Explaining Personalized Activity Limitations in Patients With Hand and Wrist Disorders: Insights from Sociodemographic, Clinical, and Mindset Characteristics.

OBJECTIVES: To investigate the association of sociodemographic, clinical, and mindset characteristics on outcomes measured with a patient-specific patient-reported outcome measure (PROM); the Patient Specific Functional Scale (PSFS). Secondly, we examined whether these factors differ when a fixed-item PROM, the Michigan Hand Outcome Questionnaire (MHQ), is used as an outcome. DESIGN: Cohort study, using the aforementioned groups of factors in a hierarchical linear regression. SETTING: Twenty-six clinics for hand and wrist conditions in the Netherlands. PARTICIPANTS: Two samples of patients with various hand and wrist conditions and treatments: n=7111 (PSFS) and n=5872 (MHQ). INTERVENTIONS: NA. MAIN OUTCOME MEASURES: The PSFS and MHQ at 3 months. RESULTS: The PSFS exhibited greater between-subject variability in baseline, follow-up, and change scores than the MHQ. Better PSFS outcomes were associated with: no involvement in litigation (ß[95% confidence interval=-0.40[-0.54;-0.25]), better treatment expectations (0.09[0.06;0.13]), light workload (0.08[0.03;0.14]), not smoking (-0.07[-0.13;-0.01]), men sex (0.07[0.02;0.12]), better quality of life (0.07[0.05;0.10]), moderate workload (0.06[0.00;0.13]), better hand satisfaction (0.05[0.02; 0.07]), less concern (-0.05[-0.08;-0.02]), less pain at rest (-0.04[-0.08;-0.00]), younger age (-0.04[-0.07;-0.01]), better comprehensibility (0.03[0.01;0.06]), better timeline perception (-0.03[-0.06;-0.01]), and better control (-0.02[-0.04;-0.00]). The MHQ model was highly similar but showed a higher R2 than the PSFS model (0.41 vs 0.15), largely due to the R2 of the baseline scores (0.23 for MHQ vs 0.01 for PSFS). CONCLUSIONS: Health care professionals can improve personalized activity limitations by addressing treatment expectations and illness perceptions, which affect PSFS outcomes. Similar factors affect the MHQ, but the baseline MHQ score has a stronger association with the outcome score than the PSFS. While the PSFS is better for individual patient evaluation, we found that it is difficult to explain PSFS outcomes based on baseline characteristics compared with the MHQ. Using both patient-specific and fixed-item instruments helps health care professionals develop personalized treatment plans that meet individual needs and goals.

Factors associated with self-reported pain and hand function following dorsal wrist ganglion excision.

This study aimed to analyse which factors contribute to pain and limited hand function after dorsal wrist ganglion excision. We included 308 patients who underwent surgery between September 2017 and August 2021. Patients completed baseline questionnaires and the patient-rated wrist/hand evaluation questionnaire at baseline and 3 months postoperatively. We observed an improvement in postoperative pain and hand function, but individual outcomes were highly variable. We performed stepwise linear regression analyses to examine which patient characteristics, disease characteristics and psychological factors were associated with postoperative pain and hand function. Higher postoperative pain intensity was associated with recurrence following previous surgery, treatment of the dominant hand, higher baseline pain intensity, lower credibility the patient attributes to the treatment and longer symptom duration. Worse hand function was associated with recurrence following prior surgery, worse baseline hand function and lower treatment credibility. Clinicians should take these findings into account during patient counselling and expectation management.Level of evidence: II.

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.