ed, Kenny DA (ed), Guildford, New York, 2005; p93-243. 6) Matsudaira K, Oka H, Kikuchi N, et al: Psychometric properties of the Japanese version of the STarT Back Tool in patients with low back pain. PLoS ONE 2016; 11(3): e0152019. 13) Plunkett A, Beltran T, Haley C, et al: Acupuncture for the treatment of chronic pain in the military population: factors associated with treatment outcomes. The Clin J Pain 2017; 33(10): 939-943. 1) Lim SS, Vos T, Flaxman AD, et al: A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380(9859): 2224-2260. 19) Witt CM, Schützler L, Lüdtke R, et al: Patient characteristics and variation in treatment outcomes: chich patients benefit most from acupuncture for chronic pain? Clin J Pain 2011; 27(6): 550-555. 10) Beneciuk JM, Fritz JM, George SZ, et al: The STarT Back Screening Tool for prediction of 6-month clinical outcomes relevance of change patterns in outpatient physical therapy settings. J Orthop Sports Phys Ther 2014; 44(9): 656-664. 18) Vickers AJ, Vertosic EA, Lewith G, et al: Acupuncture for chronic pain: update of an individual patient data meta-analysis. Rev J Pain 2018; 19(5): 455-474. |
| References_xml | – reference: 8) Suri P, Delaney K, Rundell SD, et al: Predictive validity of the STarT Back Tool for risk of persistent disabling back pain in a U.S primary care setting. Arch Phys Med Rehabil 2018; 99(8): 1533-1539. – reference: 19) Witt CM, Schützler L, Lüdtke R, et al: Patient characteristics and variation in treatment outcomes: chich patients benefit most from acupuncture for chronic pain? Clin J Pain 2011; 27(6): 550-555. – reference: 5) Hill JC, Dunn KM, Lewis M, et al: A primary care back pain screening tool: identifying patient subgroups for initial treatment. Arthritis Rheum 2008; 59(5): 632-641. – reference: 27) Cherkin DC, Deyo RA, Sherman KJ, et al: Characteristics of visits to licensed acupuncturists, chiropractors, massage therapists, and naturopathic physicians. J Am Board Fam Pract 2002; 15(6): 463-472. – reference: 12) Matsuda E, Kondo H, Kinoshita H, et al: Effects of psychosocial factors on acupuncture in patients with chronic low back pain: exploratory analysis and logistic regression analysis based on the results of immediate effect. J Jpn Soc Balneol Climatol Phys Med 2020; 83(3): 122-130 (in Japanese). – reference: 1) Lim SS, Vos T, Flaxman AD, et al: A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380(9859): 2224-2260. – reference: 15) Matsudaira K, Kikuchi N, Kawaguchi M, et al: Nihongoban STarT (Subgroupin for Targeted Treatment) Back sukuri-ningu tu-ru no kaihatsu: gengoteki datousei wo tanposhita nihongoban no sakusei [Development of the Japanese version of the STarT Back Tool: creation of a translation version ensuring linguistic validity]. J Musculoskelet Pain Res 2013; 5(1): 11-19 (in Japanese). – reference: 10) Beneciuk JM, Fritz JM, George SZ, et al: The STarT Back Screening Tool for prediction of 6-month clinical outcomes relevance of change patterns in outpatient physical therapy settings. J Orthop Sports Phys Ther 2014; 44(9): 656-664. – reference: 17) Tsuda S, Inagaki H, Sugiyama M, et al: Living alone, cognitive function, and well-being of Japanese older men and women: a cross-sectional study. Health Soc Care Community 2023; Article ID 7183821, 8 pages (Early Online Publication). – reference: 2) Cherkin DC, Eisenberg D, Sherman KJ, et al: Randomized trial comparing traditional Chinese medical acupuncture, therapeutic massage, and self-care education for chronic low back pain. Arch Intern Med 2001; 161(8): 1081-1088. – reference: 3) Sherman KJ, Cherkin DC, Ichikawa L, et al: Characteristics of patients with chronic back pain who benefit from acupuncture. BMC Musculoskelet Disord 2009; 21(10): 114. – reference: 16) Whisman M, McClelland GH: Designing, testing, and interpreting interactions and moderator effects in family research. J Fam Psychol 2005; 19(1): 111-120. – reference: 29) Kalauokalani D, Cherkin DC, Sherman KJ, et al: Lessons from a trial of acupuncture and massage for low back pain: patient expectations and treatment effects. Spine 2001; 26(13): 1418-1424. – reference: 18) Vickers AJ, Vertosic EA, Lewith G, et al: Acupuncture for chronic pain: update of an individual patient data meta-analysis. Rev J Pain 2018; 19(5): 455-474. – reference: 14) Dionne CE, Dunn KM, Croft PR, et al: A consensus approach toward the standardization of back pain definitions for use in prevalence studies. Spine (Phila Pa 1976) 2008; 33(1): 95-103. – reference: 9) Beneciuk JM, Bishop MD, Fritz JM, et al: The STarT Back Screening Tool and individual psychological measures: evaluation of prognostic capabilities for low back pain clinical outcomes in outpatient physical therapy settings. Phys Ther 2013; 93(3): 321-333. – reference: 23) Dawson JF: Moderation in management research: What, why, when, and how. J Bus Psychol 2014; 29(1): 1-19. – reference: 24) Altman DG: In relation between several variables. In: Practical Statistics for Medical Research, Chapman & Hall, London, 1999; p325-364. – reference: 6) Matsudaira K, Oka H, Kikuchi N, et al: Psychometric properties of the Japanese version of the STarT Back Tool in patients with low back pain. PLoS ONE 2016; 11(3): e0152019. – reference: 4) Witt CM, Jena S, Selim D, et al: Pragmatic randomized trial evaluating the clinical and economic effectiveness of acupuncture for chronic low back pain. Am J Epidemiol 2006; 164(5): 487-496. – reference: 26) Raykov T, Katerina M, Marcoulides M: Evaluation of variance inflation factors in regression models using Latent variable modeling methods. Educ Psychol Meas 2018; 79(1): 874-882. – reference: 22) Bishop FL, Yardley L, Cooper C, et al: Predicting adherence to acupuncture appointments for low back pain: a prospective observational study. BMC Complement Altern Med 2017; 17(1): 5. – reference: 21) Vickers AJ, Cronin AM, Maschino AC, et al: Acupuncture for chronic pain: individual patient data meta-analysis. Arch Intern Med 2012; 172(19): 1444-1453. – reference: 11) Katzan IL, Thompson NR, George SZ, et al: The use of STarT back screening tool to predict functional disability outcomes in patients receiving physical therapy for low back pain. Spine J 2019; 19(4): 645-654. – reference: 28) Linde K, Witt CM, Streng A, et al: The impact of patient expectations on outcomes in four randomized controlled trials of acupuncture in patients with chronic pain. Pain 2007; 128(3): 264-271. – reference: 30) Nilay S, Yavuz V, Gul D, et al: Comparison among pain, depression, and quality of life in cases with failed back surgery syndrome and non-specific chronic back pain. J Phys Ther Sci 2017; 29(5): 891-895. – reference: 20) Sherman KJ, Cherkin DC, Ichikawa L, et al: Treatment expectations and preferences as predictors of outcome of acupuncture for chronic back pain. Spine 2010; 35(15): 1471-1477. – reference: 13) Plunkett A, Beltran T, Haley C, et al: Acupuncture for the treatment of chronic pain in the military population: factors associated with treatment outcomes. The Clin J Pain 2017; 33(10): 939-943. – reference: 7) Storm L, Rousing R, Andersen MO, et al: Usefulness of the STarT Back Screening Tool to predict pain problems after lumbar spine surgery. Dan Med J 2018; 65(12): A5517. – reference: 25) Kline RB: Introduction to pass analysis. In: Principles and Practice of Structural Equation Modeling, 2nd ed, Kenny DA (ed), Guildford, New York, 2005; p93-243. |
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| SubjectTerms | STarT Back Screening Tool 予後予測 腰痛 鍼治療 階層的重回帰分析 |
| Title | 鍼治療の効果を予測するためのSTarT Back Screening Toolの有用性 —腰部疼痛強度visual analog scaleの変化に着目したリスク分類の評価 |
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