Changes over time in self-efficacy to cope with cancer and well-being in women with breast cancer: a cross-cultural study.

OBJECTIVE: This study aimed to examine whether self-efficacy to cope with cancer changes over time in patients with breast cancer and whether these potential changes are similar across patients. It also aimed to examine whether these trajectories are related to patient psychological well-being and overall quality of life. METHODS: Participants (N = 404) from four countries (i.e. Finland, Israel, Italy, and Portugal) were enrolled in the study few weeks after breast surgery or biopsy. Self-efficacy to cope with cancer was assessed at baseline, six and 12 months later. Well-being indices were assessed at baseline, 12 and 18 months later. RESULTS: Using Latent Class Growth Analysis, two groups of patients were identified. The majority of patients reported high levels of self-efficacy to cope, which increased over time. For almost 15% of the patients, however, self-efficacy declined over time. Diminishing levels of self-efficacy to cope predicted worse levels of well-being. The pattern of self-efficacy changes and their relationships to well-being was consistent across countries. CONCLUSION: Monitoring self-efficacy to cope with cancer is probably important in order to detect alarming changes in its levels, as a declining self-efficacy to cope may serve as a signal of the need for intervention to prevent adaptation difficulties.

The mutual determination of self-efficacy to cope with cancer and cancer-related coping over time: a prospective study in women with breast cancer.

OBJECTIVE: The aim of this study was to examine the longitudinal impact of self-efficacy to cope with cancer on the cancer-related coping reactions of breast cancer patients and vice versa. DESIGN AND MAIN OUTCOMES MEASURES: Data from the BOUNCE Project (https://www.bounce-project.eu/) were used to address the hypotheses. Participants (N = 403) were enrolled in the study a few weeks after surgery or biopsy. Coping self-efficacy was assessed at baseline and six months later (M6). Cancer-related coping was assessed three (M3) and nine months (M9) after baseline. The analyses were performed using structural equation modeling with Mplus 8.6. RESULTS: Baseline coping self-efficacy predicted all M3 coping reactions, while M6 coping self-efficacy also predicted changes in all but one M9 coping reaction. Moreover, one of the M3 coping reactions, that is, hopelessness/helplessness, predicted the changes in M6 coping self-efficacy. The relation between coping self-efficacy and one coping reaction (i.e. cognitive avoidance) was rather weak. Stability paths from M3 to M9 coping reactions were moderate to high. CONCLUSION: The relationship between self-efficacy to cope with cancer and cancer-related coping is complex. New theoretical models are needed to more accurately describe the diverse aspects of this association.

The Interplay Between Trait Resilience and Coping Self-efficacy in Patients with Breast Cancer: An International Study.

The role of self-efficacy to cope with breast cancer as a mediator and/or moderator in the relationship of trait resilience to quality of life and psychological symptoms was examined in this study. Data from the BOUNCE Project ( https://www.bounce-project.eu/ ) were used. Women diagnosed with and in treatment for breast cancer (N = 484), from four countries, participated in the study. Trait resilience and coping self-efficacy were assessed at baseline (soon after the beginning of systemic treatment), and outcomes (quality of life, psychological symptoms) 3 months later. Hierarchical regression, mediation, moderation, and conditional (moderated) mediation and moderation analyses were performed to examine the study hypotheses. Coping self-efficacy mediated the impact of trait resilience. In addition, higher levels of resilience in combination with higher levels of coping self-efficacy were associated with better outcomes. Country of origin had no impact on these results. Overall, it seems that coping self-efficacy is a key factor that should be taken into account for research and intervention efforts in cancer.

Clinically driven design of multi-scale cancer models: the ContraCancrum project paradigm.

The challenge of modelling cancer presents a major opportunity to improve our ability to reduce mortality from malignant neoplasms, improve treatments and meet the demands associated with the individualization of care needs. This is the central motivation behind the ContraCancrum project. By developing integrated multi-scale cancer models, ContraCancrum is expected to contribute to the advancement of in silico oncology through the optimization of cancer treatment in the patient-individualized context by simulating the response to various therapeutic regimens. The aim of the present paper is to describe a novel paradigm for designing clinically driven multi-scale cancer modelling by bringing together basic science and information technology modules. In addition, the integration of the multi-scale tumour modelling components has led to novel concepts of personalized clinical decision support in the context of predictive oncology, as is also discussed in the paper. Since clinical adaptation is an inelastic prerequisite, a long-term clinical adaptation procedure of the models has been initiated for two tumour types, namely non-small cell lung cancer and glioblastoma multiforme; its current status is briefly summarized.

An advanced discrete state-discrete event multiscale simulation model of the response of a solid tumor to chemotherapy: Mimicking a clinical study.

In this paper an advanced, clinically oriented multiscale cancer model of breast tumor response to chemotherapy is presented. The paradigm of early breast cancer treated by epirubicin according to a branch of an actual clinical trial (the Trial of Principle, TOP trial) has been addressed. The model, stemming from previous work of the In Silico Oncology Group, National Technical University of Athens, is characterized by several crucial new features, such as the explicit distinction of proliferating cells into stem cells of infinite mitotic potential and cells of limited proliferative capacity, an advanced generic cytokinetic model and an improved tumor constitution initialization technique. A sensitivity analysis regarding critical parameters of the model has revealed their effect on the behavior of the biological system. The favorable outcome of an initial step towards the clinical adaptation and validation of the simulation model, based on the use of anonymized data from the TOP clinical trial, is presented and discussed. Two real clinical cases from the TOP trial with variable molecular profile have been simulated. A realistic time course of the tumor diameter and a reduction in tumor size in agreement with the clinical data has been achieved for both cases by selection of reasonable model parameter values, thus demonstrating a possible adaptation process of the model to real clinical trial data. Available imaging, histological, molecular and treatment data are exploited by the model in order to strengthen patient individualization modeling. The expected use of the model following thorough clinical adaptation, optimization and validation is to simulate either several candidate treatment schemes for a particular patient and support the selection of the optimal one or to simulate the expected extent of tumor shrinkage for a given time instant and decide on the adequacy or not of the simulated scheme.

'In silico' oncology for clinical decision making in the context of nephroblastoma.

The present paper outlines the initial version of the ACGT (Advancing Clinico-Genomic Trials) -- an Integrated Project, partly funded by the EC (FP6-2005-IST-026996)I-Oncosimulator as an integrated software system simulating in vivo tumour response to therapeutic modalities within the clinical trials environment aiming to support clinical decision making in individual patients. Cancer treatment optimization is the main goal of the system. The document refers to the technology of the system and the clinical requirements and the types of medical data needed for exploitation in the case of nephroblastoma. The outcome of an initial step towards the clinical adaptation and validation of the system is presented and discussed. Use of anonymized real data before and after chemotherapeutic treatment for the case of the SIOP 2001/GPOH nephroblastoma clinical trial constitutes the basis of the clinical adaptation and validation process. By using real medical data concerning nephroblastoma for a single patient in conjunction with plausible values for the model parameters (based on available literature) a reasonable prediction of the actual tumour volume shrinkage has been made possible. Obviously as more and more sets of medical data are exploited the reliability of the model "tuning" is expected to increase. The successful performance of the initial combined ACGT Oncosimulator platform, although usable up to now only as a test of principle, has been a particularly encouraging step towards the clinical translation of the system, being the first of its kind worldwide.