The Fatigue Associated with Depression Questionnaire (FAsD): responsiveness and responder definition

Purpose

The Fatigue Associated with Depression Questionnaire (FAsD) was developed to assess fatigue and its impact among patients with depression. The purpose of this study was to examine the questionnaire’s responsiveness to change and identify a responder definition for interpretation of treatment-related changes.

Methods

Data were collected at baseline and at 6 weeks from patients with depression starting treatment with a new antidepressant.

Results

Of the 96 participants, 55.2% were women, with a mean age of 43.4 years. The total score and both subscales demonstrated statistically significant change with moderate to large effect sizes (absolute values ≥0.76). FAsD change scores were significantly correlated with change on the Brief Fatigue Inventory (r ≥ 0.73; p < 0.001). FAsD mean change scores discriminated among patient subgroups differing by degree of improvement in patient- and clinician-reported fatigue and depression. Responder definition for the two subscales and total score (0.67, 0.57, 0.62) was estimated primarily based on mean change among patients who reported a small but important improvement in fatigue.

Discussion

The FAsD was responsive to change, and the responder definition may be used when interpreting treatment-related change. Results add to previous findings suggesting the FAsD is a useful measure of fatigue among patients with depression.     

Moving from significance to real-world meaning: methods for interpreting change in clinical outcome assessment scores

Purpose

Clinical outcome assessments (COAs) require evidence not only of reliability, validity, and ability to detect change, but also a definition of what constitutes a meaningful change on the instrument. The responder definition specifies the amount of change on the COA that may be interpreted as a treatment benefit and is critical for interpreting what constitutes a meaningful change on the COA scores. However, the literature that describes methods for developing and applying responder definitions can be difficult to navigate. Clear and concise guidelines regarding which methods to apply under what circumstances and how to interpret the results are lacking. This article provides a guide to the variety of available methods and issues that should be considered when establishing responder definitions for interpreting meaningful changes in COA scores.

Methods

An overview is provided for selecting anchors, developing study designs, planning psychometric analyses, using psychometric results to set responder thresholds, and applying responder thresholds in demonstrating treatment efficacy.

Results

There are a variety of anchor-based methods for consideration, but they all rely on a preference for strongly related and easily interpretable anchors. The benefits of applying multiple anchors and multiple analytic methods are discussed. The process of triangulation can synthesize results across multiple sources to gain confidence in a proposed responder definition. Though a link to meaningfulness from the patient’s perspective is absent, distribution-based methods provide lower bound estimates of score precision and have a role in triangulation. Responder definitions are typically required within regulatory review, but their application may differ across clinical trial programs.

Conclusions

By careful planning of anchor selection, study design, and psychometric methods, COA researchers can establish defensible responder thresholds that ultimately aid patients and clinicians in making informed treatment decisions.

     

Distribution- and anchor-based methods to determine the minimally important difference on patient-reported outcome questionnaires in oncology: a structured review

Background

Interpretation of differences or changes in patient-reported outcome scores should not only consider statistical significance, but also clinical relevance. Accordingly, accurate determination of the minimally important difference (MID) is crucial to assess the effectiveness of health care interventions, as well as for sample size calculation. Several methods have been proposed to determine the MID. Our aim was to review the statistical methods used to determine MID in patient-reported outcome (PRO) questionnaires in cancer patients, focusing on the distribution- and anchor-based approaches and to present the variability of criteria used as well as possible limitations.

Methods

We performed a systematic search using PubMed. We searched for all cancer studies related to MID determination on a PRO questionnaire. Two reviewers independently screened titles and abstracts to identify relevant articles. Data were extracted from eligible articles using a predefined data collection form. Discrepancies were resolved by discussion and the involvement of a third reviewer.

Results

Sixty-three articles were identified, of which 46 were retained for final analysis. Both distribution- and anchor-based approaches were used to assess the MID in 37 studies (80.4%). Different time points were used to apply the distribution-based method and the most frequently reported distribution was the 0.5 standard deviation at baseline. A change in a PRO external scale (N =?13, 30.2%) and performance status (N =?15, 34.9%) were the most frequently used anchors. The stability of the MID over time was rarely investigated and only 28.2% of studies used at least 3 assessment timepoints. The robustness of anchor-based MID was questionable in 37.2% of the studies where the minimal number of patients by anchor category was less than 20.

Conclusion

Efforts are needed to improve the quality of the methodology used for MID determination in PRO questionnaires used in oncology. In particular, increased attention to the sample size should be paid to guarantee reliable results. This could increase the use of these specific thresholds in future studies.

     

A Review of Patient-Reported Outcome Labeling in the United States (2011–2015)

Background

A review of new drug approvals (NDAs) by the Food and Drug Administration (FDA) for 2006 to 2010 showed that 24.1% of new drugs had patient-reported outcome (PRO) labeling.

Exploration of oncologists’ attitudes toward and perceived value of patient-reported outcomes

Purpose

To understand oncologists’ attitudes toward patient-reported outcome (PRO) measures and to learn how PRO data influence their clinical decision-making.

Methods

Twenty practicing oncologists participated in 1 of 4 semi-structured focus groups.

Results

Most oncologists had no experience with PRO measures, but were able to identify several concepts appropriate for patient-reported assessment. Participants agreed that clinical measures such as performance status were more meaningful to them, but acknowledged that PRO measures were more appropriate for assessing patient symptoms and treatment response. All oncologists believed that clinical efficacy and toxicity data were of primary importance, but that PROs become increasingly important when multiple treatments are available, in advanced or incurable disease, and in palliative care. Several issues prevented oncologists from being able to draw meaningful conclusions from PRO data: lack of familiarity with PRO measures, being presented with too much data to process, lack of clarity around a meaningful change in PRO measure scores, and lack of standardization in the use of PRO measures.

Conclusions

Oncologists indicated that PRO data are most influential in advanced or incurable disease and in palliative care. Improving the interpretability of PRO measures could increase the usefulness of PRO data in treatment decision-making.     

Minimal clinically important differences in the EORTC QLQ-BM22 and EORTC QLQ-C15-PAL modules in patients with bone metastases undergoing palliative radiotherapy

Purpose

Validated tools for evaluating quality of life (QOL) in patients with bone metastases include the EORTC QLQ-BM22 and QLQ-C15-PAL modules. A statistically significant difference in metric scores may not be clinically significant. To aid in their interpretation, we performed analyses to determine the minimal clinically important differences (MCID) for these QOL instruments.

Methods

Both anchor-based and distribution-based methods were used to determine the MCID among patients with bone metastases enrolled in a randomized phase III trial. For the anchor-based approach, overall QOL as measured by the QLQ-C15-PAL module was used as the anchor and only the subscales with moderate or better correlation were used for subsequent MCID analysis. In the anchor-based approach, patients were classified as improved, stable or deteriorated by the change in the overall QOL score from baseline to follow-up after 42 days. The MCID and confidence interval was then calculated for all subscales. In the distribution-based approach, the MCID was expressed as a proportion of the standard deviation and standard error measurement from the subscale score distribution.

Results

A total of 204 patients completed the questionnaires at baseline and follow-up. Only the dyspnea and insomnia subscales did not have at least moderate correlation with the overall QOL anchor. Using the anchor-based approach, 10/11 subscales had an MCID score significantly different than 0 for improvement and 3/11 subscales had a significant MCID score for deterioration. The magnitude of MCID scores was higher for improvement in comparison with deterioration. For improvement, the anchor-based approach showed good agreement with the distribution-based approach when using 0.5 SD as the MCID. However, there was greater lack of agreement between these approaches for deterioration.

Conclusion

We present the MCID scores for the EORTC QLQ-BM22 and QLQ-C15-PAL QOL instruments. The results of this study can guide clinicians in the interpretation of these instruments.

Clinical Trials Registry

NCT01248585.

     

The impact of a recent relapse on patient-reported outcomes in subjects with multiple sclerosis

Purpose

In this study, we estimate the impact of a recent relapse on physical and mental health in subjects with relapsing-remitting multiple sclerosis (RRMS) using validated patient-reported outcome (PRO) measures.

Methods

Subjects enrolled in the Comprehensive Longitudinal Investigation of MS at the Brigham and Women??s Hospital with RRMS were eligible for enrollment. Subjects with a clinical visit within 45?days of a relapse were identified and divided into groups based on whether the relapse occurred before (recent relapse) (n?=?59) or after the visit (pre-relapse) (n?=?31). A group of subjects with no relapses was also identified (remission) (n?=?336). PRO measures in these three groups were compared. All outcomes were compared using a t test and linear regression controlling for age, disease duration, sex, and EDSS.

Results

Subjects with a recent relapse had significantly worse functioning on several physical and mental health scales compared to subjects in remission even after adjusting for potential confounders. Subjects with a recent relapse also showed significant deterioration on PRO measures over 1?year compared to subjects in remission (P?<?0.05 for each comparison). Subjects in the pre-relapse group were not significantly different than subjects in remission.

Conclusions

Clinical relapses have a measurable effect on PRO in subjects with RRMS.     

Validity of the FACT Hepatobiliary (FACT-Hep) questionnaire for assessing disease-related symptoms and health-related quality of life in patients with metastatic pancreatic cancer

Purpose

Evaluate reliability and validity of the Functional Assessment of Cancer Therapy-Hepatobiliary (FACT-Hep) questionnaire and its derivative FACT Hepatobiliary Symptom Indexes (FHSI-18 and FHSI-8) in people with metastatic pancreatic cancer.

Methods

Self-reported questionnaire data from a randomized controlled Phase II study evaluating the efficacy and safety of conatumumab (AMG 655), ganitumab (AMG 479) or placebo combined with gemcitabine were evaluated. The following were assessed: internal consistency, using Cronbach’s α; discriminant validity, comparing baseline patient-reported outcomes (PRO) scores across Eastern Cooperative Oncology Group (ECOG) performance status (PS) levels; and ability to detect change, comparing change from baseline PRO score at each cycle across PS and tumour response groups.

Results

The analysis included 96 patients. All scale scores demonstrated good internal consistency (Cronbach’s α > 0.7) and discriminant validity. Baseline scores were significantly poorer among patients with PS = 1 versus patients with PS = 0 (e.g. difference in FACT-Hep total score ?17.27; p < 0.001). Ability to detect change was established for Cycles 2/3 versus baseline; PRO scores reduced in the PS-worsened group versus the PS-stable group (e.g. difference in FACT-Hep total score ?24.29; p < 0.001). All PRO scale scores showed significant decline for progressive disease versus stable disease (e.g. difference in FACT-Hep total score ?12.58; p = 0.004). Changes on the FHSI-18 and FHSI-8 scales were similar in magnitude whether ECOG improved or worsened.

Conclusions

FACT-Hep detects change and is a reliable and valid instrument for measuring health-related quality of life in patients with metastatic pancreatic cancer.     

Psychometric evaluation of the National Eye Institute Visual Function Questionnaire and Visual Function Questionnaire Utility Index in patients with non-infectious intermediate and posterior uveitis

Objective

To evaluate the psychometric properties of the National Eye Institute Visual Function Questionnaire-25 (NEI VFQ-25) and Visual Function Questionnaire Utility Index (VFQ-UI) in patients with non-infectious intermediate and posterior uveitis.

Methods

Secondary analysis of pooled data from a 26-week, multicenter, masked, randomized, sham-controlled Phase 3 clinical trial. Health-related quality of life was assessed using the NEI VFQ-25, the EQ-5D, and SF-36. Internal consistency reliability, reproducibility, convergent validity, and known groups of BCVA and vitreous haze severity were assessed. Clinically significant difference was assessed using anchor-based and distribution-based methods.

Results

The study included 224 subjects with non-infectious intermediate (80.4 %) or posterior uveitis (19.6 %). The NEI VFQ-25 and the VFQ-UI demonstrated good internal consistency (Cronbach’s alpha 0.87–0.94) and test–retest reliability (ICCs 0.58–0.88). Spearman’s product–moment rank correlations between the NEI VFQ-25 and VFQ-UI scores and the SF-6D, EQ-5D, and BCVA ranged from small to moderate. There was a significant association between visual functioning and known groups of visual acuity (p < 0.05). Clinical significance, using the anchor-based method (difference between visual acuity groups ≥10–<15 letter better and no change), was 10.2 for change from baseline to week 26 for the NEI VFQ-25 composite score and 0.05 for the VFQ-UI. Using the distribution-based method, the clinical significance was 3.86 for the composite score and 0.04 for the VFQ-UI.

Conclusion

The NEI VFQ-25 and the VFQ-UI are reliable and valid measures of vision-related functioning and preference-based status in patients with non-infectious intermediate and posterior uveitis.     

Presenting comparative study PRO results to clinicians and researchers: beyond the eye of the beholder

Purpose

Patient-reported outcome (PRO) results from clinical trials can inform clinical care, but PRO interpretation is challenging. We evaluated the interpretation accuracy and perceived clarity of various strategies for displaying clinical trial PRO findings.

Methods

We conducted an e-survey of oncology clinicians and PRO researchers (supplemented by one-on-one clinician interviews) that randomized respondents to view one of the three line-graph formats (average scores over time for two treatments on four domains): (1) higher scores consistently indicating “better” patient status; (2) higher scores indicating “more” of what was being measured (better for function, worse for symptoms); or (3) normed scores. Two formats displayed proportions changed (pie/bar charts). Multivariate modeling was used to analyze interpretation accuracy and clarity ratings.

Results

Two hundred and thirty-three clinicians and 248 researchers responded; ten clinicians were interviewed. Line graphs with “better” directionality were more likely to be interpreted accurately than “normed” line graphs (OR 1.55; 95% CI 1.01–2.38; p?=?0.04). No significant differences were found between “better” and “more” formats. “Better” formatted graphs were also more likely to be rated “very clear” versus “normed” formatted graphs (OR 1.91; 95% CI 1.44–2.54; p?<?0.001). For proportions changed, respondents were less likely to make an interpretation error with pie versus bar charts (OR 0.35; 95% CI 0.2–0.6; p?<?0.001); clarity ratings did not differ between formats. Qualitative findings informed the interpretation of the survey findings.

Conclusions

Graphic formats for presenting PRO data differ in how accurately they are interpreted and how clear they are perceived to be. These findings will inform the development of best practices for optimally reporting PRO findings.

     

Implementing patient-reported outcomes assessment in clinical practice: a review of the options and considerations

Purpose

While clinical care is frequently directed at making patients ??feel better,?? patients?? reports on their functioning and well-being (patient-reported outcomes [PROs]) are rarely collected in routine clinical practice. The International Society for Quality of Life Research (ISOQOL) has developed a User??s Guide for Implementing Patient-Reported Outcomes Assessment in Clinical Practice. This paper summarizes the key issues from the User??s Guide.

Methods

Using the literature, an ISOQOL team outlined considerations for using PROs in clinical practice; options for designing the intervention; and strengths, weaknesses, and resource requirements associated with each option.

Results

Implementing routine PRO assessment involves a number of methodological and practical decisions, including (1) identifying the goals for collecting PROs in clinical practice, (2) selecting the patients, setting, and timing of assessments, (3) determining which questionnaire(s) to use, (4) choosing a mode for administering and scoring the questionnaire, (5) designing processes for reporting results, (6) identifying aids to facilitate score interpretation, (7) developing strategies for responding to issues identified by the questionnaires, and (8) evaluating the impact of the PRO intervention on the practice.

Conclusions

Integrating PROs in clinical practice has the potential to enhance patient-centered care. The online version of the User??s Guide will be updated periodically.     

Quality of life assessed with EQ-5D in patients undergoing glioma surgery: What is the responsiveness and minimal clinically important difference?

Purpose

To evaluate the responsiveness of EQ-5D 3L in patients undergoing intracranial glioma surgery and estimate the minimal clinically important difference (MCID).

Materials and methods

EQ-5D 3L index values from 164 patients who underwent glioma surgery in the period 2007–2012 were analysed. Responsiveness and MCID were estimated using a combination of distribution-based and anchor-based methods. Karnofsky performance status served as an anchor.

Results

Patients who improved functionally did not report significantly higher EQ-5D 3L scores post operatively with a standardized response mean (SRM) of 0.04 (p = 0.13). Patients who deteriorated functionally reported significantly lower EQ-5D 3L scores post operatively with a SRM of 0.72 (p < 0.001). With different approaches, we determined a range of MCID values from 0.13 to 0.15.

Conclusions

EQ-5D 3L is responsive to changes when glioma patients are deteriorating functionally after surgery but not responsive when the patients are improving. The MCID values for EQ-5D 3L in glioma surgery seem higher than reported MCID values for other types of cancers.     

Defining a minimal clinically important difference for endometriosis-associated pelvic pain measured on a visual analog scale: analyses of two placebo-controlled, randomized trials

Background

When comparing active treatments, a non-inferiority (or one-sided equivalence) study design is often used. This design requires the definition of a non-inferiority margin, the threshold value of clinical relevance. In recent studies, a non-inferiority margin of 15 mm has been used for the change in endometriosis-associated pelvic pain (EAPP) on a visual analog scale (VAS). However, this value was derived from other chronic painful conditions and its validation in EAPP was lacking.

Methods

Data were analyzed from two placebo-controlled studies of active treatments in endometriosis, including 281 patients with laparoscopically-confirmed endometriosis and moderate-to-severe EAPP. Patients recorded EAPP on a VAS at baseline and the end of treatment. Patients also assessed their satisfaction with treatment on a modified Clinical Global Impression scale. Changes in VAS score were compared with patients' self-assessments to derive an empirically validated non-inferiority margin. This anchor-based value was compared to a non-inferiority margin derived using the conventional half standard deviation rule for minimal clinically important difference (MCID) in patient-reported outcomes.

Results

Anchor-based and distribution-based MCIDs were-7.8 mm and-8.6 mm, respectively.

Conclusions

An empirically validated non-inferiority margin of 10 mm for EAPP measured on a VAS is appropriate to compare treatments in endometriosis.     

Patient-Reported Outcomes Are Changing the Landscape in Oncology Care: Challenges and Opportunities for Payers

Background

A patient-reported outcome (PRO) is a subjective report that comes from a patient without interpretation by a clinician. Because of the increasingly significant role of PROs in the development and evaluation of new medicines, the US Food and Drug Administration (FDA) issued a formal guidance to describe how PRO instruments will be reviewed and evaluated with respect to claims in approved medical product labeling. Meanwhile, PROs continue to appear in oncology clinical trials more frequently; however, it is unclear how payers and policymakers can use PRO data in the context of decision-making for cancer treatments.

Objective

The objective of this article is to discuss the challenges and opportunities of incorporating oncology-related PRO data into payer decision-making.

Discussion

Payer concerns with PRO instruments are often related to issues regarding measurement, relevance, quality, and interpretability of PROs. Payers may dismiss PROs that do not independently predict improved outcomes. The FDA guidance released in 2009 demonstrates, as evidenced by the case of ruxolitinib, how PRO questionnaires can be generated in a relevant, trustworthy, and meaningful way, which provides an opportunity for payers and policy decision makers to focus on how to use PRO data in their decision-making. This is particularly relevant in oncology, where a recent and sizable number of clinical trials include PRO measures.

Conclusion

As an increasing number of oncology medications enter the market with product labeling claims that contain PRO data, payers will need to better familiarize themselves with the opportunities associated with PRO questionnaires when making coverage decisions. PRO measures will continue to provide valuable information regarding the risk–benefit profile of novel agents. As such, PRO measures may provide evidence that should be considered in payers'' decisions and discussions; however, the formal role of PROs and the pertinence of PROs in decision-making has yet to be understood.A patient-reported outcome (PRO) is a subjective report that comes directly from a patient in regard to his or her health condition or treatment without interpretation by a clinician or anyone else.1 PROs have long provided a unique insight into the effectiveness of novel medical treatments.2 Indeed, PRO questionnaires have been developed to quantify a patient''s self-reported health status in a variety of areas, including symptoms, functioning, quality of life (QOL), and health-related QOL. In addition, PRO questionnaires have been developed to assess other health-related outcomes, such as treatment adherence and satisfaction.Because of its increasingly significant role in the development and evaluation of new medicines,2–4 the US Food and Drug Administration (FDA), in conjunction with industry and academic experts, published a formal guidance, “Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims,” in 2009 to describe how the FDA will review and will evaluate the existing, modified, or newly created PRO instruments in support of the claims contained in FDA-approved drug labeling.1 The guidance was in development since early 2000 when select members of the FDA, the International Society for Quality of Life Research, the International Society for Pharmacoeconomics and Outcomes Research, Pharmaceutical Research and Manufacturers of America (PhRMA), and the European Regulatory Issues on Quality of Life Assessment Group began meeting to discuss how PRO data could be incorporated into drug labeling claims.5 The FDA released its draft guidance document in 2006 and its subsequent final guidance in 2009 after receiving and responding to public commentary on the guidance.By establishing a set of standards and parameters for the use and development of PROs, the FDA has clearly acknowledged and accepted PROs as important and trustworthy means for evaluating drugs, biologics, and medical devices. Furthermore, the FDA guidance may ultimately lead to the more efficient and more appropriate use of these tools; increased collaboration has been seen among measurement-focused researchers to offer suggestions for best practice with respect to the development, implementation, and evaluation of PROs across a variety of therapeutic areas.5–10The impact of the FDA''s PRO guidance has been felt in oncology, as evidenced by a rapidly growing body of literature regarding the development, interpretation, and incorporation of PROs into oncology. More specifically, several publications have focused on the use of PROs to support product claims labeling as a means of demonstrating further product differentiation in oncology.5,11–15With the number of cancer survivors currently at 10 million and growing in the United States, it is clear that patients with cancer are living longer as a result of improvements in survival rates for several cancers thanks to new treatment options that have demonstrated control in tumor growth and reduced cancer-related morbidity and mortality.12In addition, an increasing number of therapies offer equivalent survival benefits; however, there may be differences in the type and severity of adverse events or in the way the drug affects patient functioning. Often, these differences are material for patients, and they markedly influence the clinician''s choice of therapy for corresponding malignancies from the perspective of the physician and payer. Furthermore, the difference in impact on patient-specific factors, in the absence of a substantial difference of survival benefits, has led to an emphasis on the totality of a patient''s treatment experience and an enhanced understanding of how to balance the benefits of therapy with the risks associated with treatment.Building on safety, efficacy, and health economics data, PROs further inform decision-making by contributing evidence that is reflective of the patient experience. PRO measures also add considerable value to treatment decisions made between providers and patients when they enable providers to address relevant decision-related questions (eg, does a new therapy deliver significant clinical benefit above and beyond the primary registration trial clinical end point, from the patient''s perspective?).15 PRO symptom measures can also be useful in predicting later-stage disease progression and survival.12 The association between PRO symptom assessments and drug-related toxicity can be valuable when determining the risk–benefit profile of a treatment.12

KEY POINTS

• ▸ In 2009, the FDA published a formal guidance on the review and evaluation of patient-reported outcomes (PROs) related to claims included in FDA-approved medical product labeling.
• ▸ Payers are concerned with issues related to relevance, quality, and interpretability of PROs when evaluating data from these instruments.
• ▸ Cancer drugs currently in clinical trials are increasingly incorporating PRO measures and may soon be entering the market with product labeling claims containing PRO data.
• ▸ PRO measures can provide evidence that should be considered in payers'' drug coverage decisions and providers'' discussions with patients regarding drug choice.
• ▸ The case of ruxolitinib, to date the only cancer drug that has followed the FDA guidance for the development of a PRO instrument and received a PRO-based product labeling, is a good model for marketing applications of PRO-related measures.
• ▸ Payers need to become more familiar with the FDA PRO guidance and the various PRO measures for coverage decisions to determine how each measure fits in a drug''s overall risk–benefit profile.

The use of PROs in clinical trials is increasingly necessary and accepted. Furthermore, as more oncology treatments that extend life or provide palliative care become available, PROs will continue to appear as end points in oncology trials. It is unclear, however, how payers and policymakers can use PRO data in the context of decision-making for cancer treatments,15 and, to date, there is a paucity of literature from the perspective of the payer and policy decision maker.To begin filling this gap, the objective of this article is to discuss the challenges and opportunities of incorporating oncology-related PRO data into payer decision-making. In turn, this will help third-party payers (public and private) understand the role and the potential added value that PRO data could have in determining a product''s overall risk versus benefit. We use a case study to describe the value of PRO data from the payer''s perspective for a novel oncology product (ie, ruxolitinib in patients with intermediate- or high-risk myelofibrosis) and how PRO data were incorporated into its product labeling in accordance with US regulatory guidance.     

Minimal important change and minimal detectable change in activities of daily living in community-living older people

Objective

To estimate the minimal important change (MIC) and the minimal detectable change (MDC) of the Katz-activities of daily living (ADL) index score and the Lawton instrumental activities of daily living (IADL) scale.

Design

Data from a cluster-randomized clinical trial and a cohort study.

Setting

General practices in the Netherlands.

Participants

3184 trial participants and 51 participants of the cohort study with a mean age of 80.1 (SD 6.4) years.

Measurements

At baseline and after 6 months, the Katz-ADL index score (0-6 points), the Lawton IADL scale (0-7 points), and self-perceived decline in (I)ADL were assessed using a self-reporting questionnaire. MIC was assessed using anchor-based methods: the (relative) mean change score; and using distributional methods: the effect size (ES), the standard error of measurement (SEM), and 0.5 SD. The MDC was estimated using SEM, based on a test-retest study (2-week interval) and on the anchor-based method.

Results

Anchor-based MICs of the Katz-ADL index score were 0.47 points, while distributional MICs ranged from 0.18 to 0.47 points. Similarly, anchor-based MICs of the Lawton IADL scale were between 0.31 and 0.54 points and distributional MICs ranged from 0.31 to 0.77 points. The MDC varies by sample size. For the MIC to exceed the MDC at least 482 patients are needed.

Conclusion

The MIC of both the Katz-ADL index and the Lawton IADL scale lie around half a point. The certainty of this conclusion is reduced by the variation across calculational methods.

     

Body mass index and health related quality of life in elementary school children: a pilot study

Background

Interpretation of the Hospital Anxiety and Depression Scale (HADS), commonly used to assess anxiety and depression in COPD patients, is unclear. Since its minimal important difference has never been established, our aim was to determine it using several approaches.

Methods

88 COPD patients with FEV₁ ≤ 50% predicted completed the HADS and other patient-important outcome measures before and after an inpatient respiratory rehabilitation. For the anchor-based approach we determined the correlation between the HADS and the anchors that have an established minimal important difference (Chronic Respiratory Questionnaire [CRQ] and Feeling Thermometer). If correlations were ≥ 0.5 we performed linear regression analyses to predict the minimal important difference from the anchors. As distribution-based approach we used the Effect Size approach.

Results

Based on CRQ emotional function and mastery domain as well as on total scores, the minimal important difference was 1.41 (95% CI 1.18–1.63) and 1.57 (1.37–1.76) for the HADS anxiety score and 1.68 (1.48–1.87) and 1.60 (1.38–1.82) for the HADS total score. Correlations of the HADS depression score and CRQ domain and Feeling Thermometer scores were < 0.5. Based on the Effect Size approach the MID of the HADS anxiety and depression score was 1.32 and 1.40, respectively.

Conclusion

The minimal important difference of the HADS is around 1.5 in COPD patients corresponding to a change from baseline of around 20%. It can be used for the planning and interpretation of trials.     

Psychometric characteristics of daily diaries for the Patient-Reported Outcomes Measurement Information System (PROMIS®): a preliminary investigation

Purpose

The Patient-Reported Outcomes (PRO) Measurement Information System (PROMIS^®) has developed assessment tools for numerous PROs, most using a 7-day recall format. We examined whether modifying the recall period for use in daily diary research would affect the psychometric characteristics of several PROMIS measures.

Methods

Daily versions of short-forms for three PROMIS domains (pain interference, fatigue, depression) were administered to a general population sample (n = 100) for 28 days. Analyses used multilevel item response theory (IRT) models. We examined differential item functioning (DIF) across recall periods by comparing the IRT parameters from the daily data with the PROMIS 7-day recall IRT parameters. Additionally, we examined whether the IRT parameters for day-to-day within-person changes are invariant to those for between-person (cross-sectional) differences in PROs.

Results

Dimensionality analyses of the daily data suggested a single dimension for each PRO domain, consistent with PROMIS instruments. One-third of the daily items showed uniform DIF when compared with PROMIS 7-day recall, but the impact of DIF on the scale level was minor. IRT parameters for within-person changes differed from between-person parameters for 3 depression items, which were more sensitive for measuring change than between-person differences, but not for pain interference and fatigue items. Notably, mean scores from daily diaries were significantly lower than the PROMIS 7-day recall norms.

Conclusions

The results provide initial evidence supporting the adaptation of PROMIS measures for daily diary research. However, scores from daily diaries cannot be directly interpreted on PROMIS norms established for 7-day recall.     

ISOQOL recommends minimum standards for patient-reported outcome measures used in patient-centered outcomes and comparative effectiveness research

Purpose

An essential aspect of patient-centered outcomes research (PCOR) and comparative effectiveness research (CER) is the integration of patient perspectives and experiences with clinical data to evaluate interventions. Thus, PCOR and CER require capturing patient-reported outcome (PRO) data appropriately to inform research, healthcare delivery, and policy. This initiative’s goal was to identify minimum standards for the design and selection of a PRO measure for use in PCOR and CER.

Methods

We performed a literature review to find existing guidelines for the selection of PRO measures. We also conducted an online survey of the International Society for Quality of Life Research (ISOQOL) membership to solicit input on PRO standards. A standard was designated as “recommended” when >50 % respondents endorsed it as “required as a minimum standard.”

Results

The literature review identified 387 articles. Survey response rate was 120 of 506 ISOQOL members. The respondents had an average of 15 years experience in PRO research, and 89 % felt competent or very competent providing feedback. Final recommendations for PRO measure standards included: documentation of the conceptual and measurement model; evidence for reliability, validity (content validity, construct validity, responsiveness); interpretability of scores; quality translation, and acceptable patient and investigator burden.

Conclusion

The development of these minimum measurement standards is intended to promote the appropriate use of PRO measures to inform PCOR and CER, which in turn can improve the effectiveness and efficiency of healthcare delivery. A next step is to expand these minimum standards to identify best practices for selecting decision-relevant PRO measures.     

Comparing the validity and responsiveness of the EQ-5D-5L to the Oxford hip and knee scores and SF-12 in osteoarthritis patients 1 year following total joint replacement

Purpose

(1) To assess responsiveness of the EQ-5D-5L compared to Oxford hip and knee scores and the SF-12 in osteoarthritis patients undergoing total hip (THR) or knee (TKR) replacement surgery; (2) to compare distribution and anchor-based methods of assessing responsiveness.

Methods

Questionnaires were mailed to consecutive patients following surgeon referral for primary THR or TKR and 1 year post-surgery. We assessed effect size (ES), standardized response mean (SRM), and standard error of measurement (SEM). Minimum important difference (MID) was the mean change in patients reporting somewhat better in hip or knee, health in general, and those who were satisfied with surgery (5-point scales). Responders were compared using MID versus 1 and 2SEM.

Results

The sample of 537 (50% TKR) was composed of 56% female with a mean age of 64 years (SD 10). EQ-5D-5L ES was 1.86 (THR) and 1.19 (TKR) compared to 3.00 and 2.05 for Oxford scores, respectively. MID for the EQ-5D-5L was 0.22 (THR) and 0.20 (TKR) for patients who rated their hip or knee as somewhat better. There was a wide variation in the MID and the percentage of responders, depending on the joint, method of assessment, and the outcome measure. The percent agreement of responder classification using 2SEM vs. MID ranged from 79.6 to 99.6% for the EQ-5D-5L and from 69.4 to 94.8% for the Oxford scores.

Conclusions

Responsiveness of the EQ-5D-5L was acceptable in TKR and THR. Caution should be taken in interpreting responder to TJR based on only one method of assessment.