IDENTIFYING PATIENTS WITH CHRONIC LOW BACK PAIN WHO RESPOND BEST TO MECHANICAL DIAGNOSIS AND THERAPY: SECONDARY ANALYSIS OF A RANDOMIZED CONTROLLED TRIAL
 
   

Identifying Patients With Chronic Low Back Pain Who Respond Best
to Mechanical Diagnosis and Therapy: Secondary Analysis
of a Randomized Controlled Trial

This section is compiled by Frank M. Painter, D.C.
Send all comments or additions to:
    Frankp@chiro.org
 
   

FROM:   Physical Therapy 2016 (May); 96 (5): 623–630 ~ FULL TEXT

  OPEN ACCESS   


Alessandra Narciso Garcia, Luciola da Cunha Menezes Costa, Mark Hancock,
Leonardo Oliveira Pena Costa

A.N. Garcia, PT,
Masters and Doctoral Programs in Physical Therapy,
Universidade Cidade de São Paulo,
Rua Cesario Galeno 475,
São Paulo, Brazil, CEP 03071-000.
alessandrag_narciso@yahoo.com.br


BACKGROUND:   "Mechanical Diagnosis and Therapy" (MDT) (also known as the 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 with other interventions would be an important finding.

OBJECTIVE:   The purpose of the study was to investigate whether baseline characteristics of patients with chronic LBP, already classified as derangement syndrome, can identify those who respond better to MDT compared with Back School.

METHODS   This study was a secondary analysis of data from a previous trial comparing MDT with 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 versus directional preference only, baseline pain location, baseline pain intensity, and age. The primary outcome measures 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. Interactions ≥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 with Back School) than younger participants after 1 month of treatment.

LIMITATIONS:   The sample (n=140) was powered to detect the main effects of treatment but not to detect the interactions of the potential treatment effect modifiers.

CONCLUSIONS:   The results of the study suggest 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 needed.



From the FULL TEXT Article:

Background

The cause of low back pain (LBP) cannot be definitively identified in the majority of cases, and as such the label “nonspecific low back pain” (NSLBP) is widely used. [1–3] Although approximately 85% of patients with LBP in primary care are considered to have NSLBP, [2] most clinicians believe that NSLBP includes several different subgroups and is not one condition. [4–6] Several subgrouping systems have been developed to attempt to improve outcomes for patients with NSLBP rather than using a “one-size-fits-all” approach. [5, 7–10]

“Mechanical Diagnosis and Therapy” (MDT), also known as the McKenzie method, is one such subgrouping approach. [11] This method, proposed by Robin McKenzie in 1981, [11] classifies patients into 3 syndromes or 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 movements. [11, 12]

Based on the classification, an intervention approach is selected. [11, 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), [11] or abolished pain. The MDT method emphasizes the use of simple self-management strategies that require adherence to home exercises and maintenance of correct postures. [11, 12]

Although the MDT approach attempts to improve outcomes in people with LBP 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 nonspecific low back pain (NSLBP). [12, 13] One possible reason for this conclusion is that the vast majority of patients are classified as being in the derangement group and, therefore, most get a similar approach to treatment. [14] For example, in our recent trial comparing MDT with Back School, more than 85% of participants were classified as having a derangement. [15, 16] Anecdotally, some clinicians report that within this large derangement group, some patients respond well to MDT, whereas others do not. If a group of patients classified as having a derangement who respond best to MDT can be identified, 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 [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 specific exercise direction, whereas other patients are recommended for other interventions such as manipulation or stabilization exercises. A limitation of the treatment-based classification system 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 (RCT) by Sheets et al [17] investigated responders to MDT in a group of patients with acute LBP. They investigated 6 potential effect modifiers (baseline pain, pain changes with position or movement, presence of leg pain, constant pain, pain worse with flexion, and patient expectation) that could influence the clinical response of patients treated with MDT. [17] This study showed that these potential effect modifiers did not predict more favorable response to MDT. [17] A limitation of this study was that only patients in the MDT group underwent a MDT assessment, so it was not possible to investigate whether clinical examination findings such as centralization predicted response to MDT. [17] Another study [18] included only patients with a changeable lumbar condition, (ie, centralization or peripheralization) and investigated those more likely to benefit from the MDT method or spinal manipulation. This study [18] included 350 patients with chronic LBP and showed that patients with nerve root involvement and peripheralization may have clinically important differences in response to MDT compared with spinal manipulation.

Some patients classified by the MDT method clearly centralize on assessment, whereas others have a directional preference but do not actually demonstrate centralization. [11, 19, 20] To our knowledge, no previous study has investigated whether the presence of clear centralization compared with directional preference alone is an important effect modifier for MDT. The purpose of this hypothesis-setting, secondary analysis was to investigate whether baseline characteristics of patients with chronic LBP, already classified as derangement syndrome, can identify those who respond better to MDT compared with Back School.



Method

      Study Design

This study was a secondary analysis of data from a 3–arm RCT that investigated the effect of MDT compared with Back School in patients with chronic LBP. [15, 16] To increase the validity of the current subgroup analysis, it was performed using the approach recommended by Sun et al, [21] which included investigating a limited number of prespecified predictor variables, prespecification 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 Sa˜o Paulo, Sao Paulo, Brazil, between July 2010 and July 2012. To be eligible, patients seeking care had to have NSLBP with a duration of at least 12 weeks [22] 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 Medicine [23]; serious spinal pathology (eg, tumors, fractures, inflammatory diseases); previous spinal surgery; nerve root compromise; cardiorespiratory illnesses; or pregnancy were excluded.

      Randomization

Participants were allocated to 1 of 2 intervention groups—Back School (a group-based treatment approach) or MDT (an individually based treatment approach)—by a simple randomization sequence computer generated using Microsoft Excel (Microsoft Corp, Redmond, Washington). 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 consecutively numbered, sealed, 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 method. [24] 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, and common treatment modalities and practiced exercises (breathing, stretching legs, trunk strengthening, and pelvic mobility) for the maintenance of a “healthy back.” [16, 24] Participants in the MDT group practiced specific exercises according to their mechanical diagnosis and were instructed to follow the recommendations of the book titled Treat Your Own Back. [25] The care provider, who treated the patients in both groups, completed MDT training part A certified by the McKenzie Institute of Brazil, has 1 year of experience, and received extensive Back School training during her undergraduate training program.

      Outcome Measures

The outcome measures for this study were (1) pain intensity, as measured with the pain numerical rating scale (NRS), [26] and (2) disability, as measured with the Roland-Morris Disability Questionnaire (RMDQ), [27, 28] at 1 month after randomization. These were the same outcome measures as in the primary study. [15, 16] The NRS has good levels of reliability (intraclass correlation coefficient [ICC (2,1)] = .85; 95% confidence interval [CI] = .77, .90), responsiveness (standardized effect size = 1.16), and construct validity.26 The RMDQ has good levels of internal consistency (Cronbach alpha = .90, reliability [ICC (2,1) = .94; 95% CI = .91, .96], responsiveness [standardized effect size = 0.70], and construct validity). [26]

      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 approach. [29] The variables selected were: (1) clear centralization versus directional preference only, (2) baseline pain location, (3) baseline pain intensity, and (4) age.

Clear centralization versus directional preference only.   We hypothesized that patients with clear centralization would respond better to MDT than to 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, whereas 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 whether centralization had occurred.

Baseline pain location.   We hypothesized that patients with pain located below the knee would respond better to MDT than to Back School. Some preliminary studies suggest people with leg pain may respond well to the MDT approach, [30–32] and there is little rationale why Back School would specifically help these people. The MDT approach focuses 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.

Baseline pain intensity.   We hypothesized that patients with higher baseline pain intensity (using median split) would respond better to MDT than to Back School. This hypothesis was based on clinical experience rather than any strong existing evidence.

Age.   We hypothesized that patients with younger age (using median split) would respond better to MDT than to 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 syndrome. [11, 20] This information was determined during baseline assessment.


      Data 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 4 predictor variables was investigated in separate univariate models.

The continuous effect modifiers of pain intensity and age were dichotomized using the median split method, as other methods where optimal thresholds are used have been shown to be substantially biased and are recommended against. [33] Thresholds dichotomizing pain intensity and age have been used previously [18]; however, these thresholds were not specifically intended for our purpose, and by using a median split, we 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 4 times that required to detect a main effect of the same size. [34] 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 trials. [35, 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 points on the NRS or 3 points on the RMDQ, we proceeded to investigate the potential clinical importance by assessing the effect of intervention (MDT compared with Back School) separately for those positive for the subgroup and those negative for the subgroup. This was done by calculating the marginal means for the subgroups. [35] 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 effect [18, 37] as well as the potential harms and benefits of the interventions. [38]

      Ethics

This secondary analysis was based on existing data collected for an RCT15 approved by the Ethics Committee in Research of the Universidade Cidade de Sa˜o Paulo (number 134699394). The RCT also was prospectively registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12610000435088). The research protocol was published elsewhere.16

      Role of the Funding Source

This study was funded by Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES), and International Mechanical Diagnosis and Therapy Research Foundation (IMDTRF).



Results

Figure 1

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 Sao Paulo were screened for potential entry into the study. Of these patients, 148 were considered eligible and randomized (74 to each treatment group). 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, 8 patients were not classified as having directional preference and were excluded from the analysis of this study. Therefore, 140 patients were included in this secondary analysis (Figure).


Table 1

Table 2

Table 3

Table 4

After dichotomizing, the average age of older patients was 64.81 years (SD = 5.95) (MDT group: mean age = 65.16 years, SD = 6.23; Back School group: mean age = 64.54 years, SD = 7.78), and the average age of younger people was 43.47 years (SD = 9.60) (MDT group: mean age = 44.28 years, SD = 9.50; Back School group: mean age = 42.45 years, SD = 9.78). The average score for higher pain intensity was 8.07 points (SD = 1.0) (MDT group: mean = 8.07 points, SD = 1.0; Back School group: mean = 8.07 points, SD = 1.16), and the average score for low level of pain intensity 4.35 points (SD = 1.69) (MDT group: mean = 4.40 points, SD = 1.52; Back School group: mean = 4.3 points, SD = 1.87). The baseline characteristics of both groups, including effect modifiers investigated in this study, were similar. Nearly 75% of the 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 the outcomes of pain and disability are shown in Tables 2 and 3, respectively. As expected in this hypothesissetting study, none of the interaction terms for any findings for these outcomes were statistically significant. The interaction term (–1.27) for age exceeded our prespecified threshold of > 1 for the outcome of pain (Tab. 2). However, the direction of effect was opposite to our hypothesis. Older people appeared to benefit more from MDT compared with 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 (Tab. 3). Interaction terms for the other 3 effect modifiers (clear centralization, pain below knee, and high pain intensity) were below our thresholds for potential clinical importance.

Table 4 shows the effect of MDT compared with Back School separately for patients younger and older than 54 years. Older people improved 1.42 points for pain intensity and 3.51 points for disability, more than younger people, from MDT compared with Back School.



Discussion

      Statement of Principal Findings

The purpose of this hypothesis-setting, secondary analysis was to investigate whether 4 baseline characteristics (presence of clear centralization, pain location, pain intensity, and age) of patients with chronic LBP can identify those who respond better to MDT compared with Back School. Based on our results, the interaction term of –1.27 for age exceeded our prespecified threshold of > 1 for the outcome of pain, suggesting older people may benefit more from MDT compared with 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 with Back School.

      Strengths and Weaknesses of the Study

A strength of our study was that the data were derived from a high-quality RCT. [15] The trial collected important potential treatment effect modifiers from all patients that are likely to influence the response to MDT. Only 4 potential effect modifiers were selected a priori after consideration of the theoretical rationale and consultation with a specialist musculoskeletal physical therapist who is a credentialed MDT therapist. [29] This therapist has been an educator of the McKenzie Institute since 1986 and has been the International Director of Education for the McKenzie Institute International since 1999. [29] She is currently the only teaching member of the McKenzie Institute in Australia and teaches MDT courses internationally. [29] We avoided selecting a higher number of effect modifiers in order to minimize the chance of spurious findings. [39] The methodological approach of this study, based on recommendations in the literature, can act as a model for subgroup studies within RCTs in the rehabilitation field. Another contribution of this study is the interpretation of the actual findings leading to 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 modifiers. [40] 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.

We used a simple analysis that did not contain any covariates. This approach was chosen to minimize the risk of overfitting the model and because the resulting interaction effect size is exactly equal to the difference between treatment effect in one subgroup (eg, older age) and treatment effect in the other subgroup (eg, 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 in which we added sex and duration of symptoms to the models. For both pain and disability models, this analysis resulted in the interaction effect becoming marginally greater (–2.85; 95% CI = –5.90, 0.20 for pain and –1.35; 95% CI = –3.45, 0.74 for disability) than in the simple models.

      Meaning of the Study and Comparison With Other Studies

Our study showed that patients who were older than 54 years and received MDT compared with Back School experienced an additional reduction in pain of 1.27 points compared with young people. It is important to note that the interaction does not define the main effect of the interventions, but rather the difference in effect of treatment for older patients compared with young patients.6 The treatment effect within a subgroup is a combination of the interaction and the main treatment effect. [37] The findings presented in Table 4 show that MDT was statistically more effective for pain (1.42; 95% CI = 0.02, 2.83) compared with Back School in the subgroup of older people, whereas there was no difference between the 2 interventions in younger people (0.15; 95% CI = –1.38, 1.68). Similarly, for disability, MDT was statistically more effective for disability in the subgroup of older people (3.51; 95% CI = 1.42, 5.60) compared with Back School, whereas there was no difference between the 2 interventions in younger people (1.12; 95% CI = –1.11, 3.35). We only investigated treatment effects (MDT versus Back School) within subgroups where the interaction met our criteria for clinical importance to reduce the chance of spurious findings. [40]

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 that MDT may be more effective in older people raise the question of the potential mechanism underlying this hypothesis. One possibility is that older people were more adherent to the approach that is almost entirely a self-management intervention. Another possibility is that pain has a somewhat different physiological basis in older people and responds better to MDT. However, we do not have data to support these theories. These results may simply be spurious findings 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 2 previous studies that tested possible treatment effect modifiers for MDT. [17, 18] The first study recruited patients with acute LBP who received either MDT or usual care. [17] This study tested baseline pain, pain changes with position or movement, and presence of leg pain as potential effect modifiers. The authors found that these potential effect modifiers did not predict a more favorable response to MDT. The second study18 compared MDT with spinal manipulation in 350 patients with chronic back pain. The authors included 6 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 response. [18] They concluded that it was not possible to find any statistically significant predictive factor that identified a 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 or population or may simply be a spurious finding. Subgroup effects within trials are always specific to the control group. [37] We recommend that our results be interpreted carefully and that adequately powered replication studies are needed. These studies together suggest that it is difficult to identify powerful effect modifiers for MDT. This difficulty 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 that we would recommend.

In conclusion, we conducted a secondary analysis of an RCT to determine whether potential treatment effect modifiers for MDT could be identified in patients with chronic LBP and with a directional preference. We found that patients who were older appeared to respond better to MDT compared with Back School (the direction of effect was opposite to our initial hypothesis). Clear centralization, pain below the 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 small sample size. These findings, particularly of the potential effect modification effect of age, need testing in larger trials and with different comparisons.


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 Fundac¸ao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Coordenac¸ao de Aperfeic¸oamento de Pessoal de Nivel Superior (CAPES), and International Mechanical Diagnosis and Therapy Research Foundation (IMDTRF).



References:

  1. Tulder MV.
    Chapter 1. European guidelines.
    Eur Spine J. 2006;15:134–135.

  2. Waddell G.
    The Back Pain Revolution. 2nd ed.
    Edinburgh, United Kingdom:
    Churchill Livingstone; 2004.

  3. Menezes Costa Lda C, Maher CG, Hancock MJ, et al.
    The prognosis of acute and persistent low-back pain: a meta-analysis.
    CMAJ. 2012;184:E613–E624.

  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;18:147–152.

  5. Kent P, Keating JL.
    Classification in nonspecific low back pain: what methods do primary care clinicians currently use?
    Spine (Phila Pa 1976). 2005;30:1433–1440.

  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;42:797–805.

  8. Stanton TR, Hancock MJ, Appeldoorn AT, et al.
    What characterizes people who have an unclear classification using a treatmentbased classification algorithm for low back pain? A cross-sectional study.
    Phys Ther. 2013;93:345–355.

  9. Hebert JJ, Koppenhaver SL, Walker BF.
    Subgrouping patients with low back pain: a treatment-based approach to classification.
    Sports Health. 2011;3:534 –542.

  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;16:19– 30.

  11. McKenzie R, May S.
    The Lumbar Spine: Mechanical Diagnosis & Therapy. Vol 1. 2nd ed.
    Waikanae, New Zealand: Spinal Publications Ltd; 2003.

  12. Clare HA, Adams R, Maher CG.
    A systematic review of efficacy of McKenzie therapy for spinal pain.
    Aust J Physiother. 2004;50:209–216.

  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;31:254–262.

  14. Hefford C.
    McKenzie classification of mechanical spinal pain: profile of syndromes and directions of preference.
    Man Ther. 2008;13:75–81.

  15. Garcia AN, Costa Lda C, da Silva TM, et al.
    Effectiveness of Back School versus McKenzie exercises in patients with chronic nonspecific low back pain: a randomized controlled trial.
    Phys Ther. 2013; 93:729–747.

  16. Garcia AN, Gondo FL, Costa RA, 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;21:1250–1256.

  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, van Tulder MW, Lin CW, et al.
    The McKenzie method for chronic nonspecific low back pain: study protocol.
    Cochrane Database Syst Rev. 2012;3: CD009712.

  20. McKenzie R, May S.
    The Lumbar Spine: Mechanical Diagnosis & Therapy. Vol 2. 2nd ed.
    Waikanae, New Zealand: Spinal Publications Ltd; 2003.

  21. Sun X, Briel M, Busse JW, 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;10:101–111.

  22. Airaksinen O, Brox JI, Cedraschi C, et al.
    COST B13 Working Group on Guidelines for Chronic Low Back Pain Chapter 4.
    European Guidelines for the Management of Chronic Nonspecific Low Back Pain
    European Spine Journal 2006 (Mar); 15 Suppl 2: S192–300

  23. Kenney LW, Humphrey RH, Mahler DA.
    ACSM’s Guidelines for Exercise Testing and Prescription.
    Baltimore, MD: Williams & Wilkins; 1995.

  24. Heymans MW, van Tulder MW, Esmail R, et al.
    Back schools for nonspecific low back pain: a systematic review within the framework of the Cochrane Collaboration Back Review Group.
    Spine (Phila Pa 1976). 2005;30:2153–2163.

  25. McKenzie R.
    Trate Voceˆ Mesmo a Sua Coluna.
    Waikanae, New Zealand: Spinal Publication Ltd; 1998.

  26. Costa LO, Maher CG, Latimer J, 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;33:2459–2463.

  27. Costa LO, Maher CG, Latimer J, et al.
    Psychometric characteristics of the Brazilian-Portuguese versions of the Functional Rating Index and the Roland-Morris Disability Questionnaire.
    Spine (Phila Pa 1976). 2007;32:1902–1907.

  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;34:203–210.

  29. Dr Helen Clare.
    McKenzie Institute Australia. Available at:
    http://www.mckenziemdt.org.au/event/host/dr-helenclare/
    Accessed September 9, 2015.

  30. Paatelma M, Kilpikoski S, Simonen R, et al.
    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;40:858–863 .

  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; 21:630–636.

  32. Long A, May S, Fung T.
    The comparative prognostic value of directional preference and centralization: a useful tool for frontline clinicians?
    J Man Manip Ther. 2008; 16:248–254.

  33. Altman DG, Royston P.
    The cost of dichotomising continuous variables.
    BMJ. 2006;332:1080.

  34. Brookes ST, Whitely E, Egger M, et al.
    Subgroup analyses in randomized trials: risks of subgroup-specific analyses; power and sample size for the interaction test.
    J Clin Epidemiol. 2004;57:229–236.

  35. Hancock M, Herbert RD, Maher CG.
    A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions.
    Phys Ther. 2009;89:698–704.

  36. Kamper SJ, Maher CG, Hancock MJ, et al.
    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: 181–191.

  37. Hancock MJ, Kjaer P, Korsholm L, Kent P.
    Interpretation of subgroup effects in published trials.
    Phys Ther. 2013;93:852–859.

  38. Ferreira ML, Herbert RD, Ferreira PH, et al.
    A critical review of methods used to determine the smallest worthwhile effect of interventions for low back pain.
    J Clin Epidemiol. 2012;65:253–261.

  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, et al.
    Subgroup analyses in randomised controlled trials: quantifying the risks of falsepositives and false-negatives.
    Health Technol Assess. 2001;5:1–56

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