Pezzolato M, Spada GE, Fragale E, Cutica I, Masiero M, Marzorati C, Pravettoni G. Predictive Models of Psychological Distress, Quality of Life, and Adherence to Medication in Breast Cancer Patients: A Scoping Review.
Patient Prefer Adherence 2023;
17:3461-3473. [PMID:
38143947 PMCID:
PMC10748751 DOI:
10.2147/ppa.s440148]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/27/2023] [Indexed: 12/26/2023] Open
Abstract
Purpose
An interplay of clinical and psychosocial variables affects breast cancer patients' experiences and clinical trajectories. Several studies investigated the role of socio-demographic, clinical, and psychosocial factors in predicting relevant outcomes in breast cancer care, thus developing predictive models. Our aim is to summarize predictive models for specific psychological and behavioral outcomes: psychological distress, quality of life, and medication adherence. Specifically, we aim to map the determinants of the outcomes of interest, offering a thorough overview of these models.
Methods
Databases (PubMed, Scopus, Embase) have been searched to identify studies meeting the inclusion criteria: a breast cancer patients' sample, development/validation of a predictive model for selected psychological/behavioral outcomes (ie, psychological distress, quality of life, and medication adherence), and availability of English full-text.
Results
Twenty-one papers describing predictive models for psychological distress, quality of life, and adherence to medication in breast cancer were included. The models were developed using different statistical approaches. It has been shown that treatment-related factors (eg, side-effects, type of surgery or treatment received), socio-demographic (eg, younger age, lower income, and inactive occupational status), clinical (eg, advanced stage of disease, comorbidities, physical symptoms such as fatigue, insomnia, and pain) and psychological variables (eg, anxiety, depression, body image dissatisfaction) might predict poorer outcomes.
Conclusion
Predictive models of distress, quality of life, and adherence, although heterogeneous, showed good predictive values, as indicated by the reported performance measures and metrics. Many of the predictors are easily available in patients' health records, whereas others (eg, coping strategies, perceived social support, illness perceptions) might be introduced in routine assessment practices. The possibility to assess such factors is a relevant resource for clinicians and researchers involved in developing and implementing psychological interventions for breast cancer patients.
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