[Study on the hospitalization cost and its influencing factors of imported malaria patients in Guangxi Zhuang Autonomous Region and Yunnan Province].

OBJECTIVE: To analyze the hospitalization cost and its influencing factors of imported malaria patients in Guangxi Zhuang Autonomous Region and Yunnan Province, so as to provide insights into the evaluation of the economic burden due to imported malaria, and the guiding of malaria control and the rational allocation of medical resources. METHODS: The data pertaining to the hospitalization costs of imported malaria patients admitted to Shanglin County People's Hospital in Guangxi Zhuang Autonomous Region during the period from January 1 through December 31, 2019, and Tengchong Municipal People's Hospital in Yunnan Province from January 1, 2015 to December 31, 2019, were collected, and the epidemiological data of these imported malaria patients were extracted from the Information Management System for Parasitic Diseases Control and Prevention, China. The composition of the hospitalization expenses was analyzed using a descriptive method. In addition, the factors affecting the hospitalization expenses of imported malaria patients were identified using a univariate analysis and a recursive system model. RESULTS: A total of 206 imported malaria patients were included in this study, including 194 men (94.17%) and 12 women (5.83%). The mean length of hospital stay was 5.00 days per patient and the median hospitalization expenses were 2 813.07 Yuan per time, in which the expenses for laboratory examinations were the highest (45.31%, 1 274.62/2 813.07). Univariate analysis showed that hospital (z = 5.43, P < 0.01), type of malaria (χ2 = 34.86, P < 0.01) and type of payment (χ2 = 7.72, P < 0.05) were factors affecting the hospitalization expenses of imported malaria patients. Recursion system modeling revealed that the total effects on hospitalization expenses of imported malaria patients included length of hospital stay (0.78), selection of hospital (0.34), basic medical insurance for urban and rural residents (0.19), new rural cooperative medical care (0.17), Plasmodium falciparum malaria (0.15), gender (0.11) and P. vivax malaria (0.09). CONCLUSIONS: The hospitalization expenses of imported malaria patients are affected by multiple factors in Guangxi Zhuang Autonomous Region and Yunnan Province, in which the length of hospital stay is the most predominant influencing factor. A reduction in the length of hospital stay is effective to decrease the hospitalization expenses of imported malaria patients.

Assessment of variability in GWAS with CRLMM genotyping algorithm on WTCCC coronary artery disease.

The robustness of genome-wide association study (GWAS) results depends on the genotyping algorithms used to establish the association. This paper initiated the assessment of the impact of the Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) genotyping quality on identifying real significant genes in a GWAS with large sample sizes. With microarray image data from the Wellcome Trust Case-Control Consortium (WTCCC), 1991 individuals with coronary artery disease (CAD) and 1500 controls, genetic associations were evaluated under various batch sizes and compositions. Experimental designs included different batch sizes of 250, 350, 500, 2000 samples with different distributions of cases and controls in each batch with either randomized or simply combined (4:3 case-control ratios) or separate case-control samples as well as whole 3491 samples. The separate composition could create 2-3% discordance in the single nucleotide polymorphism (SNP) results for quality control/statistical analysis and might contribute to the lack of reproducibility between GWAS. CRLMM shows high genotyping accuracy and stability to batch effects. According to the genotypic and allelic tests (P<5.0 x 10(-7)), nine significant signals on chromosome 9 were found consistently in all batch sizes with combined design. Our findings are critical to optimize the reproducibility of GWAS and confirm the genetic role in the pathophysiology of CAD.

Biomarker risk assessment and bladder cancer detection in a cohort exposed to benzidine.

BACKGROUND: Cancer screening with highly sensitive, specific biomarkers that reflect molecular phenotypic alterations is an attractive strategy for cancer control. We examined whether biomarker profiles could be used for risk assessment and cancer detection in a cohort of Chinese workers occupationally exposed to benzidine and at risk for bladder cancer. METHODS: The cohort consisted of 1788 exposed and 373 nonexposed workers, followed from 1991 through 1997. We assayed urothelial cells from voided urine samples for DNA ploidy (expressed as the 5C-exceeding rate [DNA 5CER]), the bladder tumor-associated antigen p300, and a cytoskeletal protein (G-actin). Workers were stratified into different risk groups (high, moderate, and low risk) at each examination based on a predefined biomarker profile. For workers who developed bladder cancer, tumor risk assessment was analyzed from samples collected 6-12 months before the cancer diagnosis. The associations between risk group and subsequent development of bladder cancer were analyzed by Cox proportional hazards regression analysis and logistic analysis, after adjustment. All statistical tests were two-sided. RESULTS: Twenty-eight bladder cancers were diagnosed in exposed workers and two in nonexposed workers. For risk assessment, DNA 5CER had 87.5% sensitivity, 86.5% specificity, an odds ratio (OR) of 46.2 (95% confidence interval [CI] = 8.1 to 867.0), and a risk ratio (RR) of 16.2 (95% CI = 7.1 to 37.0); p300 had 50.0% sensitivity, 97.9% specificity, an OR of 40.0 (95% CI = 9.0 to 177.8), and an RR of 37.9 (95% CI = 16.8 to 85.3). The risk of developing bladder cancer was 19.6 (95% CI = 8.0 to 47.9) times higher in workers positive for either the DNA 5CER or p300 biomarkers than in workers negative for both biomarkers and 81.4 (95% CI = 33.3 to 199.3) times higher in workers positive for both biomarkers. G-actin was a poor marker of individual risk. CONCLUSIONS: Occupationally exposed workers at risk for bladder cancer can be individually stratified, screened, monitored, and diagnosed based on predefined molecular biomarker profiles.

Validation of benzene exposure assessment.

We conducted a methodologic study to validate a quantitative retrospective exposure assessment method used in a follow-up study of workers exposed to benzene. Assessment of exposure to benzene was carried out in 672 factories in 12 cities in China. Historical exposure data were collected for 3179 unique job titles. The basic unit for exposure assessment was a factory/work-unit/job-title combination over seven periods between 1949 and 1987. A total of 18,435 exposure estimates was developed, using all available historical information, including 8477 monitoring data. Overall, 38% of the estimates were based on benzene monitoring data. The highest time-weighted average exposures occurred in the rubber industry (30.7 ppm), particularly for rubber glue applicators (52.6 ppm). Because of its recognized link with benzene exposure, the association between a clinical diagnosis of benzene poisoning (hematotoxicity) and benzene exposure was evaluated (412 cases and 614,509 person-years) to validate the exposure-assessment method. Relative risks of benzene hematotoxicity increased very sharply with increasing estimated intensity of benzene exposure. Odds ratios were 2.2 (95% CI: 1.7-2.9), 4.7 (95% CI: 3.4-6.5), and 7.2 (95% CI: 5.3-9.8) for the intensity levels of less than 5 ppm, 5-19 ppm, 20-39 ppm, and 40 and more ppm, respectively. This sharp trend between benzene hematotoxicity and estimated exposure to benzene indicated that the exposure-estimation method used in this cancer epidemiology study is reliable.

Indirect validation of benzene exposure assessment by association with benzene poisoning.

We present a validation study of a quantitative retrospective exposure assessment method used in a follow-up study of workers exposed to benzene. Assessment of exposure to benzene was carried out in 672 factories in 12 cities in China. Historical exposure data were collected for 3179 unique job titles. The basic unit for exposure assessment was a factory/work unit/job title combination over seven periods between 1949 and 1987. A total of 18,435 exposure estimates was developed, using all available historical information, including 8477 monitoring data. Overall, 38% of the estimates were based on benzene monitoring data. The highest time-weighted average exposures were observed for the rubber industry (30.7 ppm) and for rubber glue applicators (52.6 ppm). Because of its recognized link with benzene exposure, the association between a clinical diagnosis of benzene poisoning and benzene exposure was evaluated to validate the assessment method that we used in the cohort study. Our confidence in the assessment method is supported by the observation of a strong positive trend between benzene poisoning and various measures, especially recent intensity of exposure to benzene.

Cohort study among workers exposed to benzene in China: II. Exposure assessment.

This report describes a retrospective exposure assessment method used in a follow-up mortality study of workers exposed to benzene. The approach quantified historical exposure to benzene in a multi-industry, multicenter cohort, involving 672 factories in 12 cities in China. Historical exposure data were collected to obtain exposure information related to 1,427 work units (departments) and 3,179 unique job titles from benzene-producing or -using factories in which written records and other data sources were evaluated. The basic unit for exposure assessment was a factory/work unit/job title combination which was considered separately during each of seven calendar-year time periods between 1949 and 1987 for a total of 18,435 exposure assignments. Historical information collected to estimate exposure included benzene monitoring data; lists of raw materials and factory products, and the percentage of benzene in each; the total amount and dates of use of benzene or benzene-containing materials; use of engineering controls and personal protective equipment; and other available exposure information. Overall, 38% (ranging from 3% for the earliest periods to 67% for the last period) of the estimates were based primarily on benzene monitoring data. In the absence of job-specific benzene monitoring data for a given calendar period, measurement results or exposure estimates for similar jobs and/or other calendar periods were used in conjunction with other exposure information to derive estimates. Estimated exposure levels are presented by industries and occupations. The highest average exposures during 1949-1987 were observed for the rubber and plastic industry (30.7 ppm), and for rubber glue applicators (52.6 ppm).