Importance:Lung cancer (LC) remains the leading cause of cancer-related mortality worldwide, with tobacco smoking being the primary risk factor. However, the long-term LC risk among individuals with negative low-dose computed tomography (LDCT) findings and the role of tobacco smoking in risk stratification remain poorly understood, limiting evidence-based guidance for subsequent screening intervals. Objective:To evaluate the association of tobacco smoking with long-term LC risk after a negative baseline LDCT finding and to inform optimized screening strategies. Design, Setting, and Participants:This population-based, prospective cohort study was conducted under the Cancer Screening Program in Urban China. Individuals aged 40 to 74 years with negative baseline LDCT findings (October 1, 2013, to December 31, 2021) were included, with follow-up until December 2023. All participants were monitored for LC incidence. Exposures:Self-reported smoking status, pack-years, and time since quitting. Main Outcomes and Measures:The primary outcome was LC incidence, analyzed using Kaplan-Meier methods and multivariable Cox proportional hazards regression models. The association between smoking exposure and LC risk was assessed, with time-stratified analyses and dose-response associations. Results:Among 30 565 participants (14 761 never smokers and 15 804 smokers; mean [SD] age, 57.1 [7.7] years; 15 693 [51.3%] female), 76 LC cases occurred during 139 011.51 person-years (crude incidence rate, 54.67 of 100 000 person-years). Smokers had higher LC risk than never smokers (adjusted hazard ratio [AHR], 2.73; 95% CI, 1.49-5.01), driven by those with a smoking history of 20 pack-years or more (eg, ≥30 pack-years: AHR, 3.22; 95% CI, 1.85-5.58). There was no elevated risk at 2 years (AHR, 2.07; 95% CI, 0.91-4.69), but risk was significantly increased at 3 years (AHR, 2.54; 95% CI, 1.19-5.41) and onward. A nonlinear dose-response association was found between pack-years and LC risk, with risk surpassing clinically relevant thresholds at approximately 20 pack-years (eg, 20 to <30 pack-years: AHR, 2.48; 95% CI, 1.14-5.40). Females exhibited higher susceptibility than males at comparable exposure (≥30 pack-years: AHR, 5.78 [95% CI,1.87-17.83] for females vs 1.36 [95% CI, 0.18-10.39] for males). Significant risk was seen in those aged 50 to 54 years (≥30 pack-years) and 55 to 74 years (≥20 pack-years). Short-term cessation (<15 years) was not significantly associated with reduced LC risk. Conclusions and Relevance:In this cohort study, smokers with negative baseline LDCT findings exhibited a substantially elevated long-term LC risk, which became significant only after 2 years after screening. These findings suggest support for extending the initial screening interval and implementing personalized long-term monitoring based on smoking history.

Cardiovascular-kidney-metabolic (CKM) syndrome has been proposed, yet its utility for cancer risk stratification and behavior modification remains unclear. The study included 227,330 cancer-free participants from UK Biobank. CKM stages were defined using the American Heart Association (AHA) criteria, and lifestyle factors included smoking, alcohol consumption, physical activity, and diet. The hazard ratios (HRs) and lifetime risks of cancer were estimated using the Cox model and Fine and Gray's model, respectively. During a median follow-up of 11.46-13.65 years, 24,916 cancer cases and 7791 deaths were identified. Risks of cancer incidence and mortality increased progressively with advancing CKM stages (P trend < 0.001), with HRs (95% CIs) of 1.23 (1.15-1.30), and 1.58 (1.41-1.78) for stage 4. Compared with participants with unfavorable lifestyle, those with favorable lifestyle were associated with decreased risks across stages 0-4, with risk reductions of 14%-24% for cancer incidence, and 22%-40% for cancer mortality. Joint analyses showed that the increased cancer risks associated with CKM stages were eliminated or attenuated by adopting favorable lifestyle, particularly in stages 1-2. Participants in stage 4/unfavorable lifestyle had the highest risks of cancer incidence and mortality, with HRs (95% CI) of 1.54 (1.39-1.70) and 2.43 (1.97-2.99), and cumulative risks by age 80 of 34.77% and 11.65%, respectively. Furthermore, CKM stage 4/unfavorable lifestyle was associated with higher incidence of breast, colorectal, lung, kidney, pancreas, bladder, head and neck, esophagus, and liver cancers. These findings support the potential utility of CKM stages for cancer risk stratification and highlight the importance of lifestyle intervention.

BACKGROUND:Lung cancer is the leading cause of cancer-related deaths worldwide, with non-smokers in China accounting for over 40% of cases. Despite the proven efficacy of low-dose computed tomography (LDCT) in early detection and reduction of lung cancer mortality, the current paradigm of lung cancer screening, heavily focused on smoking status and age, may inadequately address the unique risk factors associated with non-smokers, particularly those with a family history of the disease. This study evaluates the cost-effectiveness of LDCT screening for non-smokers with a first-degree relative (FDR) history of lung cancer, a group at particularly high-risk. METHODS:We developed a state-transition Markov model to evaluate the incremental cost-effectiveness ratios (ICERs) of 16 screening strategies for a hypothetical cohort of 100,000 non-smoking individuals aged 50 with a FDR history of lung cancer, considering various starting ages (50, 55, 60, 65 years) and intervals (one-off, annual, biennial, triennial). The willingness-to-pay (WTP) threshold was set at three times China's 2022 per-capita GDP. Sensitivity analyses, scenario analyses and subgroup analysis by sex, were conducted. RESULTS:Compared to no screening, all strategies except one-off screening at age 50, were cost-effective for both sexes. Biennial LDCT starting at age 55 was found to be most effective, with an ICER of CNY 68,932/QALY for males, and CNY 80,056/QALY for females. This cost-effectiveness probability for this strategy was approximately 90% for both sexes. Sensitivity analyses indicated that annual screening at age 55 was optimal without discounting. For males, biennial at age 60 was optimal if the FDR-related odds ratio for lung cancer incidence was below 1.492. Triennial screening at age 55 was optimal for females at full adherence. Ignoring disutility from false-positive results, annual at age 55 was optimal for both sexes. CONCLUSIONS:LDCT screening for non-smokers with a FDR history of lung cancer is cost-effective, especially biennial screening at 55. These findings support the development of more inclusive screening guidelines, which could enhance early detection and reduce mortality rates.

BACKGROUND:Although guidelines stress the importance of early screening for individuals at high risk of lung cancer in China, there is a lack of data on risk-adapted starting ages for screening. This study aims to determine the appropriate starting age for lung cancer screening in China, considering various risk factors associated with the disease. METHODS:The data used were from the Cancer Screening Program in Urban China. A total of 413,725 eligible participants aged 40-74 years from eight cities in China were enrolled between 2013 and 2021. The outcomes of the study included lung cancer diagnosis and age at diagnosis. The risk-adapted starting age for screening was defined as the age at which individuals with varying levels of lung cancer risk reached a 10-year cumulative risk level similar to that of those aged 50 years in the general population. RESULTS:Among the 413,725 individuals who participated in the study, 1607 were diagnosed with lung cancer with a median follow-up of 4.90 (3.01, 6.84) years. The participants were categorized into different risk groups based on their lung cancer risk scores, which were determined by various risk factors, such as gender, education level, body mass index, vegetable intake, smoking pack-years, and tea consumption. In the study, the optimal starting age for lung cancer screening was determined on the basis of an individual's risk level. Using the 10-year cumulative risk of lung cancer at age 50 years in the general population as a benchmark (0.59% [95% confidence interval, 0.52-0.63%]), the study revealed that individuals with high, medium, or low risk of lung cancer should start screening at ages 46, 48, or 54 years and older, respectively. CONCLUSIONS:This study establishes the age at which lung cancer screening should begin on the basis of the principle of equal management and risk management. These findings have the potential to contribute to updates in the current screening guidelines.

INTRODUCTION:Previous studies have highlighted the importance of blood lipid levels in lung cancer. However, evidence of the association between remnant cholesterol and lung cancer remains scarce. This study aimed to investigate the association of remnant cholesterol with lung cancer morbidity and mortality and to evaluate their joint effects with C-reactive protein in women. METHODS:This prospective cohort study included 198,154 women initially without cancer from the UK Biobank. Remnant cholesterol was calculated as non-high-density lipoprotein cholesterol minus the measured low-density lipoprotein cholesterol. Cox models were adopted to estimate hazard ratios and 95% CIs for the incidence of lung cancer. Data were collected between 2006 and 2022 and analyzed in 2025. RESULTS:During a median follow-up of 11.80-13.90 years, 1,552 lung cancer cases and 1,074 related deaths were identified. Remnant cholesterol was positively associated with lung cancer morbidity and mortality in a linear manner, with respective hazard ratios (95% CIs) of 1.50 (1.23, 1.82) and 1.40 (1.11, 1.77) in Quartile 4. Compared with the low remnant cholesterol/low C-reactive protein group, the risk of incident lung cancer and lung cancer mortality increased by 115% and 102%, respectively, in the high remnant cholesterol/high C-reactive protein group. The cumulative risks of lung cancer by age 80 years were higher in the high remnant cholesterol/high C-reactive protein group than in the low remnant cholesterol/low C-reactive protein group (morbidity=3.64% vs 1.56%; mortality=1.97% vs 0.82%). CONCLUSIONS:This study found linear and positive associations of remnant cholesterol with lung cancer morbidity and mortality among women. The combination of high remnant cholesterol and C-reactive protein conferred the highest relative and absolute risks. These findings highlighted the importance of considering the combination of remnant cholesterol and C-reactive protein levels for the primary prevention of lung cancer and selection of high-risk populations for lung cancer screening among women.

BACKGROUND:Colorectal cancer (CRC) is prevalent in China, but many features of CRC patients remain to be better characterized. We aimed to describe the characteristics of clinical epidemiology in CRC patients in China and to evaluate the changes in health-related quality of life (HRQOL) before and after treatment. METHODS:A hospital-based survey was conducted among CRC patients from 2020 to 2021, covering 14 cities in China. Data on demographic and clinical characteristics, disease knowledge, medical service utilization, medical expenditure, and HRQOL before and after treatment were surveyed. The multivariable regressions and structural equation model (SEM) were used to assess the association between characteristics and HRQOL. RESULTS:In the survey of 4589 patients, nearly 80% were diagnosed at an age older than 50, with 59.5% being men and 54.5% having rectal cancer. Approximately 35.2% were diagnosed at stage IV and 37.5% had metastases. Prior to diagnosis, only 2.6% of patients had a colonoscopy screening, with the primary barrier being unawareness. After treatment, there was a significant decline in the overall HRQOL scores (66.98 vs. 65.39, P < 0.001) and a significant association between patients' awareness of CRC treatment and higher HRQOL changes (beta: 0.98, 95% CI 0.39-1.57; P = 0.001). The SEM model showed good model fit, revealing that awareness of CRC treatment was significantly associated with changes in HRQOL (beta: 0.06, 95% CI 0.04-0.09; P = 0.009). CONCLUSION:Our study highlighted a low CRC screening rate in China, largely due to limited public awareness. After treatment, HRQOL declined, and treatment awareness was significantly associated with this change.

Low dose computed tomography (LDCT) screening has been proven to be effective in reducing lung cancer mortality, but the ensuing high false-positive and overdiagnosis rates shackle the effectiveness of lung cancer screening (LCS) in China. Nodule malignancy prediction models may be an applicable solution. We conducted a prospective cohort study to develop and internally validate the model using data from the ongoing Henan province Cancer Screening Program in Urban China (CanSPUC). From 2013 to 2021, 23,031 heavy smokers underwent baseline screening with LDCT; 2553 participants were diagnosed with pulmonary nodules. Detailed questionnaire, physical assessment and follow-up were completed for all participants. Multivariable Cox proportional risk regression models were used to identify and integrate key prognostic factors for the development of a nomogram model. Data from the National Lung Screening Trial (NLST) were utilized for external validation. A total of 111 lung cancer cases with a median follow-up duration of 3.7 years occurred in the Henan CanSPUC. Age, gender, physical activity, consumption of pickled food, history of silicosis or pneumoconiosis, nodule type, size, calcification, and pleural retraction sign were included into the model. The AUC was 0.855, 0.844, and 0.863 for the 1-, 3- and 5-year lung cancer risk in the training set, respectively. Compared with Mayo model, VA model, PKU model, and Brock model, the Henan CanSPUC model yield statistically better discriminatory performance (all P values < 0.05). The model calibrated well across the deciles of predicted risk in both the overall population and all subgroups. The model demonstrated good calibration and discrimination in the internal validation cohort, while the external validation cohort showed lower predictive performance, indicating that further external validation is needed. The model developed and validated in this study may be used to estimate the probability of lung cancer in nodules detected at baseline LDCT, allowing more efficient risk-adapted follow-up in population-based LCS programs. However, further external validation in broader and more diverse populations is warranted.

Objective: To analyze the detection of colorectal advanced neoplasms in the population who underwent colonoscopy screening in Henan Province as part of the Urban China Cancer Screening Program and its influencing factors. Methods: A cross-sectional study design was employed. Based on the Cancer Screening Program conducted in Henan Province, the study enrolled 7 454 urban residents who manifested no symptoms and were recruited from eight cities in the province, including Zhengzhou, Zhumadian, Anyang, Luoyang, Nanyang, Jiaozuo, Xinxiang, and Puyang from October 2013 to October 2019, and participated in colonoscopy screening. The χ2 test was used to compare the detection rates of colorectal advanced neoplasms among participants with different characteristics, and a multivariate logistic stepwise regression model was used to analyze the factors affecting the detection rates. Results: A total of 7 454 subjects underwent colonoscopy screening, and 112 cases of colorectal advanced neoplasms were detected. Multivariate logistic regression analysis suggested that older age, smoking, higher meat intake, history of diabetes, and family history of colorectal cancer in a first-degree relative were risk factors for colorectal advanced neoplasms. The detection rate was significantly higher in people aged 60-74 years compared with those aged 40-49 years, with an odds ratio (OR) of 2.04 (95% CI: 1.23-3.38).The rates were higher in people who smoked than those who did not smoke, with an OR of 2.21 (95% CI: 1.48-3.31), and in people who consumed more meat than those who consumed less, with an OR of 1.53 (95% CI: 1.04-2.26). Those with diabetes had a higher detection rate compared with those without, with an OR of 1.69 (95% CI: 1.07-2.69), and those with a first-degree family history of colorectal cancer had a higher detection rate than those without, with an OR of 1.64 (95% CI: 1.09-2.46). Conclusion: The detection rate of colorectal advanced neoplasms through colonoscopy screening in Henan Province covered by the Urban China Cancer Screening Program is 1.50%. Older age, smoking, higher meat intake, history of diabetes, and family history of colorectal cancer in a first-degree relative are identified as risk factors for colorectal advanced neoplasms.

Rationale and Objective: There is a notable absence of robust evidence on the efficacy of ultrasound-based breast cancer screening strategies, particularly in populations with a high prevalence of dense breasts. Our study addresses this gap by evaluating the effectiveness of such strategies in Chinese women, thereby enriching the evidence base for identifying the most efficacious screening approaches for women with dense breast tissue. Methods: Conducted from October 2018 to August 2022 in Central China, this prospective cohort study enrolled 8996 women aged 35-64 years, divided into two age groups (35-44 and 45-64 years). Participants were screened for breast cancer using hand-held ultrasound (HHUS) and automated breast ultrasound system (ABUS), with the older age group also receiving full-field digital mammography (FFDM). The Breast Imaging Reporting and Data System (BI-RADS) was employed for image interpretation, with abnormal results indicated by BI-RADS 4/5, necessitating a biopsy; BI-RADS 3 required follow-up within 6-12 months by primary screening strategies; and BI-RADS 1/2 were classified as negative. Results: Among the screened women, 29 cases of breast cancer were identified, with 4 (1.3%o) in the 35-44 years age group and 25 (4.2%o) in the 45-64 years age group. In the younger age group, HHUS and ABUS performed equally well, with no significant difference in their AUC values (0.8678 vs. 0.8679, P > 0.05). For the older age group, ABUS as a standalone strategy (AUC 0.9935) and both supplemental screening methods (HHUS with FFDM, AUC 0.9920; ABUS with FFDM, AUC 0.9928) outperformed FFDM alone (AUC 0.8983, P < 0.05). However, there was no significant difference between HHUS alone and FFDM alone (AUC 0.9529 vs. 0.8983, P > 0.05). Conclusion: The findings indicate that both HHUS and ABUS exhibit strong performance as independent breast cancer screening strategies, with ABUS demonstrating superior potential. However, the integration of FFDM with these ultrasound techniques did not confer a substantial improvement in the overall effectiveness of the screening process.

Objective:To understand the current status and changing trends in the lifetime risk of residents in Henan Province, China to develop and die from cancer. Methods:Lifetime risk was estimated using the Adjusted for Multiple Primaries (AMP) method, incorporating cancer incidence, mortality, and all-cause mortality data from 55 cancer registries in Henan Province, China. Estimates were calculated overall and stratified by gender and area. The annual percent change (APC) in lifetime risk from 2010 to 2020, stratified by gender and cancer site, was estimated using a log-linear model. Results:In 2020, the lifetime risk of developing and dying from cancer was 30.19 % (95 % CI: 29.63 %-30.76 %) and 23.62 % (95 % CI: 23.28 %-23.95 %), respectively. These estimates were higher in men, with values of 31.22 % (95 % CI: 30.59 %-31.85 %) for developing cancer and 26.73 % (95 % CI: 26.29 %-27.16 %) for dying from cancer, compared with women, who had values of 29.02 % (95 % CI: 28.12 %-29.91 %) and 20.08 % (95 % CI: 19.51 %-20.64 %), respectively. There were also geographical differences, with higher estimates in urban areas compared with rural areas. Residents had the highest lifetime risk of developing lung cancer, with a rate of 6.94 %, followed by breast cancer (4.14 %), stomach cancer (3.95 %), esophageal cancer (3.75 %), and liver cancer (2.86 %). Similarly, the highest lifetime risk of dying from cancer was observed for the following sites: lung (5.99 %), stomach (3.60 %), esophagus (3.39 %), liver (2.78 %), and colorectum (1.55 %). Overall, the lifetime risk of developing cancer increased, with an APC of 0.75 % (P < 0.05). Varying trends were observed across different cancer sites. There were gradual decreases in nasopharynx, esophagus, stomach, and liver cancers. Conversely, increasing trends were noted for most other sites, with the highest APCs observed in thyroid, prostate, lymphoma, kidney, and gallbladder cancers. Conclusion:The lifetime risks of developing and dying from cancer were 30.19 % and 23.62 %, respectively. Variations in cancer risk across different regions, genders, specific cancer sites, and over calendar years provide important information for cancer prevention and policy making in the population.

Background Annual screening through low-dose computed tomography (LDCT) is recommended for heavy smokers. However, it is questionable whether all individuals require annual screening given the potential harms of LDCT screening. This study examines the benefit–harm and cost-effectiveness of risk-based screening in heavy smokers and determines the optimal risk threshold for screening and risk-stratified screening intervals. Methods We conducted a comparative cost-effectiveness analysis in China, using a cohort-based Markov model which simulated a lung cancer screening cohort of 19,146 heavy smokers aged 50 ~ 74 years old, who had a smoking history of at least 30 pack-years and were either current smokers or had quit for < 15 years. A total of 34 risk-based screening strategies, varying by different risk groups for screening eligibility and screening intervals (1-year, 2-year, 3-year, one-off, non-screening), were evaluated and were compared with annual screening for all heavy smokers (the status quo strategy). The analysis was undertaken from the health service perspective with a 30-year time horizon. The willingness-to-pay (WTP) threshold was adopted as three times the gross domestic product (GDP) of China in 2021 (CNY 242,928) per quality-adjusted life year (QALY) gained. Results Compared with the status quo strategy, nine risk-based screening strategies were found to be cost-effective, with two of them even resulting in cost-saving. The most cost-effective strategy was the risk-based approach of annual screening for individuals with a 5-year risk threshold of ≥ 1.70%, biennial screening for individuals with a 5-year risk threshold of 1.03 ~ 1.69%, and triennial screening for individuals with a 5-year risk threshold of < 1.03%. This strategy had the highest incremental net monetary benefit (iNMB) of CNY 1032. All risk-based screening strategies were more efficient than the status quo strategy, requiring 129 ~ 656 fewer screenings per lung cancer death avoided, and 0.5 ~ 28 fewer screenings per life-year gained. The cost-effectiveness of risk-based screening was further improved when individual adherence to screening improved and individuals quit smoking after being screened. Conclusions Risk-based screening strategies are more efficient in reducing lung cancer deaths and gaining life years compared to the status quo strategy. Risk-stratified screening intervals can potentially balance long-term benefit–harm trade-offs and improve the cost-effectiveness of lung cancer screenings.

[目的]分析2018年河南省白血病流行特征及2010-2018年变化趋势.[方法]收集、整理2010-2018年河南省白血病发病和死亡数据,按性别和年龄组分层估算2018年河南省白血病发病/死亡率、中国人口标化率(中标率)、世界人口标化率(世标率)、0～74岁累积发病/死亡率,应用年度变化百分比(annual percentage change,APC)分析2010-2018年河南省白血病发病率和死亡率的变化趋势.[结果]据估计,2018年河南省共有4 947例白血病新发病例,粗发病率为4.54/10万,中标率为4.04/10万,世标率为4.15/10万,累积发病率(0～74岁)为0.38％,发病例数占全部癌症新发病例数的1.73％.共有3 107例白血病死亡病例,粗死亡率为2.85/10万,中标率为2.41/10万,世标率为2.38/10万,累积死亡率(0～74岁)为0.23％,死亡病例数占全部癌症死亡病例数的1.85％.男性白血病中标发病率和中标死亡率均高于女性,城市地区白血病中标发病率高于农村地区.2010-2018年河南省白血病发病率(APC=-2.7％,95％CI:-4.3％～-1.1％)与死亡率(APC=-2.7％,95％CI:-4.6％～-0.8％)均呈显著下降趋势(P均＜0.05).[结论]2010-2018年河南省白血病发病率、死亡率均呈下降趋势,但由于河南省人口基数大,白血病防控仍不容忽视.

[目的]分析河南省2018年恶性肿瘤流行现状及2014-2018年变化趋势.[方法]收集河南省各肿瘤登记处数据并评估数据质量,分城乡、性别及年龄计算登记人群的发病率和死亡率,结合人口数据估计2018年全省恶性肿瘤发病和死亡情况.人口标化率按照2000年全国普查标准人口年龄构成(中标率)和Segi世界标准人口结构(世标率)进行计算,2014-2018年恶性肿瘤变化趋势使用Joinpoint回归模型分析.[结果]2018年河南省估计恶性肿瘤新发病例数285 770例,发病率为262.03/10万,中标率为201.40/10万,其中男性中标率(211.36/10万)高于女性(194.05/10万),城市地区中标率(210.18/10万)高于农村地区(197.23/10万);男性发病顺位前5位依次是肺癌、胃癌、肝癌、食管癌和结直肠癌,女性发病顺位前5位依次乳腺癌、肺癌、食管癌、宫颈癌和甲状腺癌.2018年河南省估计恶性肿瘤死亡病例数168 268例,死亡率为154.29/10万,中标率为110.70/10万,其中男性中标率(141.75/10万)远高于女性(81.74/10万),农村地区(112.64/10万)高于城市地区(106.76/10万);男性死亡顺位前5位分别为肺癌、胃癌、肝癌、食管癌和结直肠癌,女性分别为肺癌、食管癌、胃癌、肝癌和乳腺癌.2014-2018年恶性肿瘤中标发病率基本保持稳定水平(APC=-0.48％,P＞0.05),中标死亡率有所下降(APC=-2.54％,P＞0.05),但趋势变化均无统计学意义.[结论]肺癌、消化系统恶性肿瘤及女性乳腺癌是威胁河南省居民健康的主要恶性肿瘤,常见恶性肿瘤的发病与死亡状况呈现显著性别差异.需进一步优化和加强恶性肿瘤防控工作,提高全人群健康意识.

[目的]评估胃癌统计治愈比例现状及其与胃癌内镜筛查之间的关系.[方法]提取2005-2012年林州市以人群为基础的肿瘤登记数据库中ICD-10为C16.0～C16.9范围的胃癌病例数据(共6 172例),通过链接胃癌人群筛查数据库与肿瘤登记数据库以获取患者是否参加筛查信息,利用混合统计治愈模型建模并估计统计治愈比例及相对生存率,计算比值比(OR)值以及95％可信区间(CI)以评估胃癌内镜筛查和统计治愈之间的关系.[结果]曾参加内镜筛查和从未参加内镜筛查胃癌患者的统计治愈比例分别为75.51％(95％CI:69.18％～81.85％)和 31.69％(95％CI:30.30％～33.07％),估计治愈比例两者差值为 38.76％(32.35％～45.00％).参加内镜筛查患者与未参加筛查患者相比,受益于统计治愈的OR为5.84(95％CI:4.10～8.31),参加内镜筛查患者受益于贲门胃统计治愈(OR=6.10,95％CI:3.96～9.39)要高于非贲门胃(OR=5.34,95％CI:2.54～11.23).[结论]参加胃癌内窥镜筛查可以提高胃癌患者统计治愈比例.

[目的]综合评价2013-2019年河南省城市居民上消化道癌筛查的结果和成本效果.[方法]基于河南省2013-2019年开展的城市癌症早诊早治项目,分析40～74岁城市居民上消化道癌高危率和内镜筛查参与率,采用X2检验比较不同组间率的差异.同时分析上消化道癌及其癌前病变检出率,测算以检出1例病变的成本为指标的成本效果比.[结果]共进行有效问卷调查282 262人,评估为食管癌或胃癌高危68 651名,高危率为24.32％,其中13 191名接受了内镜检查,内镜筛查参与率为19.21％,共检出上消化道癌31例(检出率为0.24％)和癌前病变386例(检出率为2.93％).成本效果分析结果显示,筛查检出1例上消化道癌或癌前病变的成本为18 025.46元,其中检出1例上消化道癌的成本达242 471.52元;男性成本效果比小于女性;年龄组越大,成本效果比越小.敏感性分析提示,提高内镜筛查参与率可降低成本效果比.[结论]采用问卷调查浓缩高危人群以及内镜检查策略有助于发现上消化道病变和降低筛查成本,但内镜筛查参与率较低,限制了筛查整体效果和经济学收益,应进一步加强高危人群内镜检查的组织动员工作.

The rapid development of artificial intelligence (AI) technology, especially the progress in deep learning methods and computing power of hardware, has greatly promoted the application of AI in the field of biomedicine and nephrology. AI can predict the occurrence of acute kidney injury, identify chronic kidney disease, and assist in the analysis of kidney disease pathology, prognosis prediction and decision-making. The application of AI in the field of nephrology depends on the coordinated development of nephrology and artificial intelligence, and requires close interdisciplinary cooperation between multiple disciplines. This article describes the application and research progress of AI in nephrology and provides insights for future directions.

Background: It is believed that smoking is not the cause of approximately 53% of lung cancers diagnosed in women globally. Objective: The study aimed to develop and validate a simple and noninvasive model that could assess and stratify lung cancer risk in nonsmoking Chinese women. Methods: Based on the population-based Cancer Screening Program in Urban China, this retrospective, cross-sectional cohort study was carried out with a vast population base and an immense number of participants. The training set and the validation set were both constructed using a random distribution of the data. Following the identification of associated risk factors by multivariable Cox regression analysis, a predictive nomogram was developed. Discrimination (area under the curve) and calibration were further performed to assess the validation of risk prediction nomogram in the training set, which was then validated in the validation set. Results: In sum, 151,834 individuals signed up to take part in the survey. Both the training set (n=75,917) and the validation set (n=75,917) were comprised of randomly selected participants. Potential predictors for lung cancer included age, history of chronic respiratory disease, first-degree family history of lung cancer, menopause, and history of benign breast disease. We displayed 1-year, 3-year, and 5-year lung cancer risk-predicting nomograms using these 5 factors. In the training set, the 1-year, 3-year, and 5-year lung cancer risk areas under the curve were 0.762, 0.718, and 0.703, respectively. In the validation set, the model showed a moderate predictive discrimination. Conclusions: We designed and validated a simple and noninvasive lung cancer risk model for nonsmoking women. This model can be applied to identify and triage people at high risk for developing lung cancers among nonsmoking women.