Publication details
Predicting psychological distress after primary oncological treatment in elderly breast cancer survivors: Retrospective study
| Title in English | Predikce psychologického distresu po primární onkologické léčbě u přeživších starších žen s karcinomem prsu: retrospektivní studie |
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| Authors | |
| Year of publication | 2015 |
| Type | Article in Periodical |
| Magazine / Source | Praktická gynekologie |
| MU Faculty or unit | |
| Citation | |
| Field | Psychology |
| Keywords | C-reactive protein; elderly breast cancer survivors; multivariate linear regression; psychoneuroimmunology; psychological distress prediction; retrospective study |
| Attached files | |
| Description | The aim of this study was to determine the prognosis of psychological distress in breast cancer survivors after primary oncological treatment using biological and psychological variables. The test group consisted of 98 elderly breast cancer survivors (median age was 65 years) who completed the SVF 78 questionnaire (coping styles measures), NEO-FFI questionnaire (personality traits measures), SCL-90 questionnaire (psychopathology measures) completing treatment and another retrospectively at diagnosis. The SAS scale (anxiety measures) was completed by a lower number of patients. Data on tumour-related factors and treatment were obtained from medical records. Within the scope of this study, psychological distress was measured via the SCL-90 method using Global Severity Index (GSI) and Positive Symptom Distress Index (PSDI). Quantification of the relationship between biological and psychological predictors and GSI and PSDI as dependent variables was estimated using both univariate and multivariate linear regression models. C-reactive protein levels were monitored at diagnosis and one year after primary treatment. The best model for the prediction of GSI after treatment was identified by multivariate linear regression as the combination of GSI, CRP level and agreeableness (NEO-FFI subscale) predictors at the time of diagnosis in which R2 = 76.6 %. The best model for predicting PSDI after treatment consisted of PSDI, the self-accusation component of SVF 78 and the stage of the disease (IV vs lower) at the time of diagnosis with R2 = 53.9 %. Incorporating the total raw score of the SAS questionnaire into the multivariate models for prediction of GSI and PSDI caused an increase in R2 (71.5 % to 85.0 % and 46.0 % to 65.1 %), respectively. Both biological and psychological predictors proved significant and suitable for psychological distress prediction in elderly breast cancer survivors after longterm oncological treatment. |
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