Asia-Pacific Journal of Oncology Nursing最新文献

{"title":"Latent profile analysis of self-management and its association with quality of life differences in patients with cancer treated with immune checkpoint inhibitors","authors":"Ruiqi Lu ,&nbsp;Zhihui Yang ,&nbsp;Jingxia Miao ,&nbsp;Qian Xu ,&nbsp;Lili Zhang","doi":"10.1016/j.apjon.2025.100687","DOIUrl":"10.1016/j.apjon.2025.100687","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to explore latent profiles of self-management ability in patients with cancer treated with immune checkpoint inhibitors, analyze each subgroup's characteristics, and determine the relationship between self-management and quality of life.</div></div><div><h3>Methods</h3><div>This cross-sectional study included 393 patients treated with immune checkpoint inhibitors. The participants completed questionnaires containing sociodemographic information, the Functional Assessment of Cancer Therapy-Immune Checkpoint Modulator (FACT-ICM), the Cancer Patient Self-management Evaluation Scale, and the Medical Coping Modes Questionnaire. Latent profile analysis was used to examine potential latent groups of self-management. Multivariate logistic regression was used to analyze the sociodemographic variables in each profile. Kruskal-Wallis H-rank sum test was used to explore the relationships between self-management profiles and quality of life.</div></div><div><h3>Results</h3><div>The self-management abilities of the patients treated with immune checkpoint inhibitors were grouped into three latent profiles: “low self-management” (16.8%), “average self-management-avoidance of information” (44.3%), and “high self-management” (38.9%). The coping modes, educational levels, medical insurances, age, monthly family income per capita, and communication styles with health care professionals post-discharge significantly influenced the distribution of self-management. There were significant differences in the FACT-ICM scores across all three groups, except for the emotional well-being dimension.</div></div><div><h3>Conclusions</h3><div>The patients with cancer treated with immune checkpoint inhibitors exhibit three distinct self-management profiles. To enhance patients' quality of life, healthcare professionals should develop targeted self-management strategies focusing on information management and communication between patients and healthcare providers.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100687"},"PeriodicalIF":2.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143815004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Healthcare professionals' perspectives on the reproductive management of young women with breast cancer: A qualitative study based on social-ecological system theory","authors":"Jiajia Qiu ,&nbsp;Jing Li ,&nbsp;Lichen Tang ,&nbsp;Ping Li ,&nbsp;Mingxuan Cai ,&nbsp;Chenxi Zhu","doi":"10.1016/j.apjon.2025.100686","DOIUrl":"10.1016/j.apjon.2025.100686","url":null,"abstract":"<div><h3>Objective</h3><div>To explore the perspectives of healthcare professionals involved in the reproductive management of young women with breast cancer based on social-ecological systems.</div></div><div><h3>Methods</h3><div>A descriptive qualitative study was conducted. Purposive sampling was used to select 15 healthcare professionals from breast cancer specialties between January and June 2024. Face-to-face in-depth interviews were conducted. Interview data were analyzed using Colaizzi's content analysis method.</div></div><div><h3>Results</h3><div>Three themes emerged from the data: the reproductive decision-making process needs to involve multiple parties; multiple supports should be provided during reproductive management; and reproductive management requires multi-system preparedness.</div></div><div><h3>Conclusions</h3><div>From the patient's perspective, we should respect their will, consider family decisions, and strengthen learning abilities. From the professionals' perspective, we should improve the reproductive management awareness of healthcare professionals, their professional learning ability and their cancer reproductive consultation and communication abilities. At the organizational level, social resources could be integrated to provide multidisciplinary information and multi-dimensional emotional support to promote smooth reproductive decision-making in young patients with breast cancer to improve their quality of life.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100686"},"PeriodicalIF":2.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge, attitudes, and practices toward nutritional management among patients with gastrointestinal cancer: A cross-sectional study","authors":"Xiaoxu Zhi ,&nbsp;Jie Chen ,&nbsp;Liu Yang ,&nbsp;Sheng Li ,&nbsp;Liuliu Zhang ,&nbsp;Yun Zhao ,&nbsp;Min Wang ,&nbsp;Zhiyan Zhou ,&nbsp;Funa Yang ,&nbsp;Zhie Gu ,&nbsp;Xiaoju Zhang ,&nbsp;Huizi Tian ,&nbsp;Qin Xu ,&nbsp;Jun Yao","doi":"10.1016/j.apjon.2025.100688","DOIUrl":"10.1016/j.apjon.2025.100688","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to evaluate the knowledge, attitudes, and practices (KAP) regarding nutritional management among patients with gastrointestinal cancer.</div></div><div><h3>Methods</h3><div>A descriptive cross-sectional study was conducted from December 2023 to May 2024 across hospitals in Jiangsu, Henan, Shanghai, and Tianjin, China. Participants completed questionnaires that collected demographic data and assessed their KAP toward nutritional management.</div></div><div><h3>Results</h3><div>A total of 1239 valid questionnaires were analyzed. Among the participants, 769 (62.1%) were male, and 452 (36.5%) had been diagnosed with gastrointestinal cancer for less than six months. The proportion of participants demonstrating adequate knowledge, positive attitudes, and proactive practices were 1018 (82.1%), 328 (26.4%), and 403 (32.5%), respectively. Multivariate logistic regression identified several factors independently associated with proactive practices, including adequate knowledge, lack of insurance, a gastrointestinal tumor duration of 2–3 years or more, no doubts about nutritional management, absence of nutritional screening, and having others as primary caregivers. Structural equation modeling revealed direct effects of knowledge on both attitude (<em>β</em> ​= ​0.308, <em>P</em> ​&lt; ​0.001) and practice (<em>β</em> ​= ​0.475, <em>P</em> ​&lt; ​0.001), as well as of attitude on practice (<em>β</em> ​= ​0.286, <em>P</em> ​&lt; ​0.001). Additionally, knowledge indirectly influenced practice through attitude (<em>β</em> ​= ​0.088, <em>P</em> ​&lt; ​0.001).</div></div><div><h3>Conclusions</h3><div>While most gastrointestinal cancer patients demonstrated adequate knowledge regarding nutritional management, their attitudes were predominantly negative, and their practices were largely inactive. These findings highlight a critical need for targeted educational interventions to bridge knowledge gaps and encourage more active engagement with nutritional guidelines.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100688"},"PeriodicalIF":2.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An ideal portrait of the professional competence of clinical research nurses: A qualitative study","authors":"Heng Yang ,&nbsp;Yipei Chen ,&nbsp;Xin Peng","doi":"10.1016/j.apjon.2025.100682","DOIUrl":"10.1016/j.apjon.2025.100682","url":null,"abstract":"<div><h3>Objective</h3><div>This study aims to identify and define the ideal professional competencies of Clinical Research Nurses (CRNs) in China, focusing on the essential knowledge, skills, and personal attributes required for effective practice in clinical trials.</div></div><div><h3>Methods</h3><div>Interviews were conducted with CRNs, Nurse Managers (NMs), Principal Investigators (PIs), Sub-Investigators (SIs), Clinical Research Coordinators (CRCs), Clinical Research Associates (CRAs), and subjects. Thematic analysis was performed using Colaizzi's seven-step method to analyze interview data and identify key competencies.</div></div><div><h3>Results</h3><div>The study identified four primary themes that characterize the ideal CRN profile: (1) theoretical knowledge ability, (2) practical technical ability, (3) professional quality and ability, and (4) personal traits. A total of 21 specific indicators were delineated, reflecting the diverse expectations of various stakeholders in clinical trials.</div></div><div><h3>Conclusions</h3><div>The findings highlight the multifaceted nature of CRN competencies, emphasizing the importance of comprehensive training programs tailored to the needs of CRNs. This study provides a foundational framework for enhancing CRN training and professional development in China.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100682"},"PeriodicalIF":2.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"“Don't need resuscitate” in palliative care: Ethical challenge or obstacle to a good death","authors":"Mohadese Babaie ,&nbsp;Azam Shirinabadi Farahani ,&nbsp;Maryam Rassouli","doi":"10.1016/j.apjon.2025.100681","DOIUrl":"10.1016/j.apjon.2025.100681","url":null,"abstract":"","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100681"},"PeriodicalIF":2.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychometric validation of the Chinese version of the Edmonton-33 scale in patients with head and neck cancer","authors":"Yumin Zhang ,&nbsp;Min Zhou ,&nbsp;Yu Liu ,&nbsp;Li Chen ,&nbsp;Sanlan Guo ,&nbsp;Lin Zhang","doi":"10.1016/j.apjon.2025.100685","DOIUrl":"10.1016/j.apjon.2025.100685","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to translate the Edmonton-33 scale (E−33) into Chinese and evaluate its reliability and validity in patients with head and neck cancer (HNC).</div></div><div><h3>Methods</h3><div>In Phase 1, the E−33 was translated from English to Chinese using the Brislin double-back translation method. Content validity was evaluated by a panel of experts, and a pilot test was conducted with a small sample of HNC patients. In Phase 2, a cohort of 510 patients from Henan and Hubei provinces was recruited. Psychometric properties were assessed through item analysis; and reliability testing (including Cronbach's alpha, test-retest reliability, and split-half reliability), as well as construct validity (using exploratory and confirmatory factor analysis).</div></div><div><h3>Results</h3><div>The item-level content validity index (I–CVI) ranged from 0.833 to 1.000, and the scale-level content validity index (S–CVI/Ave) was 0.965. The Cronbach's alpha, the test-retest reliability coefficient, and the split-half reliability values were 0.922, 0.973, and 0.971, respectively. Four main factors were identified using exploratory factor analysis, explaining 77.07% of the total variance. Confirmatory factor analysis showed good fit indices: χ²/df ​= ​1.626, RMSEA ​= ​0.048, NFI ​= ​0.936, RFI ​= ​0.930, IFI ​= ​0.974, TLI ​= ​0.972, and CFI ​= ​0.974.</div></div><div><h3>Conclusions</h3><div>The Chinese version of the Edmonton-33 scale (CE-33) demonstrated high reliability and validity, suggesting its potential as a valuable self-report tool for assessing functional outcomes in Chinese-speaking HNC patients.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100685"},"PeriodicalIF":2.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143815002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network analysis of quality of life among young and middle-aged Korean cancer survivors","authors":"Yoonjung Kim ,&nbsp;Dahee Wi ,&nbsp;Eunjin Kim ,&nbsp;Jiae Lee","doi":"10.1016/j.apjon.2025.100684","DOIUrl":"10.1016/j.apjon.2025.100684","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to identify and compare the network structure of quality of life factors among cancer survivors to inform tailored interventions.</div></div><div><h3>Methods</h3><div>A cross-sectional study was conducted using data from 330 cancer survivors aged 18–64 years, drawn from the 2019–2021 Korea National Health and Nutrition Examination Survey (KNHANES). Participants were categorized into two groups: cancer survivors with current cancer and those without. Network analysis using the EBICglasso algorithm was performed to assess eight quality of life (QoL) components measured by the Health-related Quality of Life Instrument with 8 Items (HINT-8) scale: climbing stairs, pain, vitality, work ability, depression, memory, sleep quality, and happiness.</div></div><div><h3>Results</h3><div>The network analysis revealed distinct patterns between the two groups. Among survivors with current cancer, depression, work ability, and vitality were the most central QoL components, suggesting a need for targeted psychological and occupational support. In contrast, survivors without current cancer exhibited a network where work ability, pain, and climbing stairs (physical function) played a dominant role, emphasizing the importance of pain management and functional rehabilitation. Work ability emerged as a critical determinant in both groups, indicating its sustained impact throughout the survivorship continuum. Additionally, the network structure in survivors without current cancer showed greater interconnectedness, reflecting the complex interplay of long-term survivorship challenges.</div></div><div><h3>Conclusions</h3><div>The study highlights the need for personalized, stage-specific interventions in cancer survivorship. Work remained central in both groups, emphasizing its ongoing impact on quality of life throughout the survivorship journey. While psychological support is crucial to cancer survivors with current cancer due to the centrality of depression, long-term pain management becomes increasingly important post-treatment. These findings provide valuable insights for nursing practice, suggesting that tailored interventions addressing work-related challenges, psychological distress, and chronic symptom management could improve quality of life and facilitate survivors' reintegration into daily life.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100684"},"PeriodicalIF":2.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence-assisted machine learning models for predicting lung cancer survival","authors":"Yue Yuan ,&nbsp;Guolong Zhang ,&nbsp;Yuqi Gu ,&nbsp;Sicheng Hao ,&nbsp;Chen Huang ,&nbsp;Hongxia Xie ,&nbsp;Wei Mi ,&nbsp;Yingchun Zeng","doi":"10.1016/j.apjon.2025.100680","DOIUrl":"10.1016/j.apjon.2025.100680","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to evaluate the feasibility of large language model-Advanced Data Analysis (ADA) in developing and implementing machine learning models to predict survival outcomes for lung cancer patients, with a focus on its implications for nursing practice.</div></div><div><h3>Methods</h3><div>A retrospective study design was employed using a dataset of lung cancer patients. Data included sociodemographic, clinical, treatment-specific, and comorbidity variables. Large language model-ADA was used to build and evaluate three machine learning models. Model performance was validated, and results were presented using calibration plots.</div></div><div><h3>Results</h3><div>Of 737 patients, the survival rate of this cohort was 73.3%, with a mean age of 59.32 years. Calibration plots indicated robust model reliability across all models. The Random Forest model demonstrated the highest predictive accuracy among the models. Most critical features identified were preoperative white blood cells (2.2%), preoperative lung function of Forced Expiratory Volume in one second (2.1%), preoperative arterial oxygen saturation (1.9%), preoperative partial pressure of oxygen (1.7%), preoperative albumin (1.6%), preoperative preparation time (1.5%), age at admission (1.5%), preoperative partial pressure of carbon dioxide (1.5%), preoperative hospital stay days (1.5%), and postoperative total days of thoracic tube drainage (1.4%).</div></div><div><h3>Conclusions</h3><div>Large language model-ADA effectively facilitates the development of machine learning models for lung cancer survival prediction, enabling non-technical health care professionals to harness the power of advanced analytics. The findings underscore the importance of preoperative factors in predicting outcomes, while also highlighting the need for external validation across diverse settings.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100680"},"PeriodicalIF":2.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Home-based symptom management for patients with malignant lymphoma undergoing intermittent chemotherapy: A prospective observational study using network analysis","authors":"Qinglu Li ,&nbsp;Lu Yang ,&nbsp;Nan Wang ,&nbsp;Wenting Shi ,&nbsp;Lei Luo ,&nbsp;Hui Chen ,&nbsp;Guorong Wang","doi":"10.1016/j.apjon.2025.100683","DOIUrl":"10.1016/j.apjon.2025.100683","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to explore the symptom burden of patients with malignant lymphoma at home during the intermittent periods of chemotherapy and identify core symptoms using network analysis.</div></div><div><h3>Methods</h3><div>A prospective observational study was conducted, recruiting 208 patients from December 2019 to December 2020. Symptom burden was assessed using the MD Anderson Symptom Inventory-Chinese version (MDASI-C) at three time points during the first to third chemotherapy cycles (T1–T3). Symptom networks were constructed for each time point, and centrality indices were analyzed to identify core and bridge symptoms. Network comparison tests (NCT) were used to examine changes in symptom interconnectivity over time.</div></div><div><h3>Results</h3><div>A total of 208 participants were included in the data analysis. Fatigue and vomiting were the most prevalent and severe symptoms reported at all time points, respectively. In the presented symptom network, lack of appetite (<em>r</em>_<em>s</em> ​= ​1.13), sadness (<em>r</em>_<em>s</em> ​= ​1.20), and nausea (<em>r</em>_<em>s</em> ​= ​1.13) were the core symptoms of T1, T2, and T3, respectively. Lack of appetite (<em>r</em>_<em>b</em> ​= ​21, <em>r</em>_<em>c</em> ​= ​0.01), distress (<em>r</em>_<em>b</em> ​= ​25, <em>r</em>_<em>c</em> ​= ​0.01), and dry mouth (<em>r</em>_<em>b</em> ​= ​11, <em>r</em>_<em>c</em> ​= ​0.01) were identified as bridge symptoms at T1, T2, and T3, respectively. NCT results indicated no statistical differences in the global symptom network strength and overall edge weight among the three time points, while sadness exhibited higher betweenness and closeness in the network of T2 (T1 vs. T2, <em>P</em>_<em>c</em> ​= ​0.03, <em>P</em>_<em>b</em> ​= ​0.03; T2 vs. T3, <em>P</em>_<em>c</em> ​= ​0.01, <em>P</em>_<em>b</em> ​= ​0.03)</div></div><div><h3>Conclusions</h3><div>The findings highlight lack of appetite, sadness, and nausea as critical targets for symptom management in patients with malignant lymphoma undergoing intermittent chemotherapy. Caregivers and healthcare providers should focus on these symptoms to improve home-based symptom management and enhance patient well-being.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100683"},"PeriodicalIF":2.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143825496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning models to predict 6-month mortality risk in home-based hospice patients with advanced cancer","authors":"Wan Cheng ,&nbsp;Jianwei Zheng ,&nbsp;Yuanfeng Lu ,&nbsp;Guojuan Chen ,&nbsp;Zheng Zhu ,&nbsp;Hong Wu ,&nbsp;Yitao Wei ,&nbsp;Huimin Xiao","doi":"10.1016/j.apjon.2025.100679","DOIUrl":"10.1016/j.apjon.2025.100679","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to construct predictive models using five different machine learning algorithms for predicting 6-month mortality risk among home-based hospice patients with advanced cancer.</div></div><div><h3>Methods</h3><div>This population-based retrospective prognostic study examined data from 7023 patients in a home-based hospice center. Various algorithms including logistic regression, random forest, XGBoost, support vector machine, and neural network were implemented in this study. The model performance and effectiveness were assessed using sensitivity, specificity, accuracy, the area under the curve (AUC), and F1 Score. Additionally, a nomogram was developed to calculate individualized risk probabilities, enhancing clinical utility.</div></div><div><h3>Results</h3><div>Among the five types of predictive models, the logistic regression model achieved an AUC of 0.754 (95% CI: 0.721–0.786) in the test dataset, outperforming other machine learning algorithms. The nomogram developed from the logistic regression model included 10 independent risk factors for 6-month mortality. The Hosmer–Lemeshow test showed no significant difference between the predicted and observed outcomes (training set: 12.646, <em>P</em> ​= ​0.13; testing set: 3.807, <em>P</em> ​= ​0.87). Clinical decision curve analysis indicated that the model provided substantial net benefits across a wide range of thresholds.</div></div><div><h3>Conclusions</h3><div>Our study demonstrated that routinely collected healthcare data on the first home visit have the potential to help screen high-risk patients, which may provide evidence for targeted hospice care.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100679"},"PeriodicalIF":2.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}