Psychosocial Mediators of Change and Patient Selection Factors in Oral Immunotherapy Trials

Abstract

Health-related quality of life (HRQL) is influenced by physiological, psychological, and environmental variables and can be best understood by considering the interactions of factors that cut across multiple levels. One of the most important issues relating to treatment in food allergy is to identify, describe, and define predictors that may contribute to modify HRQL outcomes. The research presented demonstrates that measures of HRQL are able to distinguish key features of known groups (e.g. relating to reaction severity, treatment, allergen type/number, expectation of outcome) and delineate impact on hitherto unknown groups (e.g. relating to personality types and coping styles). This heterogeneity may explain why HRQL or other patient-related outcomes may differ in individuals during, or following any treatment or intervention. Patient-reported outcomes are relatively poorly defined to date. Since HRQL has only been studied in relatively few oral immunotherapy trials to date, primarily looking at caregiver HRQL, it is unclear which factors, measures, or subscales are most predictive of short- and/or long-term treatment outcomes for which type of patient, and which time points for measurement are most informative. A standardised protocol that incorporates HRQL and other relevant patient-related outcome measures and agreed definitions of outcomes would allow for the comparison of efficacy of food allergy treatments between centres, trials, or countries. Further evidence-based research aimed at exploring the effects of interventions on outcomes in food allergy is needed, including the influence of patient and parent factors on protocol design. To this end, it is vital that patient-related outcomes such as improved HRQL are seen as a primary outcome and are measured at multiple intervals during the trial duration and beyond. The creative use of methods and designs (both qualitative and quantitative) to better understand the role of HRQL in immunotherapy treatment trials will enable improved modelling of the costs, risks, and benefits of any treatment. Systematic analysis and modelling of antecedent factors, mediators, and outcomes will be important to boost intervention effects and to maximise the overall benefits of treatment.

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