A Clinical Prediction Rule for Classifying Patients
with Low Back Pain who Demonstrate Short-term
Improvement with Spinal Manipulation

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

FROM:   Spine (Phila Pa 1976). 2002 (Dec 15);   27 (24):   2835–2843 ~ FULL TEXT


Timothy Flynn, PT, PhD, Julie Fritz, PT, PhD, Julie Whitman, PT, DSc,
Robert Wainner, PT, PhD, Jake Magel, PT, DSc, Daniel Rendeiro, PT, DSc,
Barbara Butler, PT, Matthew Garber, PT, DSc, and Stephen Allison, PT, PhD

U.S. Army-Baylor University Graduate Program in Physical Therapy,
San Antonio, Texas, USA.

STUDY DESIGN:   A prospective, cohort study of patients with nonradicular low back pain referred to physical therapy.

OBJECTIVE:   Develop a clinical prediction rule for identifying patients with low back pain who improve with spinal manipulation.

SUMMARY OF BACKGROUND DATA:   Development of clinical prediction rules for classifying patients with low back pain who are likely to respond to a particular intervention, such as manipulation, would improve clinical decision-making and research.

METHODS:   Patients with nonradicular low back pain underwent a standardized examination and then underwent a standardized spinal manipulation treatment program. Success with treatment was determined using percent change in disability scores over three sessions and served as the reference standard for determining the accuracy of examination variables. Examination variables were first analyzed for univariate accuracy in predicting success and then combined into a multivariate clinical prediction rule.

RESULTS:   Seventy-one patients participated. Thirty-two had success with the manipulation intervention. A clinical prediction rule with five variables (symptom duration, fear-avoidance beliefs, lumbar hypomobility, hip internal rotation range of motion, and no symptoms distal to the knee) was identified. The presence of four of five of these variables (positive likelihood ratio = 24.38) increased the probability of success with manipulation from 45% to 95%.

CONCLUSION:   It appears that patients with low back pain likely to respond to manipulation can be accurately identified before treatment.

From the Full-Text Article:


Attempts to identify effective interventions for patients with low back pain (LBP) have been largely unsuccessful. [65, 66] One explanation offered for the lack of evidence is the inability to define subgroups of patients most likely to respond to a particular intervention. [8, 39] Without the ability to match patients to specific interventions, clinicians are left without evidence or guidance for their decision-making. Because of the difficulty in subgrouping patients with LBP based on pathoanatomy, [67] attempts have been made to classify patients based on findings from the history and physical examination. [17, 49, 60, 64] Developing effective, clinically applicable methods for classifying patients with LBP could improve decisionmaking and outcomes by matching interventions to the patients they are most likely to benefit. Classification methods would also enhance the power of clinical research by permitting researchers to study more homogeneous groups of patients. [56] Identifying methods for classifying patients with LBP has been identified as an important research priority. [1, 6, 66]

Manipulation is an intervention commonly used in the treatment of individuals with LBP. Several randomized trials have found manipulation to be more effective than placebo [52, 54, 71] or other interventions. [16, 22, 36, 63] However, other studies have not shown any benefits for manipulation versus other interventions. [10, 26–28] The disparity may be partly attributable to the admission of a heterogeneous group of patients with LBP without an attempt to identify a priori those likely to benefit from the intervention. Other randomized trials have found manipulation to be more beneficial for a subgroup of patients with more acute symptoms [30, 42] or more limited straight-leg raise range of motion. [47] No previous studies have sought to develop a multifactorial classification rule that would maximize the prediction of success with manipulation before the intervention.

One subgroup of patients for whom manipulation is proposed to be effective comprises individuals with sacroiliac (SI) region dysfunction. [16, 19, 22, 29, 62, 71] Numerous clinical findings have been promoted as capable of identifying patients with SI dysfunction; however, previous studies have questioned the reliability and validity of many of these tests. [4, 9, 20, 21, 37, 40, 41, 44, 45, 50, 53, 61] Previous studies have generally examined individual tests for SI dysfunction in isolation and typically have not included other potentially important factors from the history or examination. An exception is the work published by Cibulka et al, who described a cluster of movement and provocative tests purported to identify SI joint dysfunction. [12–14] However, this test cluster was chosen based on the authors’ clinical experience, and the predictive validity is unknown. [12] Furthermore, most studies have used short-term pain relief with an injection of an anesthetic agent into the SI joint as the reference standard against which validity has been judged. [9, 21, 32, 44] The validity of using anesthetic joint blocks as a reference standard for diagnostic studies has not been demonstrated. [3, 32, 59] The reference standard should represent the condition of interest that the diagnostic test is attempting to identify. [55] If the goal of a test is to identify patients likely to respond to an intervention directed toward the SI region (e.g., manipulation), then the use of a criterion standard of short-term pain relief with an injection is questionable. A more viable alternative may be a longer duration response to the intervention in question. A study using a more “therapeutic” reference standard, which considers a broader variety of clinical findings and attempts to combine clinical findings, will be more useful in identifying a subgroup of patients with SI dysfunction who are likely to respond to spinal manipulation. The purpose of this study was to develop a clinical prediction rule for identifying patients with LBP likely to respond favorably to a specific manipulation technique. A variety of findings were considered against a reference standard of change in disability.


A prospective cohort study of patients with LBP was conducted at two outpatient facilities: Brooke Army Medical Center and Wilford Hall Air Force Medical Center. Patients were between the ages of 18 and 60 years, referred to physical therapy with a diagnosis related to the lumbosacral spine, and had a chief complaint of pain and/or numbness in the lumbar spine, buttock, and/or lower extremity. The baseline Oswestry disability score had to be at least 30%. Exclusion criteria were current pregnancy, signs consistent with nerve root compression (positive straight-leg raise at <45°, or diminished lower extremity strength, sensation, or reflexes), prior lumbar spine surgery, or a history of osteoporosis or spinal fracture. All patients were briefed on the purpose of the study and signed an informed consent approved by the Brooke Army Medical Center and Wilford Hall Air Force Medical Center Institutional Review Boards.

Therapists.   Eight licensed physical therapists participated. Four were residents in the U.S. Army-Baylor Post-Professional Doctoral Program in Orthopedic and Manual Physical Therapy, and four were instructors in the program. This program is designed to provide physical therapists serving in the U.S. Military with advanced training in orthopedic and manual physical therapy. A 1-day training session was conducted for participating therapists to standardize examination and treatment techniques.

Examination Procedures.   Patients completed a baseline examination including demographic information and a pain rating using an 11-point scale. [34] A pain diagram [46] was used to categorize symptoms as low back, buttock/thigh, or distal to the knee based on the distal-most extent of symptoms. [70] The Modified Oswestry Disability Questionnaire (OSW) assessed disability related to LBP. [25] The Fear-Avoidance Beliefs Questionnaire (FABQ) was used to assess the patient’s beliefs about the influence of activity on LBP. [69] The FABQ contains two subscales: one is related to general physical activity and the other to work. [69]

Patients underwent a standardized history and physical examination.   History included mechanism of injury, nature of current symptoms, and prior episodes of LBP. Patients were asked to rank sitting, standing, and walking as to which was best and worst with respect to symptoms. The examination included Waddell’s nonorganic signs. [68] Range of motion and status change [49] in symptoms with single lumbar movements were recorded. Supine straight-leg raise and prone hip rotation range of motion were measured. Posteroanterior spring testing [43] was performed for pain provocation and mobility at each lumbar level. Mobility was judged as normal, hypomobile, or hypermobile. Numerous special tests proposed to be diagnostic of SI dysfunction were performed (see Appendix). The tests were divided into three categories: position (tests assessing symmetry of bony landmarks), provocation (tests to reproduce symptoms), and mobility (tests assessing symmetry of pelvic motion). [37] The examination was repeated on the first 55 subjects by a second therapist blinded to the results of the first examiner to determine the reliability of the physical examination variables.

Figure 1

Treatment.   Because response to treatment served as the reference standard, all patients were treated with the same protocol for two sessions. At the first session, the therapist performed a manipulation technique with the patient supine. The therapist stood opposite the side to be manipulated. The patient was passively side-bent away from the therapist. The therapist passively rotated the patient and then delivered a quick posterior and inferior thrust through the anterior superior iliac spine (Figure 1). The side to be manipulated was determined with the following algorithm: first, the side of the positive standing flexion test; if this test was negative, the side of tenderness during sacral sulcus palpation was manipulated. If neither side was tender, the side reported by the patient to be more symptomatic was manipulated. If the patient was unable to identify a more symptomatic side, the therapist flipped a coin to determine the side. Although the manipulation was performed on one side only, Cibulka et al [12] found changes in innominate tilt on both sides of the pelvis after applying this technique. Therefore, whereas the algorithm provided a consistent approach, it is likely the manipulation affected bilateral SI regions.

After the manipulation, the therapist noted whether a cavitation was heard or felt by the therapist or patient. If a cavitation was experienced, the therapist proceeded to the other treatment components. If no cavitation was produced, the patient was repositioned, and the manipulation was attempted again. If no cavitation was experienced again, the therapist attempted to manipulate the opposite side. A maximum of two attempts per side was permitted. If no cavitation was produced after the fourth attempt, the therapist proceeded to the other treatment components. Two additional treatment components were included:

1) instruction in a supine pelvic tilt range of motion exercise (the patient was instructed to perform 10 repetitions, 3–4 times daily; and

2) instruction to maintain usual activity level within the limits of pain. [5]

The second treatment session occurred 2–4 days after the first. Before the second session, each patient completed an OSW questionnaire. Percentage improvement in OSW was calculated (initial score – final score)/initial score X 100). If improvement was >50%, the patient was categorized as a success, and study participation ended. If the patient showed <50% improvement, the therapist repeated the examination and the manipulation procedures. The third session occurred 2–4 days after the second. The patient again completed the OSW, and the percentage improvement from the initial score was calculated. If >50% improvement was noted, the patient was categorized as a success. If improvement was ≤50%, the patient was categorized as a nonsuccess. At this point, the patient’s study participation ended, and further treatment was administered as needed.

Data Analysis.   Kappa coefficients were calculated to determine the interrater reliability of the special tests for SI dysfunction. Patients were dichotomized based on success or nonsuccess with respect to the treatment. Success or nonsuccess was then used as the reference standard. Individual variables from the self-reports, history, and physical examination were tested for their univariate association with the reference standard using independent sample t tests for continuous variables and χ2 tests for categorical variables. Variables with a significance level of P < 0.15 were retained as potential prediction variables; a more liberal significance level was chosen at this stage to avoid excluding potential predictive variables. For continuous variables with a significant univariate association, sensitivity and specificity values were calculated for all possible cut-off points and then plotted as a receiver operator characteristic (ROC) curve. [31] The point on the curve nearest the upper lefthand corner represents the value with the best diagnostic accuracy, and this point was selected as the cut-off defining a positive test. [18] Sensitivity, specificity, and positive likelihood ratios (PLR) were calculated for all potential prediction variables. [57] The PLR is calculated as sensitivity/(1 – specificity) and indicates the increase in the probability of success given a positive test result. [58] A PLR of 1 indicates the test does nothing to alter the probability of success, whereas PLR values >1 increase the probability of success given a positive test result. According to Jaeschke et al, 33 PLR values between 2.0 and 5.0 generate small shifts in probability, values between 5.0 and 10.0 generate moderate shifts, and values >10.0 generate large and often conclusive shifts in probability. We chose to focus on the PLR as opposed to the negative LR because we were attempting to predict success with manipulation based on positive test results. Potential prediction variables were entered into a stepwise logistic regression equation to determine the most parsimonious set of predictors for success using a multivariate model. A significance of 0.05 was required to enter a variable into the model and a significance of 0.10 was required to remove it. Variables retained in the regression model were used to develop a multivariate clinical prediction rule for classifying patients as likely responders to manipulation.


Figure 2

Table 1

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Seventy-five patients entered the study. Four subjects (5%) did not return after the first session and were not included in the analysis. Two subjects left the study because of personal or work-related circumstances. One subject dropped out because of complications from an ongoing episode of gastrointestinal distress, and one subject failed to return for his final visit. Of the 71 patients completing the study, 29 (41%) were female and 59 (83%) had a prior history of LBP. The mean age was 37.6 ± 10.6 years (range 18–59 years). The mean OSW score at baseline was 42.4 ± 11.7, and at study conclusion 25.1 ± 13.9. The mean percent improvement in OSW over the study period was 41.0 ± 33.9% (range -29.0–100%). Thirty-two patients (45%) were classi- fied as treatment successes, and 39 (55%) were nonsuccesses. Twenty patients were successes after one manipulation session, 12 after two sessions. The mean improvement in OSW in the success group over the study period was 32.5 ± 12.6 points, with a mean percent improvement of 73.2 ± 15.8%. In the nonsuccess group, the mean OSW improvement was 6.2 ± 7.8 points, with a mean percent improvement of 14.6 ± 18.2% (Figure 2).

Among self-reported variables (Table 1), the FABQ work subscale, the presence of symptoms in the back only, and symptoms distal to the knee were retained as potential prediction variables. From the history (Table 2), duration of symptoms, increasing episode frequency, and ranking standing as the worst position were retained. Five variables were retained from the clinical examination (Table 3): left and right hip internal rotation, hypomobility and pain with lumbar spring testing, and peripheralization with single lumbar movement testing. The special tests for SI dysfunction along with the reliability coefficients are presented in Table 4. As a group, the provocation tests were more reliable with values ranging from fair to substantial agreement. The Gillet test was the only motion test to demonstrate at least moderate agreement. The anterior superior iliac spine and iliac crest in standing and the posterior superior iliac spine symmetry in sitting were the only symmetry tests to have at least fair agreement. Among the special tests for SI dysfunction (Table 5), only the compression– distraction test was retained in the predictive model, although positive findings were more common in the nonsuccess group. Cut-off values for retained continuous variables (duration of symptoms, FABQ work subscale, left and right hip internal rotation) were obtained from receiver operator characteristic curve analyses. Because of their similarity, left and right hip internal rotations were combined into a single variable. Cut-off scores and accuracy statistics for retained variables were calculated (Table 5). Among historical variables, duration of symptoms <16 days was most predictive of success (PLR = 4.39).

The 11 potential prediction variables were entered into the logistic regression. Five were retained in the final model: duration of symptoms <16 days, at least one hip with >35° of internal rotation, hypomobility with lumbar spring testing, FABQ work subscale score <19, and no symptoms distal to the knee (model χ2 = 48.5, df = 5, P < 0.001, Nagelkerke R2 = 0.67). These five variables were used to form the clinical prediction rule. Only six subjects (all in the success group) were positive for all five retained prediction variables at baseline (Table 6). Fourteen of 15 subjects with 4 of 5 variables present were in the success group. Of subjects with two or fewer variables present, 25 of 27 were in the nonsuccess group. Accuracy statistics were calculated for each level of the clinical prediction rule (Table 7). Based on the pretest probability of success with manipulation found in this study (45%), and the PLR values calculated, a subject with four or more variables present at baseline increases his or her probability of success with manipulation from 45% to 95%. If the criteria were changed to three or more variables present, the probability of success was only increased to 68%. If two or fewer variables were present, the probability of success was virtually unchanged.


Clinicians who routinely use spinal manipulation have encountered patients who experience a rapid, even dramatic improvement as a result of one or two treatments, whereas others change very little. The ability to accurately predict which patients will have which response a priori would be immensely beneficial for clinical decision-making. Similar to other studies, [21, 40, 41, 44] we were unable to show acceptable accuracy for any individual tests proposed to identify SI dysfunction. Furthermore, we found that the reliability of these tests in a population of individuals with LBP is less than optimal. As noted by previous researchers, provocation tests as a whole are more reliable tests than motion or symmetry tests. [9, 37] However, by considering other variables and combining findings, we were able to develop a clinical prediction rule that may be useful for assisting clinicians in classifying patients as likely to respond to this manipulation technique.

The developed clinical prediction rule contains five variables: duration of symptoms <16 days, at least one hip with >35° of internal rotation, lumbar hypomobility, no symptoms distal to the knee, and an FABQ work score <19. These findings are generally consistent with previous theories and research. Randomized trials have suggested that patients with more acute symptoms respond better to manipulation. [30, 42] Our results support this hypothesis. Hip rotation range of motion discrepancies have been reported in patients with LBP. [2, 14, 51] Previous studies in patients with “nonspecific” LBP have found greater external rotation than internal rotation. [2, 11, 51] As a whole, patients in this study had greater external than internal rotation; however, increased internal rotation was associated with manipulation success. Manipulation is thought to be indicated in the presence of hypomobility. Interestingly, although the technique used in this study is described as affecting the SI region, it was lumbar hypomobility that entered the prediction model. This finding reinforces the idea that the manipulation technique is not specific to the SI region but impacts the lumbar spine as well. [7, 17, 29] Manipulation is generally thought to be contraindicated in patients with radiculopathy. [5] We excluded patients with signs of nerve root compression. However, some patients with symptoms distal to the knee were included, and these patients tended not to succeed. Finally, the FABQ quantifies a patient’s fear of pain and subsequent avoidance of activity. [69] The FABQ work subscale has been previously correlated with work loss and disability in patients with chronic and acute LBP. [24, 35, 69] Our results suggest that patients with high levels of fear-avoidance beliefs about work activities are unlikely to respond to manipulation. These individuals likely require an alternative treatment approach. [15]

The usefulness of a clinical prediction rule for classifying patients is best expressed using likelihood ratio statistics. The PLR expresses the change in odds favoring the outcome when the patient meets the prediction rule’s criteria. [57] In our sample, 45% of subjects were successful without any attempt at prediction. In other words, randomly manipulating individuals with nonradicular LBP may result in success about 45% of the time. Using a criterion of at least 4 of 5 variables present at baseline (PLR = 24.38), the probability of success is raised to 95%; therefore, these individuals should be manipulated. If only three variables are present, the probability increased to 68%, which is likely sufficient to warrant an attempt at manipulation in these patients. When two or fewer variables are present, the probability of success changes little, and clinicians should consider alternative treatments if such can be identified that may have a probability of success >%45%.

An important consideration in the examination of diagnostic tests is the reference standard against which tests are judged. Previous studies of tests for SI dysfunction have generally used immediate pain relief with SI joint anesthetic injection. In our opinion, clinicians performing these tests are not as interested in pathoanatomic speculations (i.e., is the SI joint generating the pain?) as they are in determining if the patient will respond to a particular intervention. We therefore used a reference standard representative of the desired outcome of the tests (i.e., responding to manipulation). The use of 50% improvement on the OSW as the reference standard was based on previous research involving the intervention used in this study. In three previous studies, patients thought to be matched to this intervention experienced mean improvements in OSW scores from 57% to 83%, whereas patients receiving unmatched interventions experienced mean improvements ranging from 20% to 38% over a 1–4-week period. [16, 22, 23] We therefore thought that requiring 50% improvement in the OSW over a 2–4-day period would provide adequate distinction between patients responding to the intervention and those simply benefiting from the favorable natural history of LBP.

The patients participating in this study should be representative of patients seeking physical therapy services in large metropolitan areas. The eight physical therapists involved in the study had varying degrees of skills in spinal manipulative therapy. However, the manipulation technique employed is a standard technique used in physical therapist education programs. Therefore, the results should be generalizable to outpatient clinics treating individuals with LBP.

A three-step process for developing and testing a clinical prediction rule is recommended. [48] The first step is developing the rule, the second step is validation, and the third step is an assessment of the impact of the rule on clinical behavior. The purpose of the present study was to develop a clinical prediction rule that would identify individuals with LBP who respond favorably to a specific spinal manipulation. In the present study, only one manipulation technique was used, and it is unknown whether other techniques would provide similar results. Validation of the proposed clinical prediction rule is the purpose of an ongoing randomized controlled trial where subjects meeting the prediction criteria receive either the spinal manipulation technique or a competing therapy. Ultimately, any clinical prediction rule must be shown to improve outcomes and clinical decision-making before it can be advocated for widespread use. [38, 48]

Key Points

  • Special tests purported to identify patients with low back pain who will respond
    to manipulation were largely unsuccessful in doing so.

  • The best univariate predictor of success with manipulation was the duration
    of the current symptoms; more acute symptoms were more likely to
    respond favorably.

  • Five variables were identified to form a clinical prediction rule for patients with
    low back pain likely to respond favorably to spinal manipulation:

    duration of symptoms <16 days,
    FABQ work subscale score <19,
    at least one hip with >35° of internal rotation range of motion,
    hypomobility in the lumbar spine, and
    no symptoms distal to the knee

  • The presence of four of five variables in the prediction rule increased the
    likelihood of success with manipulation from 45% to 95%.


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