Patient resilience and distress level prior to chemotherapy based on time estimation.

e24184 Background: Our prospective and multicentric study aimed to determine if the effects of breast cancer patients' resilience on their distress levels are mediated by the assessment of time before initiating neo/adjuvant chemotherapy. Methods: In 104 chemo-naive breast cancer patients, time estimation was evaluated by comparing each subject's prospective estimate of how rapidly one minute passed to the actual time. The Distress Thermometer of the National Comprehensive Cancer Network was used. The range of the scale is from 0 (no distress) to 10 (extreme distress). The Connor-Davidson Resilience Questionnaire (CD-RISC), a self-reported 10-item unidimensional scale, was utilized to measure resilience. Respondents rate statements on a 5-point Likert scale ranging from 0 (not true at all) to 4 (true nearly all the time). A higher score reflects greater resilience. Based on their RISC scores, patients were divided into three groups: low (up to the 33 rd percentile), intermediate (between the 33 rd and the 66 th percentile), and high (over the 66 th percentile). Patients' time estimations were similarly divided. Cronbach's α was 0.87 for all 10 items. Results: The mean age of the patients was 53.1±12.4 years. RISC scores correlated positively with time estimation (rho = 0.31, p = 0.002) and negatively with distress levels (rho = -0.445, p < 0.001). A significant negative correlation was observed between time estimation and distress levels (rho = -0.394, p < 0.001). Correspondence analysis revealed a significant association across the three matching groups of RISC score and time estimation (χ 2 = 9.8, p = 0.044). The Jonckheere-Terpstra test revealed that patient estimates of time varied significantly between the three groups (p = 0.013). Using Hayes simple regression, we discovered that RISC scores were a significantly positive predictor of time estimation (b = 0.844, s.e. = 0.261, p < 0.0001). Both RISC score (b = -0.136, s.e. = 0.031, p < 0.0001) and time estimation (b = -0.041, s.e. = 0.011, p = 0.0005) were significant negative predictors for higher distress levels in the second regression. Conclusions: Via time estimation, patients' resilience influences distress levels prior to treatment initiation.