Elevated mammographic density (MD) is an established breast cancer risk factor. Studies examining relationships between MD and breast cancer risk factors are limited in China, where established breast cancer risk factors are less prevalent but dense breasts are more prevalent than Western countries. This study included 11,478 women (45-69 years; 36% premenopausal) participating in an ongoing national cancer screening program in 11 urban provinces in China and predicted as having high-risk for breast cancer. Polytomous logistic regression was performed to assess associations between MD and risk factors by comparing each higher Breast Imaging Reporting and Data System (BI-RADS) category (2, 3, or 4) to the lowest category (BI-RADS, 1). We found associations of increasing age, body mass index, weight, postmenopausal status, and parity with lower MD. Higher levels of education, increasing height, and later first birth were associated with higher MD. These associations did not vary by menopausal status. Additionally, the association between longer period of breastfeeding and lower MD was seen among postmenopausal women only (Pinteraction = 0.003). Having first-degree relatives with breast cancer diagnosed before 50 years was associated with lower MD only among premenopausal women (Pinteraction = 0.061). We found effects of established breast cancer risk factors on MD showed similar directions in Chinese and Western women, supporting the hypothesis that MD represents cumulative exposure to breast cancer risk factors over the life course. Our findings help to understand the biological basis of the association of MD with breast cancer risk and have implications for breast cancer prevention research in China.

Background:To investigate the association between fasting blood glucose (FBG) levels and the risk of incident primary liver cancer (PLC) in Chinese males, a large prospective cohort was performed in the current study.Methods:A total of 109 169 males participating in the routine checkups every two years were recruited in the Kailuan male cohort study since May 2006. Cox proportional hazards regression models and restricted cubic spline (RCS) were used to evaluate the association between levels of baseline FBG and the risk of incident PLC.Results:Compared to the males with normal FBG (3.9⩽FBG<6.1 mmol l−1), the males with impaired fasting glucose (IFG: 6.1⩽FBG<7.0 mmol l−1) and diabetes mellitus (DM: FBG ⩾7.0 mmol l−1) had a 60% (95% CI: 1.09–2.35) and a 58% (95% CI: 1.07–2.34) higher risk of incident PLC, respectively. Subgroup analysis found that IFG increased the risk of PLC among the non-smoker (HR=1.73, 95% CI: 1.01–2.98) and current alcohol drinker (HR=1.80, 95% CI: 1.03–3.16). While DM increased the risk of PLC especially among the males with normal BMI (<25 kg m−2) (HR=1.76, 95% CI: 1.05–2.94) and the HBV negativity (HR=1.89, 95% CI: 1.16–3.09), RCS analysis showed a positive non-linearly association between the FBG levels and the risk of PLC (p-overall=0.041, p-non-linear=0.049).Conclusions:Increased FBG may be an important and potentially modifiable exposure that could have key scientific and clinical importance for preventing PLC development.

Objective The number of liver cancer patients in China accounts for more than half of the world. However, China currently lacks national, multicenter economic burden data, and meanwhile, measuring the differences among different subgroups will be informative to formulate corresponding policies in liver cancer control. Thus, the aim of the study was to measure the economic burden of liver cancer by various subgroups. Methods A hospital-based, multicenter and cross-sectional survey was conducted during 2012-2014, covering 39 hospitals and 21 project sites in 13 provinces across China. The questionnaire covers clinical information, sociology, expenditure, and related variables. All expenditure data were reported in Chinese Yuan (CNY) using 2014 values. Results A total of 2,223 liver cancer patients were enrolled, of whom 59.61% were late-stage cases (III-IV), and 53.8% were hepatocellular carcinoma. The average total expenditure per liver cancer patient was estimated as 53,220 CNY, including 48,612 CNY of medical expenditures (91.3%) and 4,608 CNY of non-medical expenditures (8.7%). The average total expenditures in stage I, II, III and stage IV were 52,817 CNY, 50,877 CNY, 50,678 CNY and 54,089 CNY (P>0.05), respectively. Non-medical expenditures including additional meals, additional nutrition care, transportation, accommodation and hired informal nursing were 1,453 CNY, 839 CNY, 946 CNY, 679 CNY and 200 CNY, respectively. The one-year out-of-pocket expenditure of a newly diagnosed patient was 24,953 CNY, and 77.2% of the patients suffered an unmanageable financial burden. Multivariate analysis showed that overall expenditure differed in almost all subgroups (P<0.05), except for sex, clinical stage, and pathologic type. Conclusions There was no difference in treatment expenditure for liver cancer patients at different clinical stages, which suggests that maintaining efforts on treatment efficacy improvement is important but not enough. To furtherly reduce the overall economic burden from liver cancer, more effort should be given to primary and secondary prevention strategies.

Background: It is important to understand the natural history of cervical cancer, which has implications for cancer prevention and management. However, a dearth of studies on the long-term development of cervical cancer exists in China.Methods: We investigated the natural history of cervical cancer in Chinese women by creating a multistate model using 11 years of follow-up data from the Shanxi Province Cervical Cancer Screening Study I conducted from 1999 to 2010. In 1999, a total of 1,997 eligible women, ages 35 to 45 years, were enrolled in Xiangyuan County, Shanxi Province. Participants were followed up in 2005 and 2010, respectively.Results: The average time a subject spent in CIN1 before transiting into another state was 1.4693 years [95% confidence interval (CI): 1.1215-1.9251] and the average time a subject spent in CIN2 was 2.9822 years (95% CI: 1.9790-4.4938). A subject's transition probability from CIN1 to normal increased with time. However, the transition probability from CIN1 to CIN2 was relatively lower, with 3-, 5-, and 10-year transition probabilities of 0.1415, 0.1066, and 0.0437. Comparison of 5-year transition probabilities between CIN2 to normal/CIN1 and CIN2 to CIN3 þ yielded a ratio of 2.74.

S3 of lung cancer cases and deaths were obtained from the Global Burden of Disease Study. RESULTS: The total SAE of lung cancer was estimated as US $9527.1 million in China in 2015 (accounting for 0.09% of the local gross domestic product), the decomposed direct and indirect SAE were estimated as $2505.0 million (accounting for 0.4% of total healthcare expenditure in local) and $7022.1 million (73.7% of total SAE), respectively. With 42.0% and 2.4% smoking prevalence among male and female in 2005, 93.5% of the total SAE occurred in male lung cancer in 2015 ($8903.3 million). Mainly due to the variation of burden of disease, age-specific total SAE peaked at 60-64 years group, urban areas' total SAE higher than rural areas'. In 2025, the SAE of lung cancer, compared with that in 2015, would increase by 30.9% ($12471.0 million). CONCLUSIONS: This might be the most detailed estimation on economic burden of lung cancer attributable to smoking in China. SAE caused by lung cancer accounted at least one tenth of all-diseases-caused SAE, compared to previous study. Without main population-level smoking intervention introduced, the economic burden of lung cancer attributable to smoking will continually increase over the next ten years.

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Background: Low-dose computed tomography screening has been proved to reduce lung cancer mortality, however, the issues of high false-positive rate and overdiagnosis remain unsolved. Risk prediction models for lung cancer that could accurately identify high-risk populations may help to increase efficiency. We thus sought to develop a risk prediction model for lung cancer incorporating epidemiological and metabolic markers in a Chinese population. Methods: During 2006 and 2015, a total of 122 497 people were observed prospectively for lung cancer incidence with the total person-years of 976 663. Stepwise multivariable-adjusted logistic regressions with P entry = .15 and P stay = .20 were conducted to select the candidate variables including demographics and metabolic markers such as high-sensitivity C-reactive protein (hsCRP) and low-density lipoprotein cholesterol (LDL-C) into the prediction model. We used the C-statistic to evaluate discrimination, and Hosmer-Lemeshow tests for calibration. Tenfold cross-validation was conducted for internal validation to assess the model's stability. Results: A total of 984 lung cancer cases were identified during the follow-up.The epidemiological model including age, gender, smoking status, alcohol intake status, coal dust exposure status, and body mass index generated a C-statistic of 0.731. The full model additionally included hsCRP and LDL-C showed significantly better discrimination (C-statistic = 0.735, P = .033). In stratified analysis, the full model showed better predictive power in terms of C-statistic in younger participants (<50 years, 0.709), females (0.726), and former or current smokers (0.742). The model calibrated well across the deciles of predicted risk in both the overall population (P HL = .689) and all subgroups. |Conclusions: We developed and internally validated an easy-to-use risk prediction model for lung cancer among the Chinese population that could provide guidance for screening and surveillance. K E Y W O R D Slung cancer, metabolic markers, prospective study, risk prediction model

To build a simple predictive model as a guide to stratify average-risk population for colonoscopy examinations. We collected data from 92 923 males without a prior history of cancer enrolled in the Kailuan Cohort Study of China. Risk factors included in the evaluation of colorectal cancer (CRC) were collected by questionnaire-based interviews at the baseline. Logistic regression coefficients for incident CRC predictors were converted into risk scores by the absolute value of the smallest coefficient in the model and rounding up to the nearest integer. Receiver operating characteristic (ROC) analysis with the leave-one-out cross-validation method was applied to evaluate model performance. In the 10-year follow-up, 353 CRC patients were in the cohort. Age, alcohol consumption, waist circumference, occupational sitting time, and history of diabetes were selected for the scoring system, and the adjusted area under the ROC was 0.66. Population in the highest risk group (16-19 points) had a 33.12-fold (95% CI: 13.44-81.59) higher risk of CRC than those in the lowest risk group. When we defined 13 points as the cut-off, the sensitivity and specificity of the scoring system for CRC were 67.99% and 62.42%, respectively. A simple scoring system for CRC has been developed to identify men at an increased relative risk of CRC within 10 years using several well-established risk factors, which allows selection of asymptomatic candidates for priority of CRC screening and saving the health resource in cancer prevention and control.