Quality of Life Research最新文献

Purpose: Cancer survivors often experience long-term consequences affecting their Health-Related Quality of Life (HRQoL). Sociodemographic factors, clinical characteristics, and health-related behaviours influence HRQoL, making some individuals vulnerable to adverse HRQoL. This study develops linear regression and machine learning models to predict HRQoL two-year post-diagnosis and to identify key vulnerability factors.

Methods: This longitudinal study included data of survivors of seven cancer types. Nineteen predictor variables were derived from questionnaires completed within three months post-diagnosis (baseline) from the Netherlands Cancer Registry. Linear regression, random forest, XGBoost, neural network, and Support Vector Machine (SVM) regressors were employed to predict the EORTC QLQ-C30 summary score 1.5-2.5 years post-diagnosis. Permutation testing assessed vulnerability factors.

Results: The analyses included 4,538 individuals. All models achieved similar R² (0.3) and RMSE (9) scores. Linear regression, random forest, XGBoost, and SVM models identified lower physical, cognitive, and emotional functioning at diagnosis, along with more comorbidities, cancer type (especially endometrial), and higher BMI as the top vulnerability factors. Treatment, age, and education were not associated with vulnerability. All models tended to overestimate low HRQoL which might be due to the limited number of observations with low HRQoL values.

Conclusions: The predictors used in this analysis explained only 30% of the variation in long-term HRQoL. Similar to previous studies predicting HRQoL in cancer, these predictors miss crucial information. Baseline functioning, comorbidities, cancer type and BMI appeared to be the key vulnerability factors. Future studies should prioritize accurate prediction of low HRQoL scores.

Background: Gastroesophageal cancer has a poor prognosis, and treatment significantly impacts health-related quality of life (HRQoL). Accurate prediction of HRQoL changes after treatment can support shared decision-making. This study aimed to develop and validate HRQoL prediction models for patients with gastroesophageal cancer using established risk-prediction models and a newly proposed sequential score model.

Methods: HRQoL data came from the Prospective Observational Cohort Study of Esophageal-Gastric Cancer Patients registry, linked to the Netherlands Cancer Registry. The EORTC QLQ-C30 functioning scales were used as outcomes. Risk-prediction models, based on logistic elastic-net regression, estimated the probability of meaningful HRQoL deterioration at 3, 6, and 12 months post-treatment. The sequential score model, using XGBoost regression, predicted the next HRQoL score at any time. Calibration curves and integrated calibration index (ICI) assessed predictive performance, with Brier scores and AUC for risk-prediction models and root mean squared error plus Out-of-Sample r^² for sequential models.

Results: Risk-prediction models showed strong performance (ICI: 0.03-0.08; Brier score: 0.09-0.17; AUC: 0.79-0.87) for predicting significant deterioration in Summary Score, Physical Functioning, and Fatigue, with good calibration. Sequential score models explained up to 40% of the variance in HRQoL scores.

Conclusion: Both models effectively predicted HRQoL in gastroesophageal cancer patients, demonstrating potential to enhance patient care and information sharing through accurate prediction of HRQoL outcomes.

Objective: As part of a large mixed-methods study, we aim to develop culturally relevant additional dimensions (bolt-ons) for the EQ-5D-5L in China. In the qualitative phase, we developed seven candidate bolt-ons. In this first quantitative phase, we aimed to test the psychometric properties of these bolt-ons in the Chinese adult general population.

Methods: An online survey was conducted among a representative sample of the Chinese general population (n = 1,037) to collect data on the EQ-5D-5L + bolt-ons, SF-6Dv2, EQ-HWB-9, general health status, and socio-demographics. Psychometric analysis was performed to assess the EQ-5D-5L + bolt-ons, including ceiling, informativity, convergent and divergent validity, known-group validity and explanatory power.

Results: Adding bolt-ons reduced the ceiling of the EQ-5D-5L by 2.3%-points (adaptation to society) to 7.6%-points (tiredness/lack of strength). Tiredness/lack of strength had the highest relative informativity (Shannon's evenness index = 0.67). Appetite and social relationships showed the best divergent validity from the five core dimensions. Tiredness/lack of strength demonstrated strong or moderate correlations with SF-6Dv2 vitality (r = 0.648) and EQ-HWB-9 exhaustion (r = 0.541) dimensions. Adding tiredness/lack of strength, climate adaptation and emotional control improved the explanatory power for the EQ VAS score. Tiredness/lack of strength enhanced the known-groups validity for differentiating between respondents based on the presence of chronic diseases and in group comparisons by SF-6Dv2 level sum scores.

Conclusion: The tiredness/lack of strength bolt-ons performed best, but the sleep problems and appetite bolt-ons also improved several psychometric properties of the EQ-5D-5L in the Chinese general population. Combined with patient evidence, these findings may inform evidence-based bolt-on selection in the Chinese context.

Purpose: The purpose of this study was to explore the content validity of the Danish version of the PROMIS-10 Global Health questionnaire in patients with high-impact chronic pain by (1) identifying problematic items and reasons for misunderstandings between participants' interpretations and the intended meaning, and (2) exploring how participants understand and interpret the items.

Methods: Individual cognitive interviews were conducted with participants with high-impact chronic pain referred to two Danish Pain Centers using a structured step-by-step interview approach. The first objective was analyzed mainly using a deductive structured approach, while the second objective was analyzed mainly using an inductive thematic approach focusing on participants' perspectives.

Results: Participants (n = 19) generally understood the items as intended but showed 21% and 11% non-congruency for items 8r (fatigue) and 7r (pain intensity), as they responded based on a longer timeframe than "the past 7 days". Overall, participants interpreted the items through a physical, psychological and social perspective. Further, items 5 (social activities and relationships) and 6 (daily physical activities) were perceived to overlap thematically with item 9r (social activities and roles). Additionally, the provided examples in items 5 and 6 influenced responses, and some deemed item 7r irrelevant, as it did not reflect their pain experiences.

Conclusion: The findings contribute to the validation of PROMIS-10 Global Health in patients with high-impact chronic pain by providing insights into how participants understand and interpret the items, highlighting areas for minor refinement. Further qualitative research on the validity of PROMIS-10 Global Health in this population is needed.

Purpose: Obstructive Sleep Apnea (OSA) impairs children's quality of life (QoL), but the impact of air pollution and heat wave on pediatric OSA-related QoL remains unclear. This retrospective cross-sectional study investigated associations between short-term air pollutant (PM_2.5, PM₁₀, SO₂, and NO₂) exposure, heat wave, and QoL in children with OSA, including pollutant lag effects.

Methods: A retrospective cross-sectional study was conducted at Henan Provincial Children's Hospital (2021-2023). Eligible participants were ≤ 14-year-old Henan residents with confirmed OSA (OAHI > 1) via polysomnography. QoL was assessed by the OSA-18 Scale. Air pollutant and heat wave data were from national monitoring networks. Generalized Linear Regression Models (GLMs) analyzed continuous QoL outcomes, with sensitivity analyses performed.

Results: 1943 children were included. The statistical analysis results showed that PM_2.5 lag03-lag07; PM₁₀ lag0-lag6, lag01-lag07; SO₂ lag0-lag2, lag01-lag07; NO₂ lag7, lag05-lag07 were statistically correlated with the impact on the QoL of pediatric patients. The maximum effect values OR were 1.042 (95% CI 1.006, 1.079), 1.030 (95% CI 1.016, 1.045), 1.774 (95% CI 1.279, 2.462), and 1.101 (95% CI 1.013, 1.197), respectively. Additionally, heat wave was associated with worse QoL (OR:1.537, 95% CI 1.021, 2.313). Sensitivity analyses confirmed result stability.

Conclusions: Air pollutants (especially SO₂ and NO₂) and heat waves reduce QoL in children with OSA, highlighting the need for targeted environmental interventions.