Effect of nonpharmacological interventions on nutrition status, complications and quality of life in head and neck cancer patients undergoing radiotherapy: A systematic review and meta-analysis.

PURPOSE: To evaluate the effect of nonpharmacological therapies on nutrition status, complications and quality of life in head and neck cancer patients and to provide a basis for clinical practice. METHODS: This systematic review was reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-analysis statement. Ten databases were systematically searched for all available articles from construction to November 2023. Two researchers independently conducted literature screening, data extraction and quality evaluation. Cochrane Review Manager 5.3 was used for meta-analysis. RESULTS: Finally, 27 RCT studies including 2814 patients with head and neck cancer were included. Five categories of interventions were used: nutritional support, exercise, swallowing function training, psychological intervention and low-level laser therapy. Nonpharmacological interventions can improve body weight loss in patients with HNC at the end of treatment (MD: 1.66 kg; 95% CI: 0.80 to 2.51), and subgroup analysis showed that nutritional support, psychological intervention and low-level laser therapy were effective. Nonpharmacological interventions can also ameliorate decreases in BMI (MD: 0.71; 95% CI: 0.16 to 1.26) and reduce the incidence of malnutrition (RR: 0.76; 95% CI: 0.67 to 0.86), oral mucositis (RR: 0.54; 95% CI: 0.37 to 0.80) and gastrointestinal complications (RR: 0.61; 95% CI: 0.38 to 0.96) during radiotherapy; however, no significant differences were found in other complications and quality of life. CONCLUSION: Nonpharmacological interventions can improve the nutrition status of patients with head and neck cancer and reduce the incidence of severe oral mucositis and gastrointestinal complications during radiotherapy but have no significant impact on quality of life.

Development and comparison of machine-learning models for predicting prolonged postoperative length of stay in lung cancer patients following video-assisted thoracoscopic surgery.

Objective: This study aimed to develop models for predicting prolonged postoperative length of stay (PPOLOS) in lung cancer patients undergoing video-assisted thoracoscopic surgery (VATS) by utilizing machine-learning techniques. These models aim to offer valuable insights for clinical decision-making. Methods: This retrospective cohort study analyzed a dataset of lung cancer patients who underwent VATS, identifying 25 numerical features and 45 textual features. Three classification machine-learning models were developed: XGBoost, random forest, and neural network. The performance of these models was evaluated based on accuracy (ACC) and area under the receiver operating characteristic curve, whereas the importance of variables was assessed using the feature importance parameter from the random forest model. Results: Of the 6767 lung cancer patients, 1481 patients (21.9%) experienced a postoperative length of stay of > 4 days. The majority were male (4111, 60.8%), married (6246, 92.3%), and diagnosed with adenocarcinoma (4145, 61.3%). The Random Forest classifier exhibited superior prediction performance with an area under the curve (AUC) of 0.792 and ACC of 0.804. The calibration plot revealed that all three classifiers were in close alignment with the ideal calibration line, indicating high calibration reliability. The five most critical features identified were the following: surgical duration (0.116), age (0.066), creatinine (0.062), hemoglobin (0.058), and total protein (0.054). Conclusions: This study developed and evaluated three machine-learning models for predicting PPOLOS in lung cancer patients undergoing VATS. The findings revealed that the Random Forest model is most accurately predicting the PPOLOS. Findings of this study enable the identification of crucial determinants and the formulation of targeted interventions to shorten the length of stay among lung cancer patients after VATS, which contribute to optimize the allocation of healthcare resources.

Health benefits of yoga for cancer survivors: An updated systematic review and meta-analysis.

Objective: To evaluate the effects of yoga on health-related outcomes [i.e., physical function, mental health, and overall quality of life (QOL)] of cancer survivors via a systematic review and meta-analysis of randomized controlled trials (RCTs) over the past 5 years across cancer types. Methods: An updated systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. RCTs published from January 1, 2018, to February 23, 2023, were searched in five English databases (PubMed, The Cochrane Library, ISI, PsycINFO, and CINAHL), three Chinese databases (Wan Fang, China National Knowledge Infrastructure, and Chinese Biomedical Literature Database), and three English clinical trials registry platforms (International Clinical Trials Registry Platform, ClinicalTrials.gov, and EU Clinical Trials Register). Results: A total of 34 RCTs were included in this updated review. Yoga benefited the physical function, mental health, and overall QOL of cancer survivors. The effect size of yoga for most physical and mental health-related outcomes was relatively small, but that for the QOL was generally large. The impact of yoga on the QOL of cancer survivors ranged from moderate to high. Conclusions: Yoga has health benefits for cancer survivors and could therefore be used as an optional supportive intervention for cancer-related symptom management.

Folate-receptor-targeted co-self-assembly carrier-free gemcitabine nanoparticles loading indocyanine green for chemo-photothermal therapy.

The carrier-free chemo-photothermal therapy has become a promising strategy to improve anti-cancer therapeutic efficacy owing to the combination of chemotherapy and photothermal therapy, with improved chemotherapy drug pharmacodynamics and pharmacokinetics, high drug loading, and reduced toxicity. We designed a novel carrier-free targeting nanoparticles, co-self-assembled amphiphilic prodrugs 3',5'-dioleoyl gemcitabine (DOG), and tumor-targeted γ-octadecyl folate (MOFA), with encapsulated US Food and Drug Administration (FDA)-approved photosensitizer indocyanine green (ICG) for synergistic chemo-photothermal therapy. The DOG linking oleic acid to the sugar moiety of gemcitabine (GEM) showed better self-assembly ability among GEM amphiphilic prodrugs linking different fatty acids. The readily available and highly reproducible 3',5'-dioleoyl gemcitabine/γ-octadecyl folate/indocyanine green (DOG/MOFA/ICG) nanoparticles were prepared by reprecipitation and showed nano-scale structure with mono-dispersity, great encapsulation efficiency of ICG (approximately 74%), acid- and laser irradiation-triggered GEM release in vitro and sustained GEM release in vivo after intravenous administration as well as excellent temperature conversion (57.0°C) with near-infrared laser irradiation. The combinational DOG/MOFA/ICG nanoparticles with near-infrared laser irradiation showed better anti-tumor efficacy than individual chemotherapy or photothermal therapy, with very low hemolysis and inappreciable toxicity for L929 cells. This co-self-assembly of the ICG and the chemotherapy drug (GEM) provides a novel tactic for the rational design of multifunctional nanosystems for targeting drug delivery and theranostics.

Evolving landscape of research on cancer-related cognitive impairment: A bibliometric analysis.

Objective: This study describes the state of the art in the field of cancer-related cognitive impairment (CRCI) to facilitate research opportunities in future CRCI research. Methods: Five databases were searched: PubMed, Web of Science, Cochrane Library, Cumulative Index to Nursing and Allied Health (CINAHL), and PsycINFO, from inception to August 20, 2022. Python, VOSviewer, and CiteSpace software were used for data preprocessing and analysis. Results: The published articles were predominantly from the United States, followed by China and Canada. Breast cancer and brain tumors were the dominant cancer types. The study population consisted mainly of adult cancer survivors. Prospective and multicenter studies were the most frequently used study designs. Keyword co-occurrence and mutation analysis indicated major themes: drug therapy was the most common treatment cluster, and adverse effects were another major cluster. The etiology of CRCI was a research hotspot and included the exploration of chemotherapy-associated and psychosocial factors by using measurement tools, such as neuropsychological tests and treatment outcomes. Conclusions: This study's findings highlight CRCI as a major research area, on the basis of the significantly increasing number of annual publications. Keyword co-occurrence analysis provided a quantitative visualization of the current research status for CRCI, but this method cannot provide in-depth qualitative insights explaining the potential emerging trends in this field.

A self-administered immersive virtual reality tool for assessing cognitive impairment in patients with cancer.

Objective: This study was aimed at exploring the feasibility and validity of a self-administered immersive virtual reality (VR) tool designed to assess cognitive impairment in patients with cancer. Methods: In a cross-sectional survey study, an immersive tool was used to rate the previously recommended core assessment domains of cancer-related cognitive impairment-comprising attention, verbal learning memory, processing speed, executive function and verbal fluency-via an interactive VR scenario. Results: A total of 165 patients with cancer participated in this study. The participants' mean age was 47.74 years (SD â€‹= â€‹10.59). Common cancer types included lung, liver, breast and colorectal cancer, and most patients were in early disease stages (n â€‹= â€‹146, 88.5%). Participants' performance in the VR cognition assessment showed a moderate to strong positive correlation with their paper-and-pencil neurocognitive test results (r â€‹= â€‹0.34-0.76, P â€‹< â€‹0.001), thus indicating high concurrent validity of the immersive VR cognition assessment tool. For all participants, the mean score for the VR-based cognition assessment was 5.41 (SD â€‹= â€‹0.70) out of a potential maximum of 7.0. The mean simulation sickness score for the VR-based tool, as rated by the patients, was 0.35 (SD â€‹= â€‹0.19), thereby indicating that minimal simulation sickness occurred during the VR-assisted cognition assessment. Conclusions: Given its demonstrated validity, and the patients' high presence scores and minimal sickness scores, this VR-based cognition assessment tool is a feasible and acceptable instrument for measuring cognitive impairment in patients with cancer. However, further psychometric assessments should be implemented in clinical settings.

Chinese Translation and Cross-Cultural Adaptation of the Return-to-Work Self-Efficacy Scale among Chinese Female Breast Cancer Survivors.

Breast cancer is the leading cancer type among women globally. Since breast cancer has a high survival rate, most survivors are likely to return to work (RTW). In recent years, breast cancer cases have risen significantly in younger age groups. As self-efficacy is an important factor in the success of RTW, this study performed a translation and cross-cultural adaptation of the Chinese version of the Return-To-Work Self-Efficacy Scale (CRTWSE-19) and examined its psychometric properties in patients with breast cancer. This validation study followed standard guidelines, including forward translation, back translation, cross-cultural adaptation, and psychometric testing. The results of this study show that the CRTWSE-19 met reliability standards, including high internal reliability for the total scores and subscales. An exploratory factor analysis of 19 items extracted 3 factors showing consistency with the original version of the RTWSE-19. Criterion validity was demonstrated by comparing subdomains with the Fear of Cancer Recurrence Inventory. Furthermore, the known-group validity was studied by comparing mean scores among the unemployed group and the employed group. We conclude that the CRTWSE-19 has very good screening accuracy and is able to discriminate between working and unemployed populations. It can facilitate health care professionals in triaging, planning, and evaluating interventions in clinical practice.

Dignity therapy, psycho-spiritual well-being and quality of life in the terminally ill: systematic review and meta-analysis.

OBJECTIVES: Dignity therapy (DT) is a brief, individualised psychotherapy that aims to alleviate psychosocial and spiritual distress in the final stages of life. It is unknown yet whether DT can enhance sense of dignity and improve psychological and spiritual well-being as well as quality of life of terminally ill patients. METHODS: We searched PubMed, EMBASE, CINAHL plus, ProQuest Health & Medical Complete, PsycINFO and the Cochrane Library, as well as Chinese databases including Weipu Data, Wanfang Data and China National Knowledge Infrastructure from inception to 30 April 2021, for randomised controlled trials (RCTs) assessing the effects of DT on dignity, psycho-spiritual well-being and quality of life of terminally ill patients receiving palliative care. RESULTS: We identified 507 unique records, and included 9 RCTs (871 participants). Comparator was standard palliative care. DT did not improve terminally ill patients' sense of dignity (p=0.90), hope (p=0.15), spiritual well-being (p=0.99) and quality of life (p=0.23). However, DT reduced anxiety and depression after intervention (standardised mean difference, SMD=-1.13, 95% CI (-2.21 to -0.04), p=0.04; SMD=-1.22, 95% CI (-2.25 to -0.18), p=0.02, respectively) and at 4 weeks post-intervention (SMD=-0.89, 95% CI (-1.71 to -0.07), p=0.03; SMD=-1.26, 95% CI (-2.38 to -0.14), p=0.03, respectively). CONCLUSION: DT can be offered as a psychological intervention for terminally ill patients to reduce their anxiety and depression. More studies are needed to further evaluate the effects of DT on terminally ill patients' dignity, spiritual well-being and quality of life.

Comparison of machine learning models for predicting the risk of breast cancer-related lymphedema in Chinese women.

Objective: Predictive models for the occurrence of cancer symptoms by using machine learning (ML) algorithms could be used to aid clinical decision-making in order to enhance the quality of cancer care. This study aimed to develop and validate a selection of classification models that used ML algorithms to predict the occurrence of breast cancer-related lymphedema (BCRL) among Chinese women. Methods: This was a retrospective cohort study of consecutive cases that had been diagnosed with breast cancer, stages I-IV. Forty-eight variables were grouped into five feature sets. Five classification models with ML algorithms were developed, and the models' performance and the variables' relative importance were assessed accordingly. Results: Of 370 eligible female participants, 91 had BCRL (24.6%). The mean age of this study sample was 49.89 (SD â€‹= â€‹7.45). All participants had had breast cancer surgery, and more than half of them had had a modified radical mastectomy (n â€‹= â€‹206, 55.5%). The mean follow-up time after breast cancer surgery was 28.73 months (SD â€‹= â€‹11.71). Most of the tumors were either stage I (n â€‹= â€‹49, 31.2%) or stage II (n â€‹= â€‹252, 68.1%). More than half of the sample had had postoperative chemotherapy (n â€‹= â€‹227, 61.4%). Overall, the logistic regression model achieved the best performance in terms of accuracy (91.6%), precision (82.1%), and recall (91.4%) for BCRL. Although this study included 48 predicting variables, we found that the five models required only 22 variables to achieve predictive performance. The most important variable was the number of positive lymph nodes, followed in descending order by the BCRL occurring on the same side as the surgery, a history of sentinel lymph node biopsy, a dietary preference for meat and fried food, and an exercise frequency of less than three times per week. These factors were the most influential predictors for enhancing the ML models' performance. Conclusions: This study found that in the ML training dataset, the multilayer perceptron model and the logistic regression model were the best discrimination models for predicting the outcome of BCRL, and the k-nearest neighbors and support vector machine models demonstrated good calibration performance in the ML validation dataset. Future research will need to use large-sample datasets to establish a more robust ML model for predicting BCRL deeply and reliably.

The use of immersive virtual reality for cancer-related cognitive impairment assessment and rehabilitation: A clinical feasibility study.

Objective: This brief study aimed to examine the potential effects of virtual reality (VR)-assisted cognitive rehabilitation intervention on the health outcomes of patients with cancer. Methods: A single group of pre-test and post-test study designs were used. An innovative VR system was developed to assess cancer-related cognitive impairment and provide cognitive rehabilitation. The potential effects of the system were determined by measuring changes in cognitive function (learning and memory, information processing speed, executive function, and verbal fluency) and the severity of depression, anxiety, and insomnia. Results: Nine subjects completed the entire VR intervention and were included in the analysis. The participants' mean age was 43.3 years (standard deviation, 8.9 years). The VR-based cognitive intervention significantly improved the subjective cognitive measures of perceived cognitive impairment and perceived cognitive ability (P â€‹= â€‹0.01 and P â€‹< â€‹0.01, respectively). The intervention also improved the objective cognitive measures of verbal learning memory as measured using the Auditory Verbal Learning Test (eg., P â€‹< â€‹0.01 for 5-min delay recall), information processing speed as measured using the trail-making test-A (P â€‹= â€‹0.02) and executive function as measured using the trail-making test-B (P â€‹= â€‹0.03). Only the subtest of delayed recall showed no statistically significant difference after the intervention (P â€‹= â€‹0.69). The VR-based psychological intervention significantly reduced the severity of sleep disorders (P â€‹< â€‹0.01). Conclusions: The use of immersive VR was shown to have potential effects on improving cognitive function for patients with cancer. Future studies will require a larger sample size to examine the effects of immersive VR-assisted cognitive rehabilitation on the health outcomes of patients with cancer.

Symptom clusters and their predictors in patients with lung cancer and treated with programmed cell death protein 1 immunotherapy.

Objective: The aims of this study were to examine the symptom severity and interference among patients with lung cancer treated with PD-1 immunotherapy, explore whether those symptoms were clustered together, and identify factors associated with symptom clusters. Methods: A cross-sectional study was conducted. Data were collected by demographic and clinical characteristic questionnaires and the M.D. Anderson Symptom Inventory Lung Cancer Module. Symptom clusters were identified using exploratory factor analysis, and stepwise linear regression was applied to analyze the factors affecting the symptom clusters. Results: A total of 148 patients with lung cancer treated with PD-1 immunotherapy participated in this study. The overall symptom burdens of these patients were mainly at a mild level. The patient symptom clusters identified in this study were a general cluster, a treatment-related cluster, a pulmonary cluster, a gastrointestinal cluster, and a neural cluster. The patients' Karnofsky performance status (KPS) score (ߠ​= â€‹-2.758, P â€‹< â€‹0.001) and having a history of chemotherapy (ߠ​= â€‹4.384, P â€‹= â€‹0.001) were significant predictors of the general cluster. Their KPS scores (ߠ​= â€‹-1.202, P â€‹< â€‹0.001) and having a history of chemotherapy (ߠ​= â€‹-1.957, P â€‹= â€‹0.001) were significant predictors of the pulmonary cluster. Their monthly income (ߠ​= â€‹-0.316, P â€‹= â€‹0.030) and KPS scores (ߠ​= â€‹-0.357, P â€‹= â€‹0.045) were significant predictors of the gastrointestinal cluster. Having a history of chemotherapy (ߠ​= â€‹1.868, P â€‹< â€‹0.001) was the predictor of the neural cluster. Conclusions: The symptom burdens of patients with lung cancer and treated with PD-1 immunotherapy were at a mild level and appeared to be clustered. In addition, because the symptoms that comprise a cluster are interrelated, the diagnosis and management of each symptom in a cluster should not be performed in isolation, and each symptom in a cluster should be treated either simultaneously or in an orderly manner.

Neuropsychological Interventions for Cancer-Related Cognitive Impairment: A Network Meta-Analysis of Randomized Controlled Trials.

The aim of this network meta-analysis was to evaluate the comparative effects of neuropsychological interventions for cancer-related cognitive impairment (CRCI), and to rank the best intervention options for adult cancer patients with CRCI. Twenty-seven eligible randomized controlled trials (RCTs) were searched, and a total of six interventions identified: cognitive behavioral therapies (CBT), cognitive rehabilitation (CR), cognitive training (CT), meditation/mindfulness-based interventions, psychoeducation, and supportive care. In terms of effectiveness, the relative effect size of CBT, CR, and CT in managing subjective cognition had statistically significant differences - 0.94 (0.43-1.44), 0.54 (0.03-1.05), and 0.47 (0.13-0.81), respectively. The most effective interventions to manage the objective cognition of attention were meditation or mindfulness-based interventions: intervention effect size was 0.58 (0.24-0.91). The relative effect size of CT had a statistically significant difference in managing verbal memory, and the intervention effect size was 1.16 (0.12-2.20). The relative effect size of psychoeducation in managing executive function compared with control had a statistically significant difference, which was 0.56 (0.26-0.86). For managing information processing speed, the most effective intervention was CT and the effect size was -0.58 (-1.09--0.06). This network meta-analysis found that CT is the most effective intervention for managing the objective cognition of verbal memory and processing speed; meditation/mindfulness-based interventions may be the best option for enhancing attention; psychoeducation is the most effective intervention for managing executive function; CT may be the best option for managing verbal fluency as the intervention ranking probability. For the management of subjective cognition, CBT may be the most effective intervention.

Conceptualizing problems with symptoms, function, health behavior, health-seeking skills, and financial strain in breast cancer survivors using hierarchical clustering.

PURPOSE: Determine whether a diverse set of problems experienced by breast cancer survivors (BCS) following curative treatment can be formulated into a reduced number of clusters, potentially simplifying the conceptualization of these problems. METHOD: Female BCS were recruited from four cancer hospitals in China. The Chinese translation of the Cancer Survivor Profile (CSPro) was used to measure 18 common problem areas, as supported by epidemiological and phenomenological research. The Functional Assessment of Cancer Therapy-Breast (FACT-B) was used to measure quality of life, as a validation of any observed groupings. Hierarchical clustering using multiple distance criteria and aggregation methods to detect patterns of problems was used. RESULTS: A total of 1008 BCS (mean 46.51 years old) living in both urban and rural areas were investigated. Hierarchical cluster analysis identified two major clusters of problems. One set was classified as "functional limitations," while the other cluster was labeled "multi-problems." Those who fell into the multi-problem cluster experienced poorer quality of life. CONCLUSION: Eighteen non-medical problems were broken down into two major clusters: (1) limitations in higher level functions required of daily life and (2) limitations in health care-seeking skills, problems with certain symptoms, unhealthy behaviors, and financial problems related to cancer. The breakdown of problem areas into these two clusters may help identify common mechanisms. IMPLICATIONS FOR CANCER SURVIVORS: In the future, the search for common clusters and the mechanisms for the many problems that breast cancer survivors and other cancer survivors can experience following primary treatment may improve how we help manage these problems in the future.

Ethical issues of smart home-based elderly care: A scoping review.

AIM: To explore current research on the ethics of smart home technologies including artificial intelligence and information technologies for elderly care by conducting a scoping review. BACKGROUND: The development of smart home technologies for care of the older adults provides potential solutions to reduce the caregiver burden within families where they are urgently needed. Building an ethical system to support the application of these technical products should be explored. METHODS: The literature search was performed in seven electronic databases. Relevant studies from January 2015 to February 2021 were selected; screening and analysis were completed independently by two researchers. RESULTS: There were a total of 15 included studies on the ethics of smart home technologies for elderly care, which focused on the following issues: privacy (information privacy and physical privacy), autonomy (independence, informed consent and user-centred control), safety guarantee, fairness and concerns about reduced human contact. CONCLUSIONS: There exist a number of ethical conflicts in the application of smart home technologies for elderly care. Therefore, it is necessary to further investigate the ethical issues with regards to the decision-making process of weighing the advantages and disadvantages of these technologies. IMPLICATIONS FOR NURSING MANAGEMENT: Efforts should be made to establish a corresponding ethical framework to ensure the sustainable development of smart, home-based elderly care. Nurses may play an important role in the design and implementation of these technologies to promote ethical awareness and practice.

Effects of aerobic, resistance, and combined exercise on metabolic syndrome parameters and cardiovascular risk factors: a systematic review and network meta-analysis.

This study examines the effects of aerobic, resistance, and combined exercise on metabolic syndrome parameters and cardiovascular risk factors, to identify the most effective way of improving metabolic syndrome and preventing cardiovascular disease. We searched EMBASE, the Cochrane Library, PubMed, MEDLINE, Ovid, the Chinese Biological Medicine Database (CBM), the Wanfang Database, the China National Knowledge Infrastructure (CNKI) database, and the Chinese Scientific Journal Database (VIP), for randomized controlled trials (RCTs), identifying 15 comparing the effects of aerobic, resistance, and combined exercise on metabolic syndrome parameters and cardiovascular risk factors (e.g., glucose, triglyceride, blood pressure, body mass index, etc.). We assessed the quality of the articles and performed a network meta-analysis with a Bayesian random effects model to synthesize direct and indirect evidence. Combined exercise was most effective at controlling glucose and total triglyceride (TG) levels. Aerobic, resistance, and combined exercise groups achieved significant effects regarding body fat. Aerobic exercise was superior to resistance exercise regarding body mass index (BMI). There was no statistically significant difference in weight, waist circumference (WC), levels of high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), insulin, systolic blood pressure (SBP), and diastolic blood pressure (DBP) among the exercise groups. Combined exercise was the best exercise scheme for improving weight, WC, DBP, TG, TC, glucose, and insulin levels. Resistance exercise was most effective at ameliorating body fat, LDL-C levels, and SBP. Aerobic exercise was the optimal way of improving BMI and HDL-C levels. This network meta-analysis suggests combined exercise is the most effective choice in improving the metabolic syndrome and cardiovascular risk parameters, whereas aerobic exercise reveals the minimum effect. Further studies should certify the role resistance exercises play in metabolic syndrome and cardiac rehabilitation.