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Original Article
Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model
Maomao Cao, He Li, Dianqin Sun, Lin Lei, Jiansong Ren, Jufang Shi, Ni Li, Ji Peng, Wanqing Chen
, Available online  , doi: 10.21147/j.issn.1000-9604.2020.05.05
Abstract(68) FullText HTML (36)
Abstract:
ObjectiveThis study aimed at evaluating the efficacy of the questionnaire-based prediction model in an independent prospective cohort.MethodsA cluster-randomized controlled trial was conducted in Changsha, Harbin, Luoshan, and Sheyang in eastern China in 2015−2017. A total of 182 villages/communities were regarded as clusters, and allocated to screening arm or control arm randomly. Face-to-face interview through a questionnaire interview, including of relevant risk factors of gastric cancer, was administered for each subject. Participants were further classified into high-risk or low-risk groups based on their exposure to risk factors. All participants were followed up until December 31, 2019. Cumulative incidence rates from gastric cancer between high-risk and low-risk groups were calculated and compared using the log-rank test. Cox proportional hazard regression models were applied to estimate hazard ratio (HR) and 95% confidence interval (95% CI).ResultsTotally, 89,914 residents were recruited with a mean follow-up of 3.47 years. And 42,015 (46.73%) individuals were classified into high-risk group and 47,899 (53.27%) subjects were categorized into low-risk group. Gastric cancer was diagnosed in 131 participants, of which 91 were in high-risk group. Compared with the low-risk participants, high-risk individuals were more likely to develop gastric cancer (adjusted HR=2.15, 95% CI, 1.23−3.76). The sensitivity of the questionnaire-based model was estimated at 61.82% (95% CI, 47.71−74.28) in a general population.ConclusionsOur questionnaire-based model is effective at identifying high-risk individuals for gastric cancer.
Effects of insurance status on long-term survival among non-small cell lung cancer (NSCLC) patients in Beijing, China: A population-based study
Zheng Wang, Lei Yang, Shuo Liu, Huichao Li, Xi Zhang, Ning Wang, Jiafu Ji
, Available online  , doi: 10.21147/j.issn.1000-9604.2020.05.04
Abstract(91) FullText HTML (46)
Abstract:
ObjectiveTo evaluate the effects of health insurance status on long-term cancer-specific survival of non-small cell lung cancer (NSCLC) in Beijing, China, using a population-based cancer registry data.MethodsInformation on NSCLC patients diagnosed in 2008 was derived from the Beijing Cancer Registry. The medical records of 1,134 cases were sampled and re-surveyed to obtain information on potential risk factors. Poorly-insured status was defined as Uninsured and New Rural Cooperative Medical Insurance Scheme (NRCMS), while well-insured included Urban Employees Basic Medical Insurance (UEBMI) and Free Medical Care (FMC). To estimate survival outcomes, individuals were followed-up until December 31, 2018. Cancer-specific survival probabilities at 5 and 10 years after diagnosis were estimated using the Kaplan-Meier method. Log-rank test was used to compare long-term survival with different characteristics. Multivariable Cox proportional hazard regression model was used to examine the relative effect of insurance status on cancer-specific mortality.ResultsWell-insured NSCLC patients have longer cancer-specific survival than poorly-insured individuals [hazard ratio (HR)=0.81; 95% confidence interval (95% CI): 0.67−0.97), even after adjusting for age, gender, cancer stage, smoking status, family history and residential area. Older age and rural residence were associated with a higher risk of cancer-specific mortality (HR=1.03; 95% CI: 1.02−1.03 and HR=1.25; 95% CI: 1.07−1.46, respectively). Smoking individuals had a 41% higher long-term cancer-specific mortality risk than non-smoking ones (HR=1.41; 95% CI: 1.20−1.66).ConclusionsNSCLC patients with good insurance status had better survival rates than those with poor insurance. An association was significant even after 10 years. Large population-based studies are needed to validate that high reimbursement insurance status can lead to the improvement of long-term cancer prognosis in China.