Prognostic factors and novel nomograms for overall survival and cancer specific survival of malignant ovarian cancer patients with bone metastasis: A SEER-based study.

OBJECTIVE: Ovarian cancer (OC) is a frequent and fatal disease in women, and bone metastasis of ovarian cancer (OCBM) leads to a poor survival trend. This study aimed to determine the factors which influence overall survival (OS) and cancer-specific survival (CSS) of OCBM patients and to develop prognostic predictive models. METHODS: Data of OCBM patients were stratified from the Surveillance, Epidemiology and End Results database from 2010 to 2017 and were randomly divided into training and testing datasets (7:3). Prognostic factors were identified by Cox regression analyses and nomograms were then developed. Nomogram models were examined on the discriminative ability and accuracy by calibration plots, Brier score (BS), and time-dependent receiver operating characteristic (ROC) curves. Decision curve analyses (DCA) was used for estimation of the clinical benefit of nomogram models. RESULTS: Grade, tumor size, tumor metastasis (liver, lung), primary site surgery, chemotherapy, and systemic therapy were realized as independent prognostic factors for OS and CSS, respectively. Agreement between the actual and predicted outcomes was proved by calibration plots. Nomograms performed well in OS and CSS predictions, as shown by area under the ROC curves (AUCs) and BSs for testing dataset as follows: for OS, 3-/6-/12-month AUCs and BSs were 0.778/0.788/0.822 and 19.0/18.5/15.4, respectively; for CSS, 3-/6-/12-month AUCs and BSs were 0.799/0.806/0.832 and 18.1/18.0/15.4, respectively. DCA suggested an agreeable clinical benefit of both nomograms. CONCLUSION: The nomograms developed for OCBM patients' survival prediction were proved to be accurate, efficient, and clinically beneficial, which were further deployed as web-based calculators to help in clinical decision making and future studies.

Research hotspots and trends on spinal cord stimulation for pain treatment: a two-decade bibliometric analysis.

Background: Chronic pain poses a significant social burden. Spinal cord stimulation (SCS) is considered to be the most promising treatment for refractory pain. The aim of this study was to summarize the current research hotspots on SCS for pain treatment during the past two decades and to predict the future research trends by bibliometric analysis. Methods: The literature over the last two decades (2002-2022) which was related to SCS in pain treatment was obtained from the Web of Science Core Collection. Bibliometric analyses were conducted based on the following aspects: (1) Annual publication and citation trends; (2) Annual publication changes of different publication types; (3) Publications and citations/co-citations of different country/institution/journal/author; (4) Citations/co-citation and citation burst analysis of different literature; and (5) Co-occurrence, cluster, thematic map, trend topics, and citation burst analysis of different keywords. (6) Comparison between the United States and Europe. All analyses were performed on CiteSpace, VOSviewer, and R bibliometrix package. Results: A total of 1,392 articles were included in this study, with an increasing number of publications and citations year by year. The most highly published type of literature was clinical trial. United States was the country with the most publications and citations; Johns Hopkins University was the institution with the most publications; NEUROMODULATION published the most papers; the most published author was Linderoth B; and the most cited paper was published in the PAIN by Kumar K in 2007. The most frequently occurring keywords were "spinal cord stimulation," "neuropathic pain," and "chronic pain," etc. Conclusion: The positive effect of SCS on pain treatment has continued to arouse the enthusiasm of researchers in this field. Future research should focus on the development of new technologies, innovative applications, and clinical trials for SCS. This study might facilitate researchers to comprehensively understand the overall perspective, research hotspots, and future development trends in this field, as well as seek collaboration with other researchers.

Novel Nomograms and Web-Based Tools Predicting Overall Survival and Cancer-specific Survival of Solitary Plasmacytoma of the Spine.

STUDY DESIGN: Retrospective analysis. OBJECTIVE: This study aimed to establish nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in patients with solitary plasmacytoma of the spine (SPS). SUMMARY OF BACKGROUND DATA: SPS is a rare type of malignant spinal tumor. A systematic study of prognostic factors associated with survival can provide guidance to clinicians and patients. Consideration of other causes of death (OCOD) in CSS will improve clinical practicability. METHODS: A total of 1078 patients extracted from the SEER database between 2000 and 2018 were analyzed. Patients were grouped into training and testing data sets (7:3). Factors associated with OS and CSS were identified by Cox regression and competing risk regression, respectively, for the establishment of nomograms on a training data set. The testing data set was used for the external validation of the performance of the nomograms using calibration curves, Brier's scores, C-indexes, time-dependent receiver operating characteristic curves, and decision curve analysis (DCA). RESULTS: Age and grade were identified as factors associated with both OS and CSS, along with marital status, radiation for OS, and chemotherapy for CSS. Heart disease, cerebrovascular disease, and diabetes mellitus were found to be the 3 most common causes of OCOD. The nomograms showed satisfactory agreement on calibration plots for both training and testing data sets. Integrated Brier score, C-index, and overall area under the curve on the testing data set were 0.162/0.717/0.789 and 0.173/0.709/0.756 for OS and CSS, respectively. DCA curves showed a good clinical net benefit. Nomogram-based web tools were developed for clinical application. CONCLUSION: This study provides evidence for risk factors and prognostication of survival in SPS patients. The novel nomograms and web-based tools we developed demonstrated good performance and might serve as accessory tools for clinical decision-making and SPS management. LEVEL OF EVIDENCE: 3.

Web-Based Nomograms for Overall Survival and Cancer-Specific Survival of Bladder Cancer Patients with Bone Metastasis: A Retrospective Cohort Study from SEER Database.

BACKGROUND: Our study aimed to explore the prognostic factors of bladder cancer with bone metastasis (BCBM) and develop prediction models to predict the overall survival (OS) and cancer-specific survival (CSS) of BCBM patients. METHODS: A total of 1438 patients with BCBM were obtained from the SEER database. Patients from 2010 to 2016 were randomly divided into training and validation datasets (7:3), while patients from 2017 were divided for external testing. Nomograms were established using prognostic factors identified through Cox regression analyses and validated internally and externally. The concordance index (C-index), calibration plots, and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discrimination and calibration of nomogram models, while decision curve analyses (DCA) and Kaplan-Meier (KM) curves were used to estimate the clinical applicability. RESULTS: Marital status, tumor metastasis (brain, liver, and lung), primary site surgery, and chemotherapy were indicated as independent prognostic factors for OS and CSS. Calibration plots and the overall C-index showed a novel agreement between the observed and predicted outcomes. Nomograms revealed significant advantages in OS and CSS predictions. AUCs for internal and external validation were listed as follows: for OS, 3-month AUCs were 0.853 and 0.849; 6-month AUCs were 0.873 and 0.832; 12-month AUCs were 0.825 and 0.805; for CSS, 3-month AUCs were 0.849 and 0.847; 6-month AUCs were 0.870 and 0.824; 12-month AUCs were 0.815 and 0.797, respectively. DCA curves demonstrated good clinical benefit, and KM curves showed distinct stratification performance. CONCLUSION: The nomograms as web-based tools were proved to be accurate, efficient, and clinically beneficial, which might help in patient management and clinical decision-making for BCBM patients.

Impact of dialysis modality conversion on the health-related quality of life of peritoneal dialysis patients: a retrospective cohort study in China.

BACKGROUND: To analyze the health-related quality of life associated with the conversion of dialysis modality among end-stage renal disease patients in China. METHODS: Patients were recruited from hospitals and a dialysis center in Kunshan, China. Patients converting from continuous ambulatory peritoneal dialysis to automated peritoneal dialysis were recruited as the observation group (n = 64), and patients continuing with continuous ambulatory peritoneal dialysis treatment were included in the control group (n = 64) after matching in this retrospective cohort study. Their health-related quality of life was measured using the kidney disease quality of life instrument in 2019 and 2020, respectively. Baseline socio-demographic characteristics and clinical data were collected in 2019. The before-and-after cross-group comparisons of subscale scores of two groups were conducted using a Student's t-test. Multiple linear regression models were fitted to identify the factors associated with the change of each scale. RESULTS: The health-related quality of life scores of the two groups was comparable in baseline, while the observation group had higher scores in Physical Component Summary (51.92 ± 7.50), Kidney Disease Component Summary (81.21 ± 8.41), Symptoms (90.76 ± 6.30), Effects (82.86 ± 11.42), and Burden (69.04 ± 15.69) subscales after one year. In multivariate regression analysis, the change of Physical Component Summary was significantly associated with conversion to APD (ß = 11.54, 95% CI [7.26-15.82]); the change of Mental Component Summary with higher education (ß =  - 5.96, 95% CI [-10.18--1.74]) and CCI (>2) (ß = 5.39, 95% CI [1.05-9.73]); the change of Kidney Disease Component Summary with conversion to APD (ß = 15.95, 95% CI [10.19-21.7]) and age (>60 years) (ß =  - 7.36, 95% CI [-14.11--0.61]); the change of Symptoms with CCI (>2) (ß = 7.96, 95% CI [1.49-14.44]); the change of Effects with conversion to APD (ß = 19.23, 95% CI [11.57-26.88]); and the change of Burden with conversion to APD (ß = 22.40, 95% CI [13.46-31.34]), age (>60 years) (ß =  - 12.12, 95% CI [-22.59--1.65]), and higher education (ß =  - 10.38, 95% CI [-19.79--0.98]). CONCLUSIONS: The conversion of dialysis modality had a significant impact on the scores of most subscales. Patients converting from continuous ambulatory peritoneal dialysis to automated peritoneal dialysis generally had improved health-related quality of life scores.

Machine Learning-based Prediction of Prolonged Intensive Care Unit Stay for Critical Patients with Spinal Cord Injury.

STUDY DESIGN: A retrospective cohort study. OBJECTIVE: The objective of the study was to develop machine-learning (ML) classifiers for predicting prolonged intensive care unit (ICU)-stay and prolonged hospital-stay for critical patients with spinal cord injury (SCI). SUMMARY OF BACKGROUND DATA: Critical patients with SCI in ICU need more attention. SCI patients with prolonged stay in ICU usually occupy vast medical resources and hinder the rehabilitation deployment. METHODS: A total of 1599 critical patients with SCI were included in the study and labeled with prolonged stay or normal stay. All data were extracted from the eICU Collaborative Research Database and the Medical Information Mart for Intensive Care III-IV Database. The extracted data were randomly divided into training, validation and testing (6:2:2) subdatasets. A total of 91 initial ML classifiers were developed, and the top three initial classifiers with the best performance were further stacked into an ensemble classifier with logistic regressor. The area under the curve (AUC) was the main indicator to assess the prediction performance of all classifiers. The primary predicting outcome was prolonged ICU-stay, while the secondary predicting outcome was prolonged hospital-stay. RESULTS: In predicting prolonged ICU-stay, the AUC of the ensemble classifier was 0.864 ±â€Š0.021 in the three-time five-fold cross-validation and 0.802 in the independent testing. In predicting prolonged hospital-stay, the AUC of the ensemble classifier was 0.815 ±â€Š0.037 in the three-time five-fold cross-validation and 0.799 in the independent testing. Decision curve analysis showed the merits of the ensemble classifiers, as the curves of the top three initial classifiers varied a lot in either predicting prolonged ICU-stay or discriminating prolonged hospital-stay. CONCLUSION: The ensemble classifiers successfully predict the prolonged ICU-stay and the prolonged hospital-stay, which showed a high potential of assisting physicians in managing SCI patients in ICU and make full use of medical resources.Level of Evidence: 3.

What Are the Important Factors Influencing the Recruitment and Retention of Doctoral Students in a Public Health Setting? A Discrete Choice Experiment Survey in China.

OBJECTIVES: This study aims to investigate the employment preferences of doctoral students majoring in social medicine and health care management (SMHCM), to inform policymakers and future employers on how to address recruitment and retention requirements at CDCs across China. METHODS: An online discrete choice experiment (DCE) was conducted to elicit doctoral SMHCM students' job preferences. The scenarios were described with seven attributes: monthly income, employment location, housing benefits, children's education opportunities, working environment, career promotion speed, and bianzhi. A conditional logit model and a mixed logit model were used to evaluate the relative importance of the selected attributes. RESULTS: A total of 167 doctoral SMHCM students from 24 universities completed the online survey. All seven attributes were statistically significant with the expected sign and demonstrated the existence of preference heterogeneity. Monthly income and employment location were of most concern for doctoral SMHCM students when deciding their future jobs. Among the presented attributes, working environment was of least concern. For the sub-group analysis, employment located in a first-tier city was more likely to lead to a higher utility value for doctoral students who were women, married, from an urban area, and had a high annual family income. Unsurprisingly, when compared to single students, married students were willing to forgo more for good educational opportunities for their children. CONCLUSIONS: Our study suggests that monthly income and employment location were valued most by doctoral SMHCM students when choosing a job. A more effective human resource policy intervention to attract doctoral SMHCM students to work in CDCs, especially CDCs in third-tier cities should consider both the incentives provided by the job characteristics and the background of students. Doctoral students are at the stages of career preparation, so the results of this study would be informative for policymakers and help them to design the recruitment and retention policies for CDCs.

Factors Influencing Medication Non-Adherence among Chinese Older Adults with Diabetes Mellitus.

OBJECTIVES: This study aimed to examine the prevalence of medication non-adherence among older adults with diabetes mellitus (DM) in Shandong province, China and to identify its influencing factors. METHODS: A sample of 1002 older adults aged 60 or above with DM was analyzed. Medication adherence was measured using the Morisky-Green-Levine (MGL) Medication Adherence Scale. Descriptive statistical analysis, chi-square test, univariate and multivariate logistic regression analyses were employed. RESULTS: The prevalence of self-reported medication non-adherence among older adults with DM was 19.9%. Female respondents (adjusted odds ratio (AOR) = 1.56, 95% CI: 1.09-2.24) and respondents who perceived medication adherence to be unimportant (AOR = 1.69, 95% CI: 1.05-2.74) were more likely to experience medication non-adherence. Respondents with 5 years of disease duration or longer were less likely (AOR = 0.63, 95% CI: 0.46-0.87) to experience medication non-adherence. CONCLUSIONS: This study showed that about one out of five older adults with DM in Shandong province, China, experienced medication non-adherence, and that gender, disease duration and perceived importance of medication adherence were associated with medication non-adherence in this population group. Provision of counseling and health education programs could be the future priority to raise patients' awareness of the importance of medication adherence and improve patients' self-management of DM.

Tumor microenvironment targeting with dual stimuli-responsive nanoparticles based on small heat shock proteins for antitumor drug delivery.

Tumour microenvironment (TME)-targeting nanoparticles (NPs) were developed based on Methanococcus jannaschii small heat shock proteins (Mj-sHSPs). Transactivator of transcription (TAT) were modified on the surface of Mj-sHSPs (T-HSPs) to enhance their cellular internalization ability (CIA), and a pH/enzyme dual sensitive PEG/N-(2-aminoethyl)piperidine-hyaluronic acid (PAHA) coat was combined with T-HSPs (PT-HSPs). PT-HSP NPs exhibited multi-layered morphologies and good stability against plasma protein adsorption. The release of paclitaxel (PTX) from PT-HSP NPs was negligible at physiological pH. Under conditions similar to the TME (acidic pH and overexpressed hyaluronidase (HAase)), the PAHA coat deshielded from PT-HSP NPs because of two factors: charge reversal and HAase degradation. Once the PAHA coat was shed, the size of the NPs decreased; its surface charge became positive; and remarkable drug release was triggered. Cellular experiments indicated that the CIA of PT-HSPs was shielded in the microenvironment of normal cells and recovered in that of tumour cells. In vivo imaging exhibited that the PT-HSP NPs had an impressive tumour targeting ability compared with the uncoated controls. The antitumor efficacy in vivo demonstrated that tumour-bearing mice treated with PTX-loaded PT-HSP NPs achieved better anti-tumour effects and safety than the Taxol formulation. In summary, this study provided Mj-sHSP NPs with coats that could be shed in response to the particular pH and enzymes in the TME, which improved the efficacy of tumour therapy. STATEMENT OF SIGNIFICANCE: This study reports on tumor microenvironment-targeting protein-based nanoparticles (PT-HSP NPs) for targeted tumor therapy. The NPs had a multilayered structure: a protein cage, a TAT cationic layer, and a dual-sensitive coat. PT-HSP NPs exhibited multilayered morphology, with good stability against plasma protein adsorption, and PTX release negligible at physiological pH. Under the tumor microenvironment (acidic pH and overexpressed HAase), PAHA coat deshielded from PT-HSP NPs due to two factors: the charge reversal induced by protonation of piperidines in PAHA and HAase degradation. The results of cellular uptake, cytotoxicity, in vivo imaging, and tumor inhibition experiments confirmed that PT-HSP NPs exhibited promising tumor targeting efficacy in vitro and in vivo.

Low density lipoprotein mimic nanoparticles composed of amphipathic hybrid peptides and lipids for tumor-targeted delivery of paclitaxel.

BACKGROUND: Low density lipoprotein (LDL) has been regarded as a promising antitumor drug vehicle. However some problems, such as rare source, difficulty of large-scale production, and potential safety concerns, hinder its clinical application. PURPOSE: The objective of this study is to develop a biomimetic LDL nanocarrier by replacing the native apolipoprotein B-100 (apoB-100) with an artificial amphipathic peptide and demonstrate its antitumor efficacy. METHODS: The amphipathic hybrid peptide (termed as FPL) consisting of a lipid binding motif of apoB-100 (LBMapoB)-polyethylene glycol (PEG)-folic acid (FA) was synthesized and characterized by 1H NMR and circular dichroism. FPL decorated lipoprotein-mimic nanoparticles (termed as FPLM NPs) were prepared by a modified solvent emulsification method. Paclitaxel (PTX) was incorporated into NPs and its content was quantified by HPLC analysis. The morphology of NPs was observed by transmission electron microscopy (TEM), and the particle size and zeta potential of NPs were determined by dynamic light scattering (DLS). The colloidal stability of FPLM NPs was evaluated in PBS containing bovine serum albumin (BSA). In vitro release of PTX loaded FPLM NPs was evaluated using the dialysis method. Cellular uptake and cytotoxity assayswere evaluated on human cervical cancer cells (HeLa) and lung cancer cells (A549). Tumor inhibition in vivo was investigated in M109 tumor-bearing mice via tail vein injection of Taxol formulation and PTX loaded NPs. RESULTS: The composition of FPLM NPs, including cholesteryl oleate, glyceryl trioleate, cholesterol, 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), and FPL peptides, was optimized to be 5:1:1:3:10 (w/w). FPLM NPs had a spherical shape with a mean diameter of 83 nm and a negative charge (-12 mV). FPLM NPs with optimum formulation had good colloidal stability in BSA solution.The release of PTX from FPLM NPs was slow and sustained. The uptake of FPLM NPs was higher in folate receptor (FR) overexpressing tumor cells (HeLa cells) than in FR deficient tumor cells (A549 cells). The intracellular distribution indicated that FPLM NPs had the lysosome escape capacity. The internalization mechanism of FPLM NPs was involved with clathrin- and caveolae-mediated endocytosis and FR played a positive role in the internalization of FPLM NPs. The CCK-8 assay demonstrated that FPLM NPs exhibited notably better anti-tumor effect than Taxol formulation in vitro. Moreover, PTX loaded FPLM NPs produced very marked anti-tumor efficiency in M109 tumor-bearing mice in vivo. CONCLUSION: FPLM NPs is a promising nanocarrier which can improve the therapeutic effect and reduce the side effects of antitumor drugs.

Patient Preferences For Chemotherapy In The Treatment Of Non-Small Cell Lung Cancer: A Multicenter Discrete Choice Experiment (DCE) Study In China.

OBJECTIVE: The study aims to quantify patients' risk-benefit preferences for chemotherapy in the treatment of non-small cell lung cancer (NSCLC), and to elicit their willingness to pay (WTP) for treatment outcomes. METHODS: A face-to-face discrete choice experiment (DCE) was conducted on NSCLC patients in four tertiary hospitals each from Beijing, Shanghai, Guangzhou and Chengdu in China. Patients were invited to complete choice questions that constructed by seven attributes: progression-free survival (PFS), disease control rate (DCR), rash, nausea and vomiting, tiredness, mode of administration and out-of-pocket costs. A mixed logit model was used to evaluate the choice model. Estimates of relative preferences and marginal willingness to pay for each attribute were then explored. RESULTS: A total of 361 patients completed the survey. Improvements in PFS (10, 95% CI: 8.4-11.6) were the most important attribute for patients, followed by increase in DCR (4.6, 95% CI: 3.4-5.8). Tiredness (3.9, 95% CI: 2.9-5.1) was judged to be the most important risk. While remaining attributes were ranked in decreasing order of importance: nausea and vomiting (1.9, 95% CI: 0.9-3.0), mode of administration (0.8, 95% CI: 0.2-1.4) and rash (0.5, 95% CI: -0.6-1.5). There was little variation in preferences among patients with different sociodemographic characteristics. Patients were monthly willing to pay $2304 (95% CI, $1916-$2754) that guaranteed 11 months of PFS, followed by $1465 (95% CI, $1163-$1767) per month to improve their disease control rate by 90%. CONCLUSION: The results suggested that efficacy was the most important attribute for patients. Side effects, mode of administration and treatment cost significantly influenced patient preferences. Patient engagement in prioritizing their treatment preferences should be emphasized during the clinical decision-making process and regimen implementation.

Cost-Effectiveness Analysis of Non-invasive Prenatal Testing for Down Syndrome in China.

OBJECTIVES: There is little evidence in China regarding the cost-effectiveness of non-invasive prenatal testing (NIPT) for Down syndrome (DS). This study aims to evaluate the cost-effectiveness of NIPT and provide evidence to inform decision-making. METHODS: To determine the cost-effectiveness of NIPT for DS, a decision-analytic model was developed using the TreeAge Pro software from a societal perspective in a simulated cohort of 10 000 pregnant women. Main indicators were based on field surveys from sampled hospitals in four locations in China and a literature review. RESULTS: The conventional maternal serum screening (CMSS) strategy, contingent screening strategy (NIPT delivered to high risk pregnant women after CMSS), and universal screening strategy could prevent 3.02, 7.53, and 9.97 DS births, respectively. NIPT would decrease unnecessary invasive procedures, resulting in fewer procedure-related miscarriages. The cost-effectiveness ratio of the contingent screening strategy was the lowest. When compared with the CMSS strategy, the incremental cost per DS birth averted by the contingent screening strategy and universal screening strategy were USD 20,160 and 352,388, respectively. One-way sensitivity analysis showed that, if the cost of NIPT could be decreased to USD 76.92, the cost-effectiveness ratio of the universal screening strategy would be lower than the CMSS strategy. CONCLUSIONS: Although NIPT has the merits of greater effectiveness and safety, CMSS is unlikely to be replaced by NIPT at this time because of NIPT's higher cost. Contingent screening may be an appropriate strategy to balance the effectiveness and cost factors of the new genetic testing technology.

Estimating benefit equity of government health subsidy in healthcare Services in Shandong Province, China: a cross-sectional study.

BACKGROUND: Government health subsidy (GHS) is an effective tool to improve population health in China. Ensuring an equitable allocation of GHS, particularly among the poorer socio-economic groups, is a major goal of China's healthcare reform. The paper aims to explore how GHS was allocated across different socioeconomic groups, and how well the overall health system was performing in terms of the allocation of subsidy for different types of health services. METHODS: Data from China's National Health Services Survey (NHSS) in 2013 were used. Benefit incidence analysis (BIA) was applied to examine if GHS was equally distributed across income quintile. Benefit incidence was presented as each quintile's percentage share of total benefits, and the concentration index (CI) and Kakwani index (KI) were calculated. Health benefits from three types of healthcare services (primary health care, outpatient and inpatient services) were analyzed, separated into urban and rural populations. In addition, the distribution of benefits was compared to the distribution of healthcare need (measured by self-reported illness and chronic disease) across income quintiles. RESULTS: In urban populations, the CI value of GHS for primary care was negative. (- 0.14), implying an allocation tendency toward poor region; the CI values of outpatient and inpatient services were both positive (0.174 and 0.194), indicating allocation tendencies toward rich region. Similar allocation pattern was observed in rural population, with pro-poor tendency of primary care service (CI = - 0.082), and pro-rich tendencies of outpatient (CI = 0.153) and inpatient services (CI = 0.203). All the KI values of three health services in urban and rural populations were negative (- 0.4991,-0.1851 and - 0.1651; - 0.482, - 0.247and - 0.197), indicating that government health subsidy was progressive and contributed to the narrowing of economic gap between the poor and rich. CONCLUSIONS: The inequitable distribution of GHS in China exited in different healthcare services; however, the GHS benefit is generally progressive. Future healthcare reforms in China should not only focus on expanding the coverage, but also on improving the equity of distribution of healthcare benefits.

The public health emergency management system in China: trends from 2002 to 2012.

BACKGROUND: Public health emergencies have challenged the public health emergency management systems (PHEMSs) of many countries critically and frequently since this century. As the world's most populated country and the second biggest economy in the world, China used to have a fragile PHEMS; however, the government took forceful actions to build PHEMS after the 2003 SARS outbreak. After more than one decade's efforts, we tried to assess the improvements and problems of China's PHEMS between 2002 and 2012. METHODS: We conducted two rounds of national surveys and collected the data of the year 2002 and 2012, including all 32 provincial, 139 municipal, and 489 county CDCs. The municipal and county CDCs were selected by systematic random sampling. Twenty-one indicators of four stages (preparation, readiness, response and recovery) from the National Assessment Criteria for CDC Performance were chosen to assess the ten-year trends. RESULTS: At the preparation stage, organization, mechanisms, workforce, and stockpile across all levels and regions were significantly improved after one decade's efforts. At the readiness stage, the capability for formulating an emergency plan was also significantly improved during the same period. At the response stage, internet-based direct reporting was 98.8%, and coping scores were nearly full points of ten in 2012. At the recovery stage, the capabilities were generally lower than expected. CONCLUSIONS: Due to forceful leadership, sounder regulations, and intensive resources, China's PHEMS has been improved at the preparation, readiness, and response stages; however, the recovery stage was still weak and could not meet the requirements of crisis management and preventive governance. In addition, CDCs in the Western region and counties lagged behind in performance on most indicators. Future priorities should include developing the recovery stage, establishing a closed feedback loop, and strengthening the capabilities of CDCs in Western region and counties.