Additional file 1 of Development and validation of a model and nomogram for breast cancer diagnosis based on quantitative analysis of serum disease-specific haptoglobin N-glycosylation

Additional file 1: Figure S1. Aggregation plots of missing values of clinical variables. The first plot shows the proportion of missing values in each variable. The second plot shows patterns of missing values. The frequencies of the corresponding combinations are demonstrated to the right. The blue bars represent missing values, while the orange bars represent observed values. Figure S2. Strip plots of observed and imputed data of clinicopathological variables. The strip plots display the distribution of imputed values (orange points) over observed values (blue points) in a combined way. In total, 5 multiple imputed data sets were created. Column 1 represents the original data set, while column 2-6 represent the 5 imputed data sets. The second imputed data set (column 3) was used. Most of its imputations were in a plausible range, and properly accounted for the distribution of the missing data. Figure S3. Histogram plots displaying propensity score distributions for the malignant and benign groups before and after propensity score matching (caliper = 0.333). Figure S4. Heatmap of the correlations of DSHp-β N-glycopeptides and tumor markers. The numbers in grid show the Spearman correlation coefficients. Blank indicates a Bonferroni correction p-value of ≥ 0.05. Table S1. Identified N-glycopeptides of DSHp-β, their potential structures, and intensities between benign breast diseases and breast cancer

Data_Sheet_2_COVID-19 vaccination status, side effects, and perceptions among breast cancer survivors: a cross-sectional study in China.PDF

IntroductionBreast cancer is the most prevalent malignancy in patients with coronavirus disease 2019 (COVID-19). However, vaccination data of this population are limited.MethodsA cross-sectional study of COVID-19 vaccination was conducted in China. Multivariate logistic regression models were used to assess factors associated with COVID-19 vaccination status.ResultsOf 2,904 participants, 50.2% were vaccinated with acceptable side effects. Most of the participants received inactivated virus vaccines. The most common reason for vaccination was “fear of infection” (56.2%) and “workplace/government requirement” (33.1%). While the most common reason for nonvaccination was “worry that vaccines cause breast cancer progression or interfere with treatment” (72.9%) and “have concerns about side effects or safety” (39.6%). Patients who were employed (odds ratio, OR = 1.783, p = 0.015), had stage I disease at diagnosis (OR = 2.008, p = 0.019), thought vaccines could provide protection (OR = 1.774, p = 0.007), thought COVID-19 vaccines were safe, very safe, not safe, and very unsafe (OR = 2.074, p ConclusionCOVID-19 vaccination gap exists in breast cancer survivors, which could be filled by raising awareness and increasing confidence in vaccine safety during cancer treatment, particularly for the unemployed individuals.</p

Data_Sheet_1_COVID-19 vaccination status, side effects, and perceptions among breast cancer survivors: a cross-sectional study in China.PDF

IntroductionBreast cancer is the most prevalent malignancy in patients with coronavirus disease 2019 (COVID-19). However, vaccination data of this population are limited.MethodsA cross-sectional study of COVID-19 vaccination was conducted in China. Multivariate logistic regression models were used to assess factors associated with COVID-19 vaccination status.ResultsOf 2,904 participants, 50.2% were vaccinated with acceptable side effects. Most of the participants received inactivated virus vaccines. The most common reason for vaccination was “fear of infection” (56.2%) and “workplace/government requirement” (33.1%). While the most common reason for nonvaccination was “worry that vaccines cause breast cancer progression or interfere with treatment” (72.9%) and “have concerns about side effects or safety” (39.6%). Patients who were employed (odds ratio, OR = 1.783, p = 0.015), had stage I disease at diagnosis (OR = 2.008, p = 0.019), thought vaccines could provide protection (OR = 1.774, p = 0.007), thought COVID-19 vaccines were safe, very safe, not safe, and very unsafe (OR = 2.074, p ConclusionCOVID-19 vaccination gap exists in breast cancer survivors, which could be filled by raising awareness and increasing confidence in vaccine safety during cancer treatment, particularly for the unemployed individuals.</p