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The diagnosis of cancer results in psychophysiological distress in patients, significantly reducing quality of life (QoL). Currently, self-management interventions based on e-health have been used to improve QoL among cancer patients, but the overall effects remain inconsistent.
To assess the impact of self-management interventions based on e-health on the QoL of cancer patients.
Studies were retrieved from six databases up to November 6, 2024. The methodological quality assessment was performed via ROB 2. Data synthesis and subgroup analyses were performed in Review Manager 5.3. Meta-regression was conducted using Stata 15.0.
Thirty RCTs were included. The results of meta-analysis revealed self-management interventions based on e-health significantly improved QoL (SMD = 0.18, 95% CI: 0.08 to 0.28, p < 0.01). Subgroup analyses showed that long-term, mixed-mode, theory-supported, or facilitator-supervised interventions were more effective, with greater improvements in QoL observed among patients with breast cancer than among other types.
Self-management interventions based on e-health were valuable supplements for enhancing the QoL of cancer patients. Intervention duration, delivery modes, cancer types, theoretical frameworks, and facilitators' involvement should be considered in the design of future interventions. However, additional high-quality studies are needed to confirm these findings.
The protocol was registered on PROSPERO (Registration number: CRD420251017709)
To assess caregiver burden and its relationship with health literacy, self-efficacy, stigma, and social support among caregivers of children with tuberculosis in Shanghai, China.
Explanatory sequential mixed-methods design.
In the quantitative phase, 132 caregivers were recruited from a Shanghai Hospital, and 21 participated in the qualitative interviews. Data were collected (April 2023–April 2025) using the Zarit Burden Interview scale, Chinese Health Literacy Scale for Tuberculosis, General Self-Efficacy Scale, Tuberculosis-related Stigma Scale, Multidimensional Scale of Perceived Social Support, and semi-structured interviews. Quantitative data were analysed using descriptive statistics and multiple regression analyses, and qualitative data were analysed using content analysis.
Most caregivers were mothers (72.7%). Burden levels were classified as mild (58.3%), moderate (27.3%), or severe (2.3%). The quantitative analysis identified lower health literacy, limited social support, reduced self-efficacy, and being a female caregiver as significant predictors. Social support partially mediated and self-efficacy mediated the effect of perceived stigma and health literacy on caregiver burden, respectively. Qualitative themes revealed psychological and physical effects, impact on social life, and coping strategies.
Caregiver burden in paediatric tuberculosis is multidimensional and influenced by complex mechanisms. Interventions should address health literacy gaps, enhance self-efficacy, strengthen social support systems, and implement targeted stigma-reduction strategies while considering developmental-stage-specific needs.
Healthcare systems should routinely assess caregiver burden, and multidisciplinary teams should be trained to provide integrated targeted support.
This study demonstrates distinct stigma pathways and comprehensively shows that caregiver burden is significantly associated with modifiable psychosocial factors. Consequently, healthcare providers should develop targeted support interventions that address both psychological and practical caregiving challenges, ultimately contributing to improved patient care outcomes and caregiver well-being in tuberculosis management.
This study adheres to the Good Reporting of A Mixed Methods Study checklist.
None.
To systematically review the evidence on diagnostic prediction models for depression in patients with breast cancer.
Systematic review.
Ten databases were searched from inception to 22 August 2025, with an updated search on 17 December 2025, to identify original studies developing and/or validating diagnostic prediction models for depression in patients with breast cancer.
Data were extracted using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) framework. Two reviewers independently assessed risk of bias and applicability of included studies using the Prediction Model Risk of Bias Assessment Tool (PROBAST).
Eleven studies were included. Reported area under the curve (AUC) values ranged from 0.784 to 0.890. All included studies were judged to be at high risk of bias, and seven raised high concerns regarding applicability. There was substantial heterogeneity in predictor selection across studies, with age, income level and family support being the most frequently reported predictors.
Although preliminary research on diagnostic prediction models for depression in patients with breast cancer has been undertaken, their methodological quality remains weak. Reporting of external validation and calibration assessment was limited. Current evidence is therefore insufficient to support their routine use in nursing practice. Future research should standardise model development and validation and strengthen the evaluation of model performance.
This review suggests that existing diagnostic prediction models for depression in patients with breast cancer are not yet sufficiently robust for routine nursing use, but may provide a reference for future nursing screening research and the optimisation of related tools.
This review synthesises the available evidence on diagnostic prediction models for depression in patients with breast cancer and provides a basis for future model development, validation and optimisation.
This review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis: Systematic Reviews and Meta-Analyses (TRIPOD-SRMA) checklist.
No patient or public contribution.
by Lin Zhang, Feng Luo, Yalin Chai, Lijie Sun, Xuan Wang, Le Yin, Congjuan Luo
Acute kidney injury (AKI) remains a major clinical challenge due to its high morbidity and mortality, with ischemia-reperfusion injury (IRI) as one of its primary causes. Severe IRI-associated AKI (IRI-AKI) can progress to irreversible renal failure, yet no effective therapies are currently available. Ferroptosis, an iron-dependent regulated cell death, has recently been implicated in the pathogenesis of IRI-AKI. Moreover, IL-22 may alleviate AKI by modulating the ferroptosis process through regulation of the P62-Keap1-Nrf2 signaling axis. In this study, we examined the protective role of the immune cytokine interleukin-22 (IL-22) in IRI-AKI and its mechanistic association with ferroptosis. Using a murine IRI model and an HK-2 cell hypoxia/reoxygenation system, we systematically assessed the impact of IL-22 treatment. IL-22 administration significantly enhanced renal function, reduced histological injury, and limited both reactive oxygen species accumulation and ferroptotic cell death. Further mechanistic studies demonstrated that IL-22 suppresses ferroptosis in vitro through an Nrf2-dependent mechanism and is associated with activation of the P62-Keap1-Nrf2 signaling pathway. These findings offer experimental evidence supporting IL-22 as a potential therapy for IRI-AKI and highlight ferroptosis modulation as a promising therapeutic strategy.by Li Yu, Xinlin Yu, Cheng Ma, Xialin Zhang, Ran Cui
BackgroundLimited-stage small cell lung cancer (LS-SCLC) has a poor prognosis despite being potentially curable with standard concurrent chemoradiotherapy. The success of immune checkpoint inhibitors (ICIs) in extensive-stage SCLC has prompted investigation into combining immunotherapy with radiotherapy for LS-SCLC. This systematic review and single-arm meta-analysis aims to synthesize the evidence on this combined modality, providing pooled estimates of efficacy and safety to inform clinical practice and future trials.
MethodsFollowing PRISMA guidelines, we systematically searched PubMed, Embase, Cochrane Library, and Web of Science through July 2025 for studies evaluating radiotherapy combined with immunotherapy in patients with LS-SCLC. The primary outcomes analyzed included pooled objective response rate (ORR), median progression-free survival (mPFS), and median overall survival (mOS).
ResultsSix studies, encompassing 487 patients, met the inclusion criteria. The pooled analysis demonstrated an ORR of 57.7% (95% CI: 24.9–90.5%), a weighted mPFS of 13.6 months (95% CI: 11.3–15.9 months), and a pooled mOS of 33.7 months (95% CI: 26.7–40.7 months). Grade 3−4 treatment-related adverse events occurred in 42.2% of patients. Subgroup analyses revealed that a concurrent treatment sequence yielded a significantly higher ORR compared to sequential approaches (77.6% vs. 65.2% for immunotherapy followed by radiation vs. 25.8% for radiation followed by immunotherapy). Radiation dose was also identified as a critical determinant of efficacy. Anti-PD-L1 agents showed a numerically higher ORR than anti-PD-1 agents (96.0% vs. 65.0%).
ConclusionThe combination of radiotherapy and immunotherapy is a promising therapeutic strategy for LS-SCLC, demonstrating encouraging efficacy outcomes that appear favorable compared to historical benchmarks for chemoradiotherapy alone. Optimizing treatment sequencing, particularly favoring a concurrent approach, is crucial for maximizing clinical benefit. These findings support further investigation in randomized controlled trials to confirm the value of this combined modality and to identify predictive biomarkers for patient selection.
To identify factors influencing hypoglycaemia in patients with type 2 diabetes mellitus (T2DM) undergoing colonoscopy and to construct a predictive model for assessing hypoglycaemia risk.
A retrospective cohort study.
We retrospectively collected data on 598 T2DM patients who underwent colonoscopy and randomised them into a developmental cohort and a validation cohort in a 7:3 ratio. We used multivariate logistic regression to develop a predictive model for hypoglycaemia during colonoscopy and identify independent predictors in pre- and post-colonoscopy hypoglycaemia groups.
We identified 112 of 598 (18.7%) T2DM patients who experienced hypoglycaemia during the peri-colonoscopy period: 43 pre-colonoscopy, 61 post-colonoscopy and 8 at both junctures. Ultimately, five predictors—insulin, SGLT2 inhibitors, fasting after colonoscopy, fasting C-peptide and estimated glomerular filtration rate (eGFR)—were integrated into the predictive model. The AUC for predicting hypoglycaemia was 0.78 (95% CI, 0.71–0.84) and 0.82 (95% CI, 0.74–0.90) in the development and validation cohort, respectively. Variables associated with pre-colonoscopy hypoglycaemia included SGLT2 inhibitors, fasting C-peptide and eGFR, whereas the post-colonoscopy hypoglycaemia group was associated with metformin, duration of diabetes, fasting C-peptide and fasting after the examination.
This study successfully developed and validated a predictive model for assessing hypoglycaemia risk in T2DM patients during peri-colonoscopy.
Early identification of patients at high risk for peri-colonoscopy hypoglycaemia allows nurses to implement personalised preventive strategies. The predictive model enables clinical nurses to deliver tailored interventions based on individual risk factors, potentially reducing hypoglycaemia-related complications and improving patient safety outcomes.
This study provides nurses with a validated risk prediction tool for identifying high-risk type 2 diabetes patients during colonoscopy, enabling targeted blood glucose monitoring protocols and preventive interventions in clinical practice.
This study follows the STROBE guidelines for reporting cohort studies.
Diabetes patients contributed electronic health record datasets.
In recent years, the critical role of health literacy in diabetes management has become increasingly prominent. The aim of this study was to investigate the impact of social support on health literacy among patients with diabetes, to test the mediating role of self-efficacy and empowerment between social support and health literacy, and the moderating role of eHealth literacy.
A cross-sectional study conducted between August 2023 and June 2024.
This study adopted the cluster sampling method and conducted a questionnaire survey among 251 patients with diabetes in a tertiary hospital in Wuhu City, Anhui Province. The questionnaires included the Social Support Rating Scale, the Self-Efficacy for Diabetes scale, the Health Empowerment Scale, the eHealth Literacy Scale and the Diabetes Health Literacy Scale.
Social support was positively associated with health literacy in patients with diabetes. Self-efficacy and empowerment mediated the relationship and formed chained mediation pathways respectively. eHealth literacy has a moderating role between self-efficacy and empowerment.
The results revealed that social support influences health literacy among patients with diabetes through the mediating pathways of self-efficacy and empowerment, and that this process is moderated by eHealth literacy. These findings provide a theoretical basis and practical insights for improving health literacy among patients with diabetes.
Enhancing health literacy among people with diabetes by strengthening social support, self-efficacy and empowerment levels, while focusing on the technology-enabling role of eHealth literacy in this context.
This study adheres to the relevant EQUATOR guidelines based on the STROBE cross-sectional reporting method.
We thank all patients who participated in the study for their understanding and support.
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