Paula Poikonen-Saksela

Due to the growing amount of breast cancer survivors we must understand their long-term quality of life (QoL) better. Many breast cancer survivors suffer for years from lower functioning capacity and several symptoms, but outcomes regarding their global Quality of Life (gQoL) are less clear. The current study explored the links between functions, symptoms, and gQoL using a network design. We used data from 364 women who had completed adjuvant chemotherapy or started adjuvant endocrine therapy. QoL, symptomatology and functioning were measured by the EORTC QLQ‐C30 and BR‐23 questionnaires, and depression by the Finnish version of Beck’s 13‐item depression scale. The multivariate inter-dependence between the symptom scales and gQoL was analyzed via regularized partial correlation networks (graphical LASSO). These networks identify associations, not directionality or causality. Our aim was to explore how the functions and symptoms associate with each other and with gQoL during ten-year follow-up, and to identify the most important scales in the network using centrality analysis. The results showed that three key areas—fatigue and physical functioning, emotional functioning and depression, and social and role functioning—emerged as most central to gQoL across all time points. Interventions targeting these areas may therefore have the greatest potential to improve long-term QoL in breast cancer survivors.

Background/Objectives: Patients with breast cancer show substantial heterogeneity in terms of psychological adjustment following diagnosis. We aimed to characterize longitudinal trajectories of quality of life (QoL) and depressive symptoms during the first 18 months post-diagnosis and to identify robust clinical, psychosocial, and behavioral predictors associated with distinct adjustment pathways. Methods: Women (N = 538; mean age 55.4 years; range 40–70) with operable breast cancer (stages I–III) were drawn from the multicenter BOUNCE cohort. QoL (Global Health Status/QoL scale of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30) and depressive symptoms (depression subscale of the Hospital Anxiety and Depression Scale) were assessed at baseline and months 3, 6, 9, 12, 15 and 18. Latent class growth analysis and growth mixture modeling identified distinct trajectory classes. Associations between early predictors and trajectory membership were examined using logistic regression combined with elastic net regularization. Results: Depression trajectories demonstrated heterogeneity, with groups characterized by persistent resilience (59.7%), stable moderate/high (25.3%), delayed onset (5.0%), and recovery (10.0%). QoL trajectories ranged from stable excellent (13.2%) and stable high (40.7%) to moderate (31.4%) and persistent low/deteriorating (6.9%), as well as a distinct recovering trajectory (7.8%). Trajectory differentiation was primarily driven by psychological resources, symptom burden, functional status, and coping processes, alongside specific contributions from clinical factors. Conclusions: Distinct subgroups of women with breast cancer follow divergent adjustment pathways. These findings highlight the multidimensional nature of resilience and support the need for tailored interventions that promote long-term well-being beyond simple risk reduction.

The fear of cancer recurrence (FCR) is one of the most frequently expressed concerns among breast cancer (BC) survivors. This study explored profiles of FCR and adaptation indicators, centring on body image and ‘bouncing back’, 18 months post‐diagnosis. It also examined psycho‐social predictors for profiles. The study sample comprised 494 women from Finland, Italy, Portugal, and Israel, diagnosed with Stage I–III BC. Participants' ages ranged from 40 to 70 years ( M = 54.92, SD = 8.22) and were assessed at diagnosis and after 3 and 18 months. Participants completed self‐report questionnaires, including Fear of Cancer Recurrence Inventory‐Short Form, Body Image Subscale‐ from the quality‐of‐life questionnaire‐ BC module, Bounce Back single self‐report item, Hospital Anxiety and Depression Scale, modified Medical Outcomes Study Social Support Survey along with medical–social–demographic data. Three profiles of FCR and adaptation indicators were identified: (1) the Adaptive Profile (67% of the sample), indicated relatively low levels of FCR and higher levels of body image and bounce back; (2) the Distressed Profile (19%), marked by higher FCR compared to the other profiles, moderate body image and bouncing back; and (3) the Body Image Impairment Profile (14%), with participants reporting the lowest body image levels relative to the other two profiles. Depression levels 3 months post‐diagnosis predicted more challenged coping FCR profiles. This study identifies distinct patterns of FCR and adaptation during the initial phase of BC survivorship. While most women adjust well, a considerable portion continue to face challenges. Among women experiencing elevated depressive symptoms early in the disease, these difficulties may be further compounded, highlighting the importance of early screening and timely preventive intervention.

Introduction: Women with breast cancer experience psychological distress, and resilience-strengthening psychosocial support may improve their quality of life (QoL). Identifying those at risk of low QoL is challenging. This study evaluated the cost-effectiveness of a machine learning-based QoL predictor to support clinical decision-making regarding psychosocial support (sample size: 660). Methods: A decision tree cost–utility model was developed to compare four decision-making strategies in offering psychosocial support: the clinician alone, the QoL predictor alone, the clinician supported by the predictor, and no prediction with no psychosocial support. QoL after one year was used as a proxy for resilience. Costs, health outcomes, and net monetary benefits (NMBs) were estimated using a one-year time horizon. Incremental cost-effectiveness ratios (ICERs) were calculated and dominance assessed. A societal scenario analysis incorporated productivity losses. A probabilistic sensitivity analysis generated cost-effectiveness acceptability curves. Results: Clinicians supported by the QoL predictor produced the highest NMB (EUR 16,349) and the greatest quality-adjusted life year (QALY) gain (0.759), with an ICER of EUR 22,892 compared with the next least costly strategy. Clinician-only prediction and predictor-only approaches were dominated or extendedly dominated. Under the societal perspective, all strategies produced negative NMB values due to productivity losses, but the overall ranking remained unchanged. The probabilistic sensitivity analysis showed that the combined clinician and predictor strategy had a 69% probability of being cost-effective at a willingness to pay threshold of EUR 30,000. Conclusions: Combining clinician judgement with the machine learning-based QoL predictor improved the targeting of psychosocial support and was the most cost-effective strategy. Further prospective and comparative studies are needed to confirm its long-term effectiveness and cost-effectiveness in clinical practice.

Background/Objectives: Patients with breast cancer show substantial heterogeneity in psychological adjustment following diagnosis. We aim to characterize longitudinal trajectories of quality of life (QoL) and depressive symptoms during the first 18 months post-diagnosis and to identify robust clinical, psychosocial, and behavioral predictors associated with distinct adjustment pathways. Methods: Data were drawn from the multicenter BOUNCE cohort. QoL (EORTC QLQ-C30) and depressive symptoms (HADS) were assessed repeatedly over 18 months. Latent Class Growth Analysis and Growth Mixture Modeling were used to identify distinct trajectory classes. Associations between candidate predictors and trajectory membership were ex-amined using logistic regression combined with elastic net regularization, including clinically motivated binary contrasts. Predictor robustness was evaluated under models with clinical site alternatively penalized and unpenalized. Results: Depression trajectories demonstrated heterogeneity, with groups characterized by persistent resilience (59.7%), stable moderate/high depression (25.3%), delayed-onset de-pression (5.0%), and recovery (10.0%). QoL trajectories ranged from stable excellent (13.2%) and stable high (13.2%) functioning to persistent low or deteriorating QoL (6.9%), with a distinct recovery trajectory (7.8%). Trajectory differentiation was primarily driven by psychological resources, symptom burden, functional status, and coping processes, while selected clinical factors contributed to specific trajectories. Patterns of predictors dif-fered across trajectory contrasts. Conclusions: Distinct subgroups of women with breast cancer follow divergent QoL and depres-sion trajectories after diagnosis. Differences between trajectories are shaped by a combination of psychological, functional, and clinical factors, highlighting the multidimensional nature of resilience and recovery. These findings support the need for tailored interven-tions that move beyond risk reduction toward promoting long-term well-being and mental health.

Background: An increasing number of early-stage breast cancer (EBC) survivors and limited health care resources have raised interest in developing digital methods for communication between patients and health care personnel. In 2015, Helsinki University Hospital (HUS) Comprehensive Cancer Center (CCC) launched a digital solution called Noona (Helsinki University Hospital; Noona Healthcare) for patients with cancer, which allows patients to report their symptoms or side effects and ask questions with a computer or smart mobile device. Objective: In this study, we compare the cost and contacts of surveillance of EBC by 2 follow-up methods: digital solution and phone calls during their first year of follow-up outside preplanned visits. Methods: This was a prospective, open-label, randomized crossover study. After postoperative radiotherapy, patients with EBC were randomized to surveillance with either a digital solution or phone calls in addition to routine follow-up visits. After 6 months, the patient switched to the alternative follow-up method. All patients were thus exposed to both follow-up methods, and the order was determined by randomization. Hospital contacts and the costs of specialized health care were extracted from the Ecomed database of the Helsinki and Uusimaa Hospital District. The Ecomed database records all hospital costs. The costs of follow-up visits and diagnostics at the HUS CCC were analyzed in a repeated measurements general linear model analysis. Results: The study extended from July 2015 to January 2017. Of 765 patients, 734 were included in the final analyses. For the digital solution group, the mean number of contacts per patient was 1.06 (SD 1.57) during the first 6-month period and 1.22 (SD 1.04) in the second period, with associated costs of €269 (US $313.21) and €311 (US $362.11). Similarly, in the phone call group, the mean number of contacts increased from 0.95 (SD 1.39) to 1.24 (SD 1.14) with the costs of €236 (US $274.78) and €344 (US $400.53), respectively. There were no statistically significant differences in the number of outpatient contacts (P=.46 and P=.35) or total costs (P=.80 and P=.12) between the 2 follow-up methods or randomization groups. Conclusions: We did not find any statistically significant differences in the total cost of follow-up of EBC by digital solution or phone calls. The number of visits and costs were higher during the latter follow-up period, probably due to the scheduled routine 1-year visit. There were more visits and higher costs in the digital solution group during the first 6 months, but these were higher in the phone call group during the latter 6-month period. This shows that the digital solution may enable faster access to outpatient services than conventional follow-up.

The present study aimed to identify profiles of women diagnosed with breast cancer 18 months postdiagnosis based on a combination of risk and protective factors. Additionally, the study aimed to examine various potential early predictors at 3 and 6 months postdiagnosis to determine their association with the identified profiles at 18 months postdiagnosis. The sample of the study consisted of 499 women with breast cancer from four oncology centers located in Finland, Portugal, Italy, and Israel. Women completed self-report questionnaires at three time points postdiagnosis: 3, 6, and 18 months. The measures utilized included the Hospital Anxiety and Depression Scale, the Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, fifth edition, the Distress Thermometer, a single item assessing self-efficacy, the Positive and Negative Affect Schedule, a single item of bounce-back ability, and the Posttraumatic Growth Inventory. Four profiles were identified: Resilience, High distress, Moderate distress, and Bouncing back coupled with distress. The primary predictors across all profiles were anxiety and depression, followed by posttraumatic growth, posttraumatic stress, self-efficacy, and bounce-back ability. This study highlighted that the challenges associated with breast cancer begin at the time of diagnosis and persist beyond the completion of treatment. Early provision of psychosocial support may facilitate improved positive adjustment 18 months postdiagnosis. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

The current observational study aimed to examine the relationship between mindfulness and posttraumatic growth (PTG) among patients with breast cancer. Additionally, it explores the mediating role of illness perceptions and positive emotions. A total of 697 women with breast cancer were recruited from four clinical sites as part of the Bounce project in Finland, Portugal, Italy, and Israel. The study measures were mindfulness (MAAS), illness perceptions (IPQ), positive affect (PANAS), and post-traumatic growth (PTGI) at three time points: near the time of diagnosis, 6 months, and 12 months post-diagnosis. A higher level of mindfulness was associated with perceptions of the illness as less chronic. Specifically, the perception of a limited timeline of breast cancer was associated with positive emotions, thus leading to enhanced PTG. Emphasis should be placed on promoting mindfulness, elaborating on illness perceptions, and maintaining positive affect as part of clinical interventions for PTG among breast cancer patients.

Background. Despite excellent prognosis of early breast cancer, the patients face problems related to decreased quality of life and mental health. There is a need for easily available interventions targeting modifiable factors related to these problems. The aim of this study was to test the use of a new digital supportive intervention platform for early breast cancer patients. Material and Methods. Ninety‐seven early breast cancer patients answered questions on wellbeing, exercise, and sociodemographic factors before systemic adjuvant treatment at the Helsinki University Hospital. Based on these answers and predictive algorithms for anxiety and depression, they were guided onto one or several digital intervention paths. Patients under 56 years of age were guided onto a nutrition path, those who exercised less than the current guideline recommendations onto an exercise path, and those at risk of mental health deterioration onto an empowerment path. Information on compliance was collected at 3 months on the amount of exercise and quality of life using EORTC‐C30 scale, anxiety and depression using HADS scale at baseline and 12 months, and log‐in information at 3 and 12 months. Results. Thirty‐two patients followed the empowerment path, 43 the nutrition path, and 75 the exercise path. On a scale of 1–5, most of the participants (mean = 3.4; SD 0.815) found the interventions helpful and would have recommended testing and supportive interventions to their peers (mean = 3.70; SD 0.961). During the 10‐week intervention period, the mean number of log‐ins to the empowerment path was 3.69 (SD = 4.24); the nutrition path, 4.32 (SD = 2.891); and the exercise path, 8.33 (SD = 6.293). The higher number of log‐ins to the empowerment (rho = 0.531, P = 0.008, and n = 24) and exercise paths (rho = 0.330, P = 0.01, and n = 59) was related to better global quality of life at one year. The number of log‐ins correlated to the weekly amount of exercise in the exercise path (cc 0.740, P value n = 20). Conclusion. Patients’ attitudes towards the interventions were positive, but they used them far less than was recommended. A randomized trial would be needed to test the effect of interventions on patients’ QoL and mental health.