Quality of Life Research最新文献

Purpose: Systematic reviews of patient-reported outcome measures (PROMs) are important tools to select the most suitable PROM for a study or clinical application. Conducting these reviews is challenging, and the quality of these reviews needs to be improved. We updated the COSMIN guideline for systematic reviews of PROMs, including the COSMIN Risk of Bias checklist, and the COSMIN criteria for good measurement properties.

Methods: Adaptations to the methodology were based on our experience with applying the COSMIN guideline, through discussions among the authors, and results from two related Delphi studies.

Results: The updated guideline places more emphasis on key aspects that are often missing or sub optimally conducted in published systematic reviews of PROMs, such as formulating a well-defined research question and developing a comprehensive search strategy, assessing risk of bias, applying criteria for good measurement properties, summarizing results, and grading the quality of the evidence. We also stress the importance of evaluating the measurement properties of each subscale of a PROM separately and evaluating content validity of all included PROMs.

Conclusion: The quality of systematic reviews of PROMs can be improved by using this updated version of the COSMIN guideline for systematic reviews of PROMs. Improved quality will lead to better PROM selection and increased standardization of PROM use.

Purpose: Mapping or matching the items in a clinical outcome assessment (COA) to concepts that define a condition is a common method for evaluating a COA's concept coverage. The purpose of this research was to address the lack of formal guidance for conducting this task by developing a framework for best practices in COA concept mapping and applying it to a case study.

Methods: To develop the framework, we examined the literature and created a draft set of best practices which was then reviewed by experienced researchers through focus groups before being finalized. To conduct the case study, we extracted data from a systematic review of knee osteoarthritis (KO) symptoms and impacts and used the framework to map relevant concepts to items in the SF-36v2^® Health Survey (SF-36v2).

Results: The framework guides researchers in defining the purpose of and data sources for the mapping, establishing guiding principles and decision-making thresholds, and conducting the mapping exercise. The results of the case study demonstrate the usefulness of the framework in identifying 27/36 items (75%) in the SF-36v2 that addressed concepts that define KO.

Conclusion: This case study illustrates how the framework for best practices in COA concept mapping may be used, highlighting how establishing clear concept definitions and guiding principles and following a structured process throughout can help produce consistent, reliable, and reproducible results. The results from this rigorous approach can provide valuable evidence to support decisions about the appropriateness of a COA for the intended patient population.

Purpose: Sleep problems are frequently observed in cancer patients. Multiple questionnaires for assessing sleep quality have been developed. The aim of this study was to present transfer rules that allow the conversion of the patients' scores from one questionnaire to another. In addition, we anchored this common metric to the general population.

Methods: A sample of 1,733 cancer patients completed the following questionnaires: Pittsburgh Sleep Quality Index, Insomnia Sleep Index, Jenkins Sleep Scale, EORTC QLQ-C30, and the sleep scale of the EORTC QLQ-SURV100. The methods for establishing a common metric were based on Item Response Theory.

Results: The main result of the study is a figure that allows the conversion from one of the above-mentioned sleep scales into another. Furthermore, the scores of the questionnaires can be transferred to theta scores that indicate the position within the group of cancer patients and also to T scores that indicate the position in relation to the general population. The correlations between the sleep scales ranged between 0.70 and 0.85.

Conclusions: The conversion rules presented in the study enable researchers and clinicians to directly compare single scores or mean scores across studies using different sleep scales, to assess the degree of sleep problems with regard to the general population, and to relate cutoff scores from one questionnaire to another.

Purpose: The impact of pediatric traumatic brain injury (pTBI) on health-related quality of life (HRQoL) in children and adolescents remains understudied. Short scales have some advantages in terms of economy and administration over longer scales, especially in younger children. The aim of the present study is to psychometrically evaluate the six-item German version of the QOLIBRI-OS-KID/ADO scale for children and adolescents. In addition, reference values from a general German pediatric population are obtained to assist clinicians and researchers in the interpretation of HRQoL after pTBI.

Methods: A total of 297 individuals after TBI and 1997 from a general population sample completed the questionnaire. Reliability, validity, and comparability of the assessed construct were examined.

Results: The questionnaire showed satisfactory reliability (α = 0.75 and ω = 0.81 and α = 0.85 and ω = 0.86 for the TBI and general population samples, respectively). The QOLIBRI-OS-KID/ADO was highly correlated with its long version (R² = 67%) and showed an overlap with disease-specific HRQoL (R² = 55%) in the TBI sample. The one-dimensional factorial structure could be replicated and tested for measurement invariance between samples, indicating a comparable HRQoL construct assessment. Therefore, reference values and cut-offs indicating clinically relevant impairment could be provided using percentiles stratified by factors significantly associated with the total score in the regression analyses (i.e., age group and gender).

Conclusion: In combination with the cut-offs, the QOLIBRI-OS-KID/ADO provides a cost-effective screening tool, complemented by interpretation guidelines, which may help to draw clinical conclusions and indications such as further administration of a longer version of the instrument to gain more detailed insight into impaired HRQoL domains or omission of further steps in the absence of an indication.

Purpose: Osteoarthritis (OA) often coexists with risk factors for cardiovascular disease (CVD), worsening symptoms and functional impairment. This cross-sectional study investigated the association between Life's Essential 8 (LE8) and disability in individuals with OA.

Methods: Data from 8334 United States adults (aged ≥ 20) who participated in the 2005-2018 National Health and Nutrition Examination Survey (NHANES) with complete data on LE8 components and disability status were analyzed. LE8 components, including diet, physical activity (PA), nicotine exposure, sleep, body mass index (BMI), blood lipids, glucose, and blood pressure (BP), were scored on a 0-100 scale, categorizing cardiovascular health (CVH) as low, moderate, or high. Disability mainly caused by OA was assessed using a standardized physical functioning questionnaire. Association analyses were performed using multivariable logistic regression, adjusting for demographic, socioeconomic, lifestyle, and health-related covariates.

Results: Individuals with CVH scores 10 points higher had a 15% lower prevalence of OA (95% CI 0.81-0.90). Individuals with OA were more than twice as likely to experience disability. High levels of CVH were associated with a lower prevalence of disability in various domains compared to low levels of CVH (all P < 0.05), such as in activities of daily living (OR 0.32, 95% CI 0.18-0.58). Among the LE8 components, BMI, PA, and sleep health were associated with disabilities in all domains, while blood lipid scores were not.

Conclusion: A higher adherence to LE8 is associated with a lower prevalence of different types of disability in domains of physical functioning and functional limitations in individuals with OA.

Purpose: The minimal important change (MIC) in a patient-reported outcome measure is often estimated using patient-reported transition ratings as anchor. However, transition ratings are often more heavily weighted by the follow-up state than by the baseline state, a phenomenon known as "present state bias" (PSB). It is unknown if and how PSB affects the estimation of MICs using various methods.

Methods: We simulated 3240 samples in which the true MIC was simulated as the mean of individual MICs, and PSB was created by basing transition ratings on a "weighted change", differentially weighting baseline and follow-up states. In each sample we estimated MICs based on the following methods: mean change (MC), receiver operating characteristic (ROC) analysis, predictive modeling (PM), adjusted predictive modeling (APM), longitudinal item response theory (LIRT), and longitudinal confirmatory factor analysis (LCFA). The latter two MICs were estimated with and without constraints on the transition item slope parameters (LIRT) or factor loadings (LCFA).

Results: PSB did not affect MIC estimates based on MC, ROC, and PM but these methods were biased by other factors. PSB caused imprecision in the MIC estimates based on APM, LIRT and LCFA with constraints, if the degree of PSB was substantial. However, the unconstrained LIRT- and LCFA-based MICs recovered the true MIC without bias and with high precision, independent of the degree of PSB.

Conclusion: We recommend the unconstrained LIRT- and LCFA-based MIC methods to estimate anchor-based MICs, irrespective of the degree of PSB. The APM-method is a feasible alternative if PSB is limited.

Purpose: Standardized patient-reported outcomes (PRO) monitoring during and after rectal cancer treatment provides insight into treatment-related toxicities patients experience and improves health-related quality-of-life as well as overall survival. We aimed to select a subset of the PRO version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) for standardized monitoring of treatment-related symptomatic toxicities in rectal cancer.

Methods: We used a mixed methods approach including a literature review, and semi-structured interviews with health care providers (HCPs) involved in rectal cancer care and rectal cancer patients. Results from literature and interviews were summarized and used in a modified Delphi procedure to select a PRO-CTCAE subset specific for rectal cancer.

Results: Twenty-six PRO-CTCAE symptomatic toxicities were identified from literature. Fifteen HCPs from multiple disciplines (medical, radiation and surgical oncology), and a heterogeneous group of fifteen rectal cancer patients treated with chemotherapy and/or radiotherapy and/or surgery, participated in semi-structured interviews. Ten HCPs (67%) and nine patients (90%) participated in the first Delphi round. The final selected PRO-CTCAE core-subset contained 16 symptomatic toxicities: 'diarrhea', 'fecal incontinence', 'constipation','bloating of the abdomen', 'pain in the abdomen', 'vomiting', 'decreased libido', 'pain during vaginal sex', 'ability to achieve and maintain erection', 'fatigue', 'anxiety', 'feeling that nothing could cheer you up', 'urinary incontinence', 'painful urination', 'general pain', and 'hand-foot syndrome'.

Conclusion: Based on a comprehensive mixed methods study, a PRO-CTCAE subset for standardized treatment-related symptomatic toxicity monitoring in rectal cancer was identified. Assessment of the effectiveness and compliance of symptomatic toxicity monitoring using this subset is recommended.

Background: Understanding health-related quality of life (HRQoL) dynamics is essential for assessing and improving treatment experiences; however, clinical and observational studies struggle to capture their full complexity. We use simulation modeling and the case of Chimeric Antigen Receptor T-cell therapy-a type of cancer immunotherapy that can prolong survival, but carries life-threatening risks-to study HRQoL dynamics.

Methods: We developed an exploratory system dynamics model with mathematical equations and parameter values informed by literature and expert insights. We refined its feedback structure and evaluated its dynamic behavior through iterative interviews. Model simulated HRQoL from treatment approval through six months post-infusion. Two strategies-reducing the delay to infusion and enhancing social support-were incorporated into the model. To dynamically evaluate the effect of these strategies, we developed four metrics: post-treatment HRQoL decline, recovery time to pre-treatment HRQoL, post-treatment HRQoL peak, and durability of the peak.

Results: Model captures key interactions within HRQoL, providing a nuanced analysis of its continuous temporal dynamics, particularly physical well-being, psychological well-being, tumor burden, receipt and efficacy of treatment, side effects, and their management. Model analysis shows reducing infusion delays enhanced HRQoL across all four metrics. While enhanced social support improved the first three metrics for patients who received treatment, it did not change durability of the peak.

Conclusions: Simulation modeling can help explore the effects of strategies on HRQoL while also demonstrating the dynamic interactions between its key components, offering a powerful tool to investigate aspects of HRQoL that are difficult to assess in real-world settings.

Purpose: This study aimed to examine the trajectory in health-related quality of life (HRQoL) during and after hospitalisation for worsening of heart failure (HF) in Malaysia.

Methods: 200 patients with heart failure and reduced ejection fraction (HFrEF) admitted into two hospitals in Malaysia due to worsening of HF were surveyed using the EQ-5D-5 L questionnaire. The primary outcomes were utility values at admission, discharge and 1-month post-discharge (1MPD). Secondary outcomes included the visual analogue scores (VAS) and the proportion of patients reporting each EQ-5D-5 L dimension levels. Missing data were imputed using multiple imputation, and generalised linear mixed models were fitted.

Results: At admission, the unadjusted mean utility values and VAS scores for HFrEF patients in Malaysia were as low as 0.150 ± 0.393 and 38.2 ± 20.8, respectively. After a median hospital stay of 4 days, there was a significant improvement in utility values and VAS scores by 0.510 (95% CI: 0.455-0.564) and 28.8 (95% CI: 25.5-32.1), respectively. The utility value and VAS score at 1-month post-discharge were not significantly different from discharge. The proportion of HFrEF patients reporting problems and severe problems in mobility, self-care, usual activities, and anxiety/depression, pain/discomfort reduced at varying degree from admission to discharge and 1MPD.

Conclusion: HF is a progressive condition with substantial variation in HRQoL during the disease trajectory. During hospitalisation due to worsening of HF, HFrEF population has unfavourable HRQoL. Rapid and significant HRQoL improvement was observed at discharge, which sustained over one month. The study findings can inform future cost-effectiveness analyses and policies.