Estimating anchor-based minimal important change using longitudinal confirmatory factor analysis.

PURPOSE: The minimal important change (MIC) is defined as the smallest within-individual change in a patient-reported outcome measure (PROM) that patients on average perceive as important. We describe a method to estimate this value based on longitudinal confirmatory factor analysis (LCFA). The method is evaluated and compared with a recently published method based on longitudinal item response theory (LIRT) in simulated and real data. We also examined the effect of sample size on bias and precision of the estimate. METHODS: We simulated 108 samples with various characteristics in which the true MIC was simulated as the mean of individual MICs, and estimated MICs based on LCFA and LIRT. Additionally, both MICs were estimated in existing PROMIS Pain Behavior data from 909 patients. In another set of 3888 simulated samples with sample sizes of 125, 250, 500, and 1000, we estimated LCFA-based MICs. RESULTS: The MIC was equally well recovered with the LCFA-method as using the LIRT-method, but the LCFA analyses were more than 50 times faster. In the Pain Behavior data (with higher scores indicating more pain behavior), an LCFA-based MIC for improvement was estimated to be 2.85 points (on a simple sum scale ranging 14-42), whereas the LIRT-based MIC was estimated to be 2.60. The sample size simulations showed that smaller sample sizes decreased the precision of the LCFA-based MIC and increased the risk of model non-convergence. CONCLUSION: The MIC can accurately be estimated using LCFA, but sample sizes need to be preferably greater than 125.

Differential item functioning of the PROMIS physical function, pain interference, and pain behavior item banks across patients with different musculoskeletal disorders and persons from the general population.

PURPOSE: To investigate the validity of comparisons across patients with different musculoskeletal disorders and persons from the general population by evaluating differential item functioning (DIF) for the PROMIS physical function (PROMIS-PF), pain interference (PROMIS-PI), and pain behavior (PROMIS-PB) item banks. METHODS: Patients with chronic pain, rheumatoid arthritis (RA), or osteoarthritis (OA); patients receiving physiotherapy (PT); and persons from the Dutch general population completed the full Dutch-Flemish PROMIS-PF (121-items), PROMIS-PI (40-items), or PROMIS-PB (39-items) banks. DIF was assessed with ordinal logistic regression models and McFadden's pseudo R2-change of ≥ 2% as critical value. The impact of DIF on item scores and the T-scores per bank was examined by inspecting item characteristic curves (ICCs) and test characteristic curves (TCCs). RESULTS: 2762 patients with chronic pain, 2029 with RA, 1247 with OA, 805 receiving PT, and 1310 healthy persons participated. For the PROMIS-PF, 25 out of 121 items were flagged for DIF, of which 10 items were flagged in multiple comparisons. For the PROMIS-PI, only 2 out of 40 items were flagged for DIF and for the PROMIS-PB, only 3 out of 39 items. Most DIF items had R2 values just above the critical value of 2% and all showed uniform DIF. The ICCs and TCCs showed that the magnitude and impact of DIF on the item and T-scores were negligible. CONCLUSIONS: This study supports the universal applicability of PROMIS across (patient) populations. Comparisons across patients with different musculoskeletal disorders and persons from the general population are valid, when applying the PROMIS-PF, PROMIS-PI, and PROMIS-PB banks.

Physicians using spinal manipulative treatment in The Netherlands: a description of their characteristics and their patients.

BACKGROUND: Various health care professionals apply Spinal Manipulative Treatment (SMT) in daily practice. While the characteristics of chiropractors and manual therapists and the characteristics of their patient populations are well described, there is little research about physicians who use SMT techniques. A distinct group of physicians in The Netherlands has been trained in musculoskeletal (MSK) medicine, which includes the use of SMT. Our objective was to describe the characteristics of these physicians and their patient population. METHODS: All registered MSK physicians were approached with questionnaires and telephone interviews to collect data about their characteristics. Data about patient characteristics were extracted from a web-based register. In this register physicians recorded basic patient data (age, gender, the type and duration of the main complaint, concomitant complaints and the type of referral) at the first consultation. Patients were invited to fill in web-based questionnaires to provide baseline data about previous treatments and the severity of their main complaint. Functional impairment was measured with Patient Reported Outcome Measures (PROMs). RESULTS: Questionnaires were sent to 138 physicians of whom 90 responded (65%). Most physicians were trained in MSK medicine after a career in other medical specialities. They reported to combine their SMT treatment with a variety of diagnostic and treatment options part of which were only permissible for physicians, such as prescription medication and injections. The majority of patients presented with complaints of long duration (62.1% > 1 year), most frequently low back pain (48.1%) or neck pain (16.9%), with mean scores of 6.0 and 6.2, respectively, on a 0 to10 numerical rating scale (NRS) for pain intensity. Mean scores on all PROMs showed moderate impairment. Patients most frequently reported previous treatment by physical therapists (68.1%), manual therapists (37.7%) or chiropractors (17.0%). CONCLUSION: Our study showed that MSK physicians in The Netherlands used an array of SMT techniques. They embedded their SMT techniques in a broad array of other diagnostic and treatment options, part of which were limited to medical doctors. Most patients consulted MSK physicians with spinal pain of long duration with moderate functional impairment.

The influence of study population and definition of improvement on the smallest detectable change and the minimal important change of the neck disability index.

BACKGROUND: Reported values of the minimal important change (MIC) and the smallest detectable change (SDC) for the neck disability index (NDI) differ strongly, raising questions about the generalizability of these parameters. The SDC and the MIC are possibly influenced by the study design or by the study population. We studied the influence of the type of anchor, the definition of improvement and population characteristics on the SDC and the MIC of the NDI. METHODS: A cohort study including 101 patients with non-specific, chronic neck pain. SDC and MIC were calculated using two types of external anchors. For each anchor we applied two different definitions to dichotomize the population into improved and unimproved patients. The influence of patient characteristics was assessed in relevant subgroups: patients with or without radiating pain and patients with different baseline scores. RESULTS: The influence of different anchors and different definitions of improvement on estimates of the SDC and the MIC was only minimal. The SDC and the MIC were similar for subgroups of patients with or without radiation, but differed strongly for subgroups of patients with higher or lower baseline scores. CONCLUSIONS: Our study shows that estimates of the SDC and the MIC of the NDI can be influenced by population characteristics. It is concluded that we cannot adopt a single change score to define relevant change by combining the result of previous studies.

Responsiveness and Minimal Important Change of the PROMIS Pain Interference Item Bank in Patients Presented in Musculoskeletal Practice.

We evaluated the responsiveness of the Patient Reported Outcome Information System Pain Interference item bank in patients with musculoskeletal pain by testing predefined hypotheses about the relationship between the change scores on the item bank, change scores on legacy instruments and Global Ratings of Change (GRoC), and we estimated Minimal Important Change (MIC). Patients answered the full Dutch-Flemish V1.1 item bank. From the responses we derived scores for the standard 8-item short form (SF8a) and a CAT-score was simulated. Correlations between the change scores on the item bank, GRoC and legacy instruments were calculated, together with Effect Sizes, Standardized Response Means, and Area Under the Curve. GRoC were used as an anchor for estimating the MIC with (adjusted) predictive modeling. Of 1,677 patients answering baseline questionnaires 960 completed follow-up questionnaires at 3 months. The item bank correlated moderately high with the GRoC (Spearman's rho 0.63) and with the legacy instruments (Pearson's R ranging from .45 to .68). It showed a high ES (.97) and Standardized Response Means (.71), and could distinguish well between improved and not improved patients based on the GRoC (Area Under the Curve .77). Comparable results were found for the derived SF8a and CAT-scores. The MIC was estimated to be 3.2 (CI 2.6-3.7) T-score points. PERSPECTIVE: Our study supports the responsiveness of the PROMIS-PI item bank in patients with musculoskeletal complaints. Almost all predefined hypotheses were met (94%). The PROMIS-PI item bank correlated well with several legacy instruments which supports generic use of the item bank. MIC for PROMIS-PI was estimated to be 3.2 T-score points.

A confirmatory factor analysis approach was found to accurately estimate the reliability of transition ratings.

INTRODUCTION: Transition ratings (TRs) are single item measures which ask patients to report on their health change. They allow for a simple assessment of improvement or deterioration and are frequently used as an "anchor" to determine interpretation thresholds on a patient-reported outcome measure (PROM). Despite their widespread use, a routinely applicable method to assess their reliability is lacking. This paper introduces a method to estimate the reliability of TRs based on confirmatory factor analysis (CFA) for categorical data. METHOD: We modelled longitudinal PROM data as independent factors representing Time 1 and Time 2 in a CFA model. PROM items taken at Time 1 (T1) loaded on the first factor, although the same items taken at Time 2 (T2) loaded on the second. The TR item loaded onto both T1 and T2 factors. Three models with various constraints on the loadings and thresholds were examined. The communality (R2) statistic was used as a measure of the TR reliability. The approach was evaluated using simulated data and exemplified in four empirical datasets. RESULTS: The simplest CFA model without constraints on the item loadings and thresholds performed equivalently to models with constraints on loadings and thresholds over time. Further constraints on the TR item loadings to be equal and opposite over time caused biased TR reliability estimates if the T1 and T2 loadings differed in magnitude. In the four empirical datasets, reliability of TRs ranged from 0.27 to 0.48. In three examples the TR had numerically stronger loading on T2 than on T1. DISCUSSION AND CONCLUSIONS: Results support the use of the proposed method in understanding the reliability of TRs. Empirical study results reflect the typical range of reliability that has previously been reported for single items. Methodological considerations to improve TR reliability are presented, and developments of this method, are posited.

Pain trajectories and possible predictors of a favourable course of low back pain in patients consulting musculoskeletal physicians in The Netherlands.

BACKGROUND: In The Netherlands, low back pain patients can consult physicians specialized in musculoskeletal (MSK) medicine. Previous studies have reported on the characteristics of patients consulting MSK physicians, and the treatment options used. There are no studies yet reporting on the course of Low Back Pain (LBP) after treatment by musculoskeletal (MSK) physicians in The Netherlands. METHODS: In an observational cohort study MSK physicians recorded data about all low back pain patients presenting for a first consultation. At baseline they recorded age, gender, type and duration of the main complaint, and concomitant complaints. At the end of treatment they recorded the type of treatment and the number of treatment sessions. Patients were recruited to answer questionnaires at baseline, and at 6-weekly intervals during a follow-up period of six months. Patient questionnaires included information about previous medical consumption, together with PROMs measuring the level of pain and functional status. Latent Class Growth Analysis (LCGA) was used to classify patients into different groups according to their pain trajectories. Baseline variables were evaluated as predictors of a favourable trajectory using logistic regression analyses, and treatment variables were evaluated as possible confounders. RESULTS: A total of 1377 patients were recruited, of whom 1117 patients (81%) answered at least one follow-up measurement. LCGA identified three groups of patients with distinct pain trajectories. A first group (N = 226) with high pain levels showed no improvement, a second group (N = 578) with high pain levels showed strong improvement, and a third group (N = 313) with mild pain levels showed moderate improvement. The two groups of patients presenting with high baseline pain scores were compared, and a multivariable model was constructed with possible predictors of a favourable course. Male gender, previous specialist visit, previous pain clinic visit, having work, a shorter duration of the current episode, and a longer time since the complaints first started were predictors of a favourable course. The multivariable model showed a moderate area under the curve (0.68) and a low explained variance (0.09). CONCLUSIONS: In low back pain patients treated by musculoskeletal physicians in The Netherlands three different pain trajectories were identified. Baseline variables were of limited value in predicting a favourable course.

Validation of the Dutch-Flemish PROMIS Pain Interference Item Bank in Patients With Musculoskeletal Complaints.

STUDY DESIGN: A cross-sectional study. OBJECTIVE: The aim of this study was to validate the Dutch-Flemish PROMIS Pain Interference item bank in patients with musculoskeletal complaints. SUMMARY OF BACKGROUND DATA: PROMIS item banks have been developed and validated in the US. They need to be further validated in various patient populations and in different languages. METHODS: One thousand six hundred seventy-seven patients answered the full item bank. A Graded Response Model (GRM) was used to study dimensionality with confirmatory factor analyses and by assessing local independency. Monotonicity was evaluated with Mokken scaling. An Item Response Theory (IRT) model was used to study item fit and to estimate slope and threshold parameters. Differential item functioning (DIF) for language, age, and gender was assessed using ordinal logistic regression analyses. DIF for language was evaluated by comparing our data with a similar US sample. Hypotheses concerning construct validity were tested by correlating item bank-scores with scores on several legacy instruments. RESULTS: The GRM showed suboptimal evidence of unidimensionality in confirmatory factor analysis [Comparative Fit Index (CFI): 0.903, Tucker-Lewis Index (TLI): 0.897, Root Mean Square Error of Approximation (RMSEA): 0.144], and 99 item pairs with local dependence. A bifactor model showed good fit (CFI: 0.964, TLI: 0.961, RMSEA: 0.089), with a high Omega-H (0.97), a high explained common variance (ECV: 0.81), and no local dependence. Sufficient monotonicity was shown for all items (Mokken H(i): 0.367-0.686). The unidimensional IRT model showed good fit (only two items with S-X < 0.001), with slope parameters ranging from 1.00 to 4.27, and threshold parameters ranging from -1.77 to 3.66. None of the items showed DIF for age or gender. One item showed DIF for language. Correlations with legacy instruments were high (Pearson R: 0.53-0.75), supporting construct validity. CONCLUSION: The high omega-H and the high ECV indicate that the item bank could be considered essentially unidimensional. The item bank showed good item fit, good coverage of the pain interference trait, and good construct validity. LEVEL OF EVIDENCE: N/A.

Psychometric properties of the Dutch-Flemish Patient-Reported Outcomes Measurement Information System Pain Behavior item bank in patients with musculoskeletal complaints.

We studied the psychometric properties of the 39-item v1.1 Dutch-Flemish Patient-Reported Outcomes Measurement Information System Pain Behavior item bank in a sample of 1,602 patients with musculoskeletal complaints. We evaluated the assumptions of the underlying item response theory (IRT) model (unidimensionality and local dependency with confirmatory factor analyses), and monotonicity with scalability coefficients). We studied the IRT model fit of all items and estimated the item parameters of the IRT model. Differential item functioning (DIF) was studied for age and gender, and DIF for language was studied as a measure of cross-cultural validity. Confirmatory factor analyses showed suboptimal fit of a unidimensional model, but a bifactor model showed low risk of bias when a unidimensional model was assumed (Omega H = .92, explained common variance of .70). Fifteen item pairs (2%) were locally dependent. Five items showed poor scalability. All items fitted the IRT model; slope parameters ranged from .60 to 2.00, and threshold parameters from -2.05 to 6.80. One item showed DIF for age, 1 item DIF for gender, and 5 items showed DIF for language, but the impact on total scores was low. Our study shows limitations of the Dutch-Flemish Patient-Reported Outcomes Measurement Information System Pain Behavior item bank when used in a primary care population with musculoskeletal complaints. PERSPECTIVE: We studied the psychometric properties of the Dutch-Flemish Patient-Reported Outcomes Measurement Information System Pain Behavior item bank in a large primary care population of patients with musculoskeletal complaints. It showed that the Pain Behavior item bank has limitations when used in this population.

Variance in manual treatment of nonspecific low back pain between orthomanual physicians, manual therapists, and chiropractors.

OBJECTIVE: The aim of the study was to identify differences in the diagnosis and treatment of nonspecific low back pain among 3 professional groups in the Netherlands: orthomanual physicians, manual therapists, and chiropractors. METHODS: Information was obtained from training materials from professional groups, literature searches, and observation of selected practitioners at work. RESULTS: In The Netherlands, there are differences in education between the 3 professional groups. The focus of orthomanual medicine is on abnormal positions of components of the skeleton and symmetry in the spine. Manual therapy focuses on functional disorders of the musculoskeletal system. Chiropractic focuses on the musculoskeletal and nervous systems in relation to patients' health in general. Orthomanual medicine considers inspection and palpation the most important diagnostic tools. Manual therapists and chiropractors additionally perform tests to determine functional disorders and manual therapists evaluate psychosocial influences. Chiropractors take radiographs if necessary. Orthomanual physicians apply mobilization techniques using fixed protocols. Manual therapists and chiropractors use various manipulation and mobilization techniques and their manipulation techniques differ in amplitude and velocity. CONCLUSIONS: Diagnostic techniques and treatment methods of the 3 professional groups differ considerably. For more accurate reporting of the efficacy of manipulative and mobilizing therapies, the characteristics of treatments should be described in more detail when reported in studies such as randomized clinical trials.