Effect of online interventions on reducing anxiety and depression for women with breast cancer: a systematic review and network meta-analysis protocol.

INTRODUCTION: Breast cancer has becoming the most common malignancy in women globally. Various online interventions have been conducted to help women with breast cancer to manage their psychological symptoms. However, there has been not yet a network meta-analysis that has synthesised scientific evidence about online intervention on reducing anxiety and depression for women with breast cancer. To fill the literature gap, this protocol aims to generate a systematic review and network meta-analysis to assess the effectiveness of online interventions on reducing anxiety and depression for these women with breast cancer. The study results may inform the recommendations for clinical guidelines and facilitate the decision-making process to improve psychological health of women with breast cancer. METHODS AND ANALYSIS: The protocol is in compliance with the guideline of Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols and for Systematic Reviews and Network Meta-Analysis. The electronic databases of Pubmed, EMBASE, CINAHL, PsycINFO, Web of Science, Cochrane Central Registry of Controlled Trials and OpenGrey will be used for searching of related randomised controlled trials from their inception. No restrictions on publication date and language will be applied. The primary outcomes are the symptoms of anxiety and depression, and the secondary outcome is the satisfaction with the received healthcare. Two reviewers independently evaluate the risk of bias using the Cochrane Collaboration's Risk of Bias tool. The assessment of heterogeneity, inconsistency, subgroup analysis, sensitivity analysis and publication bias will be conducted. The netmeta package of R software will be used to perform the network meta-analysis. ETHICS AND DISSEMINATION: This study will be based on previous research findings, so that ethics approval is not required. Data searching commences in July 2023 and expects to complete in January, 2024. The findings will be disseminated through peer-reviewed journals and academic conferences. PROSPERO REGISTRATION NUMBER: CRD42022318530.

Predictors of surgery choices in women with early-stage breast cancer in China: a retrospective study.

BACKGROUND: The breast-conserving surgery and reconstruction rate in China is relatively low when compared with those in Western countries. Moreover, predictors of surgical choices for women with breast cancer in China have not yet been explored. This study aims to explore differences in the surgical choices of women with different demographic and clinical characteristics and the predictors that influence surgical choices of women with early-stage breast cancer. METHODS: This retrospective study included women with early-stage (0-II) breast cancer who underwent surgeries at one of two Xiamen University-affiliated hospitals between 2009 and 2017. Using medical records, eleven variables were collected: the woman's age, year of diagnosis, hospital, marital status, payment method, cancer stage, presence of positive axillary lymph node, histology, neoadjuvant chemotherapy, radiotherapy, and the type(s) of surgery they chose. Binary logistic regression was used to analyse predictors of surgical choice. RESULTS: A total of 1,787 cases were included in this study. Of the total number of women with breast cancer, 61.3% underwent mastectomy without breast reconstruction, 26.4% underwent mastectomy with breast reconstruction, and the remaining 12.2% chose breast-conserving surgery. Women with different demographic and clinical characteristics underwent different types of surgery. Cancer stage, neoadjuvant chemotherapy, radiotherapy, and the choice of hospital were found to be predictors of breast-conserving surgery. Meanwhile, age, year of diagnosis, payment method, neoadjuvant chemotherapy, and the choice of hospital were found to be predictors of reconstruction after mastectomy in women with early-stage breast cancer. CONCLUSIONS: In China, surgical choices for women with breast cancer have diversified. Healthcare workers should understand the surgical preferences of women of different ages. For early detection of breast cancer, knowledge of breast self-examination and breast cancer screening should be provided. Adequate information about the safety of reconstruction and advocacy for medical insurance coverage of reconstruction should be offer. Breast surgeons need specialised training and standardising protocols towards different types of breast surgery. These actions will help women make better, well-informed decisions about their breast surgeries.

Development of a Prognostic App (iCanPredict) to Predict Survival for Chinese Women With Breast Cancer: Retrospective Study.

BACKGROUND: Accurate prediction of survival is crucial for both physicians and women with breast cancer to enable clinical decision making on appropriate treatments. The currently available survival prediction tools were developed based on demographic and clinical data obtained from specific populations and may underestimate or overestimate the survival of women with breast cancer in China. OBJECTIVE: This study aims to develop and validate a prognostic app to predict the overall survival of women with breast cancer in China. METHODS: Nine-year (January 2009-December 2017) clinical data of women with breast cancer who received surgery and adjuvant therapy from 2 hospitals in Xiamen were collected and matched against the death data from the Xiamen Center of Disease Control and Prevention. All samples were randomly divided (7:3 ratio) into a training set for model construction and a test set for model external validation. Multivariable Cox regression analysis was used to construct a survival prediction model. The model performance was evaluated by receiver operating characteristic (ROC) curve and Brier score. Finally, by running the survival prediction model in the app background thread, the prognostic app, called iCanPredict, was developed for women with breast cancer in China. RESULTS: A total of 1592 samples were included for data analysis. The training set comprised 1114 individuals and the test set comprised 478 individuals. Age at diagnosis, clinical stage, molecular classification, operative type, axillary lymph node dissection, chemotherapy, and endocrine therapy were incorporated into the model, where age at diagnosis (hazard ratio [HR] 1.031, 95% CI 1.011-1.051; P=.002), clinical stage (HR 3.044, 95% CI 2.347-3.928; P<.001), and endocrine therapy (HR 0.592, 95% CI 0.384-0.914; P=.02) significantly influenced the survival of women with breast cancer. The operative type (P=.81) and the other 4 variables (molecular classification [P=.91], breast reconstruction [P=.36], axillary lymph node dissection [P=.32], and chemotherapy [P=.84]) were not significant. The ROC curve of the training set showed that the model exhibited good discrimination for predicting 1- (area under the curve [AUC] 0.802, 95% CI 0.713-0.892), 5- (AUC 0.813, 95% CI 0.760-0.865), and 10-year (AUC 0.740, 95% CI 0.672-0.808) overall survival. The Brier scores at 1, 5, and 10 years after diagnosis were 0.005, 0.055, and 0.103 in the training set, respectively, and were less than 0.25, indicating good predictive ability. The test set externally validated model discrimination and calibration. In the iCanPredict app, when physicians or women input women's clinical information and their choice of surgery and adjuvant therapy, the corresponding 10-year survival prediction will be presented. CONCLUSIONS: This survival prediction model provided good model discrimination and calibration. iCanPredict is the first tool of its kind in China to provide survival predictions to women with breast cancer. iCanPredict will increase women's awareness of the similar survival rate of different surgeries and the importance of adherence to endocrine therapy, ultimately helping women to make informed decisions regarding treatment for breast cancer.

States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model.

Background: Postpartum depression (PPD) has been recognized as a severe public health problem worldwide due to its high incidence and the detrimental consequences not only for the mother but for the infant and the family. However, the pattern of natural transition trajectories of PPD has rarely been explored. Methods: In this research, a quantitative longitudinal study was conducted to explore the PPD progression process, providing information on the transition probability, hazard ratio, and the mean sojourn time in the three postnatal mental states, namely normal state, mild PPD, and severe PPD. The multi-state Markov model was built based on 912 depression status assessments in 304 Chinese primiparous women over multiple time points of six weeks postpartum, three months postpartum, and six months postpartum. Results: Among the 608 PPD status transitions from one visit to the next visit, 6.2% (38/608) showed deterioration of mental status from the level at the previous visit; while 40.0% (243/608) showed improvement at the next visit. A subject in normal state who does transition then has a probability of 49.8% of worsening to mild PPD, and 50.2% to severe PPD. A subject with mild PPD who does transition has a 20.0% chance of worsening to severe PPD. A subject with severe PPD is more likely to improve to mild PPD than developing to the normal state. On average, the sojourn time in the normal state, mild PPD, and severe PPD was 64.12, 6.29, and 9.37 weeks, respectively. Women in normal state had 6.0%, 8.5%, 8.7%, and 8.8% chances of progress to severe PPD within three months, nine months, one year, and three years, respectively. Increased all kinds of supports were associated with decreased risk of deterioration from normal state to severe PPD (hazard ratio, HR: 0.42-0.65); and increased informational supports, evaluation of support, and maternal age were associated with alleviation from severe PPD to normal state (HR: 1.46-2.27). Conclusions: The PPD state transition probabilities caused more attention and awareness about the regular PPD screening for postnatal women and the timely intervention for women with mild or severe PPD. The preventive actions on PPD should be conducted at the early stages, and three yearly; at least one yearly screening is strongly recommended. Emotional support, material support, informational support, and evaluation of support had significant positive associations with the prevention of PPD progression transitions. The derived transition probabilities and sojourn time can serve as an importance reference for health professionals to make proactive plans and target interventions for PPD.

NMR-based metabolomics Reveals Alterations of Electro-acupuncture Stimulations on Chronic Atrophic Gastritis Rats.

Chronic atrophic gastritis (CAG) is a common gastrointestinal disease which has been considered as precancerous lesions of gastric carcinoma. Previously, electro-acupuncture stimulation has been shown to be effective in ameliorating symptoms of CAG. However the underlying mechanism of this beneficial treatment is yet to be established. In the present study, an integrated histopathological examination along with molecular biological assay, as well as 1H NMR analysis of multiple biological samples (urine, serum, stomach, cortex and medulla) were employed to systematically assess the pathology of CAG and therapeutic effect of electro-acupuncture stimulation at Sibai (ST 2), Liangmen (ST 21), and Zusanli (ST 36) acupoints located in the stomach meridian using a rat model of CAG. The current results showed that CAG caused comprehensive metabolic alterations including the TCA cycle, glycolysis, membrane metabolism and catabolism, gut microbiota-related metabolism. On the other hand, electro-acupuncture treatment was found able to normalize a number of CAG-induced metabolomics changes by alleviating membrane catabolism, restoring function of neurotransmitter in brain and partially reverse the CAG-induced perturbation in gut microbiota metabolism. These findings provided new insights into the biochemistry of CAG and mechanism of the therapeutic effect of electro-acupuncture stimulations.