Network analyses of associations between cancer-related physical and psychological symptoms and quality of life in gastric cancer patients

Network Analyses Applied to the Dimensions of Cancer-Related Fatigue in Women With Breast Cancer

BACKGROUND

Understanding cancer symptom cluster through network analyses is a new approach in oncology, revealing interconnected and influential relationships among reported symptoms. We aimed to assess these relationships using network analysis in posttreatment breast cancer patients, focusing on the five dimensions of cancer-related fatigue (CRF), and on other common difficulties encountered by oncological patients (i.e., pain, anxiety, depression, sleep difficulties, cognitive impairments, and emotion regulation and mental adaptation difficulties).

METHOD

This study involved a complementary analysis of data from two interventional studies. Participants completed questionnaires before and after the intervention, with baseline scores being used in this article. Partial correlation network analysis modeled the relationships between symptoms in five distinct networks, each of them including one specific dimension of CRF. The core symptom in each network was identified based on the highest centrality indices.

RESULTS

Depression emerged as the core symptom in all networks, strongly associated with all fatigue dimensions (partial correlations ranging from 0.183 to 0.269) except mental fatigue. These findings indicate robust connections between symptoms, as variations in depression scores directly or indirectly influence fatigue and other symptoms within the cluster.

CONCLUSION

Our results support the multidimensional aspect of CRF, and its links with other common symptoms. To effectively reduce patient CRF, interventions should address not only fatigue but also the closely related symptoms from the cluster, such as depression, given its centrality in the cluster.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT03144154 and NCT04873661). Retrospectively registered on May 1, 2017 and April 29, 2021, respectively.

Symptom Network Analysis and Unsupervised Clustering of Oncology Patients Identifies Drivers of Symptom Burden and Patient Subgroups With Distinct Symptom Patterns

BACKGROUND

Interindividual variability in oncology patients' symptom experiences poses significant challenges in prioritizing symptoms for targeted intervention(s). In this study, computational approaches were used to unbiasedly characterize the heterogeneity of the symptom experience of oncology patients to elucidate symptom patterns and drivers of symptom burden.

METHODS

Severity ratings for 32 symptoms on the Memorial Symptom Assessment Scale from 3088 oncology patients were analyzed. Gaussian Graphical Model symptom networks were constructed for the entire cohort and patient subgroups identified through unsupervised clustering of symptom co-severity patterns. Network characteristics were analyzed and compared using permutation-based statistical tests. Differences in demographic and clinical characteristics between subgroups were assessed using multinomial logistic regression.

RESULTS

Network analysis of the entire cohort revealed three symptom clusters: constitutional, gastrointestinal-epithelial, and psychological. Lack of energy was identified as central to the network which suggests that it plays a pivotal role in patients' overall symptom experience. Unsupervised clustering of patients based on shared symptom co-severity patterns identified six patient subgroups with distinct symptom patterns and demographic and clinical characteristics. The centrality of individual symptoms across the subgroup networks differed which suggests that different symptoms need to be prioritized for treatment within each subgroup. Age, treatment status, and performance status were the strongest determinants of subgroup membership.

CONCLUSIONS

Computational approaches that combine unbiased stratification of patients and in-depth modeling of symptom relationships can capture the heterogeneity in patients' symptom experiences. When validated, the core symptoms for each of the subgroups and the associated clinical determinants may inform precision-based symptom management.

Early postoperative core symptoms and their relationship with resilience in oesophageal cancer patients-A multicentre cross-sectional study

AIM

To assess early postoperative core symptoms in oesophageal cancer patients and their relationship with resilience.

BACKGROUND

Patients with oesophageal cancer face a high number of severe symptoms in the early post-operative period and require the development of an effective symptom management programme. Identifying core symptoms through network analysis helps in accurate patient care.

DESIGN

A multicentre cross-sectional study.

METHODS

A cross-sectional survey was conducted from August 2022 to August 2023 at three hospitals in Anhui Province, China. A total of 469 patients were recruited for this study and 418 (89.1%) patients completed this investigation. Using network analysis to find early post-operative core symptoms in oesophageal cancer patients. Multiple linear regression was used to analyse resilience factors affecting core symptoms.

RESULTS

Sadness was the most core symptom in oesophageal cancer patients in the early post-operative period (rs = 1.41), followed by incision pain and difficulty breathing while resting (rs = 1.20, rs = 1.08). Resilience was significantly associated with patients' feelings of sadness, with optimism having the greatest impact on sadness (p < .01).

CONCLUSION

Sadness is the most core symptom in patients in the early post-operative period and special attention should be paid to improving their level of resilience. Local symptoms and dysfunction in the early post-operative period should be treated in a synergistic manner.

IMPACT

This study identifies core symptoms and their relationship to resilience in patients with oesophageal cancer in the early post-operative period. Symptoms as the main core symptom in patients in the early post-operative period, which was sadness and was significantly associated with resilience. Precise interventions can be made to target patients' core post-operative symptoms, which can help improve the effectiveness of symptom management.

REPORTING METHOD

We have complied with the relevant EQUATOR research reporting checklist.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution in the study.

Estimation of Personal Symptom Networks Using the Ising Model for Adult Survivors of Childhood Cancer: A Simulation Study with Real-World Data Application

Purpose

Childhood cancer survivors experience interconnected symptoms, patterns of which can be elucidated by network analysis. However, current symptom networks are constructed based on the average survivors without considering individual heterogeneities. We propose to evaluate personal symptom network estimation using the Ising model with covariates through simulations and estimate personal symptom network for adult childhood cancer survivors.

Patients and Methods

We adopted the Ising model with covariates to construct networks by employing logistic regressions for estimating associations between binary symptoms. Simulation experiments assessed the robustness of this method in constructing personal symptom network. Real-world data illustration included 1708 adult childhood cancer survivors from the St. Jude Lifetime Cohort Study (SJLIFE), a retrospective cohort study with prospective follow-up to characterize the etiology and late effects for childhood cancer survivors. Patients' baseline symptoms in 10 domains (cardiac, pulmonary, sensation, nausea, movement, pain, memory, fatigue, anxiety, depression) and individual characteristics (age, sex, race/ethnicity, attained education, personal income, and marital status) were self-reported using survey. Treatment variables (any chemo or radiation therapy) were obtained from medical records. Personal symptom network of 10 domains was estimated using the Ising model, incorporating individual characteristics and treatment data.

Results

Simulations confirmed the robustness of the Ising model with covariates in constructing personal symptom networks. Real-world data analysis identified age, sex, race/ethnicity, education, marital status, and treatment (any chemo and radiation therapy) as major factors influencing symptom co-occurrence. Older childhood cancer survivors showed stronger cardiac-fatigue associations. Survivors of racial/ethnic minorities had stronger pain-fatigue associations. Female survivors with above-college education demonstrated stronger pain-anxiety associations. Unmarried survivors who received radiation had stronger association between movement and memory problems.

Conclusion

The Ising model with covariates accurately estimates personal symptom networks. Individual heterogeneities exist in symptom co-occurrence patterns for childhood cancer survivors. The estimated personal symptom network offers insights into interconnected symptom experiences.

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

PURPOSE

To comprehend the complex relationship between symptoms and health-related quality of life (HRQoL) in patients with diffuse glioma, we applied symptom network analysis to identify patterns of associations between depression, cognition, brain tumor-related symptoms, and HRQoL. Additionally, we aimed to compare global strength between symptom networks to understand if symptoms are more tightly connected in different subgroups of patients.

METHODS

We included 256 patients and stratified the sample based on disease status (preoperative vs. postoperative), tumor grade (grade II vs. III/IV), and fatigue status (non-fatigued vs. fatigued). For each subgroup of patients, we constructed a symptom network. In these six networks, each node represented a validated subscale of a questionnaire and an edge represented a partial correlation between two nodes. We statistically compared global strength between networks.

RESULTS

Across the six networks, nodes were highly correlated: fatigue severity, depression, and social functioning in particular. We found no differences in GS between the networks based on disease characteristics. However, global strength was lower in the non-fatigued network compared to the fatigued network (5.51 vs. 7.49, p < 0.001).

CONCLUSIONS

Symptoms and HRQoL are highly interrelated in patients with glioma. Interestingly, nodes in the network of fatigued patients were more tightly connected compared to non-fatigued patients.

IMPLICATIONS FOR CANCER SURVIVORS

We introduce symptom networks as a method to understand the multidimensionality of symptoms in glioma. We find a clear association between multiple symptoms and HRQoL, which underlines the need for integrative symptom management targeting fatigue in particular.

The Mediating Role of Exercise in Depression and Fatigue in Patients with Advanced Cancer

This study explored the interconnections between sociodemographic elements, depression, fatigue, and exercise in patients suffering from incurable neoplasm, particularly emphasizing the mediating influence of exercise on the relationship between depression and fatigue This was a prospective, multicenter, observational study involving 15 hospitals across Spain. After three months of systemic cancer treatment, participants completed the Brief Symptom Inventory (BSI), the Godin-Shephard Leisure-Time Physical Activity Questionnaire (GSLTPAQ) and the Fatigue Assessment Scale (FAS) to measure levels of depression, fatigue, and exercise, respectively. A total of 616 subjects participated in this study. Activity levels differed markedly according to educational attainment, marital, and work status. There was a negative correlation between physical activity and depression, and a positive correlation between depression and fatigue (β = -0.18, and β = 0.46, respectively). Additionally, physical activity inversely influenced fatigue levels (β = 0.21). Physical activity served as a partial intermediary in the link between depression and fatigue among patients with advanced, unresectable cancer. Healthcare providers are urged to consider both the physical and emotional dimensions of cancer treatment, implementing physical activity programs to enhance overall patient quality of life and mental health.

Symptom cluster among cancer survivors from a nationally representative survey: a network analysis

PURPOSE

To identify the symptom cluster among cancer survivors and examine their subgroup differences via network analysis based on nationally representative data.

METHODS

This cross-sectional study included 2966 survivors participating in the 2020 National Health Interview Survey (NHIS). Participants self-reported the presence of 14 symptoms capturing four clusters (physical, somatic, sleep, and psychologic problems). Network analysis models were used to reveal the relationships between symptoms and those interactions. Network comparison tests were applied to compare subgroups.

RESULTS

The core symptoms of the symptom cluster were fatigue (Bet = 33, Clo = 0.0067, Str = 0.9397), pain (Bet = 11, Clo = 0.0060, Str = 0.9226), wake up well rested (Bet = 25, Clo = 0.0057, Str = 0.8491), and anxiety (Bet = 5, Clo = 0.0043, Str = 0.9697) among cancer survivors. The core symptoms, network structure, and global strength were invariant between time since diagnoses (< 2 years vs. ≥ 2 years) or between numbers of cancers (1 vs. ≥ 2), yet varied between the comorbidity group and non-comorbidity group (≥ 1 vs. 0).

CONCLUSIONS

Fatigue would be a potential target for alleviating other symptoms through a negative feedback loop of other related symptoms of cancer survivors. In particular, cancer survivors with other chronic diseases should be the focus of attention and strengthen targeted intervention.

Network analysis used to investigate the interplay among somatic and psychological symptoms in patients with cancer and cancer survivors: a scoping review

PURPOSE

Patients with cancer often experience multiple somatic and psychological symptoms. Somatic and psychological symptoms are thought to be connected and may reinforce each other. Network analysis allows examination of the interconnectedness of individual symptoms. The aim of this scoping review was to examine the current state of knowledge about the associations between somatic and psychological symptoms in patients with cancer and cancer survivors, based on network analysis.

METHODS

This scoping review followed the five-stage framework of Arksey and O'Malley. The literature search was conducted in May, 2023 in PubMed, APA PsycINFO, Embase Cochrane central, and CINAHL databases.

RESULTS

Thirty-two studies were included, with eleven using longitudinal data. Seventeen studies reported on the strength of the associations: somatic and psychological symptoms were associated, although associations among somatic as well as among psychological symptoms were stronger. Other findings were the association between somatic and psychological symptoms was stronger in patients experiencing more severe symptoms; associations between symptoms over time remained rather stable; and different symptoms were central in the networks, with fatigue being among the most central in half of the studies.

IMPLICATIONS FOR CANCER SURVIVORS

Although the associations among somatic symptoms and among psychological symptoms were stronger, somatic and psychological symptoms were associated, especially in patients experiencing more severe symptoms. Fatigue was among the most central symptoms, bridging the somatic and psychological domain. These findings as well as future research based on network analysis may help to untangle the complex interplay of somatic and psychological symptoms in patients with cancer.

Symptoms experienced after transcatheter arterial chemoembolization in patients with primary liver cancer: A network analysis

Objective

This study aimed to establish a symptom network for patients with primary liver cancer posttranscatheter arterial chemoembolization (TACE), identifying core and bridge symptoms. The goal is to provide a foundation for precise and comprehensive nursing interventions.

Methods

A total of 1207 post-TACE patients were included using a consecutive sampling method. Data collection involved a general information questionnaire, the Anderson Symptom Assessment Scale, and a primary liver cancer-specific symptom module. The symptom network was constructed using the R language.

Results

In the overall network, distress exhibited the highest strength (rs = 1.31) and betweenness (rb = 62). Fatigue had the greatest closeness (rc = 0.0043), while nausea and vomiting (r = 0.76 ± 0.02) had the highest marginal weights. Nausea had the highest bridge strength (rbs = 5.263). In the first-time TACE-treated symptom network, sadness (rbs = 5.673) showed the highest bridge strength, whereas in the non-first-time symptom network, fever (rbs = 3.061) had the highest bridge strength.

Conclusions

Distress serves as a core symptom, and nausea acts as a bridge symptom after TACE treatment in liver cancer patients. Interventions targeting bridge symptoms should be tailored based on the number of treatments, enhancing the quality of symptom management.

Chemotherapy-related symptom networks in distinct subgroups of Chinese patients with gastric cancer

Objective

This study aims to identify distinct subgroups among gastric cancer patients undergoing chemotherapy (CTX), delineate associated symptom networks, and ascertain the clinical and sociodemographic variables contributing to diverse symptom patterns.

Methods

Conducted in eastern China, our investigation involved gastric cancer patients receiving CTX. We gathered data using the M.D. Anderson Symptom Inventory Gastrointestinal Cancer Module along with clinical and sociodemographic variables. Subgroups were discerned based on symptom severity through latent profile analysis, and subsequent comparisons were made regarding the symptom networks in different subgroups.

Results

The analysis encompassed 677 eligible gastric cancer patients, revealing three profiles: "Profile 1: low class" (n = 354, 52.3%), "Profile 2: moderate class" (n = 222, 32.8%), and "Profile 3: all high class" (n = 101, 14.9%). Nausea-vomiting exhibited robust associations in the symptom networks of all subgroups, whereas sadness-distress, and taste change-lack of appetite were notably linked with Profile 1 and Profile 2. Distress emerged as a core symptom in Profile 1, lack of appetite dominated the symptom network in Profile 2, and fatigue attained the highest strength in Profile 3. Distinct symptom profiles were influenced by variables such as education level, CTX combined with surgical or herbal treatment, psychological resilience, and social support.

Conclusions

Patients within different subgroups manifest individualized patterns of symptom profiles. Analyzing demographics, disease characteristics, and psychosocial information among diverse subgroups facilitates healthcare providers in devising more personalized and targeted symptom management strategies, thereby alleviating the symptom burden on patients.

Global status of research on gastrointestinal cancer patients' quality of life: A bibliometric and visual analysis from 2003 to 2023

Objective

To analyze the current research status, hotspots, and frontiers in the field of Gastrointestinal (GI) cancer and quality of life (QoL) through the bibliometrics method, and to provide references and guidance for future research.

Methods

Literature related to GI cancer and QoL from April 1, 2003 to March 31, 2023 was retrieved from the Web of Science Core Collection database. CiteSpace 6.2.R1 was performed for collaboration analysis, keyword co-occurrence analysis, and document co-citation analysis.

Results

A total of 1224 publications were included in this study. There has been a significant increase in the number of publications in this field over the past two decades. The United States, the Karolinska Institute and the University of Amsterdam, and Pernilla Lagergren are the most prolific country, institution, and author, respectively. The links between most of the research constituents were relatively thin (centrality <0.1). The keyword analysis indicates that the benefits of physical activity on QoL, the levels of psychological distress and its relationship with QoL, as well as the development and validation of QoL measurement tools have been the research hotspots. Open-label/double-blind trials exploring therapeutic interventions and more targeted new drugs or more effective drug combinations, and longitudinal studies determining the direction of the association between psychological distress and QoL at different time points, may be emerging trends in this field.

Conclusion

The cooperation among countries, institutions, and authors in this field should be strengthened. In addition, the health benefits of light physical activity, interventions for QoL, trajectory and direction of the relationship between psychological distress and QoL may be the focus of future research.

Evaluation of a psychoneurological symptom cluster in patients with breast or digestive cancer: a longitudinal observational study

BACKGROUND

A psychoneurological symptom cluster composed of cancer-related fatigue, emotional distress, sleep difficulties, and pain is very common among patients with cancer. Cognitive difficulties are also frequently associated with this cluster. Network analyses allow for an in-depth understanding of the relationships between symptoms in a cluster. This paper details the study protocol of a longitudinal assessment of the psychoneurological symptom cluster in two distinct cohorts: breast cancer and digestive cancer survivors, using network analyses.

METHODS

Over two years, the symptoms involved in the psychoneurological symptom cluster, along with other common symptoms (e.g., digestive symptoms, financial difficulties) and variables (i.e., self-compassion, coping strategies) will be assessed in two cohorts: breast cancer survivors (N = 240) and digestive cancer survivors (N = 240). Online questionnaires will be completed at baseline, then 6, 12 and 24 months later. Network analyses will be used to assess the configuration of the symptom cluster at each measurement time and in each cohort. Comparison of networks between two measurement times or between the two cohorts will also be done with network comparison tests.

DISCUSSION

This study will enable a better understanding of the relationships between common symptoms endured by patients with cancer. The results will be employed to develop more cost-effective interventions which, ultimately, will significantly improve the quality of life of patients with breast or digestive cancer.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT05867966). Registered on the 27th of April 2023. url: https://classic.

CLINICALTRIALS

gov/ct2/show/NCT05867966 .

Hotspots and frontiers of the relationship between gastric cancer and depression: A bibliometric study

BACKGROUND

A significant relationship between gastric cancer (GC) and depression has been found in the last 20 years. However, there is no comprehensive information that helps researchers find popular and potential research directions on GC and depression.

AIM

To determine the research status and hotspots by bibliometric analysis of relevant publications on the relationship between GC and depression.

METHODS

We used the Web of Science Core Collection to search and collate the literature on GC and depression from 2000 to 2022 on 31 May, 2023. Then, visualization analysis was performed using VOSviewer software (version 1.6.19) and the Bibliometrix package in R software.

RESULTS

We retrieved 153 pertinent publications from 2000 to 2022. The annual publication count showed an overall upward trend. China had the most prominent publications and significant contributions to this field (n = 64, 41.83%). Before 2020, most studies focused on "the effect of GC on the development and progression of depression in patients." The latest research trends indicate that "the effect of depression on the occurrence and development of GC and its mechanism" will receive more attention in the future.

CONCLUSION

The study of "the effect of depression on the occurrence and development of GC and its mechanism" has emerged as a novel research theme over the past two years, which may become a research hotspot in this field. This study provides new insights into the hotpots and frontiers of the relationship between GC and depression, potentially guiding researchers toward hot research topics in the future.

Contemporaneous symptom networks and correlates during endocrine therapy among breast cancer patients: A network analysis

Background

Endocrine therapy-related symptoms are associated with early discontinuation and quality of life among breast cancer survivors. Although previous studies have examined these symptoms and clinical covariates, little is known about the interactions among different symptoms and correlates. This study aimed to explore the complex relationship of endocrine therapy-related symptoms and to identify the core symptoms among breast cancer patients.

Methods

This is a secondary data analysis conducted based on a multicenter cross-sectional study of 613 breast cancer patients in China. All participants completed the 19-item Chinese version of the Functional Assessment of Cancer Therapy-Endocrine Subscale (FACT-ES). Multivariate linear regression analysis was performed to identify significant factors. A contemporaneous network with 15 frequently occurring symptoms was constructed after controlling for age, payment, use of aromatase inhibitors, and history of surgery. Network comparison tests were used to assess differences in network structure across demographic and treatment characteristics.

Results

All 613 participants were female, with an average age of 49 years (SD = 9.4). The average duration of endocrine therapy was 3.6 years (SD = 2.3) and the average symptom score was 18.99 (SD = 11.43). Irritability (n = 512, 83.52%) and mood swings (n = 498, 81.24%) were the most prevalent symptoms. Lost interest in sex (mean = 1.95, SD = 1.39) and joint pain (mean = 1.57, SD = 1.18) were the most severe symptoms. The edges in the clusters of emotional symptoms ("irritability-mood swings"), vasomotor symptoms ("hot flashes-cold sweats-night sweats"), vaginal symptoms ("vaginal discharge-vaginal itching"), sexual symptoms ("pain or discomfort with intercourse-lost interest in sex-vaginal dryness"), and neurological symptoms ("headaches-dizziness") were the thickest in the network. There were no significant differences in network structure (P = 0.088), and global strength (P = 0.330) across treatment types (selective estrogen receptor modulators vs. aromatase inhibitors). Based on an evaluation of the centrality indices, irritability and mood swings appeared to be structurally important nodes after adjusting for the clinical covariates and after performing subgroup comparisons.

Conclusion

Endocrine therapy-related symptoms are frequently reported issues among breast cancer patients. Our findings demonstrated that developing targeted interventions focused on emotional symptoms may relieve the overall symptom burden for breast cancer patients during endocrine therapy.

Symptom clusters and impact on quality of life in esophageal cancer patients

BACKGROUND

Esophageal cancer patients can experience co-occurring, related symptoms labeled symptom clusters. This study aimed to identify symptom clusters and explore which SCs independently affect the quality of life (QoL) among esophageal cancer patients.

METHODS

This cross-sectional study was performed in Shenyang, China, from February 2021 to February 2022. Finally, 118 esophageal cancer patients effectively completed the survey. Questionnaires' information included the Functional Assessment of Cancer Therapy-General (FACT-G), the MD Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI), the Multidimensions Scale of Perceived Social Support, and demographic and clinical characteristics. Exploratory factor analysis with principal axis factoring was used to identify symptom clusters, and multiple regression analysis was employed to analyze the influencing factors of QoL.

RESULTS

The mean score of FACT-G was 69.88 (SD = 17.85) among 118 esophageal cancer patients. Four symptom clusters were identified: psychological-somatic, dysphagia, fatigue-pain, and gastrointestinal symptom clusters. Results of regression analysis indicated a significant impact on QoL for chemotherapy (β = 0.140, P < 0.045), psychological-somatic symptom cluster (β = - 0.329, P = 0.013), and social support (β = 0.409, P < 0.001) after adjusting demographic and clinical characteristics. The linear combination explained 47.8% of the variance in QoL.

CONCLUSIONS

There is a critical need to emphasize the importance of psychological-somatic symptoms clusters management programs and increasing social support to improve QoL in esophageal cancer patients.

Cancer-related fatigue and depression: a monocentric, prospective, cross-sectional study in advanced solid tumors

Background

Cancer-related fatigue (CRF) is common in patients with advanced solid tumors and several risk factors are described. The possible role of depression is reported by clinicians despite the association with CRF being unclear.

Material and methods

In this monocentric, cross-sectional, prospective study we recruited patients with advanced solid tumors who were hospitalized at Fondazione IRCCS Istituto Nazionale dei Tumori of Milan. The primary objective was to assess the correlation between CRF and depression. Secondary objectives were the estimation of CRF and depression prevalence and the identification of associated clinical risk factors. CRF and depression were evaluated through the Functional Assessment of Cancer Therapy-Fatigue subscale and the Zung Self Depression Scale (ZSDS) questionnaires. The Cochran-Armitage trend test was used to demonstrate the primary hypothesis. Univariate and multivariate logistic regression models were used to investigate the impact of clinical variables.

Results

A total of 136 patients were enrolled. The primary analysis found a linear correlation (P < 0.0001) between CRF and depression. The prevalence of CRF and of moderate to severe depressive symptoms was 43.5% and 29.2%, respectively. In univariate analysis, patients with poor Eastern Cooperative Oncology Group performance status (ECOG PS), anemia, distress, pain, and receiving oncological treatment were at a significantly higher risk for CRF, whereas poor ECOG PS, pain, and distress were risk factors for depression. In multivariate analysis, high levels of ZSDS were confirmed to be correlated to CRF: odds ratio of 3.86 [95% confidence interval (CI) 0.98-15.20) and 11.20 (95% CI 2.35-53.36) for ZSDS of 50-59 and 60-100, respectively (P value for trend 0.002). Moreover, the ECOG PS score was confirmed to be significantly associated with CRF (OR 7.20; 95% CI 1.73-29.96; P = 0.007).

Conclusions

Our data suggest a strong correlation between CRF and depression in patients with advanced solid tumors. Further investigations are needed to better understand this relationship and if depressive disorder therapeutic strategies could also impact on CRF.

•

Validated patient-reported outcome measures were used for screening CRF and depression in advanced cancer patients.

•

A direct strong correlation between CRF and depression was found in these patients, often unconsidered by clinicians.

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Other different clinical risk factors for the onset and worsening of CRF were identified.

•

A comprehensive evaluation of cancer patients, that should also consider mood disorders, could improve CRF management.