{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T00:56:40Z","timestamp":1789606600137,"version":"build-2803163510"},"reference-count":75,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,7,29]],"date-time":"2025-07-29T00:00:00Z","timestamp":1753747200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,7,29]],"date-time":"2025-07-29T00:00:00Z","timestamp":1753747200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Swiss Federal Institute of Technology Zurich"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Chronic low back pain (CLBP) is a prevalent condition significantly reducing quality of life. Lumbar steroid injections are a widely used conservative treatment option, but their effectiveness varies among patients. This study aimed to develop a predictive framework that integrates clinical variables and patient demographics to evaluate post-treatment pain satisfaction in CLBP patients undergoing lumbar injection therapy. We performed a retrospective analysis of 212 CLBP patients to evaluate the treatment satisfaction and pain intensity changes using the Numerical Rating Scale (NRS). A Random Forest model, validated through nested cross-validation, achieved an average precision of 0.865 in predicting treatment satisfaction. SHapley Additive exPlanations (SHAP) analysis revealed pain self-efficacy features, particularly coping mechanisms and household activities, as key outcome predictors of post-treatment pain satisfaction. Clinically significant pain reduction thresholds were identified at an absolute change of 2.09 and a relative change of 30 % on the NRS. Our findings reveal the biological and social factors influencing post-treatment pain in CLBP patients. The identified pain reduction thresholds and predictors may help clinicians to develop individualized management strategies, optimizing treatment outcomes and improving patient care. Future research should refine the predictive model by incorporating additional multimodal variables to better capture CLBP heterogeneity.<\/jats:p>","DOI":"10.1038\/s41598-025-10907-0","type":"journal-article","created":{"date-parts":[[2025,7,29]],"date-time":"2025-07-29T23:58:54Z","timestamp":1753833534000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A data-driven analysis of lumbar steroid injection satisfaction in patients with chronic low back pain"],"prefix":"10.1038","volume":"15","author":[{"given":"Maria","family":"Monzon","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iara","family":"De Schoenmacker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Cina","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R\u00e9ka","family":"Enz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Lanz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabio","family":"Galbusera","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine R.","family":"Jutzeler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zina-Mary","family":"Manjaly","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,29]]},"reference":[{"key":"10907_CR1","doi-asserted-by":"publisher","first-page":"e316","DOI":"10.1016\/S2665-9913(23)00098-X","volume":"5","author":"ML Ferreira","year":"2023","unstructured":"Ferreira, M. L. et al. Global, regional, and national burden of low back pain, 1990\u20132020, its attributable risk factors, and projections to 2050: A systematic analysis of the global burden of disease study 2021. Lancet Rheumatol. 5, e316\u2013e329. https:\/\/doi.org\/10.1016\/S2665-9913(23)00098-X (2023).","journal-title":"Lancet Rheumatol."},{"key":"10907_CR2","doi-asserted-by":"publisher","first-page":"167","DOI":"10.36076\/ppj.2000\/3\/167","volume":"3","author":"L Manchikanti","year":"2000","unstructured":"Manchikanti, L. Epidemiology of low back pain. Pain Phys. 3, 167\u2013192 (2000).","journal-title":"Pain Phys."},{"key":"10907_CR3","doi-asserted-by":"crossref","unstructured":"Meucci, R.\u00a0D., Fassa, A.\u00a0G. & Faria, N. M.\u00a0X. Prevalence of chronic low back pain: Systematic review. Rev. Saude Publ. 49 (2015).","DOI":"10.1590\/S0034-8910.2015049005874"},{"key":"10907_CR4","doi-asserted-by":"crossref","unstructured":"Eloy, O., Patricia, B.-M.\u00a0L., Gustavo, R.-C.\u00a0D. & Rafael, G.-A. Effectiveness of three treatment strategies on quality of life for patients with chronic low back pain: A multidisciplinary approach as key to success. J. Musculoskelet. Disord. Treat. (2019).","DOI":"10.23937\/2572-3243.1510064"},{"key":"10907_CR5","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1001\/archinternmed.2008.543","volume":"169","author":"JK Freburger","year":"2009","unstructured":"Freburger, J. K. et al. The rising prevalence of chronic low back pain. Arch. Intern. Med. 169, 251\u2013258 (2009).","journal-title":"Arch. Intern. Med."},{"key":"10907_CR6","doi-asserted-by":"publisher","unstructured":"Kent, P.\u00a0M. & Keating, J.\u00a0L. The epidemiology of low back pain in primary care. Chiropract. Osteopathy 13. https:\/\/doi.org\/10.1186\/1746-1340-13-13 (2005).","DOI":"10.1186\/1746-1340-13-13"},{"key":"10907_CR7","doi-asserted-by":"publisher","first-page":"299","DOI":"10.21037\/atm.2020.02.175","volume":"8","author":"A Wu","year":"2020","unstructured":"Wu, A. et al. Global low back pain prevalence and years lived with disability from 1990 to 2017: Estimates from the global burden of disease study 2017. Ann. Transl. Med. 8, 299 (2020).","journal-title":"Ann. Transl. Med."},{"key":"10907_CR8","doi-asserted-by":"publisher","first-page":"1430","DOI":"10.1136\/bmj.332.7555.1430","volume":"332","author":"BW Koes","year":"2006","unstructured":"Koes, B. W., Van Tulder, M. W. & Thomas, S. Diagnosis and treatment of low back pain. BMJ 332, 1430\u20131434. https:\/\/doi.org\/10.1136\/bmj.332.7555.1430 (2006).","journal-title":"BMJ"},{"key":"10907_CR9","doi-asserted-by":"publisher","first-page":"1483","DOI":"10.2147\/JPR.S306280","volume":"14","author":"W Li","year":"2021","unstructured":"Li, W. et al. Peripheral and central pathological mechanisms of chronic low back pain: A narrative review. J. Pain Res. 14, 1483\u20131494 (2021).","journal-title":"J. Pain Res."},{"key":"10907_CR10","doi-asserted-by":"crossref","unstructured":"Kahere, M. & Ginindza, T. The prevalence and psychosocial risk factors of chronic low back pain in KwaZulu-Natal. Afr. J. Prim. Health Care Fam. Med. 14, e1\u2013e8 (2022).","DOI":"10.4102\/phcfm.v14i1.3134"},{"issue":"4","key":"10907_CR11","doi-asserted-by":"publisher","first-page":"625","DOI":"10.3233\/BMR-160685","volume":"29","author":"I Sanzarello","year":"2016","unstructured":"Sanzarello, I. et al. Central sensitization in chronic low back pain: A narrative review. J. Back Musculoskelet. Rehabil. 29(4), 625\u2013633 (2016).","journal-title":"J. Back Musculoskelet. Rehabil."},{"key":"10907_CR12","doi-asserted-by":"publisher","first-page":"S131","DOI":"10.1097\/BRS.0b013e31822f178f","volume":"36","author":"AP White","year":"2011","unstructured":"White, A. P., Arnold, P. M., Norvell, D. C., Ecker, E. & Fehlings, M. G. Pharmacologic management of chronic low back pain. Spine 36, S131\u2013S143. https:\/\/doi.org\/10.1097\/BRS.0b013e31822f178f (2011).","journal-title":"Spine"},{"key":"10907_CR13","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/s11916-019-0757-1","volume":"23","author":"I Urits","year":"2019","unstructured":"Urits, I. et al. Low back pain, a comprehensive review: Pathophysiology, diagnosis, and treatment. Curr. Pain Headache Rep. 23, 23. https:\/\/doi.org\/10.1007\/s11916-019-0757-1 (2019).","journal-title":"Curr. Pain Headache Rep."},{"key":"10907_CR14","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1002\/14651858.CD001824.pub3","volume":"34","author":"JB Staal","year":"2008","unstructured":"Staal, J. B., de Bie, R., de Vet, H. C., Hildebrandt, J. & Nelemans, P. Injection therapy for subacute and chronic low-back pain. Cochrane Database Syst. Rev. 34, 49\u201359. https:\/\/doi.org\/10.1002\/14651858.CD001824.pub3 (2008).","journal-title":"Cochrane Database Syst. Rev."},{"key":"10907_CR15","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1186\/1471-2253-12-26","volume":"12","author":"DK Whynes","year":"2012","unstructured":"Whynes, D. K., McCahon, R. A., Ravenscroft, A. & Hardman, J. Cost effectiveness of epidural steroid injections to manage chronic lower back pain. BMC Anesthesiol. 12, 26 (2012).","journal-title":"BMC Anesthesiol."},{"key":"10907_CR16","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1097\/j.pain.0000000000002674","volume":"164","author":"M M\u00fcller-Schrader","year":"2022","unstructured":"M\u00fcller-Schrader, M. et al. Individual treatment expectations predict clinical outcome after lumbar injections against low back pain. Pain 164, 132\u2013141. https:\/\/doi.org\/10.1097\/j.pain.0000000000002674 (2022).","journal-title":"Pain"},{"key":"10907_CR17","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/0304-3959(95)00124-7","volume":"63","author":"BW Koes","year":"1995","unstructured":"Koes, B. W., Scholten, R. J., Mens, J. M. & Bouter, L. M. Efficacy of epidural steroid injections for low-back pain and sciatica: A systematic review of randomized clinical trials. Pain 63, 279\u2013288. https:\/\/doi.org\/10.1016\/0304-3959(95)00124-7 (1995).","journal-title":"Pain"},{"key":"10907_CR18","doi-asserted-by":"publisher","first-page":"2880","DOI":"10.1097\/00007632-199612150-00019","volume":"21","author":"JM Borkan","year":"1996","unstructured":"Borkan, J. M. & Cherkin, D. C. An agenda for primary care research on low back pain. Spine 21, 2880\u20132884. https:\/\/doi.org\/10.1097\/00007632-199612150-00019 (1996).","journal-title":"Spine"},{"key":"10907_CR19","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1016\/J.BERH.2013.10.005","volume":"27","author":"NE Foster","year":"2013","unstructured":"Foster, N. E., Hill, J. C., O\u2019Sullivan, P. & Hancock, M. Stratified models of care. Best Pract. Res. Clin. Rheumatol. 27, 649\u2013661. https:\/\/doi.org\/10.1016\/J.BERH.2013.10.005 (2013).","journal-title":"Best Pract. Res. Clin. Rheumatol."},{"issue":"3","key":"10907_CR20","doi-asserted-by":"publisher","first-page":"156","DOI":"10.5312\/wjo.v7.i3.156","volume":"7","author":"A Abbott","year":"2016","unstructured":"Abbott, A. Evidence base and future research directions in the management of low back pain. World J. Orthoped. 7(3), 156\u201361 (2016).","journal-title":"World J. Orthoped."},{"key":"10907_CR21","doi-asserted-by":"crossref","unstructured":"Huijnen, I.\u00a0P., Rusu, A.\u00a0C., Scholich, S., Meloto, C.\u00a0B. & Diatchenko, L. Subgrouping of low back pain patients for targeting treatments: Evidence from genetic, psychological, and activity-related behavioral approaches. Clin. J. Pain 31 (2015).","DOI":"10.1097\/AJP.0000000000000100"},{"issue":"2","key":"10907_CR22","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1148\/radiol.2382041930","volume":"238","author":"SG Pneumaticos","year":"2006","unstructured":"Pneumaticos, S. G., Chatziioannou, S. N., Hipp, J. A., Moore, W. H. & Esses, S. I. Low back pain: Prediction of short-term outcome of facet joint injection with bone scintigraphy. Radiology 238(2), 693\u20138 (2006).","journal-title":"Radiology"},{"key":"10907_CR23","doi-asserted-by":"crossref","unstructured":"Pauli, J., Starkweather, A.\u00a0R. & Robins, J. L.\u00a0W. Screening tools to predict the development of chronic low back pain: An integrative review of the literature. Pain Med. (2018).","DOI":"10.1093\/pm\/pny178"},{"key":"10907_CR24","doi-asserted-by":"publisher","first-page":"588","DOI":"10.2519\/jospt.2017.0607","volume":"47","author":"J Boissoneault","year":"2017","unstructured":"Boissoneault, J., Mundt, J., Robinson, M. & George, S. Z. Predicting low back pain outcomes: Suggestions for future directions. J. Orthopaed. Sports Phys. Ther. 47, 588\u2013592. https:\/\/doi.org\/10.2519\/jospt.2017.0607 (2017) (PMID: 28859589).","journal-title":"J. Orthopaed. Sports Phys. Ther."},{"key":"10907_CR25","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1007\/s40122-021-00249-w","volume":"10","author":"G Varrassi","year":"2021","unstructured":"Varrassi, G., Moretti, B., Pace, M. C., Evangelista, P. & Iolascon, G. Common clinical practice for low back pain treatment: A modified Delphi study. Pain Ther. 10, 589\u2013604. https:\/\/doi.org\/10.1007\/s40122-021-00249-w (2021).","journal-title":"Pain Ther."},{"key":"10907_CR26","doi-asserted-by":"publisher","first-page":"523","DOI":"10.3109\/17453674.2015.1036696","volume":"86","author":"RC Clement","year":"2015","unstructured":"Clement, R. C. et al. A proposed set of metrics for standardized outcome reporting in the management of low back pain. Acta Orthop. 86, 523\u2013533 (2015).","journal-title":"Acta Orthop."},{"key":"10907_CR27","doi-asserted-by":"publisher","first-page":"S17","DOI":"10.1007\/s00586-005-1044-x","volume":"15","author":"M Haefeli","year":"2006","unstructured":"Haefeli, M. & Elfering, A. Pain assessment. Eur. Spine J. 15, S17\u2013S24. https:\/\/doi.org\/10.1007\/s00586-005-1044-x (2006).","journal-title":"Eur. Spine J."},{"key":"10907_CR28","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1186\/s12916-016-0775-3","volume":"15","author":"MF Olsen","year":"2017","unstructured":"Olsen, M. F. et al. Pain relief that matters to patients: Systematic review of empirical studies assessing the minimum clinically important difference in acute pain. BMC Med. 15, 35 (2017).","journal-title":"BMC Med."},{"key":"10907_CR29","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1016\/S0895-4356(03)00044-1","volume":"56","author":"RD Crosby","year":"2003","unstructured":"Crosby, R. D., Kolotkin, R. L. & Williams, G. Defining clinically meaningful change in health-related quality of life. J. Clin. Epidemiol. 56, 395\u2013407. https:\/\/doi.org\/10.1016\/S0895-4356(03)00044-1 (2003).","journal-title":"J. Clin. Epidemiol."},{"key":"10907_CR30","doi-asserted-by":"crossref","unstructured":"Mannion, A.\u00a0F. et al. The quality of spine surgery from the patient\u2019s perspective: Part 2. Minimal clinically important difference for improvement and deterioration as measured with the core outcome measures index. Eur. Spine J. 18, 374\u2013379 (2009).","DOI":"10.1007\/s00586-009-0931-y"},{"key":"10907_CR31","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1007\/s00586-002-0464-0","volume":"12","author":"O H\u00e4gg","year":"2003","unstructured":"H\u00e4gg, O., Fritzell, P. & Nordwall, A. The clinical importance of changes in outcome scores after treatment for chronic low back pain. Eur. Spine J. 12, 12\u201320. https:\/\/doi.org\/10.1007\/s00586-002-0464-0 (2003).","journal-title":"Eur. Spine J."},{"key":"10907_CR32","doi-asserted-by":"publisher","first-page":"4415","DOI":"10.1007\/s00586-024-08537-7","volume":"33","author":"A Cina","year":"2024","unstructured":"Cina, A. et al. Methodological considerations in calculating the minimal clinically important change score for the core outcome measures index (comi): insights from a large single-centre spine surgery registry. Eur. Spine J. 33, 4415\u20134425. https:\/\/doi.org\/10.1007\/s00586-024-08537-7 (2024).","journal-title":"Eur. Spine J."},{"key":"10907_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0229228","volume":"15","author":"H Suzuki","year":"2020","unstructured":"Suzuki, H. et al. Clinically significant changes in pain along the pain intensity numerical rating scale in patients with chronic low back pain. PLOS ONE 15, 1\u201316. https:\/\/doi.org\/10.1371\/journal.pone.0229228 (2020).","journal-title":"PLOS ONE"},{"key":"10907_CR34","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1111\/j.2044-8287.2012.02071.x","volume":"18","author":"R Horne","year":"2013","unstructured":"Horne, R. et al. The perceived sensitivity to medicines (PSM) scale: An evaluation of validity and reliability. Br. J. Health Psychol. 18, 18\u201330. https:\/\/doi.org\/10.1111\/j.2044-8287.2012.02071.x (2013).","journal-title":"Br. J. Health Psychol."},{"key":"10907_CR35","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1055\/s-2007-970791","volume":"58","author":"M Neumann","year":"2008","unstructured":"Neumann, M. et al. Psychometrische evaluation der Deutschen version des Messinstruments ,consultation and relational empathy (CARE) am Beispiel von Krebspatienten. Psychother. Psychosom. Med. Psychol. 58, 5\u201315. https:\/\/doi.org\/10.1055\/s-2007-970791 (2008).","journal-title":"Psychother. Psychosom. Med. Psychol."},{"key":"10907_CR36","doi-asserted-by":"publisher","unstructured":"Mannion, A. F. et al. The core outcome measures index in clinical practice. The quality of spine surgery from the patient\u2019s perspective. Part 1. Eur. Spine J. 18, 367\u2013373. https:\/\/doi.org\/10.1007\/s00586-009-0942-8 (2009).","DOI":"10.1007\/s00586-009-0942-8"},{"key":"10907_CR37","doi-asserted-by":"publisher","unstructured":"Chmielewski, B. & Wilski, M. Psychometric properties of chosen scales evaluating disability in low back pain\u2014Narrative review. Healthcare 12. https:\/\/doi.org\/10.3390\/healthcare12111139 (2024).","DOI":"10.3390\/healthcare12111139"},{"key":"10907_CR38","doi-asserted-by":"publisher","first-page":"2003","DOI":"10.1097\/00007632-199809150-00018","volume":"23","author":"RA Deyo","year":"1998","unstructured":"Deyo, R. A. et al. Outcome measures for low back pain research: A proposal for standardized use. Spine 23, 2003\u20132013 (1998).","journal-title":"Spine"},{"key":"10907_CR39","doi-asserted-by":"crossref","unstructured":"Miekisiak, G. et al. Cross-cultural adaptation and validation of the polish version of the core outcome measures index for low back pain. Eur. Spine J. 22, 995\u20131001 (2013).","DOI":"10.1007\/s00586-012-2607-2"},{"key":"10907_CR40","doi-asserted-by":"publisher","first-page":"2097","DOI":"10.1007\/s00586-014-3325-8","volume":"23","author":"S Genevay","year":"2014","unstructured":"Genevay, S. et al. Validity of the French version of the core outcome measures index for low back pain patients: A prospective cohort study. Eur. Spine J. 23, 2097\u20132104 (2014).","journal-title":"Eur. Spine J."},{"key":"10907_CR41","doi-asserted-by":"publisher","first-page":"2821","DOI":"10.1007\/s00586-013-2761-1","volume":"22","author":"J Qiao","year":"2013","unstructured":"Qiao, J. et al. Validation of the simplified Chinese version of the core outcome measures index (COMI). Eur. Spine J. 22, 2821\u20132826 (2013).","journal-title":"Eur. Spine J."},{"key":"10907_CR42","doi-asserted-by":"publisher","first-page":"2638","DOI":"10.1007\/S00586-015-4292-4\/TABLES\/7","volume":"25","author":"AF Mannion","year":"2016","unstructured":"Mannion, A. F. et al. The Core Outcome Measures Index (COMI) is a responsive instrument for assessing the outcome of treatment for adult spinal deformity. Eur. Spine J. 25, 2638\u20132648. https:\/\/doi.org\/10.1007\/S00586-015-4292-4\/TABLES\/7 (2016).","journal-title":"Eur. Spine J."},{"key":"10907_CR43","doi-asserted-by":"publisher","first-page":"3115","DOI":"10.1097\/00007632-200012150-00006","volume":"25","author":"M Roland","year":"2000","unstructured":"Roland, M. & Fairbank, J. The Roland-Morris Disability Questionnaire and the Oswestry Disability Questionnaire. Spine 25, 3115\u20133124. https:\/\/doi.org\/10.1097\/00007632-200012150-00006 (2000).","journal-title":"Spine"},{"key":"10907_CR44","doi-asserted-by":"crossref","unstructured":"Ware, J.\u00a0E. & Sherbourne, C.\u00a0D. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med. Care 30, 473\u201383 (1992).","DOI":"10.1097\/00005650-199206000-00002"},{"key":"10907_CR45","doi-asserted-by":"crossref","unstructured":"Davidson, M., Keating, J.\u00a0L. & Eyres, S. A low back-specific version of the sf-36 physical functioning scale. Spine 29 (2004).","DOI":"10.1097\/01.BRS.0000103346.38557.73"},{"key":"10907_CR46","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/0304-3959(91)90095-F","volume":"44","author":"MP Jensen","year":"1991","unstructured":"Jensen, M. P., Turner, J. A. & Romano, J. M. Self-efficacy and outcome expectancies: Relationship to chronic pain coping strategies and adjustment. Pain 44, 263\u2013269. https:\/\/doi.org\/10.1016\/0304-3959(91)90095-F (1991).","journal-title":"Pain"},{"key":"10907_CR47","unstructured":"Ali, M. Pycaret: An open source, low-code machine learning library in python (2024). PyCaret version 3.3.2."},{"key":"10907_CR48","doi-asserted-by":"publisher","first-page":"e0224365","DOI":"10.1371\/journal.pone.0224365","volume":"14","author":"A Vabalas","year":"2019","unstructured":"Vabalas, A., Gowen, E., Poliakoff, E. & Casson, A. J. Machine learning algorithm validation with a limited sample size. PLOS ONE 14, e0224365. https:\/\/doi.org\/10.1371\/journal.pone.0224365 (2019).","journal-title":"PLOS ONE"},{"key":"10907_CR49","first-page":"2079","volume":"11","author":"GC Cawley","year":"2010","unstructured":"Cawley, G. C. & Talbot, N. L. On over-fitting in model selection and subsequent selection bias in performance evaluation. J. Mach. Learn. Res. 11, 2079\u20132107 (2010).","journal-title":"J. Mach. Learn. Res."},{"key":"10907_CR50","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1186\/cc3045","volume":"9","author":"V Bewick","year":"2005","unstructured":"Bewick, V., Cheek, L. & Ball, J. Statistics review 14: Logistic regression. Crit. Care 9, 112\u2013118 (2005).","journal-title":"Crit. Care"},{"key":"10907_CR51","doi-asserted-by":"publisher","unstructured":"Taunk, K., De, S., Verma, S. & Swetapadma, A. A brief review of nearest neighbor algorithm for learning and classification. In 2019 International Conference on Intelligent Computing and Control Systems (ICCS). https:\/\/doi.org\/10.1109\/iccs45141.2019.9065747 (IEEE, 2019).","DOI":"10.1109\/iccs45141.2019.9065747"},{"key":"10907_CR52","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/5254.708428","volume":"13","author":"M Hearst","year":"1998","unstructured":"Hearst, M., Dumais, S., Osuna, E., Platt, J. & Scholkopf, B. Support vector machines. IEEE Intell. Syst. Appl. 13, 18\u201328. https:\/\/doi.org\/10.1109\/5254.708428 (1998).","journal-title":"IEEE Intell. Syst. Appl."},{"key":"10907_CR53","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1080\/00401706.1970.10488634","volume":"12","author":"AE Hoerl","year":"1970","unstructured":"Hoerl, A. E. & Kennard, R. W. Ridge regression: Biased estimation for nonorthogonal problems. Technometrics 12, 55\u201367 (1970).","journal-title":"Technometrics"},{"key":"10907_CR54","volume-title":"Na\u00efve Bayes, 1\u20132","author":"GI Webb","year":"2016","unstructured":"Webb, G. I. Na\u00efve Bayes, 1\u20132 (Springer, 2016)."},{"key":"10907_CR55","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.\u00a0H. & Friedman, J.\u00a0H. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Vol.\u00a02 (Springer, 2009).","DOI":"10.1007\/978-0-387-84858-7"},{"key":"10907_CR56","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1109\/21.97458","volume":"21","author":"S Safavian","year":"1991","unstructured":"Safavian, S. & Landgrebe, D. A survey of decision tree classifier methodology. IEEE Trans. Syst. Man Cybern. 21, 660\u2013674. https:\/\/doi.org\/10.1109\/21.97458 (1991).","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"10907_CR57","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","volume":"63","author":"P Geurts","year":"2006","unstructured":"Geurts, P., Ernst, D. & Wehenkel, L. Extremely randomized trees. Mach. Learn. 63, 3\u201342. https:\/\/doi.org\/10.1007\/s10994-006-6226-1 (2006).","journal-title":"Mach. Learn."},{"key":"10907_CR58","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/a:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L. Random forest. Mach. Learn. 45, 5\u201332. https:\/\/doi.org\/10.1023\/a:1010933404324 (2001).","journal-title":"Mach. Learn."},{"key":"10907_CR59","volume-title":"A decision-theoretic generalization of on-line learning and an application to boosting, 23\u201337","author":"Y Freund","year":"1995","unstructured":"Freund, Y. & Schapire, R. E. A decision-theoretic generalization of on-line learning and an application to boosting, 23\u201337 (Springer, 1995)."},{"key":"10907_CR60","doi-asserted-by":"publisher","unstructured":"Friedman, J.\u00a0H. Greedy function approximation: A gradient boosting machine.  Ann. Stat. 29. https:\/\/doi.org\/10.1214\/aos\/1013203451 (2001).","DOI":"10.1214\/aos\/1013203451"},{"key":"10907_CR61","doi-asserted-by":"publisher","unstructured":"Chen, T. & Guestrin, C. Xgboost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Vol.\u00a011. KDD \u201916. 785\u2013794. https:\/\/doi.org\/10.1145\/2939672.2939785 (ACM, 2016).","DOI":"10.1145\/2939672.2939785"},{"key":"10907_CR62","unstructured":"Ke, G. et al. Lightgbm: A highly efficient gradient boosting decision tree. In Guyon, I. et al. (eds.) Advances in Neural Information Processing Systems. Vol.\u00a030 (Curran Associates, Inc., 2017)."},{"key":"10907_CR63","doi-asserted-by":"publisher","unstructured":"Chicco, D. & Jurman, G. The advantages of the Matthews correlation coefficient (mcc) over f1 score and accuracy in binary classification evaluation. BMC Genomics 21, https:\/\/doi.org\/10.1186\/s12864-019-6413-7 (2020).","DOI":"10.1186\/s12864-019-6413-7"},{"key":"10907_CR64","unstructured":"Lundberg, S.\u00a0M. & Lee, S.-I. A unified approach to interpreting model predictions. In Guyon, I. et al. (eds.) Advances in Neural Information Processing Systems. Vol.\u00a030 (Curran Associates, Inc., 2017)."},{"key":"10907_CR65","first-page":"627","volume":"4","author":"K Hajian-Tilaki","year":"2013","unstructured":"Hajian-Tilaki, K. Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian J. Intern. Med. 4, 627\u2013635 (2013).","journal-title":"Caspian J. Intern. Med."},{"key":"10907_CR66","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1111\/j.1651-2227.2006.00178.x","volume":"96","author":"AK Akobeng","year":"2007","unstructured":"Akobeng, A. K. Understanding diagnostic tests 3: Receiver operating characteristic curves. Acta Paediatr. 96, 644\u2013647. https:\/\/doi.org\/10.1111\/j.1651-2227.2006.00178.x (2007).","journal-title":"Acta Paediatr."},{"key":"10907_CR67","doi-asserted-by":"publisher","first-page":"3762651","DOI":"10.1155\/2017\/3762651","volume":"2017","author":"I Unal","year":"2017","unstructured":"Unal, I. Defining an optimal cut-point value in roc analysis: An alternative approach. Comput. Math. Methods Med. 2017, 3762651. https:\/\/doi.org\/10.1155\/2017\/3762651 (2017).","journal-title":"Comput. Math. Methods Med."},{"key":"10907_CR68","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1002\/bimj.200410135","volume":"47","author":"R Fluss","year":"2005","unstructured":"Fluss, R., Faraggi, D. & Reiser, B. Estimation of the Youden index and its associated cutoff point. Biometric. J. 47, 458\u2013472. https:\/\/doi.org\/10.1002\/bimj.200410135 (2005).","journal-title":"Biometric. J."},{"key":"10907_CR69","doi-asserted-by":"publisher","unstructured":"Li, J. Area under the roc curve has the most consistent evaluation for binary classification, https:\/\/doi.org\/10.1371\/journal.pone.0316019 (2024). arXiv: 2408.10193.","DOI":"10.1371\/journal.pone.0316019"},{"key":"10907_CR70","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.patrec.2020.03.030","volume":"136","author":"Q Zhu","year":"2020","unstructured":"Zhu, Q. On the performance of Matthews correlation coefficient (mcc) for imbalanced dataset. Pattern Recognit. Lett. 136, 71\u201380. https:\/\/doi.org\/10.1016\/j.patrec.2020.03.030 (2020).","journal-title":"Pattern Recognit. Lett."},{"key":"10907_CR71","unstructured":"Carriero, A. et al. The harms of class imbalance corrections for machine learning based prediction models: A simulation study (2024). arXiv: 2404.19494."},{"key":"10907_CR72","doi-asserted-by":"crossref","unstructured":"Costa, L. D. C.\u00a0M., Maher, C.\u00a0G., McAuley, J.\u00a0H., Hancock, M.\u00a0J. & Smeets, R. J. E.\u00a0M. Self-efficacy is more important than fear of movement in mediating the relationship between pain and disability in chronic low back pain. Eur. J. Pain 15, 213\u2013219 (2011).","DOI":"10.1016\/j.ejpain.2010.06.014"},{"key":"10907_CR73","doi-asserted-by":"publisher","unstructured":"Zhang, Y.-H. et al. Demographic and clinical characteristics associated with failure of physical therapy in chronic low back pain: a secondary analysis from a randomized controlled trial. Eur. J. Phys. Rehabil. Med. 60. https:\/\/doi.org\/10.23736\/s1973-9087.24.08033-x (2024).","DOI":"10.23736\/s1973-9087.24.08033-x"},{"key":"10907_CR74","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1016\/j.jmpt.2017.09.001","volume":"40","author":"R Adnan","year":"2017","unstructured":"Adnan, R. et al. Determining predictive outcome factors for a multimodal treatment program in low back pain patients: A retrospective cohort study. J. Manipul. Physiol. Ther. 40, 659\u2013667. https:\/\/doi.org\/10.1016\/j.jmpt.2017.09.001 (2017).","journal-title":"J. Manipul. Physiol. Ther."},{"key":"10907_CR75","doi-asserted-by":"publisher","unstructured":"Nicholas K, D., Emily J, G., Alexis M, V., Sergey S, T. & Andrew C, H. Prognostic factors for disability and pain outcomes in patients with axial low back pain undergoing a multidisciplinary spine treatment program. Int. J. Physiatry 6. https:\/\/doi.org\/10.23937\/2572-4215.1510019 (2020).","DOI":"10.23937\/2572-4215.1510019"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-10907-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-10907-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-10907-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T08:46:59Z","timestamp":1757321219000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-10907-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,29]]},"references-count":75,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["10907"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-10907-0","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2025.04.10.25325570","asserted-by":"object"}]},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,29]]},"assertion":[{"value":"10 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"C.R.J. serves as a scientific consultant to Abbvie and Mitsubishi Takeda; however, this role had no influence on the design, conduct, or reporting of this study. All other authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"27734"}}