Development and Validation of a Predictive Model of Severe Fatigue After Breast Cancer Diagnosis: Toward a Personalized Framework in Survivorship Care

Artificial intelligence in oncology: ensuring safe and effective integration of language models in clinical practice

In this Personal View, we address the latest advancements in automatic text analysis with artificial intelligence (AI) in medicine, with a focus on its implications in aiding treatment decisions in medical oncology. Acknowledging that a majority of hospital medical content is embedded in narrative format, natural language processing has become one of the most dynamic research fields for developing clinical decision support tools. In addition, large language models have recently reached unprecedented performance, notably when answering medical questions. Emerging applications include prognosis estimation, treatment recommendations, multidisciplinary tumor board recommendations and matching patients to recruiting clinical trials. Altogether, we advocate for a forward-looking approach in which the community efficiently initiates global prospective clinical evaluations of promising AI-based decision support systems. Such assessments will be essential to validate and evaluate potential biases, ensuring these innovations can be effectively and safely translated into practical tools for oncological practice. We are at a pivotal moment, where continued advancements in patient care must be pursued with scientific rigor.

Development and validation of machine learning models for predicting cancer-related fatigue in lymphoma survivors

BACKGROUND

New cases of lymphoma are rising, and the symptom burden, like cancer-related fatigue (CRF), severely impacts the quality of life of lymphoma survivors. However, clinical diagnosis and treatment of CRF are inadequate and require enhancement.

OBJECTIVE

The main objective of this study is to construct machine learning-based CRF prediction models for lymphoma survivors to help healthcare professionals accurately identify the CRF population and better personalize treatment and care for patients.

METHODS

A cross-sectional study in China recruited lymphoma patients from June 2023 to March 2024, dividing them into two datasets for model construction and external validation. Six machine learning algorithms were used in this study: Logistic Regression (LR), Random Forest, Single Hidden Layer Neural Network, Support Vector Machine, eXtreme Gradient Boosting, and Light Gradient Boosting Machine (LightGBM). Performance metrics like the area under the receiver operating characteristic (AUROC) and calibration curves were compared. The clinical applicability was assessed by decision curve, and Shapley additive explanations was employed to explain variable significance.

RESULTS

CRF incidence was 40.7 % (dataset I) and 44.8 % (dataset II). LightGBM showed strong performance in training and internal validation. LR excelled in external validation with the highest AUROC and best calibration. Pain, total protein, physical function, and sleep disturbance were important predictors of CRF.

CONCLUSION

The study presents a machine learning-based CRF prediction model for lymphoma patients, offering dynamic, data-driven assessments that could enhance the development of automated CRF screening tools for personalized management in clinical practice.

Evaluating the Implementation of Integrated Proactive Supportive Care Pathways in Oncology: Master Protocol for a Cohort Study

BACKGROUND

Supportive care (SC) refers to the prevention and management of complications of cancer and its treatment. While it has long been recognized as an important cancer care delivery component, a high proportion of patients face unaddressed SC needs, calling for innovative approaches to deliver SC.

OBJECTIVE

The objective of this master protocol is to evaluate the implementation of different integrated proactive SC pathways across the cancer care continuum in our institution (Gustave Roussy, Villejuif, France). Pathways studied in this master protocol may occur shortly after diagnosis to prevent treatment-related burden; during treatment to monitor the onset of toxicities and provide timely symptom management; and after treatment to improve rehabilitation, self-management skills, and social reintegration.

METHODS

This study is guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework. The primary objective is to evaluate the impact of SC pathways on patients' distress and unmet needs after 12 weeks, measured by the National Comprehensive Cancer Network's Distress Thermometer and Problem List. Secondary objectives will focus on the pathways (macrolevel) and each SC intervention (microlevel), evaluating their reach (administrative data review of the absolute number and proportion of clinical and sociodemographic characteristics of patients included in the pathways); short-term and long-term efficacy through their impact on quality of life (EQ-5D-5L and the 30-item European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire) and symptom burden (MD Anderson Symptom Inventory, Hospital Anxiety and Depression Scale, Insomnia Severity Index, and 22-item European Organization for Research and Treatment of Cancer Sexual Health Questionnaire); adoption by patients and providers (administrative data review of SC referrals and attendance or use of SC strategies); barriers to and leverage for implementation (surveys and focus groups with patients, providers, and the hospital organization); and maintenance (cost-consequence analysis). Pilot evaluations with a minimum of 70 patients per pathway will be performed to generate mean Distress Thermometer scores and SDs informing the calculation of formal sample size needed for efficacy evaluation (cohorts will be enriched accordingly).

RESULTS

The study was approved by the ethics committee, and as of February 2024, a total of 12 patients were enrolled.

CONCLUSIONS

This study will contribute toward innovative models of SC delivery and will inform the implementation of integrated SC pathways of care.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06479057; https://clinicaltrials.gov/study/NCT06479057.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/52841.

Multidisciplinary analysis of cancer-related fatigue at the time of diagnosis: preliminary results of the BIOCARE FActory cohort

PURPOSE

Cancer-related fatigue (CRF) is a common side effect of cancer and cancer treatment that significantly impairs the quality of life and can persist for years after treatment completion. Although fatigue is often associated with cancer treatment, it is also a result of the disease itself, even before intervention. CRF at the time of diagnosis may affect treatment timing or completion and is a consistent predictor of post-treatment fatigue at any time. The mechanisms underlying CRF are multidimensional and not well understood, particularly at the time of diagnosis.

METHODS

Sixty-five breast cancer patients at the time of diagnosis were included. The participants completed self-assessment questionnaires about CRF, sleep disturbances, and emotional symptoms and wore an accelerometer to assess levels of spontaneous physical activity and sleep quality. During the experimental session, the participants underwent cognitive, neuromuscular, and exercise metabolism evaluations.

RESULTS

Using augmented backward elimination regression, this study found that emotional symptoms and perceived sleep disturbances were the strongest predictors of CRF (adjusted r2 = 0.51). Neuromuscular fatigability and sleep disturbance were also associated with physical dimensions, whereas cognitive performance was associated with cognitive dimensions.

CONCLUSION

At the time of diagnosis, emotional and cognitive dimensions are over-represented compared to the general population, and specific subdimensions have specific predictors that support the idea of distinct mechanisms. Evaluating CRF subdimensions and their potential mechanisms at the time of diagnosis would be particularly relevant for identifying high-risk patients and offering them appropriate interventions.

TRIAL REGISTRATION

This study was registered at ClinicalTrials.gov (NCT04391543) in May, 2020.

Development and validation of a nomogram for predicting sever cancer-related fatigue in patients with cervical cancer

OBJECTIVE

Cancer-related fatigue (CRF) has been considered the biggest influencing factor for cancer patients after surgery. This study aimed to develop and validate a nomogram for severe cancer-related fatigue (CRF) patients with cervical cancer (CC).

METHODS

A cross-sectional study was conducted to develop and validate a nomogram (building set = 196; validation set = 88) in the Department of Obstetrics and Gynecology of a Class III hospital in Shenyang, Liaoning Province. We adopted the questionnaire method, including the Cancer Fatigue Scale (CFS), Medical Uncertainty in Illness Scale (MUIS), Medical Coping Modes Questionnaire (MCMQ), Multidimensional Scale of Perceived Social Support (MSPSS), and Sense of Coherence-13 (SOC-13). Binary logistic regression was used to test the risk factors of CRF. The R4.1.2 software was used to develop and validate the nomogram, including Bootstrap resampling method, the ability of Area Under Curve (AUC), Concordance Index (C-Index), Hosmer Lemeshow goodness of fit test, Receiver Operating Characteristic (ROC) curve, Calibration calibration curve, and Decision Curve Analysis curve (DCA).

RESULTS

The regression equation was Logit(P) = 1.276-0.947 Monthly income + 0.989 Long-term passive smoking - 0.952 Physical exercise + 1.512 Diagnosis type + 1.040 Coping style - 0.726 Perceived Social Support - 2.350 Sense of Coherence. The C-Index of the nomogram was 0.921 (95% CI: 0.877∼0.958). The ROC curve showed the sensitivity of the nomogram was 0.821, the specificity was 0.900, and the accuracy was 0.857. AUC was 0.916 (95% CI: 0.876∼0.957). The calibration showed that the predicted probability of the nomogram fitted well with the actual probability. The DCA curve showed when the prediction probability was greater than about 10%, the benefit of the nomogram was positive. The results in the validation group were similar.

CONCLUSION

This nomogram had good identifiability, accuracy and clinical practicality, and could be used as a prediction and evaluation tool for severe cases of clinical patients with CC.

Predictive Models of Psychological Distress, Quality of Life, and Adherence to Medication in Breast Cancer Patients: A Scoping Review

Purpose

An interplay of clinical and psychosocial variables affects breast cancer patients' experiences and clinical trajectories. Several studies investigated the role of socio-demographic, clinical, and psychosocial factors in predicting relevant outcomes in breast cancer care, thus developing predictive models. Our aim is to summarize predictive models for specific psychological and behavioral outcomes: psychological distress, quality of life, and medication adherence. Specifically, we aim to map the determinants of the outcomes of interest, offering a thorough overview of these models.

Methods

Databases (PubMed, Scopus, Embase) have been searched to identify studies meeting the inclusion criteria: a breast cancer patients' sample, development/validation of a predictive model for selected psychological/behavioral outcomes (ie, psychological distress, quality of life, and medication adherence), and availability of English full-text.

Results

Twenty-one papers describing predictive models for psychological distress, quality of life, and adherence to medication in breast cancer were included. The models were developed using different statistical approaches. It has been shown that treatment-related factors (eg, side-effects, type of surgery or treatment received), socio-demographic (eg, younger age, lower income, and inactive occupational status), clinical (eg, advanced stage of disease, comorbidities, physical symptoms such as fatigue, insomnia, and pain) and psychological variables (eg, anxiety, depression, body image dissatisfaction) might predict poorer outcomes.

Conclusion

Predictive models of distress, quality of life, and adherence, although heterogeneous, showed good predictive values, as indicated by the reported performance measures and metrics. Many of the predictors are easily available in patients' health records, whereas others (eg, coping strategies, perceived social support, illness perceptions) might be introduced in routine assessment practices. The possibility to assess such factors is a relevant resource for clinicians and researchers involved in developing and implementing psychological interventions for breast cancer patients.

A qualitative study on the healthcare experiences of adolescents and young adults (AYA) with an uncertain or poor cancer prognosis

PURPOSE

Treatment advancements have improved life expectancy for adolescents and young adults (AYAs) with an uncertain and/or poor cancer prognosis (UPCP) and change clinical practice. This improved survival requires a different approach and specific expertise to meet the needs of this group. The aim of this study is to explore the health care experiences of AYAs with a UPCP.

METHODS

We conducted a multicenter qualitative study using semi-structured interviews and elements of the grounded theory by Corbin and Strauss.

RESULTS

Interviews were conducted with 46 AYAs with a UPCP. They were on average 33.4 years old (age range 23-44), and most of them were woman (63%). Additionally, five AYAs with a UPCP participated as AYA research partners in two focus groups. They were on average 31.8 years old and four of them were woman. AYAs with a UPCP reported four pillars for a satisfied healthcare experience: (1) trust, (2) tailored communication, (3) holistic empathic open attitude, and (4) care being offered (pro-)actively. They reported both optimal and suboptimal experiences about distrust based on a delay in diagnostic trajectory, lack of tailored communication and discussion of sensitive topics, preference for a holistic approach, and struggles with finding the way to get additional healthcare support.

CONCLUSION

For AYAs with a UPCP, it is important that both age-specific issues and issues related to the UPCP are understood and addressed; however, this seems not yet optimally implemented in clinical practice. This emphasizes the importance of providing this patient group with tailored care incorporating both aspects. Healthcare professionals need to be supported with training and tools to understand the healthcare needs of AYAs with a UPCP. AYAs can be empowered to take more control over their own healthcare needs.

Chemotherapy-Related Amenorrhea and Quality of Life Among Premenopausal Women With Breast Cancer

Importance

Younger survivors of breast cancer frequently report more treatment-related symptoms, mostly related to the menopausal transition.

Objective

To assess factors associated with chemotherapy-related amenorrhea (CRA) and to evaluate its association with long-term quality of life (QOL).

Design, Setting, and Participants

The prospective, longitudinal Cancer Toxicities Study, a multicenter French cohort study, includes women with a diagnosis of stage I to III breast cancer and collects data approximately yearly after diagnosis. The current study reports outcomes up to 4 years after diagnosis for participants enrolled from 2012 to 2017. Participants included premenopausal women younger than 50 years treated with chemotherapy and not receiving adjuvant ovarian function suppression. Data analysis was performed from September 2021 to June 2023.

Exposures

Clinical, socioeconomic, tumor, and treatment characteristics assessed at diagnosis (for the analysis of factors associated with CRA) and persistent CRA (for the QOL analysis).

Main Outcomes and Measures

The main outcome of interest was CRA at year 1 (Y1), year 2 (Y2), and year 4 (Y4) after diagnosis. Generalized estimating equations assessed associations of exposure variables with CRA. In the QOL analysis, QOL at Y4 (assessed with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaires C30 and BR23) was the outcome of interest. Multivariable random-effect mixed models assessed the association of persistent CRA (ie, never recovering menses after treatment) with QOL.

Results

Among 1636 women, the mean (SD) age at diagnosis was 42.2 (5.6) years. Overall, 1242 of 1497 women (83.0%) reported CRA at Y1, 959 of 1323 women (72.5%) reported it at Y2, and 599 of 906 women (66.1%) reported it at Y4. Older age vs 18 to 34 years (adjusted odds ratio [OR] for 35 to 39 years, 1.84 [95% CI, 1.32 to 2.56]; adjusted OR for 40 to 44 years, 5.90 [95% CI, 4.23 to 8.24]; and adjusted OR for ≥45 years, 21.29 [95% CI, 14.34 to 31.61]) and receipt of adjuvant tamoxifen (adjusted OR, 1.97 [95% CI, 1.53 to 2.53]) were associated with higher likelihood of CRA. In the QOL analysis, 416 of 729 women (57.1%) had persistent CRA. However, late menses recovery among women aged 18 to 34 years with no menses at Y2 were reported by 11 of 21 women (52.4%) between Y2 and Y4. Persistent CRA was associated with worse insomnia (mean difference vs recovery at any time, 9.9 points [95% CI, 3.2 to 16.5 points]; P = .004), systemic therapy-related adverse effects (mean difference, 3.0 points [95% CI, 0.2 to 5.8 points]; P = .04), and sexual functioning (mean difference, -9.2 points [95% CI, -14.3 to -4.1 points]; P < .001) at Y4.

Conclusions and Relevance

In this cohort study of premenopausal women with breast cancer, persistent CRA was common, although some women recovered menses late, and was associated with worse long-term QOL. This study can help inform risk communication, personalized counseling, and early supportive care referrals for such patients.

(Pre)treatment risk factors for late fatigue and fatigue trajectories following radiotherapy for breast cancer

Fatigue is common in breast-cancer survivors. Our study assessed fatigue longitudinally in breast cancer patients receiving adjuvant radiotherapy (RT) and aimed to identify risk factors associated with long-term fatigue and underlying fatigue trajectories. Fatigue was measured in a prospective multicenter cohort (REQUITE) using the Multidimensional Fatigue Inventory (MFI-20) and analyzed using mixed models. Multivariable logistic models identified factors associated with fatigue dimensions at 2 years post-RT and latent class growth analysis identified individual fatigue trajectories. A total of 1443, 1302, 1203 and 1098 patients completed the MFI-20 at baseline, end of RT, after 1 and 2 years. Overall, levels of fatigue significantly increased from baseline to end of RT for all fatigue dimensions (P < .05) and returned to baseline levels after 2 years. A quarter of patients were assigned to latent trajectory high (23.7%) and moderate (24.8%) fatigue classes, while 46.3% and 5.2% to the low and decreasing fatigue classes, respectively. Factors associated with multiple fatigue dimensions at 2 years include age, BMI, global health status, insomnia, pain, dyspnea and depression. Fatigue present at baseline was consistently associated with all five MFI-20 fatigue dimensions (ORGeneralFatigue  = 3.81, P < .001). From latent trajectory analysis, patients with a combination of factors such as pain, insomnia, depression, younger age and endocrine therapy had a particularly high risk of developing early and persistent high fatigue years after treatment. Our results confirmed the multidimensional nature of fatigue and will help clinicians identify breast cancer patients at higher risk of having persistent/late fatigue so that tailored interventions can be delivered.

Mitigating long-term and delayed adverse events associated with cancer treatment: implications for survivorship

Despite the importance of chemotherapy-associated adverse events in oncology practice and the broad range of interventions available to mitigate them, limited systematic efforts have been made to identify, critically appraise and summarize the totality of evidence on the effectiveness of these interventions. Herein, we review the most common long-term (continued beyond treatment) and late or delayed (following treatment) adverse events associated with chemotherapy and other anticancer treatments that pose major threats in terms of survival, quality of life and continuation of optimal therapy. These adverse effects often emerge during and continue beyond the course of therapy or arise among survivors in the months and years following treatment. For each of these adverse effects, we discuss and critically evaluate their underlying biological mechanisms, the most commonly used pharmacological and non-pharmacological treatment strategies, and evidence-based clinical practice guidelines for their appropriate management. Furthermore, we discuss risk factors and validated risk-assessment tools for identifying patients most likely to be harmed by chemotherapy and potentially benefit from effective interventions. Finally, we highlight promising emerging supportive-care opportunities for the ever-increasing number of cancer survivors at continuing risk of adverse treatment effects.

Association between high body mass index and prognosis of patients with early-stage breast cancer: A systematic review and meta-analysis

Background

A high body mass index (BMI) can indicate overweight or obesity and is a crucial risk factor for breast cancer survivors. However, the association between high BMI and prognosis in early-stage breast cancer (EBC) remains unclear. We aimed to assess the effects of high BMI on the prognosis of patients with EBC.

Methods

The PubMed, Embase, and Cochrane Library databases and proceedings of major oncological conferences related to the effects of BMI on the prognosis of breast cancer were searched up to November 2021. Fixed- and random-effects models were used for meta-analyses. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) for disease-free survival (DFS) and overall survival (OS) were extracted from the included literature.

Results

Twenty retrospective cohort studies with 33,836 patients with EBC were included. Overweight patients had worse DFS (HR: 1.16, 95% CI: 1.05-1.27, P = 0.002) and OS (HR: 1.20; 95% CI: 1.09-1.33, P < 0.001). Obesity also had adverse effects on DFS (HR: 1.17, 95% CI: 1.07-1.29, P = 0.001) and OS (HR: 1.30, 95% CI: 1.17-1.45, P < 0.001). Likewise, patients with high BMI had worse DFS (HR: 1.16, 95% CI: 1.08-1.26, P < 0.001) and OS (HR: 1.25, 95% CI: 1.14-1.39, P < 0.001). In subgroup analyses, overweight had adverse effects on DFS (HR: 1.11, 95% CI: 1.04-1.18, P = 0.001) and OS (HR: 1.18, 95% CI: 1.11-1.26, P < 0.001) in multivariate analyses, whereas the relationship that overweight had negative effects on DFS (HR: 1.21, 95% CI: 0.99-1.48, P = 0.058) and OS (HR: 1.39, 95% CI: 0.92-2.10, P = 0.123) was not statistically significant in univariate analysis. By contrast, obesity had adverse effects on DFS (HR: 1.21, 95% CI: 1.06-1.38, P = 0.004 and HR: 1.14, 95% CI: 1.08-1.22, P < 0.001) and OS (HR: 1.33, 95% CI: 1.15-1.54, P < 0.001 and HR: 1.23, 95% CI: 1.15-1.31, P < 0.001) in univariate and multivariate analyses, respectively.

Conclusions

Compared with normal weight, increased body weight (overweight, obesity, and high BMI) led to worse DFS and OS in patients with EBC. Once validated, these results should be considered in the development of prevention programs.

[Latest Findings in Key Research Areas of Precision Nursing for Chronic Diseases in Older Adults]

The advent of the era of biomedical big data has helped promote the development of precision nursing. Precision nursing for chronic diseases in older adults is an interdisciplinary research field in which accurate individualized data are utilized to carry out early screening and health management of older adult populations at high risk for chronic diseases and early intervention of diseases, which plays an important role in improving the prognosis of diseases and the health level of the older adult population. Herein, we introduced the concept of precision nursing, and discussed the latest research findings in the key areas of precision nursing for chronic diseases in older adults, including precision symptom management in cancer patients and precision nursing in older patients with multimorbidity. At present, research concerning precise symptom management of cancer patients is mainly focused on prediction modelling for risks of symptoms, longitudinal change trajectories, core symptom identification, etc. Investigations in the precise nursing of cancer patients are conducted in the following areas, risk prediction, the timing of interventions, and intervention targets. Research on precision nursing for multimorbidity is mainly focused on assessment of chronic disease multimorbidity, multimorbidity pattern recognition, and health management of multimorbidity. We also discussed potential opportunities and challenges of precision nursing in the future, in order to provide a scientific basis for the improving the practice and theories of precision nursing. In the future, precision nursing will play an ever more important role in uncovering pathogenic information, the diagnosis and treatment of diseases, the health of the research population, and the promotion of medical research.

Objective, Clinician- and Patient-Reported Evaluation of Late Toxicity Following Adjuvant Radiation for Early Breast Cancer: Long-Term Follow-Up Results of a Randomised Series

Background and Purpose: This study aimed to differentially assess the frequency and severity of late radiation-induced toxicity following adjuvant whole-breast irradiation for early breast cancer with conventional fractionation (CF) and moderate hypofractionation (mHF). Materials and Methods: Patients recruited in a previous randomised controlled trial comparing acute toxicity between CF and mHF without disease recurrence were included in a post hoc analysis. Spectrophotometric and ultrasonographic examinations were performed for an objective evaluation and subsequent comparison of long-term skin toxicity. Furthermore, patient- and clinician-reported outcomes were recorded. Results: Sixty-four patients with a median age of 58 (37-81) years were included. The median follow-up was 57 (37-73) months. A total of 55% underwent CF and 45% mHF. A total of 52% received a sequential boost to the tumour bed. A significant decrease in mean L* (p = 0.011) and an increase in a* (p = 0.040) and b* values (p < 0.001) were observed, indicating hyperpigmentation. In comparison with the non-irradiated breast, there was a significant increase in both cutis (+14%; p < 0.001) and subcutis (+17%; p = 0.011) thickness, significantly more pronounced in CF patients (p = 0.049). In CF patients only, a sequential boost significantly increased the local cutis thickness and oedema compared to non-boost regions in the same breast (p = 0.001 and p < 0.001, respectively). Conclusions: mHF objectively resulted in reduced long-term skin toxicity compared to CF. A sequential boost increased the local fibrosis rate in CF, but not in mHF. This might explain the subjectively reported better cosmetic outcomes in patients receiving mHF and reinforces the rationale for favouring mHF as the standard of care.

Implementing a PROACTive Care Pathway to Empower and Support Survivors of Breast Cancer

PURPOSE

Optimal comprehensive survivorship care is insufficiently delivered. To increase patient empowerment and maximize the uptake of multidisciplinary supportive care strategies to serve all survivorship needs, we implemented a proactive survivorship care pathway for patients with early breast cancer at the end of primary treatment phase.

METHODS

Pathway components included (1) a personalized survivorship care plan (SCP), (2) face-to-face survivorship education seminars and personalized consultation for supportive care referrals (Transition Day), (3) a mobile app delivering personalized education and self-management advice, and (4) decision aids for physicians focused on supportive care needs. A mixed-methods process evaluation was performed according to the Reach, Effectiveness, Adoption, Implementation and Maintenance framework including administrative data review, pathway experience survey (patient, physician, and organization), and focus group. The primary objective was patient-perceived satisfaction with the pathway (predefined progression criteria for pathway continuation ≥70%).

RESULTS

Over 6 months, 321 patients were eligible for the pathway and received a SCP and 98 (30%) attended the Transition Day. Among 126 patients surveyed, 77 (66.1%) responded. 70.1% received the SCP, 51.9% attended the Transition Day, and 59.7% accessed the mobile app. 96.1% of patients were very or completely satisfied with the overall pathway, whereas perceived usefulness was 64.8% for the SCP, 90% for the Transition Day, and 65.2% for the mobile app. Pathway implementation seemed to be positively experienced by physicians and the organization.

CONCLUSION

Patients were satisfied with a proactive survivorship care pathway, and the majority reported that its components were useful in supporting their needs. This study can inform the implementation of survivorship care pathways in other centers.

The Future of Breast Cancer Research in the Survivorship Field

Prevalence of survivors of breast cancer has been steadily increasing in the last 20 years. Currently, more than 90% of women diagnosed with early-stage breast cancer are expected to be alive at 5 years from diagnosis thanks to early detection and breakthrough innovations in multimodal treatment strategies. Alongside this advancement in clinical outcomes, survivors of breast cancer might experience several specific challenges and present with unique needs. Survivorship trajectories after diagnosis and treatment of breast cancer can be significantly impacted by long-lasting and severe treatment-related side effects, including physical problems, psychological distress, fertility issues in young women, and impaired social and work reintegration, which add up to patients' individual risk of cancer recurrence and second primary malignancies. Alongside cancer-specific sequelae, survivors still present with general health needs, including management of chronic preexisting or ensuing conditions. Survivorship care should implement high-quality, evidence-based strategies to promptly screen, identify, and address survivors' needs in a comprehensive way and minimize the impact of severe treatment sequelae, preexisting comorbidities, unhealthy lifestyles, and risk of recurrence on quality of life. This narrative review focuses on core areas of survivorship care and discuss the state of the art and future research perspectives in key domains including selected long-term side effects, surveillance for recurrences and second cancers, well-being promotion, and specific survivors' needs.

Baseline quality of life and chemotherapy toxicities in patients with early breast cancer

BACKGROUND

The authors used the French breast cancer Cancer and Toxicities (CANTO) cohort to study the associations between baseline quality of life and chemotherapy dose-reductions (CDRs) or postchemotherapy-toxicities (PCTs).

METHODS

In total, 3079 patients with breast cancer who received chemotherapy were included in this analysis. The associations between baseline physical functioning (PF) and fatigue measured using the European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire Core 30, and two endpoints-CDRs during adjuvant or neoadjuvant chemotherapy; and selected PCTs were estimated with odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) using logistic regression models.

RESULTS

Among the 3079 patients from the CANTO cohort who were included, 718 (33.0%) received chemotherapy in the neoadjuvant setting, and 2361 (67.0%) received chemotherapy as adjuvant treatment. The chemotherapy included taxanes in 94.2% of patients and anthracyclines in 90.5% of patients. Overall, 15.5% of patients experienced CDRs and, 31.0% developed PCTs. Women with low baseline PF scores (<83) had higher multivariate odds of developing CDRs compared with those who had PF scores ≥83 (OR, 1.54; 95% CI, 1.13-2.09). The corresponding OR for PCTs was 1.50 (95% CI, 1.13-2.00). Women with high baseline fatigue scores had higher odds of CDRs (OR, 1.43; 95% CI, 1.13-1.76) and PCTs (OR, 1.32; 95% CI, 1.10-1.59).

CONCLUSIONS

By using the national CANTO cohort, baseline PF and fatigue were independently associated with CDRs and PCTs.

Schwann cell-derived CXCL2 contributes to cancer pain by modulating macrophage infiltration in a mouse breast cancer model

Pain is one of the most severe complications affecting the quality of life of cancer patients. Although substantial progress has been made in the diagnosis and treatment of cancer, the neurobiological mechanism of cancer pain is still unclear. In the present study, we identified the critical role of CXC chemokine 2 (CXCL2), released by Schwann cells after being activated by cancer cells, in maintaining cancer-induced macrophage infiltration and the resulting mechanical hypersensitivity and persistent spontaneous nociception. In vitro, Schwann cells cocultured with breast cancer cells exhibited a significant increase in CXCL2 expression; in addition, conditioned medium from Schwann cells activated by breast cancer cells had a similar effect to recombinant CXCL2 in terms of inducing macrophage migration. Targeting CXCL2 signaling by both CXC chemokine receptor 2 (CXCR2) antagonist pharmacological blockade and anti-CXCL2 mAb immunological blockade robustly prevented conditioned medium-induced macrophage migration. In vivo, both application of recombinant CXCL2 and perineural breast cancer cell implantation resulted in mechanical hypersensitivity and persistent spontaneous nociception in mice, along with increased macrophage infiltration into the sciatic nerves. Similar to the in vitro results, inhibition of CXCL2/CXCR2 signaling or conditional knockdown of CXCL2 in sciatic nerve Schwann cells effectively attenuated breast cancer cell-induced mechanical hypersensitivity, persistent spontaneous nociception, and macrophage recruitment in the sciatic nerve. Mechanistically, we found that redox effector factor-1 (Ref-1) secreted by breast cancer cells activated hypoxia inducible factor-1α (HIF-1α) expression and inhibited reactive oxygen species (ROS) production in Schwann cells, ultimately inducing CXCL2 expression in Schwann cells. In brief, the present study expands new insights into cancer pain mechanisms from promising animal models to provide new strategies for the control of cancer pain.

Contraceptive Use in Premenopausal Women With Early Breast Cancer

IMPORTANCE

As life span has increased among patients with cancer, survivorship has become an important component of breast cancer care. Among survivorship concerns, adequate contraceptive counseling is needed for premenopausal patients who are not seeking to become pregnant.

OBJECTIVE

To examine contraceptive use and chosen methods and to assess factors associated with contraceptive use over time in patients with early breast cancer.

DESIGN, SETTING, AND PARTICIPANTS

The Cancer Toxicity (CANTO) study was a multicenter nationwide prospective cohort study that enrolled women diagnosed with stage I to stage III breast cancer in France between March 2012 and December 2017. This analysis included 2900 premenopausal women who were 50 years of age or younger at diagnosis. Data were analyzed from July 2020 to July 2022.

EXPOSURES

Contraceptive use and method at diagnosis, shortly after the end of primary treatment (year 1), and during follow-up (year 2).

MAIN OUTCOMES AND MEASURES

Contraceptive use and methods were longitudinally evaluated at diagnosis, year 1, and year 2 after breast cancer diagnosis. Multivariable logistic regression models were used to assess the associations of clinical, socioeconomic, treatment, adverse effect, and patient-reported outcome variables with contraceptive use after diagnosis.

RESULTS

A total of 2900 patients (mean [SD] age, 43.1 [5.6] years) were included in the analysis; 2050 of 2894 women (70.8%) received chemotherapy, and 2305 of 2880 women (80.0%) received endocrine therapy. After diagnosis, 1182 of 2625 patients (45.0%) at year 1 and 1553 of 2363 patients (65.7%) at year 2 reported consulting with a gynecologist in the previous year. At diagnosis, 1487 of 2744 patients (54.2%) reported contraceptive use, with most patients (921 of 1470 women [62.7%]) using hormonal methods. The use of contraception significantly decreased after diagnosis (911 of 2342 patients [38.9%] at year 1 and 808 of 1961 patients [41.2%] at year 2; P < .001 for trend), when most patients (848 of 900 women [94.2%] at year 1 and 767 of 805 women [95.3%] at year 2) reported use of nonhormonal methods; these methods were primarily reversible mechanical approaches (copper intrauterine devices: 656 of 848 patients [77.4%] at year 1 and 577 of 767 patients [75.2%] at year 2; male condoms: 115 of 848 patients [13.6%] at year 1 and 110 of 767 patients [14.3%] at year 2). In the multivariable model, factors significantly associated with contraceptive use at year 1 included using contraception at diagnosis (adjusted odds ratio [aOR], 4.02; 95% CI, 3.15-5.14), being younger (aOR, 1.09; 95% CI, 1.07-1.13 per decreasing year), having better sexual function (aOR, 1.13; 95% CI, 1.07-1.19 per 10-point increment), having children (aOR, 4.21; 95% CI, 1.80-9.86), reporting the presence of leukorrhea (aOR, 1.32; 95% CI, 1.03-1.70), receiving tamoxifen treatment alone (aOR, 1.39; 95% CI, 1.01-1.92), and consulting with a gynecologist in the previous year (aOR, 1.29; 95% CI, 1.02-1.63). Similar factors were associated with contraceptive use at year 2, with the addition of partnered status (aOR, 1.61; 95% CI, 1.07-2.44).

CONCLUSIONS AND RELEVANCE

Findings from this study support the importance of raising awareness and improving targeted contraceptive counseling for premenopausal women with early breast cancer.

Long-Term Longitudinal Patterns of Patient-Reported Fatigue After Breast Cancer: A Group-Based Trajectory Analysis

PURPOSE

Fatigue is recognized as one of the most burdensome and long-lasting adverse effects of cancer and cancer treatment. We aimed to characterize long-term fatigue trajectories among breast cancer survivors.

METHODS

We performed a detailed longitudinal analysis of fatigue using a large ongoing national prospective clinical study (CANcer TOxicity, ClinicalTrials.gov identifier: NCT01993498) of patients with stage I-III breast cancer treated from 2012 to 2015. Fatigue was assessed at diagnosis and year 1, 2, and 4 postdiagnosis. Baseline clinical, sociodemographic, behavioral, tumor-related, and treatment-related characteristics were available. Trajectories of fatigue and risk factors of trajectory-group membership were identified by iterative estimates of group-based trajectory models.

RESULTS

Three trajectory groups were identified for severe global fatigue (n = 4,173). Twenty-one percent of patients were in the high-risk group, having risk estimates of severe global fatigue of 94.8% (95% CI, 86.6 to 100.0) at diagnosis and 64.6% (95% CI, 59.2 to 70.1) at year 4; 19% of patients clustered in the deteriorating group with risk estimates of severe global fatigue of 13.8% (95% CI, 6.7 to 20.9) at diagnosis and 64.5% (95% CI, 57.3 to 71.8) at year 4; 60% were in the low-risk group with risk estimates of 3.6% (95% CI, 2.5 to 4.7) at diagnosis and 9.6% (95% CI, 7.5 to 11.7) at year 4. The distinct dimensions of fatigue clustered in different trajectory groups than those identified by severe global fatigue, being differentially affected by sociodemographic, clinical, and treatment-related factors.

CONCLUSION

Our findings highlight the multidimensional nature of cancer-related fatigue and the complexity of its risk factors. This study helps to identify patients with increased risk of severe fatigue and to inform personalized interventions to ameliorate this problem.

Oncological Treatment-Related Fatigue in Oncogeriatrics: A Scoping Review

Fatigue is a highly prevalent symptom in both cancer patients and the older population, and it contributes to quality-of-life impairment. Cancer treatment-related fatigue should thus be included in the risk/benefit assessment when introducing any treatment, but tools are lacking to a priori estimate such risk. This scoping review was designed to report the current evidence regarding the frequency of fatigue for the different treatment regimens proposed for the main cancer indications, with a specific focus on age-specific data, for the following tumors: breast, ovary, prostate, urothelium, colon, lung and lymphoma. Fatigue was most frequently reported using the National Cancer Institute Common Terminology Criteria for Adverse Events (NCI CTCAE) versions 3 to 5. A total of 324 regimens were analyzed; data on fatigue were available for 217 (67%) of them, and data specific to older patients were available for 35 (11%) of them; recent pivotal trials have generally reported more fatigue grades than older studies, illustrating increasing concern over time. This scoping review presents an easy-to-understand summary that is expected to provide helpful information for shared decisions with patients regarding the anticipation and prevention of fatigue during each cancer treatment.

Dynamics of Long-Term Patient-Reported Quality of Life and Health Behaviors After Adjuvant Breast Cancer Chemotherapy

We aimed to characterize long-term quality of life (QOL) trajectories among patients with breast cancer treated with adjuvant chemotherapy and to identify related patterns of health behaviors.

A phase III randomized trial of weight loss to reduce cancer-related fatigue among overweight and obese breast cancer patients: MEDEA Study design

Background

Elevated body mass index (BMI) represents a risk factor for cancer-related fatigue (CRF). Weight loss interventions are feasible and safe in cancer survivors, leading to improved cardio-metabolic and quality of life (QOL) outcomes and modulating inflammatory biomarkers. Randomized data are lacking showing that a lifestyle intervention aimed at weight loss, combining improved diet, exercise, and motivational counseling, reduces CRF. Motivating to Exercise and Diet, and Educating to healthy behaviors After breast cancer (MEDEA) is a multi-center, randomized controlled trial evaluating the impact of weight loss on CRF in overweight or obese survivors of breast cancer. Herein, we described the MEDEA methodology.

Methods

Patients (N = 220) with stage I–III breast cancer and BMI ≥ 25 kg/m², within 12 months of primary treatment, and able to walk ≥ 400 m are eligible to enroll. Participants are randomized 1:1 to health education alone vs. a personalized telephone-based weight loss intervention plus health education. Both arms receive a health education program focusing on healthy living. Patients in the intervention arm are paired with an individual lifestyle coach, who delivers the intervention through 24 semi-structured telephone calls over 1 year. Intervention goals include weight loss ≥ 10% of baseline, caloric restriction of 500–1000 Kcal/day, and increased physical activity (PA) to 150 (initial phase) and 225–300 min/week (maintenance phase). The intervention is based on the social cognitive theory and is adapted from the Breast Cancer Weight Loss trial (BWEL, A011401). The primary endpoint is the difference in self-reported CRF (EORTC QLQ-C30) between arms. Secondary endpoints include the following: QOL (EORTC QLQ-C30, -BR45, -FA12), anxiety, and depression (HADS); weight and BMI, dietary habits and quality, PA, and sleep; health care costs (hospital-admissions, all-drug consumption, sick leaves) and cost-effectiveness (cost per quality-adjusted life-year); and patient motivation and satisfaction. The primary analysis of MEDEA will compare self-reported CRF at 12 months post-randomization between arms, with 80.0% power (two-sided α = 0.05) to detect a standardized effect size of 0.40.

Discussion

MEDEA will test the impact of a weight loss intervention on CRF among overweight or obese BC survivors, potentially providing additional management strategies and contributing to establish weight loss support as a new standard of clinical care.

Trial registration

ClinicalTrials.govNCT04304924