Health-related quality of life profiles in adolescents and young adults with chronic conditions.

Wang S, Arizmendi CJ, Blalock DV, Chen D, Lin L, Thissen D, Huang IC, DeWalt DA, Reeve BB. Health-related quality of life profiles in adolescents and young adults with chronic conditions. Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation. 2023 Nov 1; 32(11):3171-3183.

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Abstract:

PURPOSE: To assess health-related quality of life (HRQOL) among adolescents and young adults (AYAs) with chronic conditions. METHODS: AYAs (N? = 872) aged 14-20 years completed NIH''s Patient-Reported Outcomes Measurement Information System (PROMIS) measures of physical function, pain interference, fatigue, social health, depression, anxiety, and anger. Latent profile analysis (LPA) was used to group AYAs into HRQOL profiles using PROMIS T-scores. The optimal number of profiles was determined by model fit statistics, likelihood ratio test, and entropy. Multinomial logistic regression models were used to examine how LPA''s HRQOL profile membership was associated with patient demographic and chronic conditions. The model prediction accuracy on profile membership was evaluated using Huberty''s I index with a threshold of 0.35 for good effect. RESULTS: A 4-profile LPA model was selected. A total of 161 (18.5%), 256 (29.4%), 364 (41.7%), and 91 (10.4%) AYAs were classified into Minimal, Mild, Moderate, and Severe HRQOL Impact profiles. AYAs in each profile had distinctive mean scores with over a half standard deviation (5-points in PROMIS T-scores) of difference between profiles across most HRQOL domains. AYAs who were female or had conditions such as mental health condition, hypertension, and self-reported chronic pain were more likely to be in the Severe HRQOL Impact profile. The Huberty''s I index was 0.36. CONCLUSIONS: Approximately half of AYAs with a chronic condition experience moderate to severe HRQOL impact. The availability of risk prediction models for HRQOL impact will help to identify AYAs who are in greatest need of closer clinical care follow-up.