Estimating the minimally important difference for the EQ-5D-5L and EORTC QLQ-C30 in cancer.

BACKGROUND: The minimal important difference (MID) is a useful tool to interpret changes in patients' health-related quality of life. This study aims to estimate MIDs for interpreting within-patient change for both components of the EQ-5D-5L questionnaire [EQ-Visual Analogue Scale (EQ-VAS) and utility index] and domains of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) for cancer patients. METHODS: Data were obtained from the Cancer 2015 dataset, a longitudinal cohort of Australian cancer patients. Anchor-based approaches were used to estimate MIDs for the EQ-5D-5L index-based utility index [Australia and the United States (US) tariff sets], EQ-VAS scores, and the EORTC QLQ-C30. Clinical [Eastern Cooperative Oncology Group (ECOG) performance status] and patient-reported (items 29 and 30 of the EORTC QLQ-C30 and the EQ-VAS) anchors were assessed for appropriateness by their correlation strength. Clinical change groups (CCGs) were defined a priori for improvement and deterioration based on estimates used in previous literature. MIDs were estimated via linear regression and distribution-based methods. RESULTS: For the index-based utility scores in Australia, the anchor-defined MID estimates were 0.01 to 0.06 for improvement and - 0.04 to -0.03 for deterioration, with a weighted value of 0.03 for improvement and deterioration. The EQ-VAS MID estimate was 5 points for both improvement and deterioration. For the EORTC QLQ-C30, changes of at least 3.64 (improvement) and - 4.28 (deterioration) units on the physical functioning scale, 6.31 (improvement) and - 7.11 (deterioration) units on the role functioning scale, 4.65 (improvement) and - 3.41 (deterioration) units on the emotional functioning scale, and 5.41 (improvement) and - 5.56 (deterioration) units on the social functioning scale were estimated to be meaningful. CONCLUSION: This study identified lower MIDs for the EQ-5D-5L utility index, EQ-VAS, and EORTC QLQ-C30 domain scores, than those reported previously. The use of a real-world cancer-specific panel dataset may reflect smaller MID estimates that are more applicable to cancer patients in the clinical practice, rather than using MIDs that have been estimated from clinical trials.

Health-related quality of life in mild-to-moderate COVID-19 in the UK: a cross-sectional study from pre- to post-infection.

BACKGROUND: The aim of this study was to estimate the impact of mild-to-moderate COVID-19 on health-related quality of life (HRQoL) over time among individuals in the United Kingdom, adding to the evidence base that had focussed on severe COVID-19. METHODS: A bespoke online survey was administered to individuals who self-reported a positive COVID-19 test. An amended version of a validated generic HRQoL instrument (EQ-5D-5L) was used to measure HRQoL retrospectively at different timepoints over the course of an infection: pre-COVID-19, acute COVID-19, and long COVID. In addition, HRQoL post-COVID-19 was captured by the original EQ-5D-5L questionnaire. A mixed-effects model was used to estimate changes in HRQoL over time, adjusted for a range of variables correlated with HRQoL. RESULTS: The study recruited 406 participants: (i) 300 adults and 53 adolescents with mild-to-moderate COVID-19 who had not been hospitalised for COVID-19 during acute COVID-19, and (ii) 53 adults who had been hospitalised for COVID-19 in the acute phase and who had been recruited for validation purposes. Data were collected between January and April 2022. Among participants included in the base-case analysis, EQ-5D-5L utility scores were lower during both acute COVID-19 (ß=-0.080, p = 0.001) and long COVID (ß=-0.072, p < 0.001) compared to pre COVID-19. In addition, EQ-5D-5L utility scores post-COVID-19 were found to be similar to the EQ-5D-5L utility scores before COVID-19, including for patients who had been hospitalised for COVID-19 during the acute phase or for those who had experienced long COVID. Moreover, being hospitalised in the acute phase was associated with additional utility decrements during both acute COVID-19 (ß=-0.147, p = 0.026) and long (ß=-0.186, p < 0.001) COVID. CONCLUSION: Patients perceived their HRQoL to have varied significantly over the course of a mild-to-moderate COVID-19 infection. However, HRQoL was found to return to pre-COVID-19 levels, even for patients who had been hospitalised for COVID-19 during the acute phase or for those who had experienced long COVID.

Quality of life study for caregivers of people with uncontrolled focal-onset seizures.

AIM: The aim of this study was to capture and measure the impact of caregiving for an adult with uncontrolled drug-resistant focal-onset seizures (FOS) on the caregivers' quality of life (QoL), and to quantify the costs of productivity losses associated with providing informal care in this patient population. METHODS: An online survey, which included the EQ-5D-5L, CarerQol-7D and the Work Productivity and Activity Impairment: Specific-Health Problem (WPAI:SHP) questionnaires, was administered to caregivers of individuals with uncontrolled drug-resistant FOS in the United Kingdom (UK), France, Spain, Germany, Italy, and Sweden. RESULTS: The study included 345 caregivers. Most were males, aged between 25 and 34 years old whose caring responsibilities took between 15 and 24 h per week. The caregivers' mean EQ-5D-5L score was 0.6, with 95% confidence intervals (CI) of [0.58, 0.63], whilst the mean CarerQol-7D score was 72.61 [70.46, 74.76]. Caregivers' mental health was the most substantially affected aspect of their QoL. In addition, most caregivers reported deriving some or a lot of fulfilment out of their caregiving tasks. The WPAI:SHP showed that the mean percentage of work impairment due to caregiving responsibilities was 63%, [59.75, 66.26]. The mean annualised costs of productivity losses per caregiver were estimated at €14,872 [€11,908; €17,888]. LIMITATIONS: One limitation consisted in the use of an online survey instead of a face-to-face interview. However, the medical terms were clearly explained, and examples were provided to help participants to give accurate responses. Another limitation was that the respondents self-reported as caregivers. Efforts were made to mitigate this weakness by using screener questions. CONCLUSION: This study found that providing informal care for people with uncontrolled drug-resistant FOS had a negative impact on caregivers' QoL, with mental health being affected the most. However, caregivers found their role fulfilling and had support with their caring tasks.

Estimation of Health-Related Utilities for 177Lu-DOTATATE in GEP-NET Patients Using Utilities Mapped from EORTC QLQ-C30 to EQ-5D-3L and QLU-C10D Utilities.

BACKGROUND: Gastroenteropancreatic neuroendocrine tumours (GEP-NET) are a rare, life-threatening type of cancer. The survival benefit of 177Lu-DOTATATE has been demonstrated in GEP-NET patients. Health technology assessment bodies require data on health-related utility impacts of treatment. A cancer-specific instrument, EORTC QLQ-C30, was used to collect the data for 177Lu-DOTATATE within clinical studies, but utility-based instruments were not included. OBJECTIVE: The main aim of this study was to compare EQ-5D-3L and QLU-C10D utilities obtained from EORTC QLQ-C30 using two different approaches. A secondary aim was to analyse the EQ-5D-3L and QLU-C10D utilities of patients treated with 177Lu-DOTATATE versus best supportive care. A supplementary aim was to evaluate the effect of 177Lu-DOTATATE on patients' health-related utility over time. METHODS: Three datasets were used for the analysis. NETTER-1 is a clinical trial, whilst ERASMUS and Guy's and St. Thomas (GStT) are real-world datasets. Two mapping algorithms (response mapping and ordinary least square regression) were applied to generate EQ-5D-3L utilities from EORTC QLQ-C30. An algorithm was used to obtain QLU-C10D utilities from EORTC QLQ-C30. RESULTS: In all studies, EQ-5D-3L utilities were higher than QLU-C10D utilities at most time points measured, although the magnitude of the differences was small. In NETTER-1, EQ-5D-3L and QLU-C10D utilities were higher in the 177Lu-DOTATATE arm compared with the octreotide long-acting release (LAR) arm, overall and pre-progression. In all studies, patients' health-related utilities seem to be maintained over time. CONCLUSION: There were small differences between EQ-5D-3L and QLU-C10D utilities, but these did not translate to relative differences over time or between groups. In NETTER-1, patients in the 177Lu-DOTATATE arm had higher health-related utilities than patients in the octreotide LAR arm. Health-related utility may at least remain maintained in patients with GEP-NET receiving 177Lu-DOTATATE.