Optimization of prediction methods for risk assessment of pathogenic germline variants in the Japanese population.

Predicting pathogenic germline variants (PGVs) in breast cancer patients is important for selecting optimal therapeutics and implementing risk reduction strategies. However, PGV risk factors and the performance of prediction methods in the Japanese population remain unclear. We investigated clinicopathological risk factors using the Tyrer-Cuzick (TC) breast cancer risk evaluation tool to predict BRCA PGVs in unselected Japanese breast cancer patients (n = 1,995). Eleven breast cancer susceptibility genes were analyzed using target-capture sequencing in a previous study; the PGV prevalence in BRCA1, BRCA2, and PALB2 was 0.75%, 3.1%, and 0.45%, respectively. Significant associations were found between the presence of BRCA PGVs and early disease onset, number of familial cancer cases (up to third-degree relatives), triple-negative breast cancer patients under the age of 60, and ovarian cancer history (all P < .0001). In total, 816 patients (40.9%) satisfied the National Comprehensive Cancer Network (NCCN) guidelines for recommending multigene testing. The sensitivity and specificity of the NCCN criteria for discriminating PGV carriers from noncarriers were 71.3% and 60.7%, respectively. The TC model showed good discrimination for predicting BRCA PGVs (area under the curve, 0.75; 95% confidence interval, 0.69-0.81). Furthermore, use of the TC model with an optimized cutoff of TC score ≥0.16% in addition to the NCCN guidelines improved the predictive efficiency for high-risk groups (sensitivity, 77.2%; specificity, 54.8%; about 11 genes). Given the influence of ethnic differences on prediction, we consider that further studies are warranted to elucidate the role of environmental and genetic factors for realizing precise prediction.

The relation between mindfulness and the fatigue of women with breast cancer: path analysis.

BACKGROUND: Although fatigue is a common and distressing symptom in cancer survivors, the mechanism of fatigue is not fully understood. Therefore, this study aims to investigate the relation between the fatigue and mindfulness of breast cancer survivors using anxiety, depression, pain, loneliness, and sleep disturbance as mediators. METHODS: Path analysis was performed to examine direct and indirect associations between mindfulness and fatigue. Participants were breast cancer survivors who visited a breast surgery department at a university hospital in Japan for hormonal therapy or regular check-ups after treatment. The questionnaire measured cancer-related-fatigue, mindfulness, anxiety, depression, pain, loneliness, and sleep disturbance. Demographic and clinical characteristics were collected from medical records. RESULTS: Two-hundred and seventy-nine breast cancer survivors were registered, of which 259 answered the questionnaire. Ten respondents with incomplete questionnaire data were excluded, resulting in 249 participants for the analyses. Our final model fit the data well (goodness of fit index = .993; adjusted goodness of fit index = .966; comparative fit index = .999; root mean square error of approximation = .016). Mindfulness, anxiety, depression, pain, loneliness, and sleep disturbance were related to fatigue, and mindfulness had the most influence on fatigue (ß = - .52). Mindfulness affected fatigue not only directly but also indirectly through anxiety, depression, pain, loneliness, and sleep disturbance. CONCLUSIONS: The study model helps to explain the process by which mindfulness affects fatigue. Our results suggest that mindfulness has both direct and indirect effects on the fatigue of breast cancer survivors and that mindfulness can be used to more effectively reduce their fatigue. It also suggests that health care professionals should be aware of factors such as anxiety, depression, pain, loneliness, and sleep disturbance in their care for fatigue of breast cancer survivors. TRIAL REGISTRATION: This study was registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN number. 000027720) on June 12, 2017.