Minimal important change (MIC) based on a predictive modeling approach was more precise than MIC based on ROC analysis

How strong should my anchor be for estimating group and individual level meaningful change? A simulation study assessing anchor correlation strength and the impact of sample size, distribution of change scores and methodology on establishing a true meaningful change threshold

PURPOSE

Treatment benefit as assessed using clinical outcome assessments (COAs), is a key endpoint in many clinical trials at both the individual and group level. Anchor-based methods can aid interpretation of COA change scores beyond statistical significance, and help derive a meaningful change threshold (MCT). However, evidence-based guidance on the selection of appropriately related anchors is lacking.

METHODS

A simulation was conducted which varied sample size, change score variability and anchor correlation strength to assess the impact of these variables on recovering the simulated MCT for interpreting individual and group-level results. To assess MCTs derived at the individual-level (i.e. responder definitions; RDs), Receiver Operating Characteristic (ROC) curves and Predictive Modelling (PM) analyses were conducted. To assess MCTs for interpreting change at the group-level, the mean change method was conducted.

RESULTS

Sample sizes, change score variability and magnitude of anchor correlation affected accuracy of the estimated MCT. For individual-level RDs, ROC curves were less accurate than PM methods at recovering the true MCT. For both methods, smaller samples led to higher variability in the returned MCT, but higher variability still using ROC. Anchors with weaker correlations with COA change scores had increased variability in the estimated MCT. An anchor correlation of around 0.50-0.60 identified a true MCT cut-point under certain conditions using ROC. However, anchor correlations as low as 0.30 were appropriate when using PM under certain conditions. For interpreting group-level results, the MCT derived using the mean change method was consistently underestimated regardless of the anchor correlation.

CONCLUSION

Sample size and change score variability influence the necessary anchor correlation strength when recovering individual-level RDs. Often, this needs to be higher than the commonly accepted threshold of 0.30. Stronger correlations than 0.30 are required when using the mean change method. Results can assist researchers selecting and assessing the quality of anchors.

The challenges inherent with anchor-based approaches to the interpretation of important change in clinical outcome assessments

PURPOSE

Anchor-based methods are group-level approaches used to derive clinical outcome assessment (COA) interpretation thresholds of meaningful within-patient change over time for understanding impacts of disease and treatment. The methods explore the associations between change in the targeted concept of the COA measure and the concept measured by the external anchor(s), typically a global rating, chosen as easier to interpret than the COA measure. While they are valued for providing plausible interpretation thresholds, group-level anchor-based methods pose a number of inherent theoretical and methodological conundrums for interpreting individual-level change.

METHODS

This investigation provides a critical appraisal of anchor-based methods for COA interpretation thresholds and details key biases in anchor-based methods that directly influences the magnitude of the interpretation threshold.

RESULTS

Five important research issues inherent with the use of anchor-based methods deserve attention: (1) global estimates of change are consistently biased toward the present state; (2) the use of static current state global measures, while not subject to artifacts of recall, may exacerbate the problem of estimating clinically meaningful change; (3) the specific anchor assessment response(s) that identify the meaningful change group usually involves an arbitrary judgment; (4) the calculated interpretation thresholds are sensitive to the proportion of patients who have improved; and (5) examination of anchor-based regression methods reveals that the correlation between the COA change scores and the anchor has a direct linear relationship to the magnitude of the interpretation threshold derived using an anchor-based approach; stronger correlations yielding larger interpretation thresholds.

CONCLUSIONS

While anchor-based methods are recognized for their utility in deriving interpretation thresholds for COAs, attention to the biases associated with estimation of the threshold using these methods is needed to progress in the development of standard-setting methodologies for COAs.

Minimal important difference and patient acceptable symptom state for common outcome instruments in patients with a closed humeral shaft fracture - analysis of the FISH randomised clinical trial data

Background

Two common ways of assessing the clinical relevance of treatment outcomes are the minimal important difference (MID) and the patient acceptable symptom state (PASS). The former represents the smallest change in the given outcome that makes people feel better, while the latter is the symptom level at which patients feel well.

Methods

We recruited 124 patients with a humeral shaft fracture to a randomised controlled trial comparing surgery to nonsurgical care. Outcome instruments included the Disabilities of Arm, Shoulder, and Hand (DASH) score, the Constant-Murley score, and two numerical rating scales (NRS) for pain (at rest and on activities). A reduction in DASH and pain scores, and increase in the Constant-Murley score represents improvement. We used four methods (receiver operating characteristic [ROC] curve, the mean difference of change, the mean change, and predictive modelling methods) to determine the MID, and two methods (the ROC and 75th percentile) for the PASS. As an anchor for the analyses, we assessed patients’ satisfaction regarding the injured arm using a 7-item Likert-scale.

Results

The change in the anchor question was strongly correlated with the change in DASH, moderately correlated with the change of the Constant-Murley score and pain on activities, and poorly correlated with the change in pain at rest (Spearman’s rho 0.51, -0.40, 0.36, and 0.15, respectively).

Depending on the method, the MID estimates for DASH ranged from -6.7 to -11.2, pain on activities from -0.5 to -1.3, and the Constant-Murley score from 6.3 to 13.5.

The ROC method provided reliable estimates for DASH (-6.7 points, Area Under Curve [AUC] 0.77), the Constant-Murley Score (7.6 points, AUC 0.71), and pain on activities (-0.5 points, AUC 0.68).

The PASS estimates were 14 and 10 for DASH, 2.5 and 2 for pain on activities, and 68 and 74 for the Constant-Murley score with the ROC and 75th percentile methods, respectively.

Conclusion

Our study provides credible estimates for the MID and PASS values of DASH, pain on activities and the Constant-Murley score, but not for pain at rest. The suggested cut-offs can be used in future studies and for assessing treatment success in patients with humeral shaft fracture.

Trial registration

ClinicalTrials.gov NCT01719887, first registration 01/11/2012.

Patient-reported outcome measures as an outcome variable in sports medicine research

Injury prevention and rehabilitation research often address variables that would be considered clinician-oriented outcomes, such as strength, range of motion, laxity, and return-to-sport. While clinician-oriented variables are helpful in describing the physiological recovery from injury, they neglect the patient perspective and aspects of patient-centered care. Variables that capture patient perspective are essential when considering the impact of injury and recovery on the lives of patients. The inclusion of patient-reported outcome measures (PROMs) as dependent variables in sports medicine research, including injury prevention and rehabilitation research, provides a unique perspective regarding the patient's perception of their health status, the effectiveness of treatments, and other information that the patient deems important to their care. Over the last 20 years, there has been a significant increase in the use of PROMs in sports medicine research. The growing body of work gives opportunity to reflect on what has been done and to provide some ideas of how to strengthen the evidence moving forward. This mini-review will discuss ideas for the inclusion of PROMs in sports medicine research, with a focus on critical factors, gaps, and future directions in this area of research. Important elements of research with PROMs, including instrument selection, administration, and interpretation, will be discussed and areas for improvement, consideration, and standardization will be provided.

Minimal important change was on the lower spectrum of previous estimates and responsiveness was sufficient for core outcomes in chronic low back pain

OBJECTIVES

The objective of this study was to estimate the minimal important change (MIC) and responsiveness of core patient reported outcome measures for chronic low back pain (LBP) and Modic changes.

STUDY DESIGN AND SETTING

In the Antibiotics in Modic changes (AIM) trial we measured disability (RMDQ, ODI), LBP intensity (NRS) and health-related quality of life (EQ5D) electronically at baseline, three- and 12-month follow-up. MICs were estimated using Receiver Operating Curve (ROC) curve and Predictive modeling analyses against the global perceived effect. Credibility of the estimates was assessed by a standardized set of criteria. Responsiveness was assessed by a construct and criterion approach according to COSMIN guidelines.

RESULTS

The MIC estimates of RMDQ, ODI and NRS scores varied between a 15-40% reduction, depending on including "slightly improved" in the definition of MIC or not. The MIC estimates for EQ5D were lower. The credibility of the estimates was moderate. For responsiveness, five out of six hypotheses were confirmed and AUC was >0.7 for all PROMs.

CONCLUSION

When evaluated in a clinical trial of patients with chronic LBP and Modic changes, MIC thresholds for all PROMs were on the lower spectrum of previous estimates, varying depending on the definition of MIC. Responsiveness was sufficient.

Psychological Readiness to Return to Sport After Anterior Cruciate Ligament Reconstruction in the Adolescent Athlete

CONTEXT

Psychological readiness to return to sport has been shown to be associated with future play after anterior cruciate ligament (ACL) reconstruction surgery but has not been extensively studied in adolescent athletes.

OBJECTIVE

To investigate the psychometric properties of the Anterior Cruciate Ligament-Return to Sport after Injury (ACL-RSI) scale in adolescent athletes at multiple time points after ACL reconstruction surgery and determine whether psychological readiness scores at 6 months predict return to competition sport at 12 months.

DESIGN

Case series.

SETTING

Private orthopaedic clinic.

PATIENTS OR OTHER PARTICIPANTS

A total of 115 adolescent athletes (65 girls, 50 boys) 17 years and younger who had undergone primary unilateral ACL reconstruction.

MAIN OUTCOME MEASURE(S)

The ACL-RSI scale was administered at 6 and 12 months after surgery, and return-to-sport status was also documented. Factor analysis was undertaken and predictive validity assessed using between-groups comparisons and receiver operating characteristic (ROC) curve statistics.

RESULTS

The ACL-RSI scores increased between 6 and 12 months (55 to 71; P < .001, effect size = 0.98). No floor or ceiling effects were present, and the scale had high internal consistency (Cronbach α at 6 months = 0.91 and at 12 months = 0.94). Principal component analysis showed that 2 factors were present: the first represented performance confidence and risk appraisal and the second, emotions. For the full-scale ACL-RSI, scores at 6 months had acceptable predictive ability for a return to play at 12 months (area under the ROC curve = 0.7, P = .03). When the 2 identified factors were analyzed separately, the emotions factor also had acceptable predictive ability (area under the ROC curve = 0.73, P = .009), but the confidence in performance and risk appraisal factors had poor predictive ability (area under the ROC curve = 0.59, P = .09).

CONCLUSIONS

Greater psychological readiness was associated with return to sport in adolescent athletes after ACL reconstruction, with the athletes' emotional response appearing to be more influential than their confidence in their performance or their appraisal of risk.

Meaningful thresholds for patient-reported outcomes following interventions for anterior cruciate ligament tear or traumatic meniscus injury: a systematic review for the OPTIKNEE consensus

OBJECTIVE

We synthesised and assessed credibility (ie, trustworthiness) of thresholds that define meaningful scores for patient-reported outcome measures (PROMs) following interventions for anterior cruciate ligament (ACL) tear or traumatic meniscus injury.

DESIGN

Systematic review, narrative synthesis.

DATA SOURCES

We searched five databases, handsearched references of included studies and tracked citations.

ELIGIBILITY

Included studies investigated: individuals with ACL tear or meniscus injury; mean age <35 years; and PROM thresholds calculated using any method to define a minimal important change (MIC) or a meaningful post-treatment score (Patient Acceptable Symptom State (PASS) or Treatment Failure).

RESULTS

We included 18 studies (15 ACL, 3 meniscus). Three different methods were used to calculate anchor-based MICs across 9 PROMs, PASS thresholds across 4 PROMs and treatment failure for 1 PROM. Credibility was rated 'high' for only one study-an MIC of 18 for the Knee injury and Osteoarthritis Outcome Score Quality-of-life (KOOS-QOL) subscale (using the MID Credibility Assessment Tool). Where multiple thresholds were calculated among 'low' credibility thresholds in ACL studies, MICs converged to within a 10-point range for KOOS-Symptoms (-1.2 to 5.4) and function in daily living (activities of daily living, ADL 0.5-8.1) subscales, and the International Knee Documentation Committee Subjective Knee Form (7.1-16.2). Other PROM thresholds differed up to 30 points. PASS thresholds converged to within a 10-point range in KOOS-ADL for ACL tears (92.3-100), and KOOS-Symptoms (73-78) and KOOS-QOL (53-57) in meniscus injuries.

CONCLUSION

Meaningful PROM thresholds were highly susceptible to study heterogeneity. While PROM thresholds can aid interpretability in research and clinical practice, they should be cautiously interpreted.

Likely change indexes improve estimates of individual change on patient-reported outcomes

PURPOSE

Individual change on a patient-reported outcome (PRO) measure can be assessed by statistical significance and meaningfulness to patients. We explored the relationship between these two criteria by varying the confidence levels of the coefficient of repeatability (CR) on the Patient-Reported Outcomes Measurement Information System (R) Physical Function (PF) 10a (PF10a) measure.

METHODS

In a sample of 1129 adult cancer patients, we estimated individual-change thresholds on the PF10a from baseline to 6 weeks later with the CR at 50%, 68%, and 95% confidence. We also assessed agreement with group- and individual-level thresholds from anchor-based methods [mean change and receiver operating characteristic (ROC) curve] using a PF-specific patient global impression of change (PGIC).

RESULTS

CRs at 50%, 68%, and 95% confidence were 3, 4, and 7 raw score points, respectively. The ROC- and mean-change-based thresholds for deterioration were -4 and -6; for improvement they were both 2. Kappas for agreement between anchor-based thresholds and CRs for deterioration ranged between κ = 0.65 and 1.00, while for improvement, they ranged between 0.35 and 0.83. Agreement between the PGIC and all CRs always fell below "good" (κ < 0.40) for deterioration (0.30-0.33) and were lower for improvement (0.16-0.28).

CONCLUSIONS

In comparison to the CR at 95% confidence, CRs at 50% and 68% confidence (considered likely change indexes) have the advantage of maximizing the proportion of patients appropriately classified as changed according to statistical significance and meaningfulness.

Establishing thresholds for meaningful within-individual change using longitudinal item response theory

Purpose

Thresholds for meaningful within-individual change (MWIC) are useful for interpreting patient-reported outcome measures (PROM). Transition ratings (TR) have been recommended as anchors to establish MWIC. Traditional statistical methods for analyzing MWIC such as mean change analysis, receiver operating characteristic (ROC) analysis, and predictive modeling ignore problems of floor/ceiling effects and measurement error in the PROM scores and the TR item. We present a novel approach to MWIC estimation for multi-item scales using longitudinal item response theory (LIRT).

Methods

A Graded Response LIRT model for baseline and follow-up PROM data was expanded to include a TR item measuring latent change. The LIRT threshold parameter for the TR established the MWIC threshold on the latent metric, from which the observed PROM score MWIC threshold was estimated. We compared the LIRT approach and traditional methods using an example data set with baseline and three follow-up assessments differing by magnitude of score improvement, variance of score improvement, and baseline-follow-up score correlation.

Results

The LIRT model provided good fit to the data. LIRT estimates of observed PROM MWIC varied between 3 and 4 points score improvement. In contrast, results from traditional methods varied from 2 to 10 points—strongly associated with proportion of self-rated improvement. Best agreement between methods was seen when approximately 50% rated their health as improved.

Conclusion

Results from traditional analyses of anchor-based MWIC are impacted by study conditions. LIRT constitutes a promising and more robust analytic approach to identifying thresholds for MWIC.

The minimal important change for the EQ VAS based on the SF-36 health transition item: observations from 25772 spine surgery procedures

PURPOSE

The EQ VAS is an integral part of EQ-5D, a commonly used instrument for health-related quality of life assessment. This study aimed to calculate the minimal important change (MIC) thresholds for the EQ VAS for improvement and deterioration after surgery for disk herniation or spinal stenosis.

METHODS

Patients, who were surgically treated for disk herniation or spinal stenosis between 2007 and 2016, were recruited from the Swedish spine register. Preoperative and 1-year postoperative data for a total of 25772 procedures were available for analysis. We used two anchor-based methods to estimate MIC for EQ VAS: (1) a predictive model based on logistic regression and (2) receiver operating characteristics (ROC) curves. The SF-36 health transition item was used as anchor.

RESULTS

The EQ VAS MIC threshold for improvement after disk herniation surgery ranged from 8.25 to 11.8 while the corresponding value for deterioration ranged from - 6.17 to 0.5. For spinal stenosis surgery the corresponding MIC values ranged from 10.5 to 14.5 and - 7.16 to - 6.5 respectively. There were moderate negative correlations (disk herniation - 0.47, spinal stenosis - 0.46) between the 1 year change in the EQ VAS and the SF-36 health transition item (MIC anchor).

CONCLUSIONS

For EQ VAS, we recommend a MIC threshold of 12 points for improvement after surgery for disk herniation or spinal stenosis, whereas the corresponding threshold for deterioration is - 7 points. There are marked differences between the EQ VAS MIC for improvement and deterioration after surgery for disk herniation or spinal stenosis. The MIC value varied depending on the method used for MIC estimation.

Interpretation threshold values for the Oxford Knee Score in patients undergoing unicompartmental knee arthroplasty

BACKGROUND AND PURPOSE

Developing meaningful thresholds for the Oxford Knee Score (OKS) advances its clinical use. We determined the minimal important change (MIC), patient acceptable symptom state (PASS), and treatment failure (TF) values as meaningful thresholds for the OKS at 3-, 12-, and 24-month follow-up in patients undergoing unicompartmental knee arthroplasty (UKA).

PATIENTS AND METHODS

This is a cohort study with data from patients undergoing UKA collected at a hospital in Denmark between February 2016 and September 2021. The OKS was completed preoperatively and at 3, 12, and 24 months postoperatively. Interpretation threshold values were calculated with the anchor-based adjusted predictive modeling method. Non-parametric bootstrapping was used to derive 95% confidence intervals (CI).

RESULTS

Complete 3-, 12-, and 24-month postoperative data was obtained for 331 of 423 (78%), 340 of 479 (71%), and 235 of 338 (70%) patients, median age of 68-69 years (58-59% females). Adjusted OKS MIC values were 4.7 (CI 3.3-6.0), 7.1 (CI 5.2-8.6), and 5.4 (CI 3.4- 7.3), adjusted OKS PASS values were 28.9 (CI 27.6-30.3), 32.7 (CI 31.5-33.9), and 31.3 (CI 29.1-33.3), and adjusted OKS TF values were 24.4 (CI 20.7-27.4), 29.3 (CI 27.3-31.1), and 28.5 (CI 26.0-30.5) at 3, 12, and 24 months postoperatively, respectively. All values statistically significantly increased from 3 to 12 months but not from 12 to 24 months.

INTERPRETATION

The UKA-specific measurement properties and clinical thresholds for the OKS can improve the interpretation of UKA outcome and assist quality assessment in institutional and national registries.

What Are the Minimally Important Changes of Four Commonly Used Patient-reported Outcome Measures for 36 Hand and Wrist Condition-Treatment Combinations?

BACKGROUND

Patient-reported outcome measures (PROMs) are frequently used to assess treatment outcomes for hand and wrist conditions. To adequately interpret these outcomes, it is important to determine whether a statistically significant change is also clinically relevant. For this purpose, the minimally important change (MIC) was developed, representing the minimal within-person change in outcome that patients perceive as a beneficial treatment effect. Prior studies demonstrated substantial differences in MICs between condition-treatment combinations, suggesting that MICs are context-specific and cannot be reliably generalized. Hence, a study providing MICs for a wide diversity of condition-treatment combinations for hand and wrist conditions will contribute to more accurate treatment evaluations.

QUESTIONS/PURPOSES

(1) What are the MICs of the most frequently used PROMs for common condition-treatment combinations of hand and wrist conditions? (2) Do MICs vary based on the invasiveness of the treatment (nonsurgical treatment or surgical treatment)?

METHODS

This study is based on data from a longitudinally maintained database of patients with hand and wrist conditions treated in one of 26 outpatient clinics in the Netherlands between November 2013 and November 2020. Patients were invited to complete several validated PROMs before treatment and at final follow-up. All patients were invited to complete the VAS for pain and hand function. Depending on the condition, patients were also invited to complete the Michigan Hand outcomes Questionnaire (MHQ) (finger and thumb conditions), the Patient-rated Wrist/Hand Evaluation (PRWHE) (wrist conditions), or the Boston Carpal Tunnel Questionnaire (BCTQ) (nerve conditions). Additionally, patients completed the validated Satisfaction with Treatment Result Questionnaire at final follow-up. Final follow-up timepoints were 3 months for nonsurgical and minor surgical treatment (including trigger finger release) and 12 months for major surgical treatment (such as trapeziectomy). Our database included 55,651 patients, of whom we excluded 1528 who only required diagnostic management, 25,099 patients who did not complete the Satisfaction with Treatment Result Questionnaire, 3509 patients with missing data in the PROM of interest at baseline or follow-up, and 1766 patients who were part of condition-treatment combinations with less than 100 patients. The final sample represented 43% (23,749) of all patients and consisted of 36 condition-treatment combinations. In this final sample, 26% (6179) of patients were managed nonsurgically and 74% (17,570) were managed surgically. Patients had a mean ± SD age of 55 ± 14 years, and 66% (15,593) of patients were women. To estimate the MIC, we used two anchor-based methods (the anchor mean change and the MIC predict method), which were triangulated afterward to obtain a single MIC. Applying this method, we calculated the MIC for 36 condition-treatment combinations, comprising 22 different conditions, and calculated the MIC for combined nonsurgical and surgical treatment groups. To examine whether the MIC differs between nonsurgical and surgical treatments, we performed a Wilcoxon signed rank test to compare the MICs of all PROM scores between nonsurgical and surgical treatment.

RESULTS

We found a large variation in triangulated MICs between the condition-treatment combinations. For example, for nonsurgical treatment of hand OA, the MICs of VAS pain during load clustered around 10 (interquartile range 8 to 11), for wrist osteotomy/carpectomy it was around 25 (IQR 24 to 27), and for nerve decompression it was 21. Additionally, the MICs of the MHQ total score ranged from 4 (nonsurgical treatment of CMC1 OA) to 15 (trapeziectomy with LRTI and bone tunnel), for the PRWHE total score it ranged from 2 (nonsurgical treatment of STT OA) to 29 (release of first extensor compartment), and for the BCTQ Symptom Severity Scale it ranged from 0.44 (nonsurgical treatment of carpal tunnel syndrome) to 0.87 (carpal tunnel release). An overview of all MIC values is available in a freely available online application at: https://analyse.equipezorgbedrijven.nl/shiny/mic-per-treatment/. In the combined treatment groups, the triangulated MIC values were lower for nonsurgical treatment than for surgical treatment (p < 0.001). The MICs for nonsurgical treatment can be approximated to be one-ninth (IQR 0.08 to 0.13) of the scale (approximately 11 on a 100-point instrument), and surgical treatment had MICs that were approximately one-fifth (IQR 0.14 to 0.24) of the scale (approximately 19 on a 100-point instrument).

CONCLUSION

MICs vary between condition-treatment combinations and differ depending on the invasiveness of the intervention. Patients receiving a more invasive treatment have higher treatment expectations, may experience more discomfort from their treatment, or may feel that the investment of undergoing a more invasive treatment should yield greater improvement, leading to a different perception of what constitutes a beneficial treatment effect.

CLINICAL RELEVANCE

Our findings indicate that the MIC is context-specific and may be misleading if applied inappropriately. Implementation of these condition-specific and treatment-specific MICs in clinical research allows for a better study design and to achieve more accurate treatment evaluations. Consequently, this could aid clinicians in better informing patients about the expected treatment results and facilitate shared decision-making in clinical practice. Future studies may focus on adaptive techniques to achieve individualized MICs, which may ultimately aid clinicians in selecting the optimal treatment for individual patients.

All MCIDs Are Wrong, But Some May be Useful

OBJECTIVE

To demonstrate how to apply a baseline-adjusted receiver operator characteristic curve (AROC) analysis for minimum clinically important differences (MCIDs) in an empirical data set and discuss new insights relating to MCIDs.

DESIGN

Retrospective study.

METHODS

This study includes data from 999 active-duty military service patients enrolled in the United States Military Health System's Military Orthopedics Tracking Injuries and Outcomes Network. Anchored MCIDs were calculated using the standard receiver operator characteristic analysis and the AROC analysis for the Patient-Reported Outcome Measure Information System (PROMIS) Pain Interference and Defense and Veterans Pain Rating Scale (DVPRS). Point estimates where confidence intervals (CIs) crossed the 0.5 identity line on the area-under-the-curve (AUC) analysis were considered statistically invalid. MCID estimates where CIs crossed 0 were considered theoretically invalid.

RESULTS

In applying an AROC analysis, the region of AUC and MCID validity for the PROMIS Pain Interference score exists when the baseline score is greater than 61.0 but less than 72.3. For DVPRS, the region of MCID validity is when the baseline score is greater than 5.9 but less than 7.9.

CONCLUSION

Baseline values influence not only the MCID but also the accuracy of the MCID. MCIDs are statistically and theoretically valid for only a discrete range of baseline scores. Our findings suggest that the MCID may be too flawed a construct to accurately benchmark treatment outcomes. J Orthop Sports Phys Ther 2022;52(6):401-407. doi:10.2519/jospt.2022.11193.

Minimal Clinically Important Changes in HOOS-12 and KOOS-12 Scores Following Joint Replacement

BACKGROUND

For patient-reported outcome measures (PROMs) to provide meaningful information to support clinical care, we need to understand the magnitude of change that matters to patients. The aim of this study was to estimate minimal clinically important changes (MCICs) for the 12-item Hip disability and Osteoarthritis Outcome Score (HOOS-12) and Knee injury and Osteoarthritis Outcome Score (KOOS-12) among people undergoing joint replacement for osteoarthritis.

METHODS

Individual-level data from the Australian Orthopaedic Association National Joint Replacement Registry's pilot PROMs program were used for this analysis. Preoperative and 6-month postoperative HOOS-12 and KOOS-12 domain and summary impact scores plus a rating of patient-perceived change after surgery (on a 5-point scale ranging from "much worse" to "much better") were available. Three anchor-based approaches-mean change, receiver operating characteristics (ROC) based on Youden's J statistic, and predictive modeling using a binary logistic regression model-were used to calculate MCICs based on patient-perceived change.

RESULTS

Data were available for 1,490 patients treated with total hip replacement (THR) (mean age, 66 years; 54% female) and 1,931 patients treated with total knee replacement (TKR) (mean age, 66 years; 55% female). Using the mean change method, the MCIC ranged from 24.0 to 27.5 points for the HOOS-12 and 17.5 to 21.8 points for the KOOS-12. The ROC analyses generated comparable MCIC values (28.1 for HOOS-12 and a range of 15.6 to 21.9 for KOOS-12) with high sensitivity and specificity. Lower estimates were derived from predictive modeling following adjustment for the proportion of improved patients (range, 15.7 to 19.2 for HOOS-12 and 14.2 to 16.5 for KOOS-12).

CONCLUSIONS

We report MCIC values for the HOOS-12 and KOOS-12 instruments that we derived using 3 different methods. As estimates obtained using predictive modeling can be adjusted for the proportion of improved patients, these may be the most clinically applicable. These MCIC values can be used to interpret important changes in pain, function, and quality of life from the patient's perspective.

LEVELS OF EVIDENCE

Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Estimation of Patient Acceptable Symptom State (PASS) and Treatment Failure (TF) Threshold Values for the Achilles Tendon Total Rupture Score (ATRS) at 6 Months, 1 Year, and 2 Years After Acute Achilles Tendon Rupture

Interpretation of the Achilles tendon Total Rupture Score (ATRS) is challenging because limited knowledge exists about at which score the patients consider the outcome of treatment as satisfactory. The aims of the study were (1) to describe the proportion of patients who find their symptom levels to be satisfactory, to reflect treatment failure or neither after acute Achilles tendon rupture (ATR), and (2) to estimate the Patient Acceptable Symptom State (PASS) and the Treatment Failure (TF) threshold values for the ATRS at 6 months, 1 year, and 2 years after ATR. The study was based on data extracted from the nationwide Danish Achilles tendon Database which includes patients treated operatively or nonoperatively after ATR. The PASS and TF threshold values for ATRS were estimated using the adjusted predictive modeling method. One hundred and sixty-six patients were included at 6 months, 248 patients at 1 year, and 287 patients at 2 years after ATR. The proportion of patients who considered their symptom level to be satisfactory was 61% at 6 months, 50% at 1 year, and 66% at 2 years, while 5% at 6 months, 11% at 1 year, and 10% at 2 years considered their symptom level to reflect treatment failure. The PASS threshold value for ATRS (95% confidence interval) was 49 (46-52) at 6 months, 57 (54-60) at 1 year, and 52 (49-55) at 2 years. The TF threshold value for ATRS was 30 (23-36) at 6 months, 33 (26-40) at 1 year, and 35 (29-39) at 2 years. The calculated PASS and TF threshold values can help interpret the outcome of ATR when measured with the ATRS. About 50% to 66% of the patients had a satisfactory symptom level after ATR.

Minimal important difference and patient acceptable symptom state for the Numerical Rating Scale (NRS) for pain and the Patient-Rated Wrist/Hand Evaluation (PRWHE) for patients with osteoarthritis at the base of thumb

Background

The Numerical Rating Scale (NRS) and Patient-rated wrist/hand evaluation (PRWHE) are patient-reported outcomes frequently used for evaluating pain and function of the wrist and hand. The aim of this study was to determine thresholds for minimal important difference (MID) and patient acceptable symptom state (PASS) for NRS pain and PRWHE instruments in patients with base of thumb osteoarthritis.

Methods

Fifty-two patients with symptomatic base of thumb osteoarthritis wore a splint for six weeks before undergoing trapeziectomy. NRS pain (0 to 10) and PRWHE (0 to 100) were collected at the time of recruitment (baseline), after splint immobilization prior to surgery, and at 3, 6, 9 and 12 months after surgery. Four anchor-based methods were used to determine MID for NRS pain and PRWHE: the receiver operating characteristics (ROC) curve, the mean difference of change (MDC), the mean change (MC) and the predictive modelling methods. Two approaches were used to determine PASS for NRS pain and PRWHE: the 75^th percentile and the ROC curve methods. The anchor question for MID was the change perceived by the patient compared with baseline; the anchor question for PASS was whether the patient would be satisfied if the condition were to stay similar. The correlation between the transition anchor at baseline and the outcome at all time points combined was calculated using the Spearman’s rho analysis.

Results

The MID for NRS pain was 2.5 using the ROC curve method, 2.0 using the MDC method, 2.8 using the MC method, and 2.5 using the predictive modelling method. The corresponding MIDs for PRWHE were 22, 24, 10, and 20. The PASS values for NRS pain and PRWHE were 2.5 and 30 using the ROC curve method, and 2.0 and 22 using the 75th percentile method, respectively. The area under curve (AUC) analyses showed excellent discrimination for all measures.

Conclusion

We found credible MID estimates for NRS and PRWHE (including its subscales), although the MID estimates varied depending on the method used. The estimates were 20-30% of the range of scores of the instruments. The cut-offs for MID and PASS showed good or excellent discrimination, lending support for their use in future studies.

Trial registration

This clinimetrics study was approved by the Helsinki University ethical review board (HUS1525/2017).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01600-1.

Toward a rigorous assessment of the statistical performances of methods to estimate the Minimal Important Difference of Patient-Reported Outcomes: a protocol for a large-scale simulation study

Interpreting observed changes over time in Patient-Reported Outcomes (PRO) measures is still considered a challenge. Indeed, concluding an observed change at group level is statistically significant does not necessarily equate this change is meaningful from the perspective of the patient. To help interpret within and/or between group changes in the measure over time, the estimation of the Minimal Important Difference (MID) of the instrument - the smallest value that patients consider as a perceived change - is useful. In the last 30 years, a plethora of methods and estimators have been proposed to derive this MID value using clinical data from sample of patients. MIDs for hundreds of PROs have been estimated, with frequently a substantial variability in the results depending on the method used. Nonetheless, a rigorous assessment of the statistical performances of numerous proposed methods for estimating MIDs by experimental design such as Monte-Carlo study has never been performed. The purpose of this paper is to thoroughly depict a protocol for a large-scale simulation study designed to investigate the statistical performances, especially bias against a true populational value, of the common proposed estimators for MID. This paper depicts how investigated methods and estimators were retained after the conduct of a systematic review, the design of a conceptual model that formally defines what is the true populational MID value and the translation of the conceptual model into a model allowing the simulation of responses of items to a hypothetical PRO at two times of measurement along with the response to a Patient Global Rating of Change at the second time under the constraint of a known true MID value. A statistical analysis plan is depicted in order to conclude if working hypotheses on what could be appropriate MID estimators will be verified. Strengths, assumptions, and limits of the simulation model are exposed. Finally, we show how this protocol could be the basis for fostering future methodological research on the issue of interpreting changes in PRO measures.

Longitudinal Validity and Minimal Important Change for the Modified Lower Extremity Functional Scale (LEFS) in Orthopedic Foot and Ankle Patients

The lower extremity functional scale (LEFS) is a patient-reported outcome measure for lower extremity disorders. Aim of this study was to assess the longitudinal validity including responsiveness and test-retest reliability of the revised 15-item version, and to define the minimal important change (MIC) of the modified LEFS in a generic sample of orthopedic foot and ankle patients who underwent surgery. Responsiveness, effect size, and standardized response mean were measured by determining the score change between the baseline and 6 months administration of the LEFS from 156 patients. There was no significant difference between preoperative (median 78, interquartile range [IQR] 64.2-90.3) and postoperative (median 75.0, IQR 61.7-95.0) scores. Both effect size and standardized response mean were low (0.06 and 0.06, respectively). Test-retest reliability of the LEFS was satisfactory. Intraclass correlation coefficient was 0.85 (95% confidence interval 0.81-0.88). MIC value could not be estimated due to the lack of significant score change. The modified LEFS presented with relatively low longitudinal validity in a cohort of generic orthopedic foot and ankle patients. The findings of this study indicate that the modified LEFS might not be the optimal instrument in assessing the clinical change over time for these patients.

Substantial clinical benefit and patient acceptable symptom states of the Forgotten Joint Score 12 after primary knee arthroplasty

Background and purpose - Knowing how to interpret values obtained with patient reported outcome measures (PROMs) is essential. We estimated the substantial clinical benefit (SCB) and patient acceptable symptom state (PASS) for Forgotten Joint Score 12 (FJS) and explored differences depending on methods used for the estimates. Patients and methods - The study was based on 195 knee arthroplasties (KA) performed at a university hospital. We used 1 item from the Knee injury and Osteoarthritis Outcome Score domain quality of life and satisfaction with surgery, obtained 1-year postoperatively, to assess SCB and PASS thresholds of the FJS with anchor-based methods. We used different combinations of anchor questions for SCB and PASS (satisfied, satisfied with no or mild knee difficulties, and satisfied with no knee difficulties). A novel predictive approach and receiver-operating characteristics curve were applied for the estimates. Results - 70 and 113 KAs were available for the SCB and PASS estimates, respectively. Depending on method, SCB of the FJS (range 0-100) was 28 (95% CI 21-35) and 22 (12-45) respectively. PASS was 31 (2-39) and 20 (10-29) for satisfied patients, 40 (31-47) and 38 (32-43) for satisfied patients with no/mild difficulties, and 76 (39-80) and 64 (55-74) for satisfied patients with no difficulties. The areas under the curve ranged from 0.82 to 0.88. Interpretation - Both the SCB and PASS thresholds varied depending on methodology. This may indicate a problem using meaningful values from other studies defining outcomes after KA. This study supports the premise of the FJS as a PROM with good discriminatory ability in patients undergoing KA.

Minimal important change for Foot and Ankle Outcome Score (FAOS)

BACKGROUND

Although Foot and Ankle Outcome Score (FAOS) is a widely used patient-reported outcome measure (PROM) for foot and ankle conditions, research on its longitudinal validity is still needed. Minimal important change (MIC) values for the FAOS were determined using predictive modeling.

METHODS

Overall, 134 patients that underwent operative treatment for foot and ankle conditions were included. An anchor based predictive logistic modeling method was used for estimating the MIC values for the FAOS subscales after surgery.

RESULTS

Mean score changes in the improved and the unimproved groups were 17.7 and 0.43 points for Pain, 3.9 and -3.3 points for Symptoms, 21.3 and 1.8 points for Activities and daily living (ADL), 8.7 and -2.8 points for Sport, and 12.5 and -3.3 points for quality of life subscale, respectively. MIC was successfully determined to four out of five subgroups as follows: Pain 9.5 (94% CI -6.4 to 24.6); ADL 11.7 (95% CI -19.6 to 46.6); Sport (95% CI -10.4 to 15.4); QoL 5.0 (95% CI -2.6 to 12.9). The Symptoms subgroup presented with low MIC of 0.3 (95% CI -11.7 to 13.4) fitting to the measurement error.

CONCLUSION

ADL, Sports, Pain, and QoL subscales of the FAOS presented logical MIC values. The MIC can be further evaluated for specific conditions.

Examining minimal important change of the Canadian Occupational Performance Measure for subacute rehabilitation hospital inpatients

Background

The Canadian Occupational Performance Measure (COPM) is an individualized patient-reported outcome designed to evaluate the self-perceptions of a patient’s occupational performance. Our study aimed to examine the minimal important change (MIC) in inpatients undergoing subacute rehabilitation. The MIC values were calculated using the three different anchor-based analyses with the transition index as an external criterion; the mean change method (MIC_MeanChange), the receiver operating characteristic (MIC_ROC) analysis, and the predictive modeling method adjusted for the proportion of improved patients (MIC_adjust). In this study, the MIC_adjust value was considered as the most valid statistical method. We recruited 100 inpatients with various health conditions from subacute rehabilitation hospitals. Data were collected twice: an initial assessment and a reassessment one month later. The systematic interview format (Five Ws and How) was used for both the initial and second assessments to prevent information bias (response shift).

Results

Three patients who indicated deterioration on the transition index were excluded from all analyses, and 97 patients were analyzed in this study. The MIC_adjust values were 2.20 points (95% confidence interval 1.80–2.59) for the COPM performance score and 2.06 points (95% confidence interval 1.73–2.39) for the COPM satisfaction score. The MIC_MeanChange and MIC_ROC values were considered less reasonable to interpret because the proportions of the improved patients subgroup were more than 50% (82.5%).

Conclusions

The MIC_adjust value estimates from this study can help detect whether the patients’ perceived occupational performance improved or did not change. The results support the multidisciplinary use of COPM in clinical practice and research on subacute rehabilitation inpatients.

Minimal important changes and differences were estimated for Oxford hip and knee scores following primary and revision arthroplasty

OBJECTIVES

To create estimates for clinically meaningful changes and differences in pain and joint function for the Oxford Hip and Knee Scores (OHS/OKS) in primary and revision joint replacement.

STUDY DESIGN AND SETTING

694,487 primary and revision joint replacement procedures were analysed from the NHS PROMs dataset between 2012-2020. Minimal important changes (MIC) and differences (MID) were calculated using distribution and anchor-based methods (including receiver-operating characteristic (ROC) curve and predictive-modelling techniques).

RESULTS

For comparison of two or more groups (such as in a clinic trial), MID estimates were ∼5 points. For cohort studies investigating changes over time in a single group of patients, MIC_group estimates were 12.4 points (primary hip replacement), 8.6 points (revision hip replacement), 10.5 points (primary knee replacement) and 9.4 points (revision knee replacement). For studies investigating changes over time at the individual patient level, MIC_adjusted estimates were ∼8 points, ∼6 points, ∼7 points and ∼6 points respectively.

CONCLUSION

This study has calculated contemporary estimates of clinically important changes and differences for the OHS/OKS for primary and revision hip and knee replacement. These estimates can be used to inform sample size calculations and to interpret changes in joint function over time and differences between groups.

Determining the minimal important change of the 6-minute walking test in Multiple Sclerosis patients using a predictive modelling anchor-based method

BACKGROUND

The minimal important change (MIC) of the 6-minute walk test (6MWT) is not clear for patients with Multiple Sclerosis (MS), hampering treatment evaluation. The aim of our study was therefore to determine the MIC of the 6MWT in MS patients.

METHODS

MS patients did the 6MWT using the instruction to walk at comfortable speed twice with approximately one year in between. After the second 6MWT they completed 3-point anchor question. The MIC_adjusted with a 95% confidence interval (CI) was calculated with the predictive modelling method with bootstrapping.

RESULTS

118 MS patients (mean age 48.2 years, 23.7% men) were included between September 2018 and October 2019. Mean 6MWT distance was 468 ± 112 m at baseline and 469 ± 115 m one year later. Twenty-three (19.5%) patients answered their walking distance improved, 43 (36.4%) answered it worsened. A MIC_adjusted for improvement of 19.7 m (95%CI 9.8-30.9 m) was found, and for deterioration of 7.2 m (95%CI -3.3-18.2 m).

CONCLUSIONS

Using the most sophisticated statistical method, the MIC_adjusted of the 6MWT in MS patients was 19.7 m for improvement, and 7.2 m for deterioration. This knowledge allows physiotherapists and physicians to evaluate if their treatment has led to a meaningful improvement for their MS patients or if walking of their patients has deteriorated.

Evaluation of the Responsiveness of the Anterior Cruciate Ligament Return to Sport After Injury (ACL-RSI) Scale

Background

The Anterior Cruciate Ligament Return to Sport After Injury (ACL-RSI) scale is a reliable and valid tool for evaluation of psychological readiness to return to sport after ACL injury, but its responsiveness to change has not been extensively evaluated.

Purpose

To determine the responsiveness of the ACL-RSI scale.

Study Design

Cohort study (diagnosis); Level of evidence, 2.

Methods

The ACL-RSI scale and the knee confidence question from the Knee injury and Osteoarthritis Outcome Score-Quality of Life subscale was completed at 6 and 12 months after ACL reconstruction surgery. Responsiveness was assessed using distribution and anchor-based methods for the full- and short-form versions of the scale and subgroup analyzed for sex. From distribution statistics, the standardized response mean (SRM) and the smallest detectable change (SDC) were calculated. Using the anchor-based method, the minimally important change (MIC) that was associated with an improvement in knee confidence was determined using receiver operating characteristic analysis.

Results

A total of 441 patients (257 men, 184 women; mean age of 25 years) were included in this study. An SRM of 0.7 was found for both versions, indicating a moderate level of responsiveness. The MIC was 13.4 points for the full-form version and 15.1 points for the short-form version. These values were larger than SDC values at the group level but not at the individual patient level. Responsiveness was similar between male and female patients.

Conclusion

The ACL-RSI scale had sufficient responsiveness to investigate the efficacy of an intervention at a group level, but it may be more limited at an individual patient level.

Methodological approach for determining the Minimal Important Difference and Minimal Important Change scores for the European Organisation for Research and Treatment of Cancer Head and Neck Cancer Module (EORTC QLQ-HN43) exemplified by the Swallowing scale

Purpose

The aim of this study was to explore what methods should be used to determine the minimal important difference (MID) and minimal important change (MIC) in scores for the European Organisation for Research and Treatment of Cancer Head and Neck Cancer Module, the EORTC QLQ-HN43.

Methods

In an international multi-centre study, patients with head and neck cancer completed the EORTC QLQ-HN43 before the onset of treatment (t1), three months after baseline (t2), and six months after baseline (t3). The methods explored for determining the MID were: (1) group comparisons based on performance status; (2) 0.5 and 0.3 standard deviation and standard error of the mean. The methods examined for the MIC were patients' subjective change ratings and receiver-operating characteristics (ROC) curves, predictive modelling, standard deviation, and standard error of the mean. The EORTC QLQ-HN43 Swallowing scale was used to investigate these methods.

Results

From 28 hospitals in 18 countries, 503 patients participated. Correlations with the performance status were |r|< 0.4 in 17 out of 19 scales; hence, performance status was regarded as an unsuitable anchor. The ROC approach yielded an implausible MIC and was also discarded. The remaining approaches worked well and delivered MID values ranging from 10 to 14; the MIC for deterioration ranged from 8 to 16 and the MIC for improvement from − 3 to − 14.

Conclusions

For determining MIDs of the remaining scales of the EORTC QLQ-HN43, we will omit comparisons of groups based on the Karnofsky Performance Score. Other external anchors are needed instead. Distribution-based methods worked well and will be applied as a starting strategy for analyses. For the calculation of MICs, subjective change ratings, predictive modelling, and standard-deviation based approaches are suitable methods whereas ROC analyses seem to be inappropriate.

Supplementary Information

The online version of this article (10.1007/s11136-021-02939-6) contains supplementary material, which is available to authorized users.

Exploration of the methods of establishing the minimum clinical important difference based on anchor and its application in the quality of life measurement scale QLICP-ES (V2.0) for esophageal cancer

Background

The development of the minimum clinical important difference (MCID) can make it easier for researchers or doctors to judge the significance of research results and the effect of intervention measures, and improve the evaluation system of efficacy. This paper is aimed to calculate the MCID based on anchor and to develop MCID for esophageal cancer scale (QLICP-ES).

Methods

The item Q29 (How do you evaluate your overall health in the past week with 7 grades answers from 1 very poor to 7 excellent)of EORTC QLQ-C30 was used as the subjective anchor to calculate the score difference between each domain at discharge and admission. MCID was established according to two standards, "one grade difference"(A) and "at least one grade difference"(B), and developed by three methods: anchor-based method, ROC curve method and multiple linear regression models. In terms of anchor-based method, the mean of the absolute value of the difference before and after treatments is MCID. The point with the best sensitivity and specificity-Yorden index at the ROC curve is MCID for ROC curve method. In contrast, the predicted mean value based on a multiple linear regression model and the parameters of each factor is MCID.

Results

Most of the correlation coefficients of Q29 and various domains of the QLICP-ES were higher than 0.30. The rank of MCID values determined by different methods and standards were as follows: standard B > standard A, anchor-based method > ROC curve method > multiple linear regression models. The recommended MCID values of physical domain, psychological domain, social domain, common symptom and side-effects domain, the specific domain and the overall of the QLICP-ES were 7.8, 9.7, 4.7, 3.6, 4.3, 2.3 and 2.9, respectively.

Conclusion

Different methods have their own advantages and disadvantages, and also different definitions and standards can be adopted according to research purposes and methods. A lot of different MCID values were presented in this paper so that it can be easy and convenient to select by users.

Interpreting Quality-of-Life Questionnaires in Patients with Long-Standing Facial Palsy

Objective(s): To interpret change in quality-of-life scores in facial palsy patients by calculating the smallest detectable change (SDC) and minimal important change (MIC) for the Facial Disability Index (FDI), Facial Clinimetric Evaluation (FaCE) scale, and Synkinesis Assessment Questionnaire (SAQ). Materials and Methods: The SDC, for individuals and groups, was calculated using previously collected test-retest data (2-week interval). The MIC (predictive modeling method) was calculated in a second similar facial palsy population using two measurements (1-1.5-year interval) and an anchor question assessing perceived change. Results: SDC_individual of FaCE was 17.6 and SAQ was 28.2. SDC_group of FaCE was 2.9 and SAQ was 4.6 (n = 62). Baseline FaCE and SAQ scores were 43.3 (interquartile range [IQR]: 35.8;55.0) and 51.1 (IQR: 32.2;60.0), respectively. MIC for important improvement of FDI physical/social function, FaCE total, and SAQ total were 4.4, 0.4, 0.7, and 2.8, respectively (n = 88). MIC for deterioration was 8.2, -1.8, -8.5, and 0.6, respectively. Baseline scores were 70.0 (IQR: 60.0;80.0), 76.0 (68.0;88.0), 55.0 (IQR: 40.0;61.7), and 26.7 (IQR: 22.2;35.6), respectively. Number of participants reporting important change for the different questionnaires ranged from 3 to 23 per subscale. Conclusion: Interpreting change scores of the FDI, FaCE, and SAQ is appropriate for groups, but for individual patients it is limited by a substantial SDC.

The minimal perceived change: a formal model of the responder definition according to the patient's meaning of change for patient-reported outcome data analysis and interpretation

Background

Patient-Reported Outcomes (PROs) are standardized questionnaires used to measure subjective outcomes such as quality of life in healthcare. They are considered paramount to assess the results of therapeutic interventions. However, because their calibration is relative to internal standards in people’s mind, changes in PRO scores are difficult to interpret.

Knowing the smallest value in the score that the patient perceives as change can help. An estimator linking the answers to a Patient Global Rating of Change (PGRC: a question measuring the overall feeling of change) with change in PRO scores is frequently used to obtain this value. In the last 30 years, a plethora of methods have been used to obtain these estimates, but there is no consensus on the appropriate method and no formal definition of this value.

Methods

We propose a model to explain changes in PRO scores and PGRC answers.

Results

A PGRC measures a construct called the Perceived Change (PC), whose determinants are elicited. Answering a PGRC requires discretizing a continuous PC into a category using threshold values that are random variables. Therefore, the populational value of the Minimal Perceived Change (MPC) is the location parameter value of the threshold on the PC continuum defining the switch from the absence of change to change.

Conclusions

We show how this model can help to hypothesize what are the appropriate methods to estimate the MPC and its potential to be a rigorous theoretical basis for future work on the interpretation of change in PRO scores.

Cutoff Values to Interpret Short-term Treatment Outcomes After Arthroscopic Meniscal Surgery, Measured With the Knee Injury and Osteoarthritis Outcome Score

OBJECTIVE

To determine the proportions of patients who (1) perceived their symptoms to be satisfactory, (2) perceived their treatment to have failed, or (3) perceived that they improved to an important degree at 3 months after arthroscopic meniscal surgery; and to determine Knee injury and Osteoarthritis Outcome Score (KOOS) subscale scores corresponding to the Patient Acceptable Symptom State (PASS), treatment failure, and the minimal important change (MIC) for improvement.

DESIGN

Prospective cohort study.

METHODS

Patients from the Knee Arthroscopy Cohort Southern Denmark who had arthroscopic meniscal surgery were included. The PASS, treatment failure, and MIC improvement values were calculated for the KOOS subscales with anchor-based approaches, using the adjusted predictive modeling method. Subgroup analyses were performed by stratifying by age (40 years or younger versus older than 40 years) and surgery type.

RESULTS

Six hundred fourteen patients (44% female; mean ± SD age, 50 ± 13 years) were included. At 3 months after arthroscopic meniscal surgery, 45% of patients perceived their symptoms to be satisfactory, 19% perceived the treatment to have failed, and 44% to 60% perceived that they had improved to an important degree across the 5 KOOS subscales (for PASS/treatment failure, respectively: pain, 74 and 60 points; symptoms, 72 and 61 points; function in activities of daily living, 81 and 68 points; sport and recreational function, 43 and 26 points; and knee-related quality of life, 52 and 40 points; for MIC improvement: pain, 12 points; symptoms, 8 points; function in activities of daily living, 12 points; sport and recreational function, 17 points; and knee-related quality of life, 9 points). The PASS values were 6 to 17 points higher for patients 40 years or younger compared to patients older than 40 years.

CONCLUSION

At 3 months after meniscal surgery, approximately half of the patients perceived their symptoms to have improved to an important degree, 4 in every 10 patients perceived their symptoms to be satisfactory, and 2 in every 10 patients perceived the treatment to have failed. J Orthop Sports Phys Ther 2021;51(6):281-288. Epub 30 Jan 2021. doi:10.2519/jospt.2021.10149.

Interpretation of change scores for the National Eye Institute Visual Function Questionnaire-25: the minimally important difference

AIM

To estimate the minimally important difference (MID) in change in National Eye Institute Visual Function Questionnaire-25 (VFQ-25) composite score using methods aligned with patient perception.

METHODS

Retrospective analysis of prospectively collected data from adults with primary angle closure or primary angle closure glaucoma enrolled in the Effectiveness, in Angle-closure Glaucoma, of Lens Extraction study. We included data from 335 participants with patient reported visual function (VFQ-25) and health status measured by the EQ-5D-3L over 36 months. We used the recommended anchor-based methods (receiver operating characteristic (ROC), predictive modelling and mean change) to determine the MID of the VFQ-25. EQ-5D-3L anchor change was defined as none (<0.065); minimal (0.065≤EQ-5D-3L change ≤0.075 points) and greater change (>0.075 points).

RESULTS

Mean baseline VFQ-25 score was 87.6 (SD 11.8). Estimated MIDs in the change in VFQ-25 scores (95% CI) were 10.5 (1.9 to 19.2); 3.9 (-2.3 to 10.1); 5.8 (1.9 to 7.2) and 8.1 (1.7 to 14.8) for the 'within-patient', 'between-patient' change, ROC and predictive modelling anchor methods respectively. Excluding estimates from the methodologically weaker 'within-patient' method, the MID of a change in VFQ-25 composite score is 5.8 (median value).

CONCLUSIONS

Estimates of the MID using multiple methods assist in the interpretation of the VFQ scores. In the context of early glaucoma related visual disability, a change score of around six points on the VFQ-25 is likely to be important to patients. Further confirmatory research is required. Studies comparing changes in patient-reported outcome measure scores with a global measure of patients' perceived change are required.

Patient-reported outcome measures ( PROMs): making sense of individual PROM scores and changes in PROM scores over time

Patient-reported outcome measures (PROMs) are increasingly being used in nephrology care. However, in contrast to well-known clinical measures such as blood pressure, health-care professionals are less familiar with PROMs and the interpretation of PROM scores is therefore perceived as challenging. In this paper, we provide insight into the interpretation of PROM scores by introducing the different types and characteristics of PROMs, and the most relevant concepts for the interpretation of PROM scores. Concepts such as minimal detectable change, minimal important change and response shift are explained and illustrated with examples from nephrology care.

Validity and responsiveness of EQ-5D-5L and SF-6D in patients with health complaints attributed to their amalgam fillings: a prospective cohort study of patients undergoing amalgam removal

Background

Evidence of health utility changes in patients who suffer from longstanding health complaints attributed to dental amalgam fillings are limited. The change in health utility outcomes enables calculating quality-adjusted life-year (QALY) and facilitates the comparison with other health conditions. The purpose of this study was to estimate the validity and responsiveness of the EQ-5D-5L and SF-6D utilities following removal of dental amalgam fillings in patients with health complaints attributed to their amalgam fillings, and examine the ability of these instruments to detect minimally important changes over time.

Methods

Patients with medically unexplained physical symptoms, which they attributed to dental amalgam restorations, were recruited to a prospective cohort study in Norway. Two health state utility instruments, EQ-5D-5L and SF-6D, as well as self-reported general health complaints (GHC-index) and visual analogue scale (EQ-VAS) were administered to all patients (n = 32) at baseline and at follow-up. The last two were used as criteria measures. Concurrent and predictive validities were examined using correlation coefficients. Responsiveness was assessed by the effect size (ES), standardized response mean (SRM), and relative efficiency. Minimally important change (MIC) was examined by distribution and anchor-based approaches.

Results

Concurrent validity of the EQ-5D-5L was similar to that of SF-6D utility. EQ-5D-5L was more responsive than SF-6D: the ES were 0.73 and 0.58 for EQ-5D-5L and SF-6D, respectively; SRM were 0.76 and 0.67, respectively. EQ-5D-5L was more efficient than SF-6D in detecting changes, but both were less efficient compared to criteria-based measures. The estimated MIC of EQ-5D-5L value set was 0.108 and 0.118 based on distribution and anchor-based approaches, respectively. The corresponding values for SF-6D were 0.048 and 0.064, respectively.

Conclusions

In patients with health complaints attributed to dental amalgam undergoing amalgam removal, both EQ-5D-5L and SF-6D showed reasonable concurrent and predictive validity and acceptable responsiveness. The EQ-5D-5L utility appears to be more responsive compared to SF-6D.

Trial registration The research was registered at ClinicalTrials.gov., NCT01682278. Registered 10 September 2012, https://clinicaltrials.gov/ct2/show/NCT01682278.

Minimal important change and minimum clinically important difference values of the KOOS-12 after total knee arthroplasty

PURPOSE

The minimal important change (minimal amount of change vs. baseline that a patient recognizes as a clinical change) and minimum clinically important difference (smallest difference between two measurements that are deemed important by patients) are important values to evaluate the clinical relevance of changes over time and differences between groups. This study aims to establish these values for the KOOS-12 at 1 year postoperatively.

METHODS

KOOS-12 scores were calculated from the full-length KOOS completed by patients undergoing primary TKA preoperatively and at 1 year follow up. Minimal important change (MIC) values were estimated using the anchor-based predictive modeling approach and adjustment for the large proportion of improved patients in the study cohort was performed. The MCID was defined as the difference in the mean change in the KOOS-12 between the 'no improvement' and 'little improvement' groups.

RESULTS

A total of 352 patients (161 male:191 female) with an overall mean age of 67.9 years (standard deviation (SD) 8.2) and a mean body mass index of 31.4 kg/m² (SD 6.3) were included: 97.1% of patients reported an important improvement, 1.1% reported being about the same and 1.7% reported being importantly worse. The MIC improvement values were 11.5 for Pain, 13.7 for Function, 5.5 for Quality of Life (QoL) and 14.9 for the total KOOS-12 score. MCID values were 13.5 for Pain, 15.2 for Function, 8.0 for QoL and 11.1 for the total KOOS-12 score.

CONCLUSION

MIC of 14.9 and MCID of 11.1 established in this study can assist clinicians and researchers in the interpretation of within-group changes (MIC) and differences between groups (MCID) at 1 year after TKA.

A Patient-Reported Outcomes Measurement Information System Short Form for Measuring Physical Function During Geriatric Rehabilitation: Test-Retest Reliability, Construct Validity, Responsiveness, and Interpretability

OBJECTIVES

To study the test-retest reliability and measurement error, construct validity, responsiveness, interpretability, and floor/ceiling effects of a Patient-Reported Outcomes Measurement Information System (PROMIS) short form designed to measure physical function in geriatric rehabilitation patients (PROMIS-PF-GR).

DESIGN

Prospective cohort.

SETTING AND PARTICIPANTS

Inpatient geriatric rehabilitation patients.

METHODS

We evaluated the test-retest reliability by re-administering PROMIS-PF-GR 3 to 5 days after the admission measurement. The intraclass correlation coefficient (ICC) was calculated to determine test-retest reliability; an ICC of ≥0.70 was considered sufficient. Measurement error was established by calculating the standard error of measurement and smallest detectable change. Construct validity and responsiveness were determined by testing a priori formulated hypotheses (criterion: ≥75% hypothesis not rejected). Interpretability was evaluated by calculating the minimal important change using predictive modeling and a global rating as criterion for change. Floor/ceiling effects were established by calculating the percentage patients with the minimum/maximum raw score (criterion: ≤15%) at admission and discharge.

RESULTS

A total of 207 patients participated in the study [mean ± standard deviation age (80 ± 8.3 years), 58% female]. More than one-half of patients (56%) reported to be improved during rehabilitation. The ICC was 0.79 (95% confidence interval 0.70-0.84), the standardized error of measurement was 3.8, and the smallest detectable change 10.6. None of the 4 hypotheses for construct validity were rejected; 2 out of 5 hypotheses for responsiveness were rejected. The minimal important change was 8.0 (95% confidence interval 4.1-12.5). No floor/ceiling effects were found.

CONCLUSIONS AND IMPLICATIONS

The PROMIS-PG-GR showed sufficient test-retest reliability, measurement error, and construct validity. We did not find sufficient evidence for responsiveness, which may be due to the unexplained weak correlation between the PROMIS change score and the Global Rating Scale. We still recommend the use the PROMIS-PG-GR for measuring self-reported physical function in geriatric rehabilitation.

Minimal important change for the visual analogue scale foot and ankle (VAS-FA)

BACKGROUND

Visual analogue scale foot and ankle (VAS-FA) is a patient-reported outcome measure for foot and ankle disorders. The VAS-FA is validated into several languages and well adopted into use. Nonetheless, minimal important change (MIC) for the VAS-FA has not been estimated thus far.

METHODS

The VAS-FA score was obtained from 106 patients undergoing surgery for various foot and ankle complaints. MIC was estimated using an anchor-based predictive method.

RESULTS

The adjusted MIC was 6.8 for total VAS-FA score, and 9.3 for the Pain, 5.8 for the Function, and 5.7 for the Other complaints subscales. The VAS-FA score was found to separate improvement and deterioration in patients' foot and ankle condition.

CONCLUSIONS

MIC was successfully defined for the VAS-FA in the current study. The VAS-FA can be used to evaluate foot and ankle patients' clinical foot and ankle status and its change. Further research on estimating disease-specific MICs is recommended.

Which Oxford Knee Score level represents a satisfactory symptom state after undergoing a total knee replacement?

Background and purpose - Meaningful interpretation of postoperative Oxford Knee Score (OKS) levels is challenging. We established Patient Acceptable Symptoms State (PASS) and Treatment Failure (TF) values for the OKS in patients undergoing primary total knee replacement (TKR) in Denmark.Patients and methods - Data from patients undergoing primary TKR between February 2015 and January 2019 was extracted from the arthroplasty registry at the Copenhagen University Hospital, Hvidovre in Denmark. Data included 3, 12, and 24 months postoperative responses to the OKS and 2 anchor questions asking whether they considered their symptom state to be satisfactory, and if not, whether they considered the treatment to have failed. PASS and TF threshold values were calculated using the adjusted predictive modeling method. Non-parametric bootstrapping was used to derive 95% confidence intervals (CI).Results - Complete 3, 12, and 24 months postoperative data was obtained for 187 of 209 (89%), 884 of 915 (97%), and 575 of 586 (98%) patients, with median ages from 68 to 70 years (59 to 64% female). 72%, 77%, and 79% considered as having satisfactory symptoms, while 6%, 11%, and 11% considered the treatment to have failed, at 3, 12, and 24 months postoperatively, respectively. OKS PASS values (CI) were 27 (26-28), 30 (29-31), and 30 (29-31) at 3, 12, and 24 months postoperatively. TF values were 27 (26-28) and 27 (26-29) at 12 and 24 months postoperatively.Interpretation - The OKS PASS values can be used to guide the interpretation of TKR outcome and support quality assessment in institutional and national registries.

Challenges and solutions in prognostic prediction models in spinal disorders

Methodological shortcomings in prognostic modeling for patients with spinal disorders are highly common. This general commentary discusses methodological challenges related to the specific nature of this field. Five specific methodological challenges in prognostic modeling for patients with spinal disorders are presented with their potential solutions, as related to the choice of study participants, purpose of studies, limitations in measurements of outcomes and predictors, complexity of recovery predictions, and confusion of prognosis and treatment response. Large studies specifically designed for prognostic model research are needed, using standard baseline measurement sets, clearly describing participants' recruitment and accounting and correcting for measurement limitations.

Minimal important change (MIC): a conceptual clarification and systematic review of MIC estimates of PROMIS measures

We define the minimal important change (MIC) as a threshold for a minimal within-person change over time above which patients perceive themselves importantly changed. There is a lot of confusion about the concept of MIC, particularly about the concepts of minimal important change and minimal detectable change, which questions the validity of published MIC values. The aims of this study were: (1) to clarify the concept of MIC and how to use it; (2) to provide practical guidance for estimating methodologically sound MIC values; and (3) to improve the applicability of PROMIS by summarizing the available evidence on plausible PROMIS MIC values. We discuss the concept of MIC and how to use it and provide practical guidance for estimating MIC values. In addition, we performed a systematic review in PubMed on MIC values of any PROMIS measure from studies using recommended approaches. A total of 50 studies estimated the MIC of a PROMIS measure, of which 19 studies used less appropriate methods. MIC values of the remaining 31 studies ranged from 0.1 to 12.7 T-score points. We recommend to use the predictive modeling method, possibly supplemented with the vignette-based method, in future MIC studies. We consider a MIC value of 2-6 T-score points for PROMIS measures reasonable to assume at this point. For surgical interventions a higher MIC value might be appropriate. We recommend more high-quality studies estimating MIC values for PROMIS.

Assessing baseline dependency of anchor-based minimal important change (MIC): don't stratify on the baseline score!

PURPOSE

The minimal important change (MIC) of a patient-reported outcome measure (PROM) is often suspected to be baseline dependent, typically in the sense that patients who are in a poorer baseline health condition need greater improvement to qualify as minimally important. Testing MIC baseline dependency is commonly performed by creating two or more subgroups, stratified on the baseline PROM score. This study's purpose was to show that this practice produces biased subgroup MIC estimates resulting in spurious MIC baseline dependency, and to develop alternative methods to evaluate MIC baseline dependency.

METHODS

Datasets with PROM baseline and follow-up scores and transition ratings were simulated with and without MIC baseline dependency. Mean change MICs, ROC-based MICs, predictive MICs, and adjusted MICs were estimated before and after stratification on the baseline score. Three alternative methods were developed and evaluated. The methods were applied in a real data example for illustration.

RESULTS

Baseline stratification resulted in biased subgroup MIC estimates and the false impression of MIC baseline dependency, due to redistribution of measurement error. Two of the alternative methods require a second baseline measurement with the same PROM or another correlated PROM. The third method involves the construction of two parallel tests based on splitting the PROM's item set. Two methods could be applied to the real data.

CONCLUSION

MIC baseline dependency should not be tested in subgroups based on stratification on the baseline PROM score. Instead, one or more of the suggested alternative methods should be used.

Responsiveness, minimal important difference, minimal relevant difference, and optimal number of patients for a study

Several terms are used to describe changes in PROM scores in relation to treatments. Whether the change is small, large, or relevant is defined in different ways, yet these change scores are used to recommend or oppose treatments. They are also used to calculate the necessary number of patients for a study. This article offers a theoretical explanation behind the terms responsiveness, minimal important difference (MID), minimal important change (MIC), minimal relevant difference (MIREDIF), and threshold of clinical importance. It also gives instructions on how these and the optimal number of patients for a study are calculated. Responses to two domains of the Knee Injury and Osteoarthritis Outcome Score (KOOS), before and 1 year after reconstruction of the anterior cruciate ligament of 164 patients, are used to illustrate the calculations. This paper presents the most common methods used to calculate and interpret MID. Results vary substantially across domains, patient location on the scale, and health conditions. The optimal number of patients depends on the minimal relevant difference (MIREDIF), the standard error of the measure (SEM), the desired statistical power for the measurement, and the responsiveness of the measurement instrument (the PROM). There is often uncertainty surrounding the calculation and interpretation of responsiveness, MID, and MIREDIF, as these concepts are complex. When MID is used to evaluate research results, authors should specify how the MID was calculated, and its relevance for the study population. These measures should only be used after thorough consideration to justify healthcare decisions.

German translation, cross-cultural adaptation and validation of the Musculoskeletal Health Questionnaire: a cohort study

BACKGROUND

The Musculoskeletal Health Questionnaire (MSK-HQ) was developed to measure the health status of patients with various musculoskeletal conditions across multiple settings including rehabilitation.

AIM

Formal translation and cross-cultural adaptation of the MSK-HQ into German (MSK-HQ<inf>G</inf>), to determine test-retest-reliability, standard error of measurement (SEM), smallest detectable change (SDC), construct validity, responsiveness, minimal important change (MIC), and to test for floor or ceiling effects.

DESIGN

Cohort study with six weeks follow-up.

SETTING

Seven physiotherapy clinics/rehabilitation centres.

POPULATION

Patients with a referral for physiotherapy indicating musculoskeletal complaints of the spine or extremities.

METHODS

Translation and cross-cultural adaptation were carried out in accordance with guidelines provided by the developers. As reference standards we used pain intensity (0-10 numeric rating scale), quality of life (EQ5D-5L) and disability measures (RMDQ, NDI, WOMAC and SPADI) that were combined using z-scores.

RESULTS

On 100 patients (age 44.8±13.4 years, 66% female) the test-retest-reliability intraclass correlation coefficient was 0.87 (95% CI 0.72; 0.93) and for construct validity correlation with the combined disability measure was r<inf>s</inf>=-0.81 (95% CI -0.88, -0.72), the SEM was 3.4, the SDC (individual) 9.4, and the MIC 8.5.

CONCLUSIONS

Overall, the study provides evidence for good reliability and validity for the MSK-HQ<inf>G</inf>. Further studies in different settings and diagnostic subgroups should follow to better understand the psychometric properties of this measure in primary care, rehabilitation and specialist care settings.

CLINICAL REHABILITATION IMPACT

The results demonstrate that the MSK-HQ<inf>G</inf> has sufficient psychometric properties for use in musculoskeletal research and practice. However, the SDC should be kept in mind when using the tool for individual patients. The MSK-HQ<inf>G</inf> has the advantage of being a single instrument that can measure musculoskeletal health status across different pain sites, reducing the burden from the use of multiple tools.

Measurement properties of the musculoskeletal health questionnaire (MSK-HQ): a between country comparison

BACKGROUND

The Musculoskeletal Health Questionnaire (MSK-HQ) has been developed to measure musculoskeletal health status across musculoskeletal conditions and settings. However, the MSK-HQ needs to be further evaluated across settings and different languages.

OBJECTIVE

The objective of the study was to evaluate and compare measurement properties of the MSK-HQ across Danish (DK) and English (UK) cohorts of patients from primary care physiotherapy services with musculoskeletal pain.

METHODS

MSK-HQ was translated into Danish according to international guidelines. Measurement invariance was assessed by differential item functioning (DIF) analyses. Test-retest reliability, measurement error, responsiveness and minimal clinically important change (MCIC) were evaluated and compared between DK (n = 153) and UK (n = 166) cohorts.

RESULTS

The Danish version demonstrated acceptable face and construct validity. Out of the 14 MSK-HQ items, three items showed DIF for language (pain/stiffness at night, understanding condition and confidence in managing symptoms) and three items showed DIF for pain location (walking, washing/dressing and physical activity levels). Intraclass Correlation Coefficients for test-retest were 0.86 (95% CI 0.81 to 0.91) for DK cohort and 0.77 (95% CI 0.49 to 0.90) for the UK cohort. The systematic measurement error was 1.6 and 3.9 points for the DK and UK cohorts respectively, with random measurement error being 8.6 and 9.9 points. Receiver operating characteristic (ROC) curves of the change scores against patients' own judgment at 12 weeks exceeded 0.70 in both cohorts. Absolute and relative MCIC estimates were 8-10 points and 26% for the DK cohort and 6-8 points and 29% for the UK cohort.

CONCLUSIONS

The measurement properties of MSK-HQ were acceptable across countries, but seem more suited for group than individual level evaluation. Researchers and clinicians should be aware that some discrepancy exits and should take the observed measurement error into account when evaluating change in scores over time.

Minimal important differences for the WOMAC osteoarthritis index and the Forgotten Joint Score-12 in total knee arthroplasty patients

BACKGROUND

Total knee arthroplasty (TKA) is an effective treatment for end-stage osteoarthritis. Patient reported-outcome measures (PROMs) capture the patients' perception of the success of an intervention. The minimal important difference (MID) is an important characteristic of the PROM, which helps to interpret results. The aim of this study was to identify the MID for the Forgotten Joint Score-12 (FJS-12) and Western Ontario and McMaster Universities (WOMAC) osteoarthritis index.

METHODS

Data were collected in a prospective cohort study. Patients were asked to complete the FJS-12, WOMAC osteoarthritis index and transition items evaluating change over time to determine the MID. We employed an anchor-based methodology relating score change to the response categories of the transition items using both binary logistic regression and receiver operating characteristic (ROC) analysis.

RESULTS

Data from 199 patients were analysed. Mean age was 72.3 years, 58% were women. Employing binary logistic regression the MID for the FJS-12 was 10.8 points, for the WOMAC pain score 7.5 points and for the WOMAC function score 7.2 points. ROC analyses found a MID of 13.0 points for the FJS-12, 12.5 points for WOMAC pain and 14.7 points for WOMAC function.

CONCLUSION

We report MIDs for the FJS-12 and the WOMAC Pain and Function scales in a TKA patient cohort, which can be used to interpret meaningful differences in score. In line with previous research, we found more advanced statistical methods to result in smaller MID estimates for both scores.

TRIAL REGISTRATION

Written consent for this study was obtained from all participants and ethical approval was granted by the local ethics committee (Ethikkommission St. Gallen; EKSG 14/973; Registered 03 July 2014; http://www.sg.ch/home/gesundheit/ethikkommission.html).

Evaluating the credibility of anchor based estimates of minimal important differences for patient reported outcomes: instrument development and reliability study

OBJECTIVE

To develop an instrument to evaluate the credibility of anchor based minimal important differences (MIDs) for outcome measures reported by patients, and to assess the reliability of the instrument.

DESIGN

Instrument development and reliability study.

DATA SOURCES

Initial criteria were developed for evaluating the credibility of anchor based MIDs based on a literature review (Medline, Embase, CINAHL, and PsycInfo databases) and the experience of the authors in the methodology for estimation of MIDs. Iterative discussions by the team and pilot testing with experts and potential users facilitated the development of the final instrument.

PARTICIPANTS

With the newly developed instrument, pairs of masters, doctoral, or postdoctoral students with a background in health research methodology independently evaluated the credibility of a sample of MID estimates.

MAIN OUTCOME MEASURES

Core credibility criteria applicable to all anchor types, additional criteria for transition rating anchors, and inter-rater reliability coefficients were determined.

RESULTS

The credibility instrument has five core criteria: the anchor is rated by the patient; the anchor is interpretable and relevant to the patient; the MID estimate is precise; the correlation between the anchor and the outcome measure reported by the patient is satisfactory; and the authors select a threshold on the anchor that reflects a small but important difference. The additional criteria for transition rating anchors are: the time elapsed between baseline and follow-up measurement for estimation of the MID is optimal; and the correlations of the transition rating with the baseline, follow-up, and change score in the patient reported outcome measures are satisfactory. Inter-rater reliability coefficients (ĸ) for the core criteria and for one item from the additional criteria ranged from 0.70 to 0.94. Reporting issues prevented the evaluation of the reliability of the three other additional criteria for the transition rating anchors.

CONCLUSIONS

Researchers, clinicians, and healthcare policy decision makers can consider using this instrument to evaluate the design, conduct, and analysis of studies estimating anchor based minimal important differences.

Responsiveness and minimal important change of the QuickDASH and PSFS when used among patients with shoulder pain

Background

The Quick Disabilities of the Arm, Shoulder and Hand questionnaire (QuickDASH) and the Patient-Specific Functional Scale (PSFS) are commonly used outcome instruments for measuring self-reported disability in patients with shoulder pain. To date, few studies have evaluated the responsiveness and estimated their minimal important change (MIC). Further assessment will expand the current knowledge and improve the interpretability of these instruments in clinical and research practice. The purpose of this prospective cohort study with 3 months follow-up was to evaluate the responsiveness of the QuickDASH and PSFS in patients with shoulder pain, and to estimate their MICs by using two different anchor-based methods.

Methods

Patients with shoulder pain recruited at a multidisciplinary hospital outpatient clinic completed the QuickDASH and PSFS at baseline and at 3 months follow-up. The responsiveness was evaluated by using a criterion approach with the area under the receiver operating characteristic curve (AUC) and a construct approach by testing 9 a-priori hypotheses. The MIC was assessed using two anchor-based MIC methods.

Results

134 patients participated at baseline and 117 (87.3%) at 3 months follow-up. The AUC was acceptable for both QuickDASH (0.75) and PSFS (0.75). QuickDASH met 7 (77.8%) and PSFS 8 (88.9%) of the hypotheses. None of the instruments showed signs of floor and ceiling effects. The MIC estimates ranged from 10.8 to 13.6 for QuickDASH and from 1.9 to 2.0 for PSFS, depending on the method used.

Conclusion

This study demonstrates that both the QuickDASH and PSFS are responsive measures of disability in patients with shoulder pain. The estimated MIC values were presented.

Minimal important change in physical function in trauma patients: a study using the short musculoskeletal function assessment

Purpose

The Short Musculoskeletal Function Assessment (SMFA) questionnaire can be used to evaluate physical functioning in patients with traumatic injuries. It is not known what change in score reflects a meaningful change to patients. The aim was to determine minimal important change (MIC) values of the subscales (0–100) of the Dutch SMFA-NL in a sample of patients with a broad range of injuries.

Methods

Patients between 18 and 65 years of age completed the SMFA-NL and the Global Rating of Effect (GRE) questions at 6-week and 12-month post-injury. Anchor-based MIC values were calculated using univariable logistic regression analyses.

Results

A total of 225 patients were included (response rate 67%). The MIC value of the Upper Extremity Dysfunction (UED) subscale was 8 points, with a misclassification rate of 43%. The Lower Extremity Dysfunction subscale MIC value was 14 points, with a misclassification rate of 29%. The MIC value of the Problems with Daily Activities subscale was 25 points, with a misclassification rate of 33%. The MIC value of the Mental and Emotional Problems (MEP) subscale was 7 points, with a misclassification rate 37%.

Conclusion

MIC values of the SMFA-NL were determined. The MIC values aid interpreting whether a change in physical functioning can be considered clinically important. Due to the considerable rates of misclassification, the MIC values of the UED and MEP subscales should be used with caution.

The Patient-Oriented Eczema Measure: estimating the minimal important change in an outpatient clinic cohort

BACKGROUND

Patient-Oriented Eczema Measure (POEM) measures patient-reported symptoms in atopic dermatitis (AD). It is the recommended core outcome instrument to capture the symptoms domain in AD clinical trials. Understanding the minimal important change (MIC) in the POEM score is therefore important in both trial and clinical care settings. Previous studies have mainly evaluated MIC estimates among children in trial settings. The MIC estimate for POEM in a clinical setting is often lacking.

OBJECTIVES

We aim to estimate the MIC of the POEM using both distribution-based and anchor-based methods in a clinical cohort of adult eczema patients.

METHODS

Both distribution-based and anchor-based methods were used to calculate the MIC of the POEM in a clinical cohort of Asian adult patients attending the eczema clinic at a tertiary dermatology centre in Singapore. Scoring AD (SCORAD) was used as the disease severity anchor for the anchor-based methods. The smallest detectable change (SDC) for POEM was also calculated as the threshold for any measurement error.

RESULTS

There were a total of 85 adult AD patients in the cohort that contributed a total of 114 paired measurements of both POEM and SCORAD. The SDC in our study was 1.68. The MIC estimates were 3.64 and 1.46 based on 0.5 standard deviation (SD) and 0.2 SD distribution-based methods. Anchor-based methods such as the receiver operating curve and predictive modelling methods yielded MIC values of 0.50 and 1.05, respectively.

CONCLUSIONS

Minimal important change for POEM varied according to the methods and approaches used. Only a change of two points or more in POEM could be considered beyond any measurement errors and clinically important. This finding is consistent even in a clinical setting of Asian adults with eczema.

Longitudinal changes in patient-reported outcome measures following total hip arthroplasty and predictors of deterioration during follow-up

Aims

The primary aim of this study was to quantify the improvement in patient-reported outcome measures (PROMs) following total hip arthroplasty (THA), as well as the extent of any deterioration through the seven-year follow-up. The secondary aim was to identify predictors of PROM improvement and deterioration.

Patients and Methods

A total of 976 patients were enrolled into a prospective, international, multicentre study. Patients completed a battery of PROMs prior to THA, at three months post-THA, and at one, three, five, and seven-years post-THA. The Harris Hip Score (HHS), the 36-Item Short-Form Health Survey (SF-36) Physical Component Summary (PCS), the SF-36 Mental Component Summary (MCS), and the EuroQol five-dimension three-level (EQ-5D) index were the primary outcomes. Longitudinal changes in each PROM were investigated by piece-wise linear mixed effects models. Clinically significant deterioration was defined for each patient as a decrease of one half of a standard deviation (group baseline).

Results

Improvements were noted in each PROM between the preoperative and one-year visits, with one-year values exceeding age-matched population norms. Patients with difficulty in self-care experienced less improvement in HHS (odds ratio (OR) 2.2; p = 0.003). Those with anxiety/depression experienced less improvement in PCS (OR -3.3; p = 0.002) and EQ-5D (OR -0.07; p = 0.005). Between one and seven years, obesity was associated with deterioration in HHS (1.5 points/year; p = 0.006), PCS (0.8 points/year; p < 0.001), and EQ-5D (0.02 points/year; p < 0.001). Preoperative difficulty in self-care was associated with deterioration in HHS (2.2 points/year; p < 0.001). Preoperative pain from other joints was associated with deterioration in MCS (0.8 points/year; p < 0.001). All aforementioned factors were associated with clinically significant deterioration in PROMs (p < 0.035), except anxiety/depression with regard to PCS (p = 0.060).

Conclusion

The present study finds that patient factors affect the improvement and deterioration in PROMs over the medium term following THA. Special attention should be given to patients with risk factors for decreased PROMs, both preoperatively and during follow-up. Cite this article: Bone Joint J 2019;101-B:768–778.