Health Utility Decrement of Injection Treatment-Related Attributes Using Time Trade-Off Among Type 2 Diabetes Patients: A Vignette-Based Study

Abstract

Objectives

To identify health utility decrements of injection treatment-related attributes among patients with type 2 diabetes mellitus (T2DM) in China.

Methods

Health states of four attributes (hypoglycemia, dose frequency, flexibility and injection site reaction) were generated using a vignette-based method. Patients with T2DM were recruited from eight cities in China. The sample was broadly consistent with Chinese T2DM population with regard to age and sex distribution. Respondents completed seven time trade-off (TTO) tasks during face-to-face interviews. The ordinary least square (OLS), fixed effects (FE) and random effects (RE) models were used for TTO data. In subgroup analysis, groups were categorized based on whether injection treatment was currently used, number of medications, needle phobia, duration of injectable treatment and travel frequency.

Results

A total of 400 patients (52.75% male, mean [SD] age 50.30 [12.05] years) were included in this study. Severe hypoglycemia had the largest disutility value of all attributes (−0.023, P < 0.001). Three times daily, twice daily and once daily injection (needed to be carried with the patient on short trips) were associated with −0.023 (P < 0.001), −0.018 (P < 0.001) and −0.011 (P = 0.022) disutility values compared with once weekly injection (not required to be carried with the patient on short trips), respectively. The disutility value associated with injection site reaction attribute was −0.013 (P < 0.001). In subgroup analysis, the relative importance of treatment-related attributes was found to depend on patient characteristics.

Conclusions

This study provides disutility values associated with several injection treatment-related attributes for Chinese patients with T2DM. Hypoglycemia appears to be the most important attribute, followed by dose frequency, flexibility and injection site reaction.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41669-025-00615-w.

Key Points for Decision Makers

There is an unmet need for data on disutility values related to the attributes of injectable therapy in Chinese patients with type 2 diabetes mellitus (T2DM), which can be used within cost-utility analyses of therapies in T2DM.

This study quantified disutility values associated with hypoglycemia, injection site reaction, dose frequency and flexibility attributes among Chinese patients with T2DM using time trade-off method.

The results showed that all attributes had statistically significant impacts on patients’ preferences in our main analysis. Hypoglycemia had the largest disutility value, followed by dose frequency, flexibility and injection site reaction.

Introduction

Type 2 diabetes mellitus (T2DM) is one of the most serious threats to global health due to its high prevalence and disease burden. According to the International Diabetes Federation (IDF), diabetes affected approximately 10.5% of the worldwide population aged 20–79 years (536.6 million) in 2021, with projections indicating a rise to 12.2% (783.2 million) by 2045 [1]. China has the world’s largest diabetic population, with 11.2% of adults affected [2]. In 2021, diabetes-related healthcare expenditure in China reached 165.3 billion USD, making it the second-highest globally [1]. With the growing diabetic population, diabetes has become a substantial burden on both individuals and society in China [3, 4].

Injectable treatments, such as glucagon-like peptide 1 receptor agonists (GLP-1 RAs) and insulin, are essential components of T2DM management, particularly when lifestyle interventions and oral treatments fail to achieve adequate glycemic control [5–7]. In recent years, there has been a significant increase in the use of injectable treatments among patients with T2DM. Injectable treatments for T2DM have shown wide variations in dose frequency, flexibility, and side effects [6, 8]. Therefore, cost-utility analyses (CUAs) are often conducted to estimate the value of various injectable treatments and used to guide decisions on the allocation of healthcare resources [9, 10].

Health utility is a key parameter in measuring health outcomes in CUAs, anchoring on a scale of 0–1, where 0 represents death and 1 represents full health [11]. Previous studies have emphasized the assessment of attributes beyond treatment effectiveness that are important to patients, such as treatment-related attributes [12]. Disutility values (i.e., health utility decrements) of T2DM treatment-related attributes have been explored using vignette-based methods such as time trade-off (TTO) and standard gamble (SG) with patients in Canada, Italy, Sweden and the UK [13–19]. However, existing studies mainly recruited patients with T2DM through convenience sampling without applying quotas based on key demographic characteristics (e.g., age and sex) of T2DM populations in their countries, which may reduce the generalizability of the study findings. Furthermore, disutility values were calculated by simply subtracting mean utility values from reference values, rather than using modelling approaches that are widely used to estimate disutility values [20, 21]. Although two studies included the Chinese population, they quantified disutility values among the general public rather than patients with T2DM [22, 23]. According to health technology assessment (HTA) guidelines in several countries, including Sweden and Germany, patients appear to be the most accurate source of information for utility values because it can be assumed that they are better informed about their own state of health [24]. Therefore, utility values elicited from patients should also be emphasized to inform condition-specific resource allocation and individual-level treatment decisions [25].

The aim of this study was to estimate disutility values associated with four injection treatment-related attributes (hypoglycemia, injection site reaction, dose frequency, flexibility) among Chinese patients with T2DM.

Methods

This study used a vignette-based method to generate descriptions of treatment scenarios with several treatment-related attributes [26], and used the time trade-off (TTO) method to elicit health utility values of these scenarios. We recruited patients with T2DM from eight cities in China. The sample was broadly consistent with Chinese patients with T2DM with regard to age and sex distribution. This study has been reviewed and approved by the Academic Ethics Committee at Tianjin University (no. TJUE-2023-206). Informed consent was obtained from all study respondents before the interview. This study also complied with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [27] and Checklist for Reporting Valuation Studies of Multi-Attribute Utility-Based Instruments (CREATE) [28] (Appendix Tables 1, 2).

Health State Development

The health states were drafted and refined based on a comprehensive process including a literature review, interviews with patients and clinicians, clinical guidelines and prescribing information, and a pilot study. First, we conducted a systematic literature review focusing on the disutility of treatment-related attributes for T2DM [12]. Briefly, we conducted a literature search in Medline (Ovid), Embase, Cochrane Library, PsycINFO, EconLit, and CINAHL (EBSCOHost) databases with keywords of T2DM and disutility value. In this review, eight treatment-related attributes (weight change, dose frequency, gastrointestinal side effects, dose flexibility, administration requirement, injection site reaction, fear of hypoglycemia and HbA_1c levels) assessed by nine relevant studies were identified [13–19, 22, 23]. More detailed information on the review can be found elsewhere [12]. Second, qualitative interviews were conducted with patients with T2DM (N = 16) and clinicians (N = 7) using a semi-structured interview protocol. Participants were asked to identify which attributes were the most important to them during the treatment process. Qualitative information provided by patients and clinicians was used to inform the development of health state descriptions. Third, the descriptions of health states, e.g., the definition of severe and nonsevere hypoglycemia, dose frequency of injections and symptoms of injection site reaction, were refined based on clinical guidelines and prescribing information to ensure clarity and accuracy. Finally, 42 general public respondents were involved in the pilot study using convenience sampling. Each respondent was asked to complete the pilot interview under the supervision of the investigator, and they did not appear to have difficulty understanding the task or distinguishing among the health states. Therefore, no additional revisions were made to the health states before their use in the main study.

The final set of four selected injection treatment-related attributes were hypoglycemia (severe, nonsevere), dose frequency (three times daily, twice daily, once daily, and once weekly), flexibility (need to be carried with the patient on short trips, not need to be carried with the patient on short trips) and injection site reaction (with, without) among which the two attributes of dose frequency and flexibility had a binding relationship (Table 1). Once weekly injection does not need to be carried with the patient on short trips, while the other three levels require carrying for short trips. This design could generate a total of 16 (2 × 3 × 2 + 2 × 1 × 2 = 16) states. The descriptions of all health states are also presented in Table 1.

Table 1.

Attribute, level and description of health state

Attribute	Level	Description
Hypoglycemia	Severe	You may experience severe hypoglycemia (severe event characterized by altered mental and/or physical functioning e.g., seizures or coma that requires assistance from another person for recovery)
	Non-severe	You may experience nonsevere hypoglycemia (e.g., sweating, shakiness, anxiety, confusion, headache, nausea and palpitation)
Dose frequency	Three times daily	You give yourself injection three times daily
	Twice daily	You give yourself injection twice daily
	Once daily	You give yourself injection once daily
	Once weekly	You give yourself injection once a week
Flexibility	Need to be carried for short trips	You give yourself injection and it is required to be carried for short trips
	Not need to be carried for short trips	You give yourself injection and it is not required to be carried for short trips
Injection site reaction	With	You may experience injection site reaction (e.g., hematoma, pain, hemorrhage, erythema, nodules, swelling, discoloration, pruritus, warmth, and injection site mass)
	Without	You do not experience injection site reaction after your injections

Health State Valuation

A total of 150 representative health states among all potential combinations were generated based on the balanced overlap method using Lighthouse Studio 9.15 from Sawtooth Software. These 150 health states were then allocated into 30 blocks, and each respondent was assigned one of 30 blocks (5 TTO tasks). Two additional fixed tasks, e.g., the mildest state (nonsevere hypoglycemia, once weekly injection does not need to be carried with the patient on short trips, without injection site reaction) and the worst state (severe hypoglycemia, three times daily injection need to be carried with the patient on short trips, with injection site reaction), were also included. Therefore, a total of seven TTO tasks (five randomly selected tasks and two fixed tasks) were asked for each respondent.

Each TTO task began by choosing between a health state describing a treatment scenario for 10 years (choice A) or full health for 10 years (choice B) (Fig. 1a). Typically, the latter was preferred. Respondents who preferred living in a treatment health state for 10 years (choice A) or who were indifferent between the alternatives (choices A and B are about the same) were considered irrational and excluded from the analysis. Then, respondents were asked to choose between living with the treatment health state for 10 years or die immediately (Fig. 1b). Health states of worse than death are unrealistic and rare in this therapeutic area, therefore, respondents who preferred to die immediately (choice B) or who were indifferent between the alternatives (choices A and B are about the same) were also considered impossible and excluded from the analysis [18, 23]. After these two quality control processes, a bisection step was used, and respondents were asked to choose between living with the treatment health state for 10 years or full health for 5 years (Fig. 1c). The time in full health was then made shorter if it was preferred or longer otherwise. One-year steps were used unless a change in direction was needed, and the smallest trading increment was half-year. Finally, the respondents’ indifference point was located by varying the time in full health (x, 0 ≤ x ≤ 10), and the utility value of each treatment health state was calculated as x/10 (0 ≤ utility value ≤ 1).

Fig. 1.

a Example of TTO task. b Example of TTO task. c Example of TTO task

Study Sample

Patients with T2DM were recruited from eight cities (Beijing, Guangzhou, Shanghai, Baoding, Chongqing, Jiujiang, Mianyang, and Wuhan) to achieve sufficient geographical spread and varied economic development levels in China. Quota sampling was used to ensure that the age and sex distribution of the sample resembled those of the Chinese patients with T2DM [2]. Taking into account the requirement of at least 25 TTO observations per health state to result in robust model estimation and the requirement of subgroup analysis, the target sample size was 400 [29, 30]. All respondents were required to be: (1) age ≥ 18 years, (2) diagnosed with type 2 diabetes ≥ 3 months by a recognized medical professional (patients were required to show proof of diagnosis or medication packaging during the videoconference), (3) were literate and had no disease that limited cognitive function, and (4) gave informed consent.

Data Collection

Online face-to-face interviews were used for data collection. Recruitment of the respondents was conducted through a professional online panel company and one interviewer was involved during the interview with each respondent. In each of the selected cities, all the interviewers were led by a local lead investigator and supervised by the principal investigator. Before the beginning of data collection, interviewers attended an online training to ensure equivalent task understanding, iterative procedures, and interactions with respondents. Eligibility for formal survey administration required all interviewers to complete TTO practice tasks, which were assessed by the principal investigator to ensure methodological compliance. The interview started with the respondent completing the quota questions (e.g., age and sex) and providing a series of socio-demographic characteristics (e.g., education level, marital and employment status). Second, all respondents were asked to report their own health state on the EQ-5D-5L and then complete seven TTO tasks. Last, respondents provided diabetes-related information (e.g., current treatment, number of medications and diabetes-related complications). A quality control check was conducted, where respondents were required to correctly identify diabetes therapeutics from a medication list including: metformin, repaglinide, acarbose, dapagliflozin, liraglutide, and distractors amlodipine and bisoprolol. Selection of either nondiabetes therapeutics (amlodipine or bisoprolol) resulted in exclusion. All interviews were conducted from October 2023 to January 2024.

Data collected by the interviews were directly excluded from the analysis if they: (1) contained any missing data, (2) provided a wrong answer to the quality control question of choosing T2DM drugs, and (3) failed to pass TTO quality control processes.

Data Analysis

Descriptive analyses were first conducted to present the respondents’ characteristics. The utility value for the self-reported EQ-5D-5L health state was calculated using the China value set [31]. Ordinary least square (OLS), fixed effects (FE), and random effects (RE) models were used to estimate disutility values of treatment-related attributes:

$$y_i=\alpha +\sum _d\sum _l{\beta }_{\mathit{dl}}{x}_{\mathit{dl}}+ϵ,$$ 1

where $y_i$ represented the disutility value; $\alpha$ represented the intercept (i.e. the mildest state in our study); $x_{\mathit{dl}}$ represented five dummy variables indicating the health state described by dimension $d$ at level $l$, except the mild level of each dimension (for reference); ${\beta }_{\mathit{dl}}$ represented the coefficient representing the estimated disutility value of having problems on dimension $d$ at level $l$; and $ϵ$ represented the error term. Considering each respondent completed seven TTO tasks, in addition to the OLS estimator with cluster-robust standard errors, the FE and RE models were also considered to account for the panel structure in the data [32].

The disutility value was used as the response variable and each level of the attribute as predictor variable. The preferred models for TTO were selected based on the Breusch Pagan LM test, Hausman test, and the goodness of fit of the model using the Akaike information criterion (AIC) and Bayesian information criterion (BIC). The prediction accuracy was also assessed by comparing predicted and observed mean values for health states valued in the study, using the intraclass correlation coefficient (ICC), the mean absolute error (MAE), and the mean squared error (MSE). Lower MAE and MSE and higher ICC values indicated better accuracy.

After the main analysis, five subgroup analyses were conducted based on five key characteristics of patients with T2DM [33, 34]: (1) current use of injectable treatment, (2) number of medications, (3) presence of needle phobia, (4) duration of injectable treatment, and (5) travel frequency. These analyses aimed to report the significance of parameters and compare disutility values within each subgroup and between groups. By incorporating interaction terms between various attribute levels and subgroup variables, we tested for statistically significant differences in coefficients between subgroups.

All statistical analyses were conducted using STATA 16.0, model coefficients were considered statistically significant if P < 0.05.

Results

Respondents

Of 632 respondents who were invited to participate in the survey, 529 respondents agreed to participate, with a response rate of 83.70%. Overall, 127 respondents were excluded because they were not eligible for the quotas (N = 112) or could not provide proof of diagnosis or medication (N = 15). Therefore, 402 respondents were eligible for the inclusion criteria. Two respondents were excluded because they did not complete the interview. Finally, a total of 400 respondents were included in this study (Appendix Fig. 1).

As presented in Table 2, 52.75% (N = 211) of total respondents were male, the mean (SD) age was 50.30 (12.05) years, and the mean (SD) BMI was 24.43 (3.92). Respondents reported being diagnosed with T2DM an average of 76.27 months. Most of the patients were currently receiving injectable treatment (N = 285, 71.25%), with a mean (SD) duration of 57.66 (55.93) months. The mean (SD) EQ-5D-5L utility value was 0.923 (0.099) and the mean (SD) EQ-VAS was 79.7 (12.2).

Table 2.

Characteristics of respondents

Characteristics	N = 400
Sexa (n, %)
Male	211 (52.75%)
Female	189 (47.25%)
Age (mean, SD)	50.30 (12.05)
Age group (years)a (n, %)
18–39	71 (17.75%)
40–59	206 (51.50%)
≥ 60	123 (30.75%)
Cityb (n, %)
Beijing	57 (14.25%)
Guangzhou	57 (14.25%)
Shanghai	56 (14.00%)
Baoding	46 (11.50%)
Chongqing	46 (11.50%)
Jiujiang	46 (11.50%)
Mianyang	46 (11.50%)
Wuhan	46 (11.50%)
BMI (mean, SD)	24.43 (3.92)
Residence (n, %)
Urban area	352 (88.00%)
Rural area	48 (12.00%)
Ethnic group (n, %)
Han	389 (97.25%)
Minority	11 (2.75%)
Education (n, %)
Primary or below	2 (0.50%)
Junior high school	41 (10.25%)
Senior high school	127 (31.75%)
College or above	230 (57.50%)
Marital status (n, %)
Unmarried	23 (5.75%)
Married	359 (89.75%)
Divorced	13 (3.25%)
Widowed	5 (1.25%)
Employment status (n, %)
Employed	254 (63.50%)
Retired	134 (33.50%)
Student	3 (0.75%)
Unemployed	9 (2.25%)
Personal monthly income (n, %)
<2000 RMB	22 (5.50%)
2000–5000 RMB	158 (39.50%)
5000–10000 RMB	170 (42.50%)
>10000 RMB	50 (12.50%)
Duration of diabetes (month) (mean, SD)	76.27 (67.68)
Current treatment (n, %)
Diet control	270 (67.50%)
Oral medication	256 (64.00%)
Injectable medication	285 (71.25%)
Other	3 (0.75%)
None	0 (0.00%)
Duration of injectable treatment (month) (mean, SD)	57.66 (55.93) (N = 285)
Number of medication (n, %)
0	6 (1.50%)
1	194 (48.50%)
2	141 (35.25%)
3	45 (11.25%)
4	10 (2.50%)
5	4 (1.00%)
Needle phobia (n, %)
No	192 (48.00%)
Slight	167 (41.75%)
Moderate	23 (5.75%)
Severe	12 (3.00%)
Extreme	6 (1.50%)
Travel frequency per year (n, %)
Barely travel	114 (28.50%)
1–2	185 (46.25%)
3–4	73 (18.25%)
5–9	21 (5.25%)
≥ 10	7 (1.75%)
EQ-5D-5L utility (mean, SD)	0.923 (0.099)
EQ-VAS (mean, SD)	79.685 (12.238)

SD, standard deviation; BMI, body mass index; EQ-5D-5L, EuroQol 5-Dimension 5-Level; EQ-VAS, EuroQol visual analogue scale

^aQuota sampling was used in this study, age group and sex were predefined on the basis of the distribution in the Chinese patients with T2DM

^bThree first-tier (Beijing, Guangzhou, Shanghai) and five second- and third-tier cities (Baoding, Chongqing, Jiujiang, Mianyang and Wuhan) were selected to recruit samples

Main analysis

The estimated coefficients from the TTO analysis are presented in Table 3 and Appendix Table 3. The random effects model demonstrated superior fit based on predefined selection criteria and was therefore selected for final analysis. All attribute levels exhibited statistically significant disutility values when compared with the reference health state (intercept = −0.208). Severe hypoglycemia was associated with a mean disutility of −0.023 (P < 0.001) compared with nonsevere hypoglycemia. Compared with once weekly injection (not required to be carried with the patient on short trips), three times daily, twice daily and once daily injection (needed to be carried with the patient) showed disutility values of −0.023 (P < 0.001), −0.018 (P < 0.001), and −0.011 (P = 0.022). The health state with an injection site reaction also showed a disutility of −0.013 (P < 0.001) compared with the state without an injection site reaction.

Table 3.

Estimated coefficients (SEs) of the RE models on time trade-off data

	RE model
	Coef.	SE	P value
Intercept	−0.208	0.008	< 0.001
Hypoglycemia (Ref: nonsevere)
Severe	−0.023	0.004	< 0.001
Injection site reaction (Ref: without)
With	−0.013	0.003	< 0.001
Dose frequency and flexibility (Ref: once weekly and not need to be carried for short trips)
Three times daily and need to be carried for short trips	−0.023	0.005	< 0.001
Twice daily and need to be carried for short trips	−0.018	0.004	< 0.001
Once daily and need to be carried for short trips	−0.011	0.005	0.022
MAE	0.0104328
MSE	0.0001571
ICC	0.7577

RE, random-effects; MAE, mean absolute error; MSE, mean squared error; ICC, intraclass correlation coefficient; Coef., coefficient; SE, standard error

Subgroup Analysis

Disutility values estimated from subgroups of respondents are presented in Fig. 2a–e. Statistical comparisons revealed no statistically significant differences between subgroups, except for the dose frequency of the injectable treatment duration subgroup (Fig. 2d). When we compared disutility values within each subgroup, patients with injectable treatment (N = 285) showed smaller disutility values for severe hypoglycemia (−0.021, P < 0.001) and injection site reaction (−0.011, P = 0.001) than patients without injectable treatment (N = 115). For patients with injectable treatment, disutility values of dose frequency were larger than that of patients without injectable treatment (except for twice daily injection needed to be carried with the patient on short trips) (Fig. 2a). A similar pattern was also observed in patients whose number of medications was ≥ 2 (N = 200); their disutility values for each level of dose frequency were all larger than in patients whose number of medications was < 2 (N = 200). The disutility values of severe hypoglycemia for patients whose number of medications was < 2 group (−0.026, P < 0.001) was larger than for patients whose number of medications was ≥ 2 (−0.021, P < 0.001) (Fig. 2b). For the subgroup of patients with needle phobia (N = 208), the mildest health state was associated with a larger disutility value (Intercept = −0.215), but severe hypoglycemia (−0.021, P < 0.001), injection site reaction (−0.011, P = 0.008) and dose frequency were all associated with relatively smaller disutility values (Fig. 2c). When comparing the subgroups of different durations of injectable treatment, patients with injectable treatment ≤ 25 months (N =100) gave larger disutility values to severe hypoglycemia and dose frequency than other groups with longer duration of injectable treatment. There was also a clear trend that patients became less sensitive to changes in dose frequency as the duration of injectable treatment increased. For example, for patients with injectable treatment ≤ 25 months (N =100), disutility values of three times daily, twice daily and once daily injection (needed to be carried with the patient on short trips) were −0.028 (P = 0.002), −0.026 (P = 0.005), −0.027 (P = 0.006) compared with once weekly injection (not required to be carried with the patient), but for patients with injectable treatment > 60 months (N =94), the disutility values were −0.022 (P = 0.022), −0.000 (P = 0.973) and −0.002 (P = 0.768) correspondingly (Fig. 2d). Finally, we compared whether travel frequency would have an impact on patients’ disutility for injection-related attributes. Patients in the travel group (N =286) gave smaller disutility value to severe hypoglycemia (−0.030, P < 0.001) and once daily injection needed to be carried with the patient on short trips (−0.016, P = 0.062) than patients who barely travelled. However, they gave greater disutility values to dose frequency of twice daily and three times daily injection needed to be carried with the patient on short trips which means that they might be more sensitive to multiple-daily injection regimens (Fig. 2e).

Fig. 2.

a Disutility of injectable treatment subgroup. b Disutility of number of medication subgroup. c Disutility of needle phobia subgroup. d Disutility of duration of injectable treatment subgroup. e Disutility of travel frequency subgroup

Discussion

This study quantified injection-related disutility values using the TTO method among Chinese patients with T2DM. In the main analysis, the disutility values associated with hypoglycemia, dose frequency, flexibility and injection site reaction were all statistically significant. The mean disutility values were largely consistent across the main and subgroup analyses. Although the impacts of these treatment-related attributes were smaller than those of serious diabetes complications, even minor differences may have a substantial influence on outcomes when modelling large samples over an extended period [17, 18, 35, 36].

The mean disutility estimates indicated that hypoglycemia, dose frequency and flexibility were rated as the most impactful attributes on health-related quality of life, with injection site reaction perceived as the least burdensome. These findings align with previous studies. A pooled disutility value of −0.028 for hypoglycemia was reported in a systematic review of studies from East and Southeast Asia [36], closely matching our estimate for severe versus nonsevere hypoglycemia (−0.023). Similarly, the disutility value for injection site reaction was −0.011 in a UK study [17], aligning with our result (−0.013).

However, respondents reported smaller disutility values for daily versus weekly administration (range: −0.023 to −0.011) in this study compared with previous studies (range: −0.095 to −0.023) [17, 22, 23]. One of the potential reasons is that two previous studies calculated disutility values among the general public rather than patients with T2DM [22, 23]. Prior comparisons between patient and general public preferences have revealed significant differences [25, 37, 38]. The general public may insufficiently comprehend health state impacts on daily life, particularly for injection-related attributes tied to specific procedures [16–18, 39]. Another reason might be that the age of respondents in our study (mean age 50.3 years) was younger than that of the respondents in a previous study on patients with T2DM (mean age 59.2 years), which may also affect preferences [17]. Quota sampling was employed in our study to enhance the reliability of disutility values for Chinese patients with T2DM. Besides, methodological differences in modelling may contribute to discrepancies. Previous approaches neglecting patient heterogeneity risk overestimating attribute impacts on health utility [21, 40, 41]. By contrast, our model incorporated participant-level random effects to account for correlated valuations across health states [20], while also utilizing all data to estimate values for unobserved state combinations [20, 42]. Indeed, we acknowledge that this is the first study to employ this approach, and further evidence is required to explore its validity. Both our results and prior evidence highlight dose frequency as a key treatment attribute affecting patient preference. Reduced dose frequency enhances convenience, adherence, and glycemic control in T2DM [17, 22, 23, 43]. Therefore, the observed preference for lower frequency in our study may guide future drug development and clinical decision-making to align with patient-centric care.

On the basis of previous studies and the results of subgroup analysis in our study, the relative importance of treatment-related attributes was found to depend on patient characteristics (e.g., injection experience) [8, 17, 44, 45]. The subgroup analysis revealed that patients currently receiving injectable treatment with ≥ 2 medications exhibited greater disutility values for changes in the dose frequency attribute. This suggests that direct experience with injectable therapies may enhance patients’ awareness of injection-related inconveniences, making them more sensitive to frequency adjustments as treatment complexity increases. Notably, sensitivity to dose frequency variations displayed a progressive decline with increasing treatment duration. This pattern supports existing evidence that newly diagnosed patients face particular challenges in adapting to treatment regimens, whereas long-term patients develop coping mechanisms over time [46].

Injection-related anxiety (i.e., fear of injection pain or needle) is prevalent among patients with diabetes and has been associated with both delayed insulin initiation and suboptimal adherence to injectable therapies [47]. Compared with patients without needle phobia, those with needle phobia reported a larger disutility value for the reference health state, while exhibiting smaller disutility values for level changes across all attributes. This indicates that patients with needle phobia perceive treatments involving injections as particularly burdensome, regardless of the severity and complexity of the injectable treatment. Consequently, once they have received injectable treatment, they are less responsive to changes in the severity levels of these injection-related attributes.

This study has several limitations. First, TTO tasks occasionally ended with nontrading (NT) in our study, indicating participants’ reluctance to exchange life years for improved health states. The limited discriminatory power of TTO may be related to the relatively mild severity of treatment-related health states assessed, which is consistent with findings from previous research [48]. Future studies could enhance sensitivity by using longer time horizons (e.g., 20 years) or smaller increments (e.g., 1 month). Second, although our sample was broadly consistent with Chinese T2DM population with regards to age and sex distribution, selection bias may have led to the recruitment of healthier patients, potentially influencing the study findings. For instance, the mean EQ-5D-5L utility value was 0.923 in our studies, which was slightly lower than the population norm for EQ-5D-5L (0.946) but higher than patients with T2DM in China (0.891) in previous studies [49, 50]. Third, the statistical significance may have been compromised owing to the limited sample sizes in certain subgroups, and further study into the differences in outcomes among these subgroups is needed in future research. Fourth, limitations related to our vignette approach are important to acknowledge. The use of uncertain language (e.g., “may experience”) in describing attributes of the adverse event heath states may have introduced variability in respondents' interpretations of the likelihood and severity of events, making it difficult to know exactly what the resulting utility values represent. The uncertainty may interfere with the interpretation of results and reduce confidence in utility values, therefore the disutility values for hypoglycemia and injection site reaction should be interpreted and applied with caution in CUAs. The selected medical terms used in the health states aligned with language routinely encountered by diabetes patients managing injectable therapies in China. In a Chinese language, the medical terms were identical to the words used in everyday language. However, there is a risk that some patients did not understand some of the medical terms that were used in the health states. Although no comprehension issues were observed during interviews, unrecognized misunderstandings could undermine the interpretability of utility values. Finally, the debate over whether health states should be valued by patients or the general public is longstanding. Some HTA agencies argue that societal perspectives should guide resource allocation to reflect the views of those who are funding the service. Considering patients’ potentially better understanding of diabetes injection therapy procedures and the absence of existing studies targeting Chinese patients with T2DM, our study estimated disutility values from patients. Additional research replicating current methods within a general public sample could help determine the disparities between patient and general public health preferences.

Conclusions

This study provides quantitative evidence regarding the disutility values associated with four injection-related attributes among patients with T2DM in China. The disutility values corresponding to changes in hypoglycemia, dose frequency, flexibility, and injection site reaction all demonstrated statistical significance. Given the uncertainty within the descriptions of adverse event health states, interpretation of the results or use of the utility values from this vignette study in a CUA should be done with caution.

Supplementary Information

Below is the link to the electronic supplementary material.

Funding/Role of the Funder

This study was funded by the National Natural Science Foundation of China (grant no. 72404205 and No. 72174142) and the Natural Science Foundation of Tianjin, China (grant no. 23JCQNJC01650). The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Declarations

Author Contributions

Concept and design: SX and JW. Acquisition of data: SX and XL. Analysis and interpretation of data: XL, CL, and SX. Drafting of the manuscript: XL, CL, and SX. Statistical analysis: XL, CL, and SX. Obtaining funding: SX and JW. Supervision: JW. All authors commented on previous versions of the manuscript and approved the final manuscript.

Conflicts of Interest/Competing Interests

SX reported receiving grants from the National Natural Science Foundation of China, and the Natural Science Foundation of Tianjin, China during the conduct of the study. JW reported receiving grants from the National Natural Science Foundation of China during the conduct of the study. Jing Wu is an Editorial Board member of PharmacoEconomics - Open. Jing Wu was not involved in the selection of peer reviewers for the manuscript nor any of the subsequent editorial decisions. No other conflicts of interest were reported by the authors.

Consent to Participate

Informed consent was obtained from all individual participants included in the study. Participants were informed about their freedom of refusal. Anonymity and confidentiality were maintained throughout the research process.

Availability of Data and Material

The datasets used and analyzed can be obtained from the corresponding author on reasonable request.

Ethics Approval

Informed consent was obtained prior to data collection. This study was approved by the Academic Ethics Committee at Tianjin University (No. TJUE-2023-206).

Code Availability

The code can be obtained from the corresponding author on reasonable request.

Consent for Publication

Informed consent for publication was obtained from all participants prior to their involvement in the study.