Adaptation of the Patient Benefit Assessment Scale for Hospitalised Older Patients: development, reliability and validity of the P-BAS picture version

Background The Patient Benefit Assessment Scale for Hospitalised Older Patients (P-BAS HOP) is a tool developed to both identify the priorities of the individual patient and to measure the outcomes relevant to him/her, resulting in a Patient Benefit Index (PBI), indicating how much benefit the patient had experienced from the hospitalisation. The reliability and the validity of the P-BAS HOP appeared to be not yet satisfactory and therefore the aims of this study were to adapt the P-BAS HOP and transform it into a picture version, resulting in the P-BAS-P, and to evaluate its feasibility, reliability, validity, responsiveness and interpretability. Methods Process of instrument development and evaluation performed among hospitalised older patients including pilot tests using Three-Step Test-Interviews (TSTI), test-retest reliability on baseline and follow-up, comparing the PBI with Intraclass Correlation Coefficient (ICC), and hypothesis testing to evaluate the construct validity. Responsiveness of individual P-BAS-P scores and the PBI with two different weighing schemes were evaluated using anchor questions. Interpretability of the PBI was evaluated with the visual anchor-based minimal important change (MIC) distribution method and computation of smallest detectable change (SDC) based on ICC. Results Fourteen hospitalised older patients participated in TSTIs at baseline and 13 at follow-up after discharge. After several adaptations, the P-BAS-P appeared feasible with good interviewer’s instructions. The pictures were considered relevant and helpful by the participants. Reliability was tested with 41 participants at baseline and 50 at follow-up. ICC between PBI1 and PBI2 of baseline test and retest was 0.76, respectively 0.73. At follow-up 0.86, respectively 0.85. For the construct validity, tested in 169 participants, hypotheses regarding importance of goals were confirmed. Regarding status of goals, only the follow-up status was confirmed, baseline and change were not. The responsiveness of the individual scores and PBI were weak, resulting in poor interpretability with many misclassifications. The SDC was larger than the MIC. Conclusions The P-BAS-P appeared to be a feasible instrument, but there were methodological barriers for the evaluation of the reliability, validity, and responsiveness. We therefore recommend further research into the P-BAS-P.

Subsequent surgery after primary ACLR results in a significantly inferior subjective outcome at a 2-year follow-up

Purpose To analyze minimal important change (MIC), patient-acceptable symptom state (PASS) and treatment failure after reoperation within 2 years of primary ACL reconstruction and compare them with patients without additional surgery. Methods This is a retrospective follow-up study of a cohort from a single-clinic database with all primary ACLRs enrolled between 2005 and 2015. Additional surgery within 2 years of the primary ACLR on the ipsilateral knee was identified using procedural codes and analysis of medical records. Patients who completed the Knee injury and Osteoarthritis Outcome Score (KOOS) questionnaire preoperatively and at the 2-year follow-up were included in the study. MIC, PASS and treatment failure thresholds were applied using the aggregate KOOS (KOOS4) and the five KOOS subscales. Results The cohort included 6030 primary ACLR and from this 1112 (18.4%) subsequent surgeries were performed on 1018 (16.9%) primary ACLRs. 24 months follow-up for KOOS was obtained on 523 patients (54%) in the reoperation group and 2084 (44%) in the no-reoperation group. MIC; the no-reoperation group had a significantly higher improvement on all KOOS subscales, Pain 70.3 vs 60.2% (p < 0.01), Symptoms 72.1 vs 57.4% (p < 0.01), ADL 56.3 vs 51.2% (p < 0.01), Sport/Rec 67.3 vs 54.4% (p < 0.01), QoL 73.9 vs 56.3% (p < 0.01). PASS; 62% in the non-reoperation group reported their KOOS4 scores to be satisfactory, while only 35% reported satisfactory results in the reoperated cohort (p < 0.05). Treatment failure; 2% in the non-reoperation group and 6% (p < 0.05) in the reoperation group considered their treatment to have failed. Conclusion Patients who underwent subsequent surgeries within 2 years of primary ACLR reported significantly inferior outcomes in MIC, PASS and treatment failure compared to the non-reoperated counterpart at the 2-year follow-up. This study provides clinicians with important information and knowledge about the outcomes after an ACLR with subsequent additional surgery. Level of evidence III.

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 (MICMeanChange), the receiver operating characteristic (MICROC) analysis, and the predictive modeling method adjusted for the proportion of improved patients (MICadjust). In this study, the MICadjust 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 MICadjust 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 MICMeanChange and MICROC values were considered less reasonable to interpret because the proportions of the improved patients subgroup were more than 50% (82.5%). Conclusions The MICadjust 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.

Changes and thresholds in the Forgotten Joint Score after total hip arthroplasty

Aims The aim of this study was to identify the minimal clinically important difference (MCID), minimal important change (MIC), minimal detectable change (MDC), and patient-acceptable symptom state (PASS) in the Forgotten Joint Score (FJS) according to patient satisfaction six months following total hip arthroplasty (THA) in a UK population. Methods During a one-year period, 461 patients underwent a primary THA and completed preoperative and six-month FJS, with a mean age of 67.2 years (22 to 93). At six months, patient satisfaction was recorded as very satisfied, satisfied, neutral, dissatisfied, or very dissatisfied. The difference between patients recording neutral (n = 31) and satisfied (n = 101) was used to define the MCID. MIC for a cohort was defined as the change in the FJS for those patients declaring their outcome as satisfied, whereas receiver operating characteristic curve analysis was used to determine the MIC for an individual and the PASS. Distribution-based methodology was used to calculate the MDC. Results Using satisfaction as the anchor, the MCID for the FJS was 8.1 (95% confidence interval (CI) 3.7 to 15.9; p = 0.040), which was affirmed when adjusting for confounding. The MIC for the FJS for a cohort of patients was 17.7 (95% CI 13.7 to 21.7) and for an individual patient was 18. The MDC90 for the FJS was eight, meaning that 90% of patients scoring more than this will have experienced a real change that is beyond measurement error. The PASS threshold for the FJS was defined as 29. Conclusion The MCID and MIC can be used respectively to assess whether there is a clinical difference between two groups, or whether a cohort or patient has had a meaningful change in their FJS. Both values were greater than measurement error (MDC90), suggesting a real change. The PASS threshold for the postoperative FJS can be used as a marker of achieving patient satisfaction following THA. Cite this article: Bone Joint J 2021;103-B(12):1759–1765.

Uterine Fibroid Symptom and Quality of Life questionnaire (UFS-QOL NL) in the Dutch population: a validation study

ObjectiveUterine fibroids can cause a variety of symptoms in women, from heavy menstrual bleeding and dysmenorrhea to bulk symptoms. The Uterine Fibroid Symptom and health-related Quality Of Life questionnaire (UFS-QOL) is a patient-reported outcome measure developed for assessing fibroid-related symptoms in a standardised way. Our aim was to translate and validate the UFS-QOL in Dutch.DesignValidation study.SettingPatients were recruited by a gynaecologist at the outpatient clinic.ParticipantsWomen with uterine fibroids.MethodsThe UFS-QOL was translated into Dutch (UFS-QOL NL) and validated through testing construct validity (comprising of structural validity and hypotheses testing), reliability, responsiveness and interpretability, assessing floor and ceiling effects and minimal important change. An option to answer ‘not applicable’ was added to the translated questionnaire.Results191 women with uterine fibroids completed the UFS-QOL NL at baseline, after 2 weeks and after 3 months. The questionnaire retained the same factor structure after translation (Comparative Fit Index 0.94–0.95; Tucker-Lewis fit Index 0.93–0.95; Root Mean Square Error of Approximation 0.10–0.11) and correlations to other questionnaires (RAND 36, Hospital Anxiety and Depression Scale and Golombok Rust Inventory of Sexual Satisfaction) were generally moderate, as hypothesised (Pearson’s r 0.3–0.7). We found a sufficient reliability with intraclass correlation coefficients of approximately 0.8–0.9 for all subscales. Responsiveness was sufficient when testing hypotheses comparing women who had surgery with those who did not. Cronbach’s alpha was higher than 0.7 for all subscales, indicating sufficient internal consistency and there were no concerns about floor or ceiling effects. Minimal important change could not be calculated due to low correlation between the different subscales and the anchor question.ConclusionsThe results support the measurement properties of the Dutch UFS-QOL for assessing fibroid-related symptoms and health-related quality of life in Dutch women with uterine fibroids.

Minimal important change and responsiveness of the Migraine Disability Assessment Score (MIDAS) questionnaire

Background The MIDAS is the most used questionnaire to evaluate migraine-related disability, but its utility to assess treatment response remains unclear. Our aim was to estimate the MIDAS’ minimal important change (MIC) value and its responsiveness. Methods A total of 103 patients were enrolled in a non-pharmacological, preference-based clinical trial. MIDAS and global rating of self-perceived change (GRoC) scores were collected at baseline, after 5 weeks of treatment, 4-weeks and 3-months follow-up after treatment. Anchor-based approaches were used to establish MIC values and responsiveness. Findings In all 3 timepoint comparisons, MIDAS presented a MIC of 4.5 points. A moderate positive correlation was identified between the MIDAS change and GRoC scores. The area under the curve ranged from 0.63 to 0.68. Conclusions This study showed that MIDAS has a limited responsiveness to change. A change of 4.5 points or more represents a clinically important change for patients with high frequent migraine and chronic migraine receiving non-pharmacological treatment.

The minimal important change for the QuickDASH in patients with thumb carpometacarpal arthritis

Evaluating the effect of treatment through change in patient-reported outcomes requires an understanding of the minimal important change. The aim of this study was to report the minimal important change for the Quick Disability of the Arm, Shoulder and Hand questionnaire (QuickDASH) in patients receiving surgical treatment for thumb carpometacarpal joint osteoarthritis. Three hundred and fifteen patients were seen before and 6 months following surgery. Two methods were used to calculate the minimal important change: a distribution-based method calculating the standard error of measurement and an anchor-based method based on the receiver operating characteristic curve. The minimal important change for QuickDASH was estimated to be 18.2 points using the anchor-based method. The area under the receiver operating curve was 0.82, indicating a satisfactory accuracy. The minimal important change was estimated to be 10.3 points using the distribution-based method. These values may be useful in future research on thumb carpometacarpal joint osteoarthritis. Level of evidence: III

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.

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.