Predicting psychological distress after primary oncological treatment in elderly breast cancer survivors: Retrospective study

Investor logo

Warning

This publication doesn't include Faculty of Arts. It includes Faculty of Medicine. Official publication website can be found on muni.cz.
Title in English Predikce psychologického distresu po primární onkologické léčbě u přeživších starších žen s karcinomem prsu: retrospektivní studie
Authors

SKŘIVANOVÁ Kateřina SVĚRÁK Tomáš BRANČÍKOVÁ Dagmar JARKOVSKÝ Jiří BENEŠOVÁ Klára ANDERKOVÁ Ľubomíra ELFMARKOVÁ Nela PETERKOVÁ Hana BENDOVÁ Marcela MINÁŘ Luboš HOLOUBKOVÁ Eva NEDVĚD Jan PROTIVÁNKOVÁ Markéta DUŠEK Ladislav

Year of publication 2015
Type Article in Periodical
Magazine / Source Praktická gynekologie
MU Faculty or unit

Faculty of Medicine

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.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.