Literature DB >> 21424338

Examining the ability to detect change using the TRIM-Diabetes and TRIM-Diabetes Device measures.

Meryl Brod1, Torsten Christensen, Mette Hammer, Anne K Busk, Donald M Bushnell.   

Abstract

PURPOSE: Responsiveness is defined as the ability of an instrument to accurately detect change when it has occurred and is an essential psychometric property of a patient-reported outcomes (PRO) measure to understand and interpret study findings. This study examined the responsiveness of 2 Treatment Related Impact Measures (TRIMs): The TRIM-Diabetes (TRIM-D) and TRIM-Diabetes Device (TRIM-DD) as well as confirmed their measurement models in a randomized controlled trial (RCT) design.
METHODS: The data were collected in a multi-center, randomized, open-label (2 × 12 week), cross-over study of two prefilled pens in subjects with type 1 or type 2 diabetes, age 18 or older. Internal and external responsiveness were examined. To confirm the measurement model identified in the previous study, the Bentler comparative fit index (CFI) and internal consistency for the RCT sample scores were examined and compared.
RESULTS: Based on a priori criteria, tests of responsiveness were confirmed with patients having significant improvements over time ranging from 2.7 (Psychological Health) to 11.1 (Treatment Burden) (P < 0.01) (effect sizes ranging from 0.2 to 0.8). The previous measurement model factor structure was confirmed (CFI ranging from 0.8 to 1.0), and internal consistency of the TRIMs was similar to the developmental findings.
CONCLUSIONS: The total score as well as all domain scores of the TRIMs was significantly responsive over time, thus acceptable internal and external responsiveness of TRIM-D and TRIM-DD are concluded. To date, all validation evidence supports the use of these two measures in future clinical trials.

Entities:  

Mesh:

Year:  2011        PMID: 21424338      PMCID: PMC3195684          DOI: 10.1007/s11136-011-9886-7

Source DB:  PubMed          Journal:  Qual Life Res        ISSN: 0962-9343            Impact factor:   4.147


Introduction

Responsiveness is defined as an instrument’s ability to accurately detect change that has occurred [1, 2]. Internal responsiveness is defined as an instrument’s ability to change during a prespecified time frame. External responsiveness is the extent to which a measure’s degree of change corresponds to an external reference value or measure (assesses an instrument’s ability to reflect both change and no change in the external standard) [3, 4]. This study examined the responsiveness of 2 patient-reported outcomes (PRO) measures, the Treatment Related Impact Measure-Diabetes (TRIM-D) and Treatment Related Impact Measure-Diabetes Device (TRIM-DD), which were developed as disease-specific PRO measures to assess the impact of diabetes treatment for both type 1 and 2 diabetes and across the spectrum of pharmacological treatments and delivery methods [5]. The TRIM-D is a 28 item measure with 5 domains assessing Treatment Burden, Daily Life, Diabetes Management, Compliance and Psychological Health. The TRIM-DD is an 8 item measure with 2 domains assessing Device Bother and Device Function. Both measures can be scored independently for each domain or as a total score. Higher scores indicate a better health state. The item generation and preliminary validation were conducted following FDA guidelines for PRO measures development [1]. Initial validation data for the TRIM-D and TRIM-DD were collected via an online, cross-sectional survey of 507 US patients. The cross-sectional validation showed that both measures have acceptable psychometric properties [5]. The purpose of the current study was to continue the validation process by examining the measures’ responsiveness and to confirm the measurement model under randomized controlled trial (RCT) conditions.

Methods

The data used to assess responsiveness came from a multi-center, randomized, open-label, 2 × 12 week period cross-over study of two prefilled pens in subjects with type 1 or 2 diabetes. All subjects were using insulin by vial/syringe previous to inclusion in the study and were pen naïve. Data for these analyses came from all patients who had completed the TRIM-D and TRIM-DD at randomization (baseline) and time of cross-over (week 12). Non-superiority for glucose control between groups was hypothesized. The study was approved by Sterling IRB (approval #2925), and all persons gave informed consent.

Analyses

Analyses were conducted according to an a priori statistical analysis plan. All statistical tests were two-tailed and conducted with an alpha level of 0.05 as minimal threshold for significance. As the TRIM-D and TRIM-DD are intended to be used as either a total score or as independent domains, change scores were examined for both the totals and domain scores.

Responsiveness analyses

To examine internal responsiveness, t tests were used to examine differences in TRIM scores between baseline and week 12 (time of cross-over) with the expectation that significant improvement over time would be shown. Effect size (ES), measured by Cohen’s d, was examined by calculating the mean change in score divided by the standard deviation of the mean baseline TRIM score. ES was categorized: small, 0.2–0.3; medium, 0.4–0.7; and large, 0.8 or above [6]. External responsiveness was examined by testing the hypothesis that there will be a linear relationship between the TRIMs and treatment satisfaction (TS) as assessed by the insulin treatment satisfaction questionnaire (ITSQ) [7]. The ITSQ, a disease-specific PRO assessing insulin TS, has been shown to be reliable and valid [7, 8]. Pearson correlation coefficients between the change in ITSQ overall summary score (from baseline to week 12) and the change in each item and domain of the TRIM-D and TRIM-DD were examined.

Confirmatory analyses of measurement model

A confirmatory factor analysis (CFA) was conducted using the Bentler comparative fit index (CFI) and root mean square error of approximation (RMSEA) to determine the goodness of fit between the models previously identified [5] and the current sample data. The criterion used to indicate acceptable fit was a CFI of at least 0.90 [9] and an RMSEA of 0.06 [9] or less. Internal consistency reliability was examined and compared with the original sample with Cronbach’s alpha, a statistic calculated from the pairwise correlations between items. Alphas range between zero and one, with coefficients of greater than 0.70 indicating acceptable reliability [10].

Results

In the cross-over study, 242 subjects completed the TRIM-D and TRIM-DD at baseline and week 12 (Table 1).
Table 1

Sample description

AgeMean (SD) (n = 242)58.0 (13.9)
Range 22–87
GenderN (%) Male147 (60.7%)
N (%) Female95 (39.3%)
Body mass index (BMI) at randomizationMean (SD) (n = 242)31.4 (6.1)
Range 18.7–44.9
Diabetes typeN (%) Type 170 (28.9%)
N (%) Type 2172 (71.1%)
HbA1c at randomizationMean (SD) (n = 240)7.3 (0.9)
Range 5.2–10.2
EthnicityN (%) White199 (82.2%)
N (%) Black29 (12.0%)
N (%) Asian7 (2.9%)
N (%) Other7 (2.9%)
Sample description

Internal responsiveness

All TRIM-D and TRIM-DD domains and overall total scores and most individual items (TRIM-D: 23/28; TRIM-DD: 6/8) changed significantly after 12 weeks of randomized treatment. For the Treatment Burden, Diabetes Management, Daily Life, and total TRIM-D, these significant change scores were associated with large to moderate ES. For the Psychological Health and Compliance domains, the significant change scores were associated with a small ES. Score changes ranged from 18.6 (ES 0.84, TRIM-D Treatment Burden) to 3.1 (ES 0.17, TRIM-D Psychological Health). For the TRIM-DD domains and total score, large changes (9.4–10.1) along with moderate ES (0.43–0.56) were seen (Table 2).
Table 2

Responsiveness of the TRIM-Diabetes and TRIM-Diabetes Device items and domains

BaselineWeek 12Change score
Abbreviated item contentMean (SD)Mean (SD)Mean (SD) t-statEffect sizea ITSQ overall summary (Pearson r)
TRIM-Diabetes TOTAL SCORE (n = 226)65.9 (15.0)74.2 (13.0)8.3 (13.5)9.2***0.550.72**
Treatment Burden (n = 225)54.7 (22.1)73.3 (19.2)18.6 (25.0)11.1***0.840.58**
The ease and convenience of your medication3.4 (0.8)4.0 (0.9)0.6 (1.1)8.7***0.750.53**
Carry your medication and supplies around with you2.8 (1.2)3.7 (1.0)1.0 (1.4)10.2***0.750.48**
Store your medication3.2 (1.2)4.0 (1.0)0.8 (1.4)8.1***0.670.44**
Take your medication at the right time3.3 (1.1)3.9 (0.9)0.65 (1.3)7.5***0.550.44**
Prepare your medication for use3.4 (1.1)4.2 (0.9)0.8 (1.4)9.0***0.730.51**
Monitor your blood sugar as often as necessary3.1 (1.1)3.7 (1.0)0.6 (1.2)7.9***0.550.32**
Daily Life (n = 226)68.4 (18.5)75.6 (16.8)7.2 (17.9)6.0***0.390.58**
Meal time planning3.6 (0.9)4.0 (0.9)0.4 (1.0)6.1***0.440.45**
Social activities3.5 (1.1)4.0 (0.9)0.5 (1.1)6.3***0.450.45**
Do you have to limit your daily activities?4.0 (0.8)4.2 (0.8)0.2 (1.0)2.5*0.250.39**
Do you accomplish less than you would like to?3.5 (1.1)3.8 (1.0)0.2 (1.1)3.3**0.270.37**
Do you feel tension in your relationships with friends or family?4.1 (0.9)4.3 (0.9)0.15 (1.0)2.4*0.220.39**
Diabetes Management (n = 226)52.5 (19.2)61.7 (17.9)9.3 (19.2)7.2***0.480.43**
Help you control your diabetes3.3 (0.9)3.7 (0.8)0.35 (1.0)5.1***0.440.38**
Help you avoid high blood sugar (hyperglycemia)3.2 (1.0)3.6 (0.9)0.4 (1.2)5.0***0.400.34**
Help you avoid low blood sugar (hypoglycemia)3.4 (0.9)3.8 (0.8)0.35 (0.9)5.7***0.440.31**
Help you manage your weight2.7 (1.2)3.0 (1.1)0.35 (1.1)4.8***0.300.22**
Help you prevent feeling tired or a lack of energy2.8 (1.0)3.3 (1.1)0.4 (1.0)6.3***0.500.31**
Compliance (n = 226)75.7 (17.0)79.3 (15.0)3.7 (15.1)3.7***0.220.30**
Miss a dose4.3 (0.7)4.4 (0.7)0.1 (0.7)2.5**0.140.21**
Delay or postpone taking your medication3.9 (0.9)4.1 (0.8)0.2 (0.8)3.3**0.220.14*
Take your medication at a different time than prescribed3.9 (0.9)4.1 (0.8)0.1 (1.0)2.2*0.220.23**
Worry that you forgot to take/or missed your last dose of medication4.0 (0.9)4.2 (0.8)0.2 (1.0)2.5*0.220.25**
Psychological Health (n = 221)76.2 (18.6)79.2 (17.2)3.1 (16.9)2.7**0.170.59**
Depressed4.3 (0.9)4.4 (0.9)0.1 (0.8)1.5 (P = 0.137)0.110.36**
Worried that the medication is not helping to slow down or prevent complications from my diabetes3.9 (1.0)4.0 (1.0)0.1 (1.1)0.7 (P = 0.494)0.100.44**
Nervous or anxious4.2 (0.8)4.4 (0.8)0.1 (0.9)2.2*0.250.41**
Worried about my blood sugar control3.4 (1.1)3.5 (1.0)0.1 (1.1)1.7 (P = 0.084)0.090.47**
Unhealthy4.1 (1.0)4.1 (1.0)0.05 (1.0)0.8 (P = 0.434)0.000.40**
Angry4.3 (1.0)4.4 (0.9)0.05 (0.9)0.8 (P = 0.417)0.100.35**
Worried about side effects from my medication3.9 (1.1)4.2 (1.0)0.25 (1.1)3.2**0.270.38**
Feel embarrassed or awkward when taking your medication4.3 (0.9)4.5 (0.7)0.2 (0.9)3.8***0.220.51**
TRIM-Diabetes Device TOTAL SCORE (n = 214)72.2 (17.1)81.8 (15.2)9.6 (20.6)6.9***0.560.68**
Device Function (n = 214)71.6 (18.5)81.0 (17.0)9.4 (22.7)6.0***0.510.56**
Learn how to use your device3.9 (0.9)4.4 (0.8)0.6 (1.1)7.3***0.560.47**
Keep your device functioning properly4.1 (0.8)4.4 (0.8)0.3 (1.1)4.2***0.380.42**
Adjust your medication for small dose changes3.8 (1.0)4.4 (0.9)0.6 (1.4)6.4***0.600.51**
That your device delivers the correct, full dose of your medication3.7 (1.0)3.8 (1.1)0.2 (1.4)1.7 (P = 0.094)0.100.34**
That you are using the device properly4.0 (0.9)4.2 (1.0)0.2 (1.2)2.8**0.220.30**
Device Bother (n = 214)73.2 (23.3)83.3 (19.5)10.1 (26.1)5.6***0.430.64**
Size of your device4.3 (0.9)4.4 (0.9)0.1 (1.2)1.8 (P = 0.076)0.110.40**
Physical discomfort related to using your device3.9 (1.0)4.4 (0.9)0.5 (1.2)5.5***0.500.55**
Using your device in public3.6 (1.4)4.2 (1.1)0.6 (1.4)6.1***0.430.57**

TRIM Treatment Related Impact Measure, SD Standard deviation, ITSQ Insulin treatment satisfaction questionnaire

aEffect size = mean change in score divided by the standard deviation of mean baseline score

*** Correlation is significant at the 0.001 level (2-tailed)

** Correlation is significant at the 0.01 level (2-tailed)

* Correlation is significant at the 0.05 level (2-tailed)

Responsiveness of the TRIM-Diabetes and TRIM-Diabetes Device items and domains TRIM Treatment Related Impact Measure, SD Standard deviation, ITSQ Insulin treatment satisfaction questionnaire aEffect size = mean change in score divided by the standard deviation of mean baseline score *** Correlation is significant at the 0.001 level (2-tailed) ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)

External responsiveness

Strong associations were found between the ITSQ change, TRIM-D Total score (r = 0.72, P < 0.001) and TRIM-DD Total score (r = 0.68, P < 0.001). Moderate to strong correlations were noted between the ITSQ overall summary score and items from the domains: Treatment Burden (r ranging between 0.32 and 0.53), Daily Life (0.37–0.45), Diabetes Management (0.22–0.38), Psychological Health (0.35–0.51), Device Function (0.30–0.51), and Device Bother (0.40–0.57). Lower associations were noted between ITSQ score and the Compliance domain (0.14–0.25).

Confirmatory measurement model analyses

Fit statistics

The model fit statistics for the TRIM-D and TRIM-DD Total domains were confirmed and are presented in Table 3.
Table 3

TRIM-Diabetes and TRIM-Diabetes Device measurement model properties

n CFIRMSEA
Chi-Square (Sig.) df
TRIM-Diabetes total (28 items)2220.9550.0313602.4 (P < 0.001)378
Treatment Burden (6 items)2350.9720.020763.7 (P < 0.001)15
Daily Life (5 items)2350.8180.072447.6 (P < 0.001)10
Diabetes Management (5 items)2350.8880.051498.2 (P < 0.001)10
Compliance (4 items)2350.9880.018310.9 (P < 0.001)6
Psychological (8 items)2290.9480.037923.5 (P < 0.001)28
TRIM-Diabetes Device total (8 items)2261.0000.000722.6 (P < 0.001)28
Device Function (5 items)2261.0000.000476.9 (P < 0.001)10
Device Bother (3 items)2271.0000.000181.7 (P < 0.001)3

CFI Comparative fit index, RMSEA Root mean square error of approximation, df degrees of freedom

TRIM-Diabetes and TRIM-Diabetes Device measurement model properties CFI Comparative fit index, RMSEA Root mean square error of approximation, df degrees of freedom

Internal consistency

All alphas for the TRIM-D and TRIM-DD (overall score and all domains) were above 0.70 indicating acceptable internal consistency. Additionally, the confirmatory RCT sample alphas were similar to the development coefficients (within 0.1).

Discussion

These analyses found that the TRIMs total scores as well as all domain scores were significantly responsive over time and had the ability to differ between levels of change of an external criterion. Thus, internal and external responsiveness for the TRIM-D and TRIM-DD have been confirmed in an RCT sample. The measurement model was confirmed for all domains with lower than expected fit statistics for the Daily Life and Diabetes Management domains. Given that these domains were shown to have a strong factor structure in the development of the measures [3], this finding may be specific to this trial design or sample. Further testing the TRIM-D domain structure in other trials is warranted to confirm these findings. The total score and all domain scores of the TRIMs were significantly responsive over time with the Treatment Burden domain showing the greatest responsiveness and the Psychological Health domain the least responsiveness. Additionally, the greatest number of individual items which were not responsive over time came from the Psychological Health domain. These findings should be interpreted in light of the study’s nature. Given that all patients received the same insulin treatment, it is understandable that the psychological component of treatment, which is often driven by treatment efficacy, would be the least responsive. However, the fact that the overall Psychological Health domain was still significant as an overall concept and suggests that insulin pen delivery system does contribute positively to the psychological impact of treatment. As expected, given that the study was a device cross-over with non-superiority for drug effect, the Treatment Burden domain, the domain which should be most impacted by delivery mode, was the most responsive domain. These findings underscore the importance of understanding the independent contribution of domains, given the specific study design and hypotheses, in order to optimally identify, a priori, domains of a measure which will be responsive to change. As the TRIMs were developed and validated for stand-alone use of each domain as well as the total score, future use of the TRIMs can and should take independent domain responsiveness into consideration when making these a priori hypotheses. Certain study limitations should be considered in interpreting results. To assess external validity, the ITSQ, a PRO measure rather than a clinical measure, was used as the reference value. It was not possible to use a clinical reference value due to two factors. First, HbA1c ≤9% was a study eligibility criterion and the majority of patients entered the study in good or adequate HbA1c control (61%, <7.5). Thus, there could only be a limited number of patients who could change from inadequate to adequate glucose control. In fact, in this sample, there were only 11 patients (4.8%) who changed from randomization poor control (>7.0%) to adequate control over the 12-week period (<7.0%). Second, the study was designed as a non-inferiority trial to examine difference in insulin delivery mode rather than drug treatment efficacy, and all patients received the same insulin treatment during the study. Thus, no differences in glucose control were expected or found. As a result of these design features, there was not an adequate size sample of patients who had a significant improvement or worsening of HbA1c to conduct responsiveness analyses using a clinical reference value. Further, the fact that a majority of these patients were in good control at study start may limit the external generalizability of findings. Validation is an iterative process. This study continues that process for the TRIM-Diabetes and TRIM-Diabetes Device measures. To date, all evidence supports the use of these measures in future clinical trials.
  6 in total

Review 1.  Methods for assessing responsiveness: a critical review and recommendations.

Authors:  J A Husted; R J Cook; V T Farewell; D D Gladman
Journal:  J Clin Epidemiol       Date:  2000-05       Impact factor: 6.437

2.  A taxonomy for responsiveness.

Authors:  D E Beaton; C Bombardier; J N Katz; J G Wright
Journal:  J Clin Epidemiol       Date:  2001-12       Impact factor: 6.437

3.  Responsiveness of the Adult Attention-Deficit/Hyperactivity Disorder Quality of Life Scale (AAQoL).

Authors:  Louis S Matza; Joseph A Johnston; Douglas E Faries; Karen G Malley; Meryl Brod
Journal:  Qual Life Res       Date:  2007-09-12       Impact factor: 4.147

4.  Development and validation of the insulin treatment satisfaction questionnaire.

Authors:  Roger T Anderson; Soren E Skovlund; David Marrero; Douglas W Levine; Keith Meadows; Meryl Brod; Rajesh Balkrishnan
Journal:  Clin Ther       Date:  2004-04       Impact factor: 3.393

5.  Maximizing the value of validation findings to better understand treatment satisfaction issues for diabetes.

Authors:  Meryl Brod; Torsten Christensen; Donald Bushnell
Journal:  Qual Life Res       Date:  2007-05-22       Impact factor: 4.147

6.  Understanding and assessing the impact of treatment in diabetes: the Treatment-Related Impact Measures for Diabetes and Devices (TRIM-Diabetes and TRIM-Diabetes Device).

Authors:  Meryl Brod; Mette Hammer; Torsten Christensen; Suzanne Lessard; Donald M Bushnell
Journal:  Health Qual Life Outcomes       Date:  2009-09-09       Impact factor: 3.186

  6 in total
  11 in total

1.  A Pragmatic Clinical Trial to Compare the Real-World Effectiveness of V-Go versus Standard Delivery of Insulin in Patients with Advanced Type 2 Diabetes.

Authors:  Mark J Cziraky; Scott Abbott; Matt Nguyen; Kay Larholt; Elizabeth Apgar; Thomas Wasser; Poul Strange; Leon Shi; H Courtenay Harrison; Beverly Everitt; Lynn Nowak
Journal:  J Health Econ Outcomes Res       Date:  2019-03-27

2.  Understanding Patients' Willingness to Pay for Biphasic Insulin Aspart 30/70 in a Pen Device for Type 2 Diabetes Treatment in an Out-of-Pocket Payment Market.

Authors:  Sreenivasa Murthy; Pankaj Aneja; Arthur Joseph Asirvatham; Lise Lotte N Husemoen; Nicolai A Rhee; Jothydev Kesavadev
Journal:  Pharmacoecon Open       Date:  2021-01-06

Review 3.  Measuring the burden of treatment for chronic disease: implications of a scoping review of the literature.

Authors:  Adem Sav; Asiyeh Salehi; Frances S Mair; Sara S McMillan
Journal:  BMC Med Res Methodol       Date:  2017-09-12       Impact factor: 4.615

4.  Injecting without pressing a button: An exploratory study of a shield-triggered injection mechanism.

Authors:  Eric Zijlstra; Hans-Veit Coester; Tim Heise; Leona Plum-Mörschel; Ole Rasmussen; Tord Rikte; Line Kynemund Pedersen; Marianne Qvist; Thomas Sparre
Journal:  Diabetes Obes Metab       Date:  2018-01-25       Impact factor: 6.577

5.  Superior efficacy of insulin degludec/liraglutide versus insulin glargine U100 as add-on to sodium-glucose co-transporter-2 inhibitor therapy: A randomized clinical trial in people with uncontrolled type 2 diabetes.

Authors:  Athena Philis-Tsimikas; Liana K Billings; Robert Busch; Cristobal Morales Portillo; Rakesh Sahay; Natalie Halladin; Sarah Eggert; Kamilla Begtrup; Stewart Harris
Journal:  Diabetes Obes Metab       Date:  2019-04-04       Impact factor: 6.577

6.  Patient-reported outcomes in transition from high-dose U-100 insulin to human regular U-500 insulin in severely insulin-resistant patients with type 2 diabetes: analysis of a randomized clinical trial.

Authors:  Samaneh Kabul; Robert C Hood; Ran Duan; Amy M DeLozier; Julie Settles
Journal:  Health Qual Life Outcomes       Date:  2016-09-30       Impact factor: 3.186

7.  The Efficacy of IDegLira (Insulin Degludec/Liraglutide Combination) in Adults with Type 2 Diabetes Inadequately Controlled with a GLP-1 Receptor Agonist and Oral Therapy: DUAL III Randomized Clinical Trial.

Authors:  Sultan Linjawi; Bruce W Bode; Louis B Chaykin; Jean-Pierre Courrèges; Yehuda Handelsman; Lucine M Lehmann; Abhishek Mishra; Richard W Simpson
Journal:  Diabetes Ther       Date:  2016-12-10       Impact factor: 2.945

8.  Development of the Diabetes Injection Device Experience Questionnaire (DID-EQ) and Diabetes Injection Device Preference Questionnaire (DID-PQ).

Authors:  Louis S Matza; Kristina S Boye; Katie D Stewart; Rosirene Paczkowski; Jessica Jordan; Lindsey T Murray
Journal:  J Patient Rep Outcomes       Date:  2018-09-12

9.  Psychometric evaluation of the Diabetes Injection Device Experience Questionnaire (DID-EQ) and Diabetes Injection Device Preference Questionnaire (DID-PQ).

Authors:  Louis S Matza; Katie D Stewart; Rosirene Paczkowski; Karin S Coyne; Brooke Currie; Kristina S Boye
Journal:  J Patient Rep Outcomes       Date:  2018-09-19

10.  IDegLira improves patient-reported outcomes while using a simple regimen with fewer injections and dose adjustments compared with basal-bolus therapy.

Authors:  Eden Miller; Ankur Doshi; Randi Grøn; Esteban Jódar; Petra Őrsy; Mattis F Ranthe; Danny Sugimoto; Nikolaos Tentolouris; Adie Viljoen; Liana K Billings
Journal:  Diabetes Obes Metab       Date:  2019-08-28       Impact factor: 6.577

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