Using protection motivation theory to explain the intention to initiate human papillomavirus vaccination among men who have sex with men in China

Human papillomavirus (HPV) infection and related diseases are common among men who have sex with men (MSM). The most effective prevention is HPV vaccination. In China, however, men are not included in the HPV vaccination plan. We investigated the intention to initiate HPV vaccination and associated factors among MSM in China. Methods We surveyed 563 unvaccinated MSM aged 18 or older from six cities in China. Participants completed an electronic questionnaire about demographics, knowledge of and attitude towards HPV and HPV vaccine, intention to initiate HPV vaccination, willingness to recommend HPV vaccine to peers, feeling about government policy about HPV vaccination. We used the structural equation modeling (SEM) to analyze factors associated with HPV vaccine intention. Results The knowledge of HPV and HPV vaccine among participants was low. The mean score of knowledge about HPV and HPV vaccine was only 1.59 (range 0–11). The intention to initiate HPV vaccination within 6 months among participants was moderate (43.3% in total, 18.1% for ‘very high' and 25.2% for ‘above average')

Stakeholder efforts to mitigate antiretroviral therapy interruption among people living with HIV during the COVID-19 pandemic in China: a qualitative study.

INTRODUCTION: The COVID-19 pandemic has affected antiretroviral therapy (ART) continuity among people living with HIV (PLHIV) worldwide. We conducted a qualitative study to explore barriers to ART maintenance and solutions to ART interruption when stringent COVID-19 control measures were implemented in China, from the perspective of PLHIV and relevant key stakeholders. METHODS: Between 11 February and 15 February 2020, we interviewed PLHIV, community-based organization (CBO) workers, staff from centres for disease control and prevention (CDC) at various levels whose work is relevant to HIV care (CDC staff), HIV doctors and nurses and drug vendors from various regions in China. Semi-structured interviews were conducted using a messaging and social media app. Challenges and responses relevant to ART continuity during the COVID-19 pandemic were discussed. Themes were identified by transcript coding and mindmaps. RESULTS: Sixty-four stakeholders were recruited, including 16 PLHIV, 17 CBO workers, 15 CDC staff, 14 HIV doctors and nurses and two drug vendors. Many CDC staff, HIV doctors and nurses responsible for ART delivery and HIV care were shifted to COVID-19 response efforts. Barriers to ART maintenance were (a) travel restrictions, (b) inadequate communication and bureaucratic obstacles, (c) shortage in personnel, (d) privacy concerns, and (e) insufficient ART reserve. CBO helped PLHIV maintain access to ART through five solutions identified from thematic analysis: (a) coordination to refill ART from local CDC clinics or hospitals, (b) delivery of ART by mail, (c) privacy protection measures, (d) mental health counselling, and (e) providing connections to alternative sources of ART. Drug vendors contributed to ART maintenance by selling out-of-pocket ART. CONCLUSIONS: Social and institutional disruption from COVID-19 contributed to increased risk of ART interruption among PLHIV in China. Collaboration among key stakeholders was needed to maintain access to ART, with CBO playing an important role. Other countries facing ART interruption during current or future public health emergencies may learn from the solutions employed in China

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides

Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical labels, whereas biomarkers are often continuous measurements. We hypothesized that regression-based DL outperforms classification-based DL. Therefore, we developed and evaluated a new self-supervised attention-based weakly supervised regression method that predicts continuous biomarkers directly from images in 11,671 patients across nine cancer types. We tested our method for multiple clinically and biologically relevant biomarkers: homologous repair deficiency (HRD) score, a clinically used pan-cancer biomarker, as well as markers of key biological processes in the tumor microenvironment. Using regression significantly enhances the accuracy of biomarker prediction, while also improving the interpretability of the results over classification. In a large cohort of colorectal cancer patients, regression-based prediction scores provide a higher prognostic value than classification-based scores. Our open-source regression approach offers a promising alternative for continuous biomarker analysis in computational pathology

Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study

Background: Deep learning (DL) can extract predictive and prognostic biomarkers from routine pathology slides in colorectal cancer. For example, a DL test for the diagnosis of microsatellite instability (MSI) in CRC has been approved in 2022. Current approaches rely on convolutional neural networks (CNNs). Transformer networks are outperforming CNNs and are replacing them in many applications, but have not been used for biomarker prediction in cancer at a large scale. In addition, most DL approaches have been trained on small patient cohorts, which limits their clinical utility. Methods: In this study, we developed a new fully transformer-based pipeline for end-to-end biomarker prediction from pathology slides. We combine a pre-trained transformer encoder and a transformer network for patch aggregation, capable of yielding single and multi-target prediction at patient level. We train our pipeline on over 9,000 patients from 10 colorectal cancer cohorts. Results: A fully transformer-based approach massively improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training on a large multicenter cohort, we achieve a sensitivity of 0.97 with a negative predictive value of 0.99 for MSI prediction on surgical resection specimens. We demonstrate for the first time that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem. Interpretation: A fully transformer-based end-to-end pipeline trained on thousands of pathology slides yields clinical-grade performance for biomarker prediction on surgical resections and biopsies. Our new methods are freely available under an open source license

Factors associated with immunological non-response after ART initiation: a retrospective observational cohort study

Abstract Background Among people living with HIV (PLHIV) on antiretroviral therapy (ART), the mortality of immunological non-responders (INRs) is higher than that of immunological responders (IRs). However, factors associated with immunological non-response following ART are not well documented. Methods We obtained data for HIV patients from the National Free Antiretroviral Treatment Program database in China. Patients were grouped into IRs (CD4 cell count ≥ 350 cells/μl after 24 months’ treatment), immunological incomplete responders (ICRs) (200–350 cells/μl) and INRs (< 200 cells/μl). Multivariable logistic regression was used to assess factors associated with immunological non-response. Results A total of 3900 PLHIV were included, among whom 2309 (59.2%) were IRs, 1206 (30.9%) ICRs and 385 (9.9%) INRs. In multivariable analysis, immunological non-response was associated with being male (2.07, 1.39–3.09), older age [40–49 years (vs. 18–29 years): 2.05, 1.29–3.25; 50–59 years: 4.04, 2.33-7.00; ≥ 60 years: 5.51, 2.84–10.67], HBV co-infection (1.63, 1.14–2.34), HCV co-infection (2.01, 1.01–4.02), lower CD4 + T cell count [50–200 cells/μl (vs. 200–350 cells/μl): 40.20, 16.83–96.01; < 50 cells/μl: 215.67, 85.62-543.26] and lower CD4/CD8 ratio (2.93, 1.98–4.34) at baseline. Compared with patients treated with non-nucleoside reverse transcriptase inhibitors (NNRTIs) based regimens, those receiving protease inhibitors (PIs) based regimens were less likely to be INRs (0.47, 0.26–0.82). Conclusions We found a sizable immunological non-response rate among HIV-infected patients. Being male, older age, coinfection with HBV and HCV, lower CD4 + T cell count and lower CD4/CD8 ratio are risk factors of immunological non-response, whereas PIs-based regimens is a protective factor

Spatiotemporal Distribution of HIV Self-testing Kits Purchased on the Web and Implications for HIV Prevention in China: Population-Based Study

BackgroundHIV self-testing (HIVST) holds great promise for expanding HIV testing. Nonetheless, large-scale data on HIVST behavior are scant. Millions of HIVST kits are sold through e-commerce platforms each year. ObjectiveThis study aims to analyze the spatiotemporal distribution of the HIVST kit–purchasing population (HIVSTKPP) in China. MethodsDeidentified transaction data were retrieved from a leading e-commerce platform in China. A joinpoint regression model was used to examine annual trends of the HIVSTKPP rates by calculating average annual percentage change. Bayesian spatiotemporal analysis was performed to locate hot spots with HIVSTKPP rates. Spatial autocorrelation analysis and space-time cluster analysis were conducted to identify clusters of HIVSTKPP. High-high clusters of HIVSTKPP can be identified by spatial autocorrelation analysis, and high-high clusters indicate that a region and its surrounding region jointly had a higher-than-average HIVSTKPP rate. Spatial regression analysis was used to elucidate the association between the number of HIV testing facilities, urbanization ratio (the proportion of urban population in the total population), and gross domestic product per capita and the HIVSTKPP. ResultsBetween January 1, 2016, and December 31, 2019, a total of 2.18 million anonymous persons in China placed 4.15 million orders and purchased 4.51 million HIVST kits on the web. In each of these 4 years, the observed monthly size of the HIVSTKPP peaked in December, the month of World AIDS Day. HIVSTKPP rates per 100,000 population significantly increased from 20.62 in 2016 to 64.82 in 2019 (average annual percentage change=48.2%; P<.001). Hot spots were mainly located in municipalities, provincial capitals, and large cities, whereas high-high clusters and high-demand clusters were predominantly detected in cities along the southeast coast. We found positive correlations between a region’s number of HIV testing facilities, urbanization ratio, and gross domestic product per capita and the HIVSTKPP. ConclusionsOur study identified key areas with larger demand for HIVST kits for public health policy makers to reallocate resources and optimize the HIV care continuum. Further research combining spatiotemporal patterns of HIVST with HIV surveillance data is urgently needed to identify potential gaps in current HIV-monitoring practices

Uptake and adverse reactions of COVID-19 vaccination among people living with HIV in China: a case–control study

Objectives The coronavirus disease-2019 (COVID-19) pandemic continues to ravage the world. People living with HIV (PLHIV) are one of the most vulnerable groups. This study aims to identify the factors associated with the uptake and adverse reactions of COVID-19 vaccination. Methods We recruited PLHIV in China by convenience sampling between 7 and 23 February 2021. Participants were asked to complete an online questionnaire. Chi-squared test and multivariable logistic regression were used to assess factors associated with vaccine uptake. Results A total of 527 vaccinated and 1091 unvaccinated PLHIV were recruited. Individuals who had a higher education, engaged in occupations with a higher risk of COVID-19 infection, received influenza or pneumonia vaccine in the past 3 years (5.40, 3.36–8.77), believed in the effectiveness of vaccines (3.01, 2.20–4.12), and received media information regarding COVID-19 vaccine (2.23, 1.61–3.11), were more likely to be vaccinated. Concerning about adverse reactions (0.31, 0.22–0.44), negative impact on the progression of HIV/AIDS (0.36, 0.26–0.50) or antiretroviral therapy (ART) (0.61, 0.44–0.85), disclosure of HIV infection status (0.69, 0.49–0.96), comorbidities (0.33, 0.22–0.47), being unmarried (0.43, 0.28–0.66) and older age were negatively associated with vaccination. Of the 527 vaccinated PLHIV, 155 (29.4%) PLHIV reported adverse reactions, with pain at the injection site being the most common (18.2%). Conclusions PLHIV, who are concerned about adverse reactions, negative impact on ART outcome and disclosure of HIV infection status, were less likely to adopt COVID-19 vaccination. To increase vaccination coverage among PLHIV, health-care professionals should emphasize the benefits and necessity of vaccination and provide consultancy regarding adverse reactions

Development and external validation of a prognostic model for survival of people living with HIV/AIDS initiating antiretroviral therapy

Background: Most existing prognostic models for people living with HIV/AIDS (PLWHA) were derived from cohorts in high-income settings established a decade ago and may not be applicable for contemporary patients, especially for patients in developing settings. The aim of this study was to develop and externally validate a prognostic model for survival in PLWHA initiating ART based on a large population-based cohort in China. Methods: We obtained data for patients from the Chinese National Free Antiretroviral Treatment Program database. The derivation cohort consisted of PLWHA treated between February 2004 and December 2019 in a tertiary center in Guangzhou, South China, and validation cohort of patients treated between February 2004 to December 2018 in another tertiary hospital in Shenyang, Northeast China. We included ART-naive patients aged above 16 who initiated a combination ART regimen containing at least three drugs and had at least one follow-up record. We assessed 20 candidate predictors including patient characteristics, disease characteristics, and laboratory tests for an endpoint of death from all causes. The prognostic model was developed from a multivariable cox regression model with predictors selected using the least absolute shrinkage and selection operator (Lasso). To assess the model's predictive ability, we quantified the discriminative power using the concordance (C) statistic and calibration accuracy by comparing predicted survival probabilities with observed survival probabilities estimated with the Kaplan-Meier method. Findings: The derivation cohort included 16481 patients with a median follow-up of 3·41 years, among whom 735 died. The external validation cohort comprised 5751 participants with a median follow-up of 2·71 years, of whom 185 died. The final model included 10 predictors: age, body mass index, route of HIV acquisition, coinfection with tuberculosis, coinfection with hepatitis C virus, haemoglobin, CD4 cell count, platelet count, aspartate transaminase, and plasma glucose. The C-statistic was 0·84 (95% confidence interval 0·82-0·85) in internal validation after adjustment of optimism and 0·84 (0·82-0·87) in external validation, which remained consistently above 0·75 in all landmark time points within five years of follow up when using time-updated laboratory measurements. The calibration accuracy was satisfactory in both derivation and validation cohorts. Interpretation: We have developed and externally validated a model to predict long-term survival in PLWHA on ART. This model could be applied to individualized patient counseling and management during treatment, and future innovative trial design. Funding: Natural Science Foundation of China Excellent Young Scientists Fund, Natural Science Foundation of China International/Regional Research Collaboration Project, Natural Science Foundation of China Young Scientist Fund, the National Science and Technology Major Project of China,National Special Research Program of China for Important Infectious Diseases, 13th Five-Year Key Special Project of Ministry of Science and Technology, and the Joint-innovation Program in Healthcare for Special Scientific Research Projects of Guangzhou

Development and external validation of a prognostic model for survival of people living with HIV/AIDS initiating antiretroviral therapy

Background: Most existing prognostic models for people living with HIV/AIDS (PLWHA) were derived from cohorts in high-income settings established a decade ago and may not be applicable for contemporary patients, especially for patients in developing settings. The aim of this study was to develop and externally validate a prognostic model for survival in PLWHA initiating ART based on a large population-based cohort in China. Methods: We obtained data for patients from the Chinese National Free Antiretroviral Treatment Program database. The derivation cohort consisted of PLWHA treated between February 2004 and December 2019 in a tertiary center in Guangzhou, South China, and validation cohort of patients treated between February 2004 to December 2018 in another tertiary hospital in Shenyang, Northeast China. We included ART-naive patients aged above 16 who initiated a combination ART regimen containing at least three drugs and had at least one follow-up record. We assessed 20 candidate predictors including patient characteristics, disease characteristics, and laboratory tests for an endpoint of death from all causes. The prognostic model was developed from a multivariable cox regression model with predictors selected using the least absolute shrinkage and selection operator (Lasso). To assess the model's predictive ability, we quantified the discriminative power using the concordance (C) statistic and calibration accuracy by comparing predicted survival probabilities with observed survival probabilities estimated with the Kaplan-Meier method. Findings: The derivation cohort included 16481 patients with a median follow-up of 3·41 years, among whom 735 died. The external validation cohort comprised 5751 participants with a median follow-up of 2·71 years, of whom 185 died. The final model included 10 predictors: age, body mass index, route of HIV acquisition, coinfection with tuberculosis, coinfection with hepatitis C virus, haemoglobin, CD4 cell count, platelet count, aspartate transaminase, and plasma glucose. The C-statistic was 0·84 (95% confidence interval 0·82-0·85) in internal validation after adjustment of optimism and 0·84 (0·82-0·87) in external validation, which remained consistently above 0·75 in all landmark time points within five years of follow up when using time-updated laboratory measurements. The calibration accuracy was satisfactory in both derivation and validation cohorts. Interpretation: We have developed and externally validated a model to predict long-term survival in PLWHA on ART. This model could be applied to individualized patient counseling and management during treatment, and future innovative trial design. Funding: Natural Science Foundation of China Excellent Young Scientists Fund, Natural Science Foundation of China International/Regional Research Collaboration Project, Natural Science Foundation of China Young Scientist Fund, the National Science and Technology Major Project of China,National Special Research Program of China for Important Infectious Diseases, 13th Five-Year Key Special Project of Ministry of Science and Technology, and the Joint-innovation Program in Healthcare for Special Scientific Research Projects of Guangzhou

Clinical characteristics of coronavirus disease 2019 (COVID-19) in China : A systematic review and meta-analysis

Objective: To better inform efforts to treat and control the current outbreak with a comprehensive characterization of COVID-19. Methods: We searched PubMed, EMBASE, Web of Science, and CNKI (Chinese Database) for studies published as of March 2, 2020, and we searched references of identified articles. Studies were reviewed for methodological quality. A random-effects model was used to pool results. Heterogeneity was assessed using I2. Publication bias was assessed using Egger's test. Results: 43 studies involving 3600 patients were included. Among COVID-19 patients, fever (83.3% [95% CI 78.4–87.7]), cough (60.3% [54.2–66.3]), and fatigue (38.0% [29.8–46.5]) were the most common clinical symptoms. The most common laboratory abnormalities were elevated C-reactive protein (68.6% [58.2–78.2]), decreased lymphocyte count (57.4% [44.8–69.5]) and increased lactate dehydrogenase (51.6% [31.4–71.6]). Ground-glass opacities (80.0% [67.3–90.4]) and bilateral pneumonia (73.2% [63.4–82.1]) were the most frequently reported findings on computed tomography. The overall estimated proportion of severe cases and case-fatality rate (CFR) was 25.6% (17.4–34.9) and 3.6% (1.1–7.2), respectively. CFR and laboratory abnormalities were higher in severe cases, patients from Wuhan, and older patients, but CFR did not differ by gender. Conclusions: The majority of COVID-19 cases are symptomatic with a moderate CFR. Patients living in Wuhan, older patients, and those with medical comorbidities tend to have more severe clinical symptoms and higher CFR.</p