Measuring fear of cancer recurrence in patients with primary brain tumors

Abstract BACKGROUND Fear of cancer recurrence (FCR) differs for those living with primary brain tumor compared to other cancers due to poorer prognosis, neurologic symptoms, and often lifelong treatment. The gold-standard instrument used to assess FCR–the FCR Inventory (FCRI)–has not been validated in patients with PBT. The present study explored the psychometric properties of the FCRI in patients with brain tumors, with items added assessing brain tumor-specific distress. METHODS Adult patients with brain tumors (n = 87) completed the FCRI and other psychological medical, and demographic questionnaires. Exploratory factor analysis (EFA) was conducted on the FCRI with five additional items informed by neuro-oncology patients and professionals assessing brain tumor-specific hypervigilance (e.g., interpreting headache or cognitive difficulties as possible tumor growth) and one item assessing tendency to research treatments—for a total of 48 items. Correlations investigated convergent/discriminant validity and relationships with relevant medical and demographic variables. RESULTS After iteration, EFA revealed a seven-factor model with 24 retained items, accounting for 68.19% of variance, with factor correlations between .12 and .65. The seven-factor model echoed but did not fully replicate the original FCRI. FCRI-Brain factors were: Triggers, Psychological Distress, Functional Impairments, Insight, Reassurance, Emotion-Focused Coping, and Problem-Focused Coping (Total: Cronbach’s a = .92). The resultant FCRI-Brain demonstrated good convergent validity with measures of depression (r = .57), anxiety (r = .71), and death anxiety (r = .81; ps< .05). Lack of correlation with education (p > .05) supported discriminant validity. There was no relationship with time since diagnosis (p > .05). CONCLUSIONS These data represent the initial validation of an FCR measure in patients with brain tumors. Factor analysis identified a theoretically similar; yet unique seven-factor model for the FCRI-Brain. Item-level exploration will be presented, including further discussion of factor iteration and construction. Future work will build on this data in larger samples and inform intervention development.