Identifying Patients With Chronic Low Back Pain Who Respond Best to Mechanical Diagnosis and Therapy: Secondary Analysis of a Randomized Controlled Trial Alessandra Narciso Garcia, Luciola da Cunha Menezes Costa, Mark Hancock and Leonardo Oliveira Pena Costa PHYS THER. Published online October 22, 2015 doi: 10.2522/ptj.20150295
The online version of this article, along with updated information and services, can be found online at: http://ptjournal.apta.org/content/early/2015/10/14/ptj.20150295 E-mail alerts
Sign up here to receive free e-mail alerts
Online First articles are published online before they appear in a regular issue of Physical Therapy (PTJ). PTJ publishes 2 types of Online First articles: Author manuscripts: PDF versions of manuscripts that have been peer-reviewed and accepted for publication but have not yet been copyedited or typeset. This allows PTJ readers almost immediate access to accepted papers. Page proofs: edited and typeset versions of articles that incorporate any author corrections and replace the original author manuscript.
Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Running head: Chronic Low Back Pain and Mechanical Diagnosis and Therapy
Research Report
Identifying Patients With Chronic Low Back Pain Who Respond Best to Mechanical Diagnosis and Therapy: Secondary Analysis of a Randomized Controlled Trial
Alessandra Narciso Garcia, Luciola da Cunha Menezes Costa, Mark Hancock, Leonardo Oliveira Pena Costa
A.N. Garcia, Masters and Doctoral Programs in Physical Therapy, Universidade Cidade de São, Rua Cesario Galeno 475, Sao Paulo, Sao Paulo, Brazil, CEP 03071-000. Address all correspondence to Miss Garcia at:
[email protected].
L.C.M. Costa, Masters and Doctoral Programs in Physical Therapy, Universidade Cidade de São Paulo.
M. Hancock, Discipline of Physiotherapy, Macquarie University, Sydney, New South Wales, Australia.
L.O.P. Costa, PT, PhD, Masters and Doctoral Programs in Physical Therapy, Universidade Cidade de São Paulo.
[Garcia AN, Costa LCM, Hancock M, Costa LOP. Identifying patients with chronic low back pain who respond best to mechanical diagnosis and therapy: secondary analysis of a randomized controlled trial. Phys Ther. 2015;95:xxx–xxx.] 1 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
© 2015 American Physical Therapy Association Published Ahead of Print: xxxx Accepted: October 4, 2015 Submitted: May 25, 2015
2 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Abstract Background “Mechanical Diagnosis and Therapy (MDT)” also known as McKenzie method like other interventions for low back pain (LBP) has been found to have small effects for people with LBP. It is possible that a group of patients respond best to MDT and have larger effects. Identification of patients who respond best to MDT compared to other interventions would be an important finding.
Methods This study was a secondary analysis of data from a previous trial comparing MDT to Back School in 148 patients with chronic LBP. Only patients classified at baseline assessment as being in the directional preference group (n=140) were included. The effect modifiers tested were: Clear centralization vs directional preference only; Baseline pain location; Baseline pain intensity; and Age. The primary outcomes for this study were pain intensity and disability at the end of treatment (1 month). Treatment effect modification was evaluated by assessing the group versus predictor interaction terms from linear regression models. An interaction ≥ 1.0 for pain and > 3 for disability were considered clinically important.
Results Being older met our criteria for being a potentially important effect modifier; however, the effect occurred in the opposite direction to our hypothesis. Older people had 1.27 points more benefit in pain reduction from MDT (compared to Back School) than younger participants after 1 month of treatment.
Conclusions Our study suggests older age may be an important factor that can be considered as a treatment effect modifier for patients with chronic LBP receiving MDT. As the main trial was not powered for the investigation of subgroups, the results of this secondary analysis have to be interpreted cautiously and replication is required.
3 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Background The cause of low back pain (LBP) cannot be definitively identified in the majority of cases and as such the label ‘non-specific LBP’ (NSLBP) is widely used1-3. While approximately 85% of patients with LBP in primary care are considered to have NSLBP2, most clinicians believe that NSLBP includes several different subgroups and is not one condition4-6. Several subgrouping systems have been developed to attempt to improve outcomes for patients with NSLBP rather than using a ‘one-size-fits all’ approach5, 7-10.
The “Mechanical Diagnosis and Therapy (MDT)” also known as McKenzie method is one such subgrouping approach11.This method, proposed by Robin McKenzie in 198111 classifies patients into three syndromes/groups: derangement, dysfunction and postural based on responses to repeated end range movements performed by the patient and assessed by the clinician. Classification is based largely on a patient’s response to sustained postures and repeated movements11, 12. Based on the classification, an intervention approach is selected11, 12. During the assessment, it is important to identify the directional preference response which is characterized by a reduction of pain intensity, centralization (pain referred in a peripheral location from the spine moves to the central lower back and is progressively abolished)11or abolished pain. The MDT method emphasizes the use of simple self-management strategies that require adherence to home exercises and maintenance of correct postures11, 12. While the MDT approach attempts to improve outcomes in people with low back pain by targeting interventions to the 3 subgroups, systematic reviews conclude that MDT has relatively small effect sizes and is not superior to other approaches for NSLBP12, 13. One possible reason for this is that the vast majority of patients are classified as being in the derangement group and as such most get a similar approach to treatment14. For example in our recent trial comparing MDT to Back School over 85 % of participants were classified as having a derangement15, 16. Anecdotally some clinicians report that within this large derangement group, some patients respond well to MDT therapy while others do not. If a group of patients classified as having a derangement who respond best to MDT can be identified then the outcomes of using the MDT approach in these patients could be improved and those patients who are unlikely to respond well could be treated with a different approach. The Treatment Based Classification System (TBC)7-9, is an example of a hybrid subgrouping system for LBP that attempts to identify a subset of patients with a directional preference for 4 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
specific exercise direction while other patients are recommended for other interventions such as manipulation or stabilization exercises. A limitation of the TBC is that patients assigned to the specific exercise (MDT category) are tested in one plane only and are not subjected to the multitude of planes of motion assessed and loading and unloading strategies characteristic of MDT. The recommended intervention for the specific exercise subset is similar to that used for the derangement syndrome in the MDT approach. A previous secondary analysis of a randomized controlled trial by Sheets et al17 investigated responders to MDT in patients with acute LBP. They investigated six potential effect modifiers (baseline pain, pain changes with position or movement, presence of leg pain, constant pain, pain worse with flexion and patient expectation), which could influence the clinical response of patients treated with MDT17. This study found that these potential effect modifiers did not predict more favorable response to MDT17. A limitation of this study was that only patients in the MDT group underwent a MDT assessment, so it was not possible to investigate if clinical examination findings such as centralization predicted response to MDT17. Another study18 included only patients with a changeable lumbar condition, (i.e. centralization or peripheralization), and investigated those more likely to benefit from the MDT method or spinal manipulation. This study18 included 350 patients with chronic LBP and found that patients with nerve root involvement and peripheralization may have clinically important differences in response to MDT compared to spinal manipulation.
Some patients classified by the MDT method clearly centralize on assessment while others have a directional preference but do not actually demonstrate centralization11, 19, 20. No previous study has investigated if the presence of clear centralization compared to directional preference alone is an important effect modifier for MDT. The purpose of this hypothesis-setting, secondary analysis was to investigate if baseline characteristics of patients with chronic LBP, already classified as derangement syndrome, can identify those who respond better to MDT compared to Back School.
Methods Study design This study was a secondary analysis of data from a (two-arm) randomized controlled trial (RCT) that investigated the effect of MDT compared to Back School in patients with chronic LBP15, 16.
5 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
To increase the validity of the current subgroup analysis it was performed using the approach recommended by Sun et al21 which included investigating a limited number of pre-specified predictor variables, pre-specification of the hypothesized direction of subgroup effects and use of interaction terms.
Study population This study was conducted in the outpatient physical therapy clinic of the Universidade Cidade de São Paulo, Brazil, between July 2010 and July 2012. To be eligible patients seeking care had to have NSLBP with duration of at least 12 weeks22 and be aged between 18 and 80 years. Patients with any contraindication to physical exercise based on the recommendations of the guidelines of the American College of Sports Medicine23; serious spinal pathology(for example tumors, fractures and inflammatory diseases); previous spinal surgery; nerve root compromise; cardio respiratory illnesses and pregnancy were excluded.
Randomization Patients were allocated into one of two intervention groups: Back School (a group-based treatment approach) and MDT (an individually-based treatment approach) by a simple randomization sequence computer generated using Microsoft Excel. The randomization sequence was conducted by one of the investigators of the study who was not directly involved with the assessments and treatment of patients. The allocation was concealed by using consecutive numbered, sealed and opaque envelopes.
Interventions Participants from both groups received 4 one-hour sessions over 1 month, once a week. The number of sessions was chosen following the recommendations from the original Back School manual method24. Therefore the same number of sessions was used for the MDT group. Patients treated with Back School method received advice about anatomy and spinal biomechanics; epidemiology; physiopathology of the most frequent back disorders; posture; ergonomics; common treatment modalities and practiced exercises (breathing, stretching legs, trunk strengthening and pelvic mobility for the maintenance of a “healthy back”)16, 24. Patients from the MDT group practiced specific exercises according to their mechanical diagnosis and were also instructed to follow the recommendations of the “Treat Your Own Back" book25. The care provider, who treated the patients in both groups, completed MDT training Part A certified by
6 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
the McKenzie Institute of Brazil, with one year of experience and has received extensive Back School training during her undergraduate training program.
Outcomes The outcomes for this study were: 1) pain intensity measured by Pain Numerical Rating Scale (NRS)26 and 2) disability measured by the Roland Morris Disability Questionnaire (RMDQ)27, 28 at 1 month after randomization. These were the same as the primary study15, 16. The NRS has good levels of reliability (Type 2,1 Intraclass Correlation Coefficient - ICC 2,1=0.85 (95% CI 0.77 to 0.90), responsiveness (Standardized Effect Size of 1.16) and construct validity26. The RMDQ has good levels of internal consistency: Cronbach’s alpha of 0.90; reliability (ICC2,1=0.94 (95% CI 0.91 to 0.96), responsiveness (Standardized Effect Size of 0.70) and construct validity26.
Variables of interest Four potential effect modifiers for treatment were selected after consideration of the theoretical rationale and consultation with an educator in the MDT approach29. The variables selected were:
1. Clear centralization vs directional preference only: We hypothesized that patients with clear centralization would respond better to MDT than Back School. Centralization is considered a more ”positive” response to MDT assessment than directional prefence alone. Patients were considered to have centralization of symptoms if their pain referred in a peripheral location moved to the central lower back and was progressively abolished, while if their pain just decreased but did not move to the central lower back they were considered to have directional preference without centralization. Symptom diagram and patient report of the location of symptoms were used to determine if centralization had occurred. 2. Baseline pain location: We hypothesized that patients with pain located below the knee would respond better to MDT than Back School. Some preliminary studies suggest people with leg pain may respond well to MDT30-32 approach and there is little rationale why back school would specifically help these people. The MDT approach focusses on achieving centralization of pain from the periphery into the low back. Whether patients had pain extending below the knee was determined using a body chart and patient self-report during the baseline assessment. 3. Baseline pain intensity: We hypothesized that patients with higher baseline pain intensity (using median split) would respond better to MDT than Back School. This was based on clinical experience rather than any strong existing evidence.
7 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
4. Age: We hypothesized that patients with younger age (using median split) would respond better to MDT than Back School. The rationale was that they might be able to move further into the range of motion and therefore better achieve an end of range position. Movement to end of range is proposed to be important to optimize response to MDT in people classified as having a derangement syndrome11, 20. This information was determinedduring baseline assessment.
Analysis We investigated baseline patient characteristics associated with greater effect of MDT versus Back School separately for outcomes of pain and disability. Each of the four predictor variables was investigated in separate univariate models.
The continuous effect modifiers of pain intensity and age were dichotomized using median split as other methods where optimal thresholds are used have been shown to be substantially biased and are recommended against33. Thresholds dichotomizing pain intensity and age have been used previosly18; however, these were not specifically intended for our purpose and by using a median split we also enhanced our statistical power by creating equal sized groups positive and negative for the predictor. Each model included terms for group, predictor and the interaction term, group x predictor. The interaction term was used to quantify size of the effect modification.
It has been estimated that the detection of a statistically significant subgroup interaction effect in an RCT requires a sample size approximately four times that required to detect a main effect of the same size34. Previous authors have suggested secondary analysis of RCTs as an approach to develop hypotheses for potentially important effect modifiers that can then be tested in suitably large trials35, 36.As the current hypothesis setting study was underpowered; we focused on the estimated effect size rather than statistical significance. If the interaction was greater than 1.0 point on the NRS or 3 points on the RMDQ then we proceeded to investigate the potential clinical importance by assessing the effect of intervention (MDT compared to Back School) separately for those positive for the subgroup and negative for the subgroup. This was done by calculating the marginal means for the subgroups35. These thresholds are somewhat arbitrary as it is difficult to determine exactly what a clinically important interaction effect is. Previous work suggests this is influenced by the main treatment effect18, 37 as well as the potential harms and benefits of the interventions38.
8 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Ethics This secondary analysis was based on existing data collected for a randomized controlled trial15 approved by the Ethics Committee in Research of UNICID (number 134699394). The RCT trial was also prospectively registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12610000435088). The research protocol was published elsewhere16.
Results Between July 2010 and January 2012 a total of 182 patients who were seeking care for LBP in the physical therapy clinic of the Universidade Cidade de São Paulo were screened for potential entry into the study. Of these 148 were considered eligible and randomized (74 to each treatment). The reasons for ineligibility were cardiorespiratory illnesses (n=8), age over 80 years (n=5), acute LBP (n=4), nerve root compromise (n=4), neck pain instead LBP (n=3), grade II spondylolisthesis (n=2), vertebral fracture (n=1), rib fracture (n=1), deep vein thrombosis (n=1), abdominal tumor (n=1), advanced osteoporosis (n=1), metabolic myopathy (n=1), colitis (n=1) and urinary tract infection (n=1). All patients received the treatments as allocated. A total of 148 patients were included in the main RCT. However,eight patients were not classified as having directional preference and because of this were excluded from the analysis of this study. Therefore, 140 patients were included in this secondary analysis (Fig 1).
After dichotomizing the average age of older patients was 64.81 (5.95) years [MDT group 65.16 (6.23); Back School 64.54 (7.78)] and for younger people 43.47 (9.60) years [MDT group 44.28 (9.50); Back School 42.45 (9.78)]. The average of higher pain intensity was 8.07 (1.0) points [MDT group 8.07 (1.0); Back School 8.07 (1.16)] and for low level of pain intensity 4.35 points (1.69) [MDT group 4.40 (1.52); Back School 4.31 (1.87)]. The baseline characteristics of both groups including effect modifiers investigated in this study were similar. Nearly 75% of patients were women and the average symptom duration was approximately 2 years. Patients generally had moderate levels of pain and disability (Table 1). The results of the linear regression analyses for pain and disability outcomes are shown in Tables 2 and 3 respectively. As expected in this hypothesis setting study, none of the interaction terms for any outcomes findings were statistically significant. The interaction term (1.27) for age exceeded our pre-specified threshold of >1 for the outcome of pain (table 2). However, the direction of effect was opposite to our hypothesis. Older people appeared to benefit more from 9 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
MDT compared to Back School. For the outcome of disability the interaction term for age was 2.39 and therefore did not meet out threshold for clinical importance of >3 (table 3). Interaction terms for the 3 other effect modifiers (clear centralization, pain below knee, high pain intensity) were below our thresholds for potential clinical importance.
Tables 4 shows the effect of MDT compared to Back School separately for those younger and older than 54. Older people improved 1.42 points for pain intensity and 3.51 points for disability more than younger from MDT compared to Back School.
10 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Discussion Statement of principal findings The purpose of this hypothesis-setting, secondary analysis was to investigate if four baseline characteristics of patients (presence of clear centralization, pain location, pain intensity and age) with chronic LBP, can identify those who respond better to MDT compared to Back School. Based on our results, the interaction term of 1.27 for age exceeded our pre-specified threshold of >1 for the outcome of pain, suggesting older people may benefit more from MDT compared to Back School. However, the direction of effect was opposite to our initial hypothesis and as expected the effect was not statistically significant, so caution is required when interpreting this finding. The presence of clear centralization, pain located below the knee and pain intensity were not found to be effect modifiers for response to MDT compared to Back School.
Strengths and weaknesses of the study A strength of our study was that the data was derived from a high quality randomized controlled trial15. The trial collected important potential treatment effect modifiers from all patients that are likely to influence the response to MDT. Only four potential effect modifiers were selected a priori after consideration of the theoretical rationale and consultation with a specialist musculoskeletal physiotherapist who is a credentialed MDT therapist29. This therapist has been an educator of the McKenzie Institute since 1986 and is the International Director of Education for the McKenzie Institute International since 199929. She is currently the only teaching member of the McKenzie Institute in Australia and also teaches MDT courses internationally29. We avoided selecting a higher number of effect modifiers in order to minimize the chance of spurious findings39. The methodological approach of this paper, based on recommendations in the literature, can act as a model for subgroup studies within randomized controlled trials in the rehabilitation field. Another contribution of this study is the interpretation of the actual findings leading into hypotheses that can be tested in future trials. The main limitation of this study was the lack of statistical power for an ideal subgroup analysis. Our sample (n=140) was powered to detect the main effects of treatment, but not to detect the interactions of the potential treatment effect modifiers40. For this reason this study was set up as a hypothesis generating study and the focus was on estimated effect size rather than statistical significance.
11 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
We used a simple analysis that did not contain any covariates. This approach was chosen to minimise the risk of over fitting the model and also because the resulting interaction effect size is exactly equal to the difference between treatment effect in one subgroup (e.g. older age) compared to the other subgroup (e.g. younger age)18, 35-37 which makes the finding easier to interpret. However, to test potential confounding we conducted a post hoc analysis for the predictor of age where we added gender and duration of symptoms into the models. For both pain and disability models this resulted in the interaction effect becoming marginally greater (2.85; 95% CI -5.90 to 0.20 for pain and -1.35; 95% CI -3.45 to 0.74 for disability) than in the simple models.
Meaning of the study and comparison with other studies Our study found that patients that were older than 54 years and received MDT compared to Back School experienced an additional reduction in pain of 1.27 points compared to young people. It is important to note that the interaction does not define the main effect of the interventions per se, but the difference in effect of treatment for older patients compared to young patients6. The treatment effect within a subgroup is a combination of the interaction and the main treatment effect37. The finding presented in Table 4 show that in the subgroup of older people MDT was statistically more effective for pain (1.42; 95% CI 0.02 to 2.83) compared to Back School while in younger people there was no difference between the 2 interventions (0.15; 95% CI -1.38 to 1.68). Similarly for disability, in the subgroup of older people MDT was statistically more effective for disability (3.51; 95% CI 1.42 to 5.60) compared to Back School while in younger people there was no difference between the 2 interventions (1.12; 95% CI 1.11 to 3.35). We only investigated treatment effects (MDT vs Back School) within subgroups where the interaction met our criteria for clinical importance to reduce the chance of spurious findings40. We initially hypothesized that MDT would be more effective in younger patients as they might be able to move further into range of lumbar spine motion and therefore gain more benefit. Our findings suggesting MDT may be more effective in older people raises the question of the potential mechanism underlying this. One possibility is that older people were more adherent, with the approach which is almost entirely a self-management intervention. Another possibility is that older people have a somewhat different physiological basis to their pain which responds better to MDT; however, we do not have data to support these theories. These results may
12 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
simply be a spurious finding due to lack of statistical power. We recommend the investigation of age as a potential effect modifier in future rehabilitation trials, including but not limited to those investigating MDT for spinal pain. There are two previous studies that tested possible treatment effect modifiers for MDT17, 18. The first study recruited patients with acute LBP who received either MDT or usual care17. This study tested baseline pain, pain changes with position or movement, and presence of leg pain as potential effect modifiers. They found that these potential effect modifiers did not predict more favorable response to MDT. The second study18 compared MDT with spinal manipulation in 350 patients with chronic back pain. They included six predictor variables: centralization, age below 40 years, duration of symptoms more than 1 year, leg pain, pain below the knee, signs of nerve root involvement and pain response18. They concluded that it was not possible to find any statistically significant predictive factor, which identified better response to either MDT or spinal manipulation. The difference in our findings regarding age as an effect modifier may be due to a different control intervention, population or simply a spurious finding. Subgroup effects within trials are always specific to the control group37. We recommend that our results be interpreted carefully and adequately powered replication studies are needed. These studies together suggest it is difficult to identify powerful effect modifiers for MDT. This may be due to the fact that the MDT approach already uses a stratified approach to care. Interestingly the existing studies have not investigated psychosocial characteristics as effect modifiers and this is an area of future investigation we would recommend.
Conclusion We conducted a secondary analysis of an RCT to determine if potential treatment effect modifiers for MDT could be identified in patients with chronic LBP and with a directional preference. We found that those who were older appeared to respond better to MDT compared to Back School (the direction of effect was opposite to our initial hypothesis). Clear centralization, pain below knee and high pain intensity do not appear to be useful effect modifiers. The results of this hypothesis setting, secondary analysis, have to be interpreted cautiously because of the sample size. These findings, particularly of the potential effect modification effect of age, need testing in larger trials and with different comparisons.
13 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Acknowledgements All authors provided concept/idea/research design. Ms Garcia, Dr Hancock, and Dr Leonardo Costa provided writing and data analysis. Ms Garcia and Dr Luciola Costa provided data collection, project management, and consultation (including review of manuscript before submission). Dr Hancock and Dr Leonardo Costa provided fund procurement. Dr Leonardo Costa provided participants and institutional liaisons.
This study was funded by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), and International Mechanical Diagnosis and Therapy Research Foundation (IMDTRF).
DOI: 10.2522/ptj.20150295
14 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
References 1. Tulder MV. Chapter 1. European Guidelines Eur Spine J. 2006; 15 (2): 134-35. 2. Waddell G. The Back Pain Revolution. Second ed: Churchill Livingstone; 2004. 3. Menezes Costa Lda C, Maher CG, Hancock MJ, McAuley JH, Herbert RD, Costa LO. The prognosis of acute and persistent low-back pain: a meta-analysis. CMAJ. 2012; 184 (11): E61324. 4. Kent P, Hancock M, Petersen DH, Mjosund HL. Clinimetrics corner: choosing appropriate study designs for particular questions about treatment subgroups. J Man Manip Ther. 2011; 18 (3): 147-52. 5. Kent P, Keating JL. Classification in nonspecific low back pain: what methods do primary care clinicians currently use? Spine (Phila Pa 1976). 2005; 30 (12): 1433-40. 6. Kent P, Keating JL, Leboeuf-Yde C. Research methods for subgrouping low back pain. BMC Med Res Methodol. 2010; 10: 62. 7. Henry SM, Fritz JM, Trombley AR, Bunn JY. Reliability of a treatment-based classification system for subgrouping people with low back pain. J Orthop Sports Phys Ther. 2012; 42 (9): 797-805. 8. Stanton TR, Hancock MJ, Appeldoorn AT, Wand BM, Fritz JM. What characterizes people who have an unclear classification using a treatment-based classification algorithm for low back pain? A cross-sectional study. Phys Ther. 2013; 93 (3): 345-55. 9. Hebert JJ, Koppenhaver SL, Walker BF. Subgrouping patients with low back pain: a treatment-based approach to classification. Sports Health. 2011; 3 (6): 534-42. 10. Beneciuk JM, Robinson ME, George SZ. Subgrouping for patients with low back pain: a multidimensional approach incorporating cluster analysis and the STarT Back Screening Tool. J Pain. 2015; 16 (1): 19-30. 11. McKenzie R, May S. The Lumbar Spine Mechanical Diagnosis & Therapy Vol I. Second ed. New Zealand: Spinal Publications; 2003. 12. Clare HA, Adams R, Maher CG. A systematic review of efficacy of McKenzie therapy for spinal pain. Aust J Physiother. 2004; 50 (4): 209-16. 13. Machado LA, de Souza MS, Ferreira PH, Ferreira ML. The McKenzie method for low back pain: a systematic review of the literature with a meta-analysis approach. Spine (Phila Pa 1976). 2006; 31 (9): 254-62. 14. Hefford C. McKenzie classification of mechanical spinal pain: profile of syndromes and directions of preference. Man Ther. 2008; 13 (1): 75-81. 15. Garcia AN, Costa Lda C, da Silva TM, Gondo FL, Cyrillo FN, Costa RA, et al. Effectiveness of Back School Versus McKenzie Exercises in Patients With Chronic Nonspecific Low Back Pain: A Randomized Controlled Trial. Phys Ther. 2013; 93 (6): 729-47.
15 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
16. Garcia AN, Gondo FL, Costa RA, Cyrillo FN, Silva TM, Costa LC, et al. Effectiveness of the back school and mckenzie techniques in patients with chronic non-specific low back pain: a protocol of a randomised controlled trial. BMC Musculoskelet Disord. 2011; 12: 179. 17. Sheets C, Machado LA, Hancock M, Maher C. Can we predict response to the McKenzie method in patients with acute low back pain? A secondary analysis of a randomized controlled trial. Eur Spine J. 2011; 21 (7): 1250-6. 18. Petersen T, Christensen R, Juhl C. Predicting a clinically important outcome in patients with low back pain following McKenzie therapy or spinal manipulation: a stratified analysis in a randomized controlled trial. BMC Musculoskelet Disord. 2015; 16: 74-80. 19. Machado L, VanTulder MW, Lin CWC, Clare H, Hayden JA. The Mckenzie method for chronic non specific low back pain: study protocol. Cochrane Database of Systematic Rev. 2012: 1-16. 20. McKenzie R, May S. The Lumbar Spine Mechanical Diagnosis & Therapy Vol II. Second ed. New Zealand Spinal Publications; 2003. 21. Sun X, Briel M, Busse JW, E.A A, J.J Y, Mejza F, et al. Subgroup Analysis of Trials Is Rarely Easy (SATIRE): a study protocol for a systematic review to characterize the analysis, reporting, and claim of subgroup effects in randomized trials. Trials. 2009; 10: 101-11. 22. Airaksinen O, Brox JI, Cedraschi C, Hildebrandt J, Klaber-Moffett J, Kovacs F, et al. Chapter 4. European guidelines for the management of chronic nonspecific low back pain. Eur Spine J. 2006; 15 (2): 192-300. 23. Kenney LW, Humphrey RH, Mahler DA. ACSM's Guidelines for exercise testing and prescription: Williams & Walkins Baltimore; 1995. 24. Heymans MW, van Tulder MW, Esmail R, Bombardier C, Koes BW. Back schools for acute and subacute non-specific low-back pain. Cochrane Database of Syst Rev. 2004. 25. McKenzie R. Trate você mesmo a sua coluna: Spinal Publication LTD; 1998. 26. Costa LO, Maher CG, Latimer J, Ferreira PH, Ferreira ML, Pozzi GC, et al. Clinimetric testing of three self-report outcome measures for low back pain patients in Brazil: which one is the best? Spine (Phila Pa 1976). 2008; 33 (22): 2459-63. 27. Costa LO, Maher CG, Latimer J, Ferreira PH, Pozzi GC, Ribeiro RN. Psychometric characteristics of the Brazilian-Portuguese versions of the Functional Rating Index and the Roland Morris Disability Questionnaire. Spine (Phila Pa 1976). 2007; 32 (17): 1902-7. 28. Nusbaum L, Natour J, Ferraz MB, Goldenberg J. Translation, adaptation and validation of the Roland-Morris questionnaire--Brazil Roland-Morris. Braz J Med Biol Res. 2001; 34 (2): 203-10. 29. Dr. Helen Clare. McKenzie Institute Australia. [accessed: September 9 2015]; Available from: www.mckenziemdt.org.au/event/host/dr-helen-clare/. 30. Paatelma M, Kilpikoski S, Simonen R, Heinonen A, Alen M, Videman T. Orthopaedic manual therapy, McKenzie method or advice only for low back pain in working adults: a randomized controlled trial with one year follow-up. J Rehabil Med. 2008; 40 (10): 858-63. 16 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
31. Albert HB, Hauge E, Manniche C. Centralization in patients with sciatica: are pain responses to repeated movement and positioning associated with outcome or types of disc lesions? Eur Spine J. 2012; 21 (4): 630-6. 32. Long A, May S, Fung T. The comparative prognostic value of directional preference and centralization: a useful tool for front-line clinicians? J Man Manip Ther. 2008; 16 (4): 248-54. 33. Altman DG, Royston P. The cost of dichotomising continuous variables. Bmj. 2006; 332 (7549): 1080. 34. Brookes ST, Whitely E, Egger M, Smith GD, Mulheran PA, Peters TJ. Subgroup analyses in randomized trials: risks of subgroup-specific analyses; power and sample size for the interaction test. J Clin Epidemiol. 2004; 57 (3): 229-36. 35. Hancock M, Herbert RD, Maher CG. A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions. Phys Ther. 2009; 89 (7): 698-704. 36. Kamper SJ, Maher CG, Hancock MJ, Koes BW, Croft PR, Hay E. Treatment-based subgroups of low back pain: a guide to appraisal of research studies and a summary of current evidence. Best Pract Res Clin Rheumatol. 2010; 24 (2): 181-91. 37. Hancock MJ, Kjaer P, Korsholm L, Kent P. Interpretation of subgroup effects in published trials. Phys Ther. 2013; 93 (6): 852-9. 38. Ferreira ML, Herbert RD, Ferreira PH, Latimer J, Ostelo RW, Nascimento DP, et al. A critical review of methods used to determine the smallest worthwhile effect of interventions for low back pain. J Clin Epidemiol. 2012; 65 (3): 253-61. 39. Sun X, Briel M, Walter SD, Guyatt GH. Is a subgroup effect believable? Updating criteria to evaluate the credibility of subgroup analyses. Bmj. 2010; 340: c117. 40. Brookes ST, Whitley E, Peters TJ, Mulheran PA, Egger M, Davey Smith G. Subgroup analyses in randomised controlled trials: quantifying the risks of false-positives and falsenegatives. Health Technol Assess. 2001; 5 (33): 1-56.
17 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Table 1. Baseline characteristics (n=140) Variables
Back School Group
MDT Group
40 (57.1) 23 (32.9) 25 (35.7)
35 (50.0) 25 (35.7) 30 (42.9)
11 (15.7) 42 (60) 5 (7.1) 11 (15.7) 1 (1.4)
17 (24.3) 38 (54.3) 5 (7.1) 9 (13) 1 (1.4)
27 (38.6) 30 (43) 13 (18.6) 0 51 (74) 26 (37.1) 5 (7.5) 45 (64.3)
26 (37.1) 32 (46) 11 (16) 1 (1.4) 18 (26) 19 (27.1) 8 (12) 46 (66)
50 (71.4) 54.76 (13.50) 67.60 (99.58) 73.81 (13.93) 1.64 (0.09) 6.67 (2.34) 11.29 (5.91)
56 (80) 53.53 (13.26) 42.20 (82.20) 70.19 (12.72) 1.61 (0.90) 6.76 (2.14) 11.26 (4.95)
51.68 (17.49) 59.46 (15.90) 62.50 (20.15) 54.06 (16.41) 78.45 (22.89)
52 (14.58) 62.91 (15.95) 64.16 (17.70) 55.27 (13.27) 80.10 (17.21)
Categorical variables
Effect modifiers Clear centralization Pain below the knee High pain intensity (>7 points) Marital status Single Married Divorced Widow Other Education status Elementary degree High school University Illiterate Use of medication Physically active Smoker Recent low back pain episode Continuous variables Gender (female) Age (years) Duration of symptoms (months)* Weight (kilograms) Height (meters) Pain intensity (0-10) Disability (0-24) Quality of life (0-100) Physical Domain Psychological Domain Social Domain Environmental Domain Trunk flexion range of motion (degrees)
Categorical variables are expressed as number (%), continuous variables are expressed as mean (SD); MDT: Mechanical Diagnosis and Therapy
18 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Table 2. Results of linear regression models in pain intensity Beta
p-value
coefficient
95% confidence interval
Clear centralization Treatment
0.84
0.28
-0.70; 2.40
Clear centralizer
0.33
0.66
-1.18; 1.85
Interaction: treatment x clear centralizer
-0.33
0.75
-2.45; 1.78
Constant
1.89
0.00
0.75; 3.04
Treatment
0.66
0.31
-0.62; 1.94
Pain below the knee
0.63
0.44
-0.98; 2.24
Interaction: treatment x pain below the knee
-0.10
0.92
-2.33; 2.12
Constant
1,89
0.00
0.99; 2.79
Treatment
0.28
0.65
-0.97; 1.54
High pain intensity
2.05
0.00
0.59; 3.51
Interaction: treatment x high pain intensity
0.50
0.62
-1.51; 2.51
Constant
1.36
0.00
0.49; 2;23
Treatment
1.42
0.05
-0.04; 2.89
Age younger than 54
-0.57
0.43
-2.04; 0.89
Interaction: treatment x age younger than 54
-1.27
0.22
-3.33; 0.79
Constant
2.35
0.00
1.36; 3.34
Pain below the knee
High pain intensity
Age younger than 54
Note: Interaction terms provide the critical information for assessing if effect modification exists. Positive interactions mean that the direction of the effect was in favor of the study´s hypothesis. Negative interactions mean the effect was in the opposite direction to that hypothesized.
19 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Table 3. Results of linear regression models in disability Beta
p-value
coefficient
95% confidence interval
Clear centralization Treatment
2.06
0.73
-0.19; 4.31
Clear centralizer
0.66
0.55
1.54; 2.86
Interaction: treatment x clear centralizer
0.88
0.57
-2.19; 3.95
Constant
2.31
0.07
0.64; 4.0
Treatment
2.76
0.004
0.89; 4.64
Pain below the knee
1.62
1.18
-0.74; 4.0
Interaction: treatment x pain below the knee
-1.09
0.51
-4.35; 2.16
Constant
2.19
0.001
0.88; 3.50
Treatment
1.68
0.09
-2.64; 3.64
High pain intensity
0.28
0.80
-1.99; 2.55
Interaction: treatment x high pain intensity
1.74
0.27
-1.39; 4.87
Constant
2.60
0.00
1.24; 3.94
Treatment
3.50
0.00
1.35; 5.66
Age younger than 54
2.70
0.01
0.54; 4.85
Interaction: treatment x age younger than 54
-2.39
0.12
-5.42; 0.64
Constant
1.46
0.49
0.00; 2.91
Pain below the knee
High pain intensity
Age younger than 54
Note: Interaction terms provide the critical information for assessing if effect modification exists. Positive interactions mean that the direction of the effect was in favor of the study´s hypothesis. Negative interactions mean the effect was in the opposite direction to that hypothesized. It does not mean there was no effect modification just opposite to hypothesis.
20 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Table 4. Effects of MDT compared to Back School for subgroups based on age MDT
Back School
Mean(SD)
Mean(SD)
Treatment effect (MDT compared to Back School) Mean difference (95% CI)
Changes in Pain (NRS) Age older than 54
3.77 (3.06)
2.35 (2.75)
1.42 (0.02; 2.83)
Age younger than 54
1.92 (3.56)
1.77 (2.65)
0.15 (-1.38; 1.68)
Changes in Disability (RMDQ) Age older than 54
4.97 (4.78)
1.46 (3.85)
3.51(1.42; 5.60)
Age younger than 54
5.28 (4.94)
4.16 (4.24)
1.12 (-1.11; 3.35)
NRS (Numerical Rating Scale); RMDQ (Roland Morris Disability Questionnaire)
21 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Randomisation (n=148) Excluded (n=8) Not classified as having directional preference d 140 patients analyzed (Directional Preference)
70 patients were assigned to the McKenzie group
70 patients were assigned to the Back School group
70 patients were followed up at 1 mo (100%)
Follow up
70 patients were followed up at 1mo (100%)
Figure 1. Flow of patients within the study.
22 Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
Identifying Patients With Chronic Low Back Pain Who Respond Best to Mechanical Diagnosis and Therapy: Secondary Analysis of a Randomized Controlled Trial Alessandra Narciso Garcia, Luciola da Cunha Menezes Costa, Mark Hancock and Leonardo Oliveira Pena Costa PHYS THER. Published online October 22, 2015 doi: 10.2522/ptj.20150295
http://ptjournal.apta.org/subscriptions/
Subscription Information
Permissions and Reprints http://ptjournal.apta.org/site/misc/terms.xhtml Information for Authors
http://ptjournal.apta.org/site/misc/ifora.xhtml
Downloaded from http://ptjournal.apta.org/ at Fisher Library on October 23, 2015
