Symptoms associated with concurrent chemoradiotherapy in patients with cervical cancer: application of latent profile analysis and network analysis DOI Creative Commons

X.-H. Lu,

Lingling Zheng, Jin Xue

et al.

Asia-Pacific Journal of Oncology Nursing, Journal Year: 2024, Volume and Issue: 12, P. 100649 - 100649

Published: Dec. 28, 2024

This study aims to explore symptom subgroups and influencing factors among patients undergoing concurrent chemoradiotherapy (CCRT) for cervical cancer, construct a network, identify core symptoms within the overall sample its various subgroups. A cross-sectional survey was conducted with 378 CCRT cancer from June 2023 May 2024 at tertiary hospital in Anhui Province. Participants completed General Information Questionnaire, Symptom Assessment Scale Patients Undergoing Intermediate Advanced Cervical Cancer, Dyadic Coping Inventory. Latent profile analysis (LPA) identified subgroups, while multivariate logistic regression examined influences on these networks were developed using R language analyze centrality indices symptoms. classified into three subgroups: low burden (n ​= ​200, 52.91%), moderate prominent intestinal response ​75, 19.84%), high ​103, 27.25%). Multivariate indicated that age, tumor stage, chemotherapy frequency, dyadic coping (DC) predictive of subgroup membership (P ​< ​0.05). Network revealed sadness (r s ​1.320) as sample, nausea ​0.801) group, vomiting ​0.705, 0.796) both prominence group group. Three exist sadness, nausea, Health care professionals should provide individualized management tailored

Language: Английский

Exploring symptom clusters and core symptoms during the vulnerable phase in patients with chronic heart failure: a network-based analysis DOI
Zekun Bian,

Bin Shang,

Caifeng Luo

et al.

European Journal of Cardiovascular Nursing, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Abstract Aims To construct a symptom network of chronic heart failure patients in the vulnerable period and identify core symptoms bridge between different clusters. Methods results A convenience sampling method was used to select 402 with within 3 months after discharge from cardiology departments two tertiary-level hospitals Zhenjiang City, symptom-related entries Minnesota living questionnaire (MLHFQ) were conduct survey. Symptom networks constructed using R language. The structurally stable, correlation stability coefficient 0.595. In network, ‘depression’ (MLHFQ9), ‘dyspnoea on exertion’ (MLHFQ3), ‘worry’ (MLHFQ7) are symptoms. ‘Cognitive problems’ (MLHFQ8), ‘sleep difficulties’ (MLHFQ4), ‘fatigue’ (MLHFQ6) connecting emotional-cognitive somatic comparison test, there no significant differences genders places residence. Conclusion ‘Depression’ ‘increased need rest’ most severe symptoms, respectively, phase failure, ‘cognitive is important symptom. Clinical caregivers can build precise intervention programme based focus emotional cognitive clusters, order improve efficacy management during failure.

Language: Английский

Citations

1
Core preoperative symptoms and patients’ symptom experiences in oral cancer: a mixed-methods study DOI Creative Commons
Yu Zhang, Jingya Yu, Tingting Liu

et al.

Supportive Care in Cancer, Journal Year: 2025, Volume and Issue: 33(4)

Published: March 25, 2025

Patients with oral cancer frequently experience a substantial symptom burden, especially during the preoperative phase, which is typically marked by increased anxiety, pain, and functional impairments. This study aimed to construct contemporaneous networks investigate experiences of patients in China. employed mixed-methods design that integrated cross-sectional qualitative research. Data were collected from 527 at Department Head Neck Oncology tertiary hospital between September 2023 May 2024 The MD Anderson Symptom Inventory for Cancer (MDASI-H&N) was used assess prevalence severity cancer-related symptoms. constructed using networktools, qgraph, Bootnet packages R, centrality indices calculated identify core symptoms within network. Qualitative data analyzed content analysis NVivo software extract themes, thereby providing comprehensive understanding patients' experiences. Distress (89.56%) sadness (63.95%) most prevalent severe symptoms, respectively. Two distinct clusters emerged: Emotional-Sleep Symptoms Cluster (Cluster 1) Eating Disorder 2). Difficulty swallowing or chewing (rs = 0.87, rb 102) disturbed sleep 0.64, 77) exhibited highest indices, indicating these more likely co-occur others Additionally, fatigue had significant negative impact on quality life (r - 0.16). identified through network offered valuable insights into lived regarding their These findings serve as foundation personalized targeted treatment strategies designed improve management enhance care.

Language: Английский

Citations

0
Exploring the relationship between postoperative psychological resilience and symptom burden in esophageal cancer patients DOI
Mengmeng Yuan, Aiyu Miao,

Ranran Qin

et al.

Supportive Care in Cancer, Journal Year: 2025, Volume and Issue: 33(6)

Published: May 10, 2025

Language: Английский

Citations

0
Symptom Network Analysis and Unsupervised Clustering of Oncology Patients Identifies Drivers of Symptom Burden and Patient Subgroups With Distinct Symptom Patterns DOI Creative Commons
Brandon Hwa-Lin Bergsneider, Terri S. Armstrong, Yvette P. Conley

et al.

Cancer Medicine, Journal Year: 2024, Volume and Issue: 13(19)

Published: Oct. 1, 2024

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

Language: Английский

Citations

3
Symptom network connectivity and interaction among people with HIV in China: secondary analysis based on a cross-sectional survey DOI Creative Commons
Meilian Xie, Xiaoyu Liu, Aiping Wang

et al.

BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Aug. 28, 2024

The symptom burden in people with HIV (PWH) is considerable. Nonetheless, the identification of a central symptom, or bridge among myriad symptoms experienced by PWH remains unclear. This study seeks to establish networks experiences within different clusters and investigate relationships interconnectedness between these PWH.

Language: Английский

Citations

1
Identification of the Core Nutrition Impact Symptoms Cluster in Patients with Lung Cancer During Chemotherapy: A Symptom Network Analysis DOI Creative Commons
Dandan Zheng, Ting Jin, Dan Li

et al.

Seminars in Oncology Nursing, Journal Year: 2024, Volume and Issue: unknown, P. 151794 - 151794

Published: Dec. 1, 2024

Language: Английский

Citations

1
Exploring core and bridge symptoms in patients recovering from stroke: a network analysis DOI Creative Commons
Yao Huang, Songmei Cao, Li Teng

et al.

Frontiers in Neurology, Journal Year: 2024, Volume and Issue: 15

Published: Oct. 2, 2024

Patients recovering from stroke experience a variety of symptoms that present as synergistic and mutually reinforcing "symptom cluster," rather than singular symptoms. In this study, we researched systematic analyzed these symptom clusters, including core bridge symptoms, to help determine the relationships between identify key targets, providing new approach for formulating precise management interventions.

Language: Английский

Citations

0
Symptoms associated with concurrent chemoradiotherapy in patients with cervical cancer: application of latent profile analysis and network analysis DOI Creative Commons

X.-H. Lu,

Lingling Zheng, Jin Xue

et al.

Asia-Pacific Journal of Oncology Nursing, Journal Year: 2024, Volume and Issue: 12, P. 100649 - 100649

Published: Dec. 28, 2024

This study aims to explore symptom subgroups and influencing factors among patients undergoing concurrent chemoradiotherapy (CCRT) for cervical cancer, construct a network, identify core symptoms within the overall sample its various subgroups. A cross-sectional survey was conducted with 378 CCRT cancer from June 2023 May 2024 at tertiary hospital in Anhui Province. Participants completed General Information Questionnaire, Symptom Assessment Scale Patients Undergoing Intermediate Advanced Cervical Cancer, Dyadic Coping Inventory. Latent profile analysis (LPA) identified subgroups, while multivariate logistic regression examined influences on these networks were developed using R language analyze centrality indices symptoms. classified into three subgroups: low burden (n ​= ​200, 52.91%), moderate prominent intestinal response ​75, 19.84%), high ​103, 27.25%). Multivariate indicated that age, tumor stage, chemotherapy frequency, dyadic coping (DC) predictive of subgroup membership (P ​< ​0.05). Network revealed sadness (r s ​1.320) as sample, nausea ​0.801) group, vomiting ​0.705, 0.796) both prominence group group. Three exist sadness, nausea, Health care professionals should provide individualized management tailored

Language: Английский

Citations

0