There is a growing need to identify patient pre-treatment characteristics that could predict adherence and outcome following specific interventions.
OBJECTIVE:
To identify predictors of adherence and outcome to outpatient multimodal rehabilitation in chronic low back pain (CLBP).
METHODS:
A total of 273 CLBP patients participated in an exercise-based rehabilitation program. Patients who completed 70% of the treatment course were classified as adherent. Patients showing a post-treatment reduction of 30% in Oswestry Disability Index (ODI) and Visual Analogue Scale (VAS) back pain intensity scores were assigned to the favorable outcome group.
RESULTS:
Multivariate logistic regression revealed that higher age, higher ability to perform low-load activities, and higher degrees of kinesiophobia increased the odds to complete the rehabilitation program. By contrast, lower levels of education and back pain unrelated to poor posture increased the odds for non-adherence. Furthermore, a favorable outcome was predicted in case the cause for LBP was known, shorter symptom duration, no pain in the lower legs, no difficulties falling asleep, and short-term work absenteeism.
CONCLUSIONS:
Assessment and consideration of patient pre-treatment characteristics is of great importance as they may enable therapists to identify patients with a good prognosis or at risk for non-responding to outpatient multimodal rehabilitation.
AiraksinenOBroxJICedraschiCHildebrandtJKlaber-MoffettJKovacsF, et al. Chapter 4. European guidelines for the management of chronic nonspecific low back pain. European spine journal: official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society.2006; 15(Suppl 2): S192-300.
2.
VosTFlaxmanADNaghaviMLozanoRMichaudCEzzatiM, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet (London, England).2012; 380(9859): 2163-96.
3.
PincusTBurtonAKVogelSFieldAP. A systematic review of psychological factors as predictors of chronicity/disability in prospective cohorts of low back pain. Spine (Phila Pa 1976).2002; 27(5): E109-20.
4.
PerrotS. [Factors in the chronic progression of common low back pain]. La Revue du praticien.2000; 50(16): 1770-3.
5.
VavrekDHaasMNeradilekMBPolissarN. Prediction of pain outcomes in a randomized controlled trial of dose-response of spinal manipulation for the care of chronic low back pain. BMC Musculoskeletal Disorders.2015; 16: 205.
6.
HicksGEFritzJMDelittoAMcGillSM. Preliminary development of a clinical prediction rule for determining which patients with low back pain will respond to a stabilization exercise program. Archives of Physical Medicine and Rehabilitation.2005; 86(9): 1753-62.
7.
HaskinsRRivettDAOsmotherlyPG. Clinical prediction rules in the physiotherapy management of low back pain: a systematic review. Manual Therapy.2012; 17(1): 9-21.
8.
HaskinsROsmotherlyPGRivettDA. Validation and impact analysis of prognostic clinical prediction rules for low back pain is needed: a systematic review. Journal of Clinical Epidemiology.2015; 68(7): 821-32.
9.
TurkDCRudyTE. Neglected topics in the treatment of chronic pain patients–relapse, noncompliance, and adherence enhancement. Pain.1991; 44(1): 5-28.
10.
ThompsonEBroadbentJBertinoMDStaigerPK. Do Pain-related Beliefs Influence Treatment adherence? A Systematic Review. The Clinical Journal of Pain.2015.
11.
van MiddelkoopMRubinsteinSMKuijpersTVerhagenAPOsteloRKoesBW, et al. A systematic review on the effectiveness of physical and rehabilitation interventions for chronic non-specific low back pain. European spine journal: official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society.2011; 20(1): 19-39.
12.
PeekALStevensML. Different forms of exercise for chronic low back pain (PEDro synthesis). British Journal of Sports Medicine.2016; 50(3): 188.
13.
HestbaekLLeboeuf-YdeCMannicheC. Low back pain: what is the long-term course? A review of studies of general patient populations. European spine journal: official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society.2003; 12(2): 149-65.
14.
BergstromCJensenIHagbergJBuschHBergstromG. Effectiveness of different interventions using a psychosocial subgroup assignment in chronic neck and back pain patients: a 10-year follow-up. Disability and Rehabilitation.2012; 34(2): 110-8.
15.
GustavssonCBergstromJDenisonEvon KochL. Predictive factors for disability outcome at twenty weeks and two years following a pain self-management group intervention in patients with persistent neck pain in primary health care. Journal of Rehabilitation Medicine.2013; 45(2): 170-6.
16.
HebertJJKoppenhaverSLWalkerBF. Subgrouping patients with low back pain: a treatment-based approach to classification. Sports Health.2011; 3(6): 534-42.
17.
HeneweerHvan WoudenbergNJvan GenderenFVanheesLWittinkH. Measuring psychosocial variables in patients with (sub) acute low back pain complaints, at risk for chronicity: a validation study of the Acute Low Back Pain Screening Questionnaire-Dutch Language Version. Spine.2010; 35(4): 447-52.
18.
OsteloRWde VetHC. Clinically important outcomes in low back pain. Best Practice & Research Clinical Rheumatology.2005; 19(4): 593-607.
19.
ChapmanJRNorvellDCHermsmeyerJTBransfordRJDeVineJMcGirtMJ, et al. Evaluating common outcomes for measuring treatment success for chronic low back pain. Spine.2011; 36(21 Suppl): S54-68.
20.
FairbankJCPynsentPB. The Oswestry Disability Index. Spine.2000; 25(22): 2940-52; discussion 52.
21.
FairbankJCCouperJDaviesJBO’BrienJP. The Oswestry low back pain disability questionnaire. Physiotherapy.1980; 66(8): 271-3.
22.
SullivanMJLBishopSRPivikJ. The Pain Catastrophizing Scale: Development and validation. Psychological Assessment.1995; 7(4): 524-32.
23.
Van DammeSCrombezGBijttebierPGoubertLVan HoudenhoveB. A confirmatory factor analysis of the Pain Catastrophizing Scale: invariant factor structure across clinical and non-clinical populations. Pain.2002; 96(3): 319-24.
24.
RoelofsJGoubertLPetersMLVlaeyenJWCrombezG. The Tampa Scale for Kinesiophobia: further examination of psychometric properties in patients with chronic low back pain and fibromyalgia. European Journal of Pain (London, England).2004; 8(5): 495-502.
25.
VlaeyenJWKole-SnijdersAMBoerenRGvan EekH. Fear of movement/(re)injury in chronic low back pain and its relation to behavioral performance. Pain.1995; 62(3): 363-72.
26.
ZigmondASSnaithRP. The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica.1983; 67(6): 361-70.
27.
BeckATWardCHMendelsonMMockJErbaughJ. An inventory for measuring depression. Archives of General Psychiatry.1961; 4: 561-71.
28.
ShaferAB. Meta-analysis of the factor structures of four depression questionnaires: Beck, CES-D, Hamilton, and Zung. Journal of Clinical Psychology.2006; 62(1): 123-46.
29.
Von KorffMJensenMPKarolyP. Assessing global pain severity by self-report in clinical and health services research. Spine.2000; 25(24): 3140-51.
30.
De PauwRKregelJDe BlaiserCVan AkeleyenJLoggheTDanneelsL, et al. Identifying prognostic factors predicting outcome in patients with chronic neck pain after multimodal treatment: A retrospective study. Man Ther.2015; 20(4): 592-7.
31.
Medina-MirapeixFEscolar-ReinaPGascon-CanovasJJMontilla-HerradorJJimeno-SerranoFJ, refauthor . Predictive factors of adherence to frequency and duration components in home exercise programs for neck and low back pain: an observational study. BMC Musculoskeletal Disorders.2009; 10: 155.
32.
OsteloRWDeyoRAStratfordPWaddellGCroftPVon KorffM, et al. Interpreting change scores for pain and functional status in low back pain: towards international consensus regarding minimal important change. Spine.2008; 33(1): 90-4.
33.
FieldA. Discovering Statistics Using SPSS. Second ed. London: SAGE Publications; 2005.
34.
DongYPengCY. Principled missing data methods for researchers. SpringerPlus.2013; 2(1): 222.
35.
van BuurenS. Multiple imputation of discrete and continuous data by fully conditional specification. Statistical Methods in Medical Research.2007; 16(3): 219-42.
36.
RoyuelaAKovacsFMCampilloCCasamitjanaMMurielAAbrairaV. Predicting outcomes of neuroreflexotherapy in patients with subacute or chronic neck or low back pain. The Spine Journal: Official Journal of the North American Spine Society.2014; 14(8): 1588-600.
37.
PillastriniPBonfiglioliRBanchelliFCapraFResende FdeLVillafaneJH, et al. The effect of a multimodal group programme in hospital workers with persistent low back pain: a prospective observational study. La Medicina del Lavoro.2013; 104(5): 380-92.
38.
RantonenJKarppinenJVehtariALuotoSViikari-JunturaEHupliM, et al. Effectiveness of three interventions for secondary prevention of low back pain in the occupational health setting – a randomised controlled trial with a natural course control. BMC Public Health.2018; 18(1): 598.
39.
VergouwDHeymansMWvan der WindtDAFosterNEDunnKMvan der HorstHE, et al. Missing data and imputation: a practical illustration in a prognostic study on low back pain. Journal of Manipulative and Physiological Therapeutics.2012; 35(6): 464-71.
40.
RainvilleJAhernDKPhalenL. Altering beliefs about pain and impairment in a functionally oriented treatment program for chronic low back pain. The Clinical Journal of Pain.1993; 9(3): 196-201.
41.
VerbeekJSengersMJRiemensLHaafkensJ. Patient expectations of treatment for back pain: a systematic review of qualitative and quantitative studies. Spine.2004; 29(20): 2309-18.
42.
CarosellaAMLacknerJMFeuersteinM. Factors associated with early discharge from a multidisciplinary work rehabilitation program for chronic low back pain. Pain.1994; 57(1): 69-76.
43.
Al-EisaE. Indicators of adherence to physiotherapy attendance among Saudi female patients with mechanical low back pain: a clinical audit. BMC Musculoskeletal Disorders.2010; 11: 124.
44.
TanBKSmithAJO’SullivanPBChenGBurnettAFBriggsAM. Low back pain beliefs are associated to age, location of work, education and pain-related disability in Chinese healthcare professionals working in China: a cross sectional survey. BMC Musculoskeletal Disorders.2014; 15: 255.
45.
NicholasMKAsghariACorbettMSmeetsRJWoodBMOvertonS, et al. Is adherence to pain self-management strategies associated with improved pain, depression and disability in those with disabling chronic pain? European Journal of Pain (London, England).2012; 16(1): 93-104.
46.
MannionAFHelblingDPulkovskiNSprottH. Spinal segmental stabilisation exercises for chronic low back pain: programme adherence and its influence on clinical outcome. European spine journal: official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society.2009; 18(12): 1881-91.
47.
RossCEWuC-l.The Links Between Education and Health. American Sociological Review.1995; 60(5): 719-45.
48.
DamianiGBassoDAcamporaABianchiCBSilvestriniGFrisicaleEM, et al. The impact of level of education on adherence to breast and cervical cancer screening: Evidence from a systematic review and meta-analysis. Preventive Medicine.2015; 81: 281-9.
49.
JordanJLHoldenMAMasonEEFosterNE. Interventions to improve adherence to exercise for chronic musculoskeletal pain in adults. The Cochrane Database of Systematic Reviews.2010; (1): Cd005956.
50.
HaydenJAvan TulderMWMalmivaaraAVKoesBW. Meta-analysis: exercise therapy for nonspecific low back pain. Annals of Internal Medicine.2005; 142(9): 765-75.
51.
HenschkeNvan EnstAFroudROsteloRW. Responder analyses in randomised controlled trials for chronic low back pain: an overview of currently used methods. European spine journal: official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society.2014; 23(4): 772-8.
52.
LillefjellMKrokstadSEspnesGA. Prediction of function in daily life following multidisciplinary rehabilitation for individuals with chronic musculoskeletal pain; a prospective study. BMC Musculoskeletal Disorders.2007; 8: 65.
53.
HegedusEJMoodyJ. Clinimetrics corner: the many faces of selection bias. The Journal of Manual & Manipulative Therapy.2010; 18(2): 69-73.
54.
PakpourAHYaghoubidoustMCampbellP. Persistent and Developing Sleep Problems: A Prospective Cohort Study on the Relationship to Poor Outcome in Patients Attending a Pain Clinic with Chronic Low Back Pain. Pain Practice: The Official Journal of World Institute of Pain.2018; 18(1): 79-86.
55.
KellyGABlakeCPowerCKO’KeeffeDFullenBM. The association between chronic low back pain and sleep: a systematic review. The Clinical Journal of Pain.2011; 27(2): 169-81.
56.
LardonADuboisJDCantinVPicheMDescarreauxM. Predictors of disability and absenteeism in workers with non-specific low back pain: A longitudinal 15-month study. Applied Ergonomics.2018; 68: 176-85.
57.
CookCEMooreTJLearmanKShowalterCSnodgrassSJ. Can experienced physiotherapists identify which patients are likely to succeed with physical therapy treatment? Archives of Physiotherapy.2015; 5: 3.
58.
Haxby AbbottJKinganEM. Accuracy of physical therapists’ prognosis of low back pain from the clinical examination: a prospective cohort study. The Journal of Manual & Manipulative Therapy.2014; 22(3): 154-61.
59.
DagfinrudHStorheimKMagnussenLHOdegaardTHoftaniskaILarsenLG, et al. The predictive validity of the Orebro Musculoskeletal Pain Questionnaire and the clinicians’ prognostic assessment following manual therapy treatment of patients with LBP and neck pain. Manual Therapy.2013; 18(2): 124-9.
60.
NijsJMeeusMCagnieBRousselNADolphensMVan OosterwijckJ, et al. A modern neuroscience approach to chronic spinal pain: combining pain neuroscience education with cognition-targeted motor control training. Physical Therapy.2014; 94(5): 730-8.
61.
van HooffMLSpruitMO’DowdJKvan LankveldWFairbankJCvan LimbeekJ. Predictive factors for successful clinical outcome 1 year after an intensive combined physical and psychological programme for chronic low back pain. European spine journal: official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society.2014; 23(1): 102-12.
62.
ChildsJDClelandJA. Development and application of clinical prediction rules to improve decision making in physical therapist practice. Physical Therapy.2006; 86(1): 122-31.
63.
HerbertR. Dealing with heterogeneity in clinical trials. Manual Therapy.2007; 12(1): 1-2.
64.
RazafshaMBehforuziHAzariHZhangZWangKKKobeissyFH, et al. Qualitative versus quantitative methods in psychiatric research. Methods in Molecular Biology (Clifton, NJ).2012; 829: 49-62.
65.
DorfmanDGeorgeMCRobinson-PappJRahmanTTamlerRSimpsonDM. Patient reported outcome measures of pain intensity: Do they tell us what we need to know? Scand J Pain.2016; 11: 73-6.
