Effects of joint screening for prostate, lung, colorectal, and ovarian cancer - results from a controlled trial.

Background: Although screening is widely used to reduce cancer burden, untargeted cancers are frequently missed after single cancer screening. Joint cancer screening is presumed as a more effective strategy to reduce overall cancer burden. Methods: Gender-specific screening effects on PLCO cancer incidence, PLCO cancer mortality, all-neoplasms mortality and all-cause mortality were evaluated, and meta-analyses based on gender-specific screening effects were conducted to achieve the pooled effects. The cut-off value of time-dependent receiver-operating-characteristic curve of 10-year combined PLCO cancer risk was used to reclassify participants into low- and high-risk subgroups. Further analyses were conducted to investigate screening effects stratified by risk groups and screening compliance. Results: After a median follow-up of 10.48 years for incidence and 16.85 years for mortality, a total of 5,506 PLCO cancer cases, 1,845 PLCO cancer deaths, 3,970 all-neoplasms deaths, and 14,221 all-cause deaths were documented in the screening arm, while 6,261, 2,417, 5,091, and 18,516 outcome-specific events in the control arm. Joint cancer screening did not significantly reduce PLCO cancer incidence, but significantly reduced male-specific PLCO cancer mortality (hazard ratio and 95% confidence intervals [HR(95%CIs)]: 0.88(0.82, 0.95)) and pooled mortality [0.89(0.84, 0.95)]. More importantly, joint cancer screening significantly reduced both gender-specific all-neoplasm mortality [0.91(0.86, 0.96) for males, 0.91(0.85, 0.98) for females, and 0.91(0.87, 0.95) for meta-analyses] and all-cause mortality [0.90(0.88, 0.93) for male, 0.88(0.85, 0.92) for female, and 0.89(0.87, 0.91) for meta-analyses]. Further analyses showed decreased risks of all-neoplasm mortality was observed with good compliance [0.72(0.67, 0.77) for male and 0.72(0.65, 0.80) for female] and increased risks with poor compliance [1.61(1.40, 1.85) for male and 1.30(1.13, 1.40) for female]. Conclusion: Joint cancer screening could be recommended as a potentially strategy to reduce the overall cancer burden. More compliance, more benefits. However, organizing a joint cancer screening not only requires more ingenious design, but also needs more attentions to the potential harms. Trial registration: NCT00002540 (Prostate), NCT01696968 (Lung), NCT01696981 (Colorectal), NCT01696994 (Ovarian).

Associations of chest X-ray trajectories, smoking, and the risk of lung cancer in two population-based cohort studies.

Objectives: Despite the increasing use of computed tomography (CT), chest X-ray (CXR) remains the first-line investigation for suspected lung cancer (LC) in primary care. However, the associations of CXR trajectories, smoking and LC risk remain unknown. Methods: A total of 52,486 participants from the PLCO and 22,194 participants from the NLST were included. The associations of CXR trajectories with LC risk were evaluated with multivariable COX regression models and pooled with meta-analyses. Further analyses were conducted to explore the stratified associations by smoking status and the factors associated with progression and regression in CXR. Results: Compared to stable negative CXR (CXRSN), HRs (95%CIs) of LC incidence were 2.88(1.50-5.52), 3.86(2.03-7.35), and 1.08(0.80-1.46) for gain of positive CXR (CXRGP), stable positive CXR (CXRSP), and loss of positive CXR (CXRLP), while the risk of LC mortality were 1.58(1.33-1.87), 2.56(1.53-4.29), and 1.05(0.89-1.25). Similar trends were observed across different smoking status. However, LC risk with CXRGP overweighed that with CXRSP among ever smokers [2.95(2.25-3.88) vs. 2.59(1.33-5.02)] and current smokers [2.33(1.70-3.18) vs. 2.26(1.06-4.83)]. Moreover, compared to CXRSN among never smokers, even no progression in CXR, the HRs(95%CIs) of LC incidence were 7.39(5.60-9.75) and 31.45(23.58-41.95) for ever and current smokers, while risks of LC mortality were 6.30(5.07-7.81) and 27.17(21.65-34.11). If participants gained positive CXR, LC incidence risk significantly climbed to 22.04(15.37-31.60) and 71.97(48.82-106.09) for ever and current smokers, while LC mortality risk climbed to 11.90(8.58-16.50) and 38.92(27.04-56.02). CXRLP was associated with decreased LC risk. However, even smokers lost their positive CXR, and the increased risks of LC incidence and mortality did not decrease to non-significant level. Additionally, smoking was significantly associated with increased risk of CXRGP but not CXRLP. Conclusion: LC risk differed across CXR trajectories and would be modified by smoking status. Comprehensive intervention incorporating CXR trajectories and smoking status should be recommended to reduce LC risk.

Risk-stratified multi-round PSA screening for prostate cancer integrating the screening reference level and subgroup-specific progression indicators.

BACKGROUND: Although prostate-specific antigen (PSA) is widely used in prostate cancer (PCa) screening, nearly half of PCa cases are missed and less than one-third of cases are non-lethal. Adopting diagnostic criteria in population-based screening and ignoring PSA progression are presumed leading causes. METHODS: A total of 31,942 participants with multi-round PSA tests from the PLCO trial were included. Time-dependent receiver-operating-characteristic curves and area under curves (tdAUCs) were performed to determine the screening reference level and the optimal subgroup-specific progression indicator. Effects of risk-stratified multi-round PSA screening were evaluated with multivariable Cox regression and measured with hazard ratio [HR (95%CIs)]. RESULTS: After a median follow-up of 11.6 years, a total of 3484 PCa cases and 216 PCa deaths were documented. The tdAUC of 10-year incidence PCa with PSA was 0.816, and the cut-off value was 1.61 ng/ml. Compared to subgroup with stable negative PSA in both first-round (FR) and last-round (LR) tests [FR(-)/LR(-)], HRs (95%CI) of PCa incidence were 1.66 (1.20-2.29), 8.29 (7.25-9.48), and 14.52 (12.95-16.28) for subgroups with loss of positive PSA[FR(+)/LR(-)], gain of positive PSA[FR(-)/LR(+)], and stable positive PSA[FR(+)/LR(+)]; while HRs(95%CI) of PCa mortality were 1.47 (0.52-4.15), 5.71 (3.68-8.86), and 5.01 (3.41-7.37). After excluding regressive PSA [(namely FR(+)/LR(-)], absolute velocity was the shared optimal progression indicator for subgroups with FR(-)/LR(-), FR(-)/LR(+), and FR(+)/LR(+), with tdAUCs of 0.665, 0.681 and 0.741, and cut-off values of 0.07, 0.21, and 0.33 ng/ml/year. After reclassifying participants into groups with positive and negative progression based on subgroup-specific progression indicators, incidence HR (95%CI) were 2.41 (1.87-3.10), 2.91 (2.43-3.48), and 3.16 (2.88-3.46) for positive progression compared to negative progression within subgroups of FR(-)/LR(-), FR(-)/LR(+), and FR(+)/LR(+), while mortality HR (95%CI) were 2.22 (0.91-5.38), 2.37 (1.28-4.38), and 2.98 (1.94-4.59). To improve screening performances by excluding regressive PSA and low-risk positive progression in FR(-)/LR(-), optimized screening strategy not only significantly reduce 32.4% of missed PCa (54.0% [1881/3484] vs. 21.6% [754/3484], P < 0.001), but also detected additional 8.0% of high-grade PCa (Gleason score 7-10: 36.0% [665/1849] vs. 28.0% [206/736], P < 0.001) than traditional screening strategy. CONCLUSIONS: Risk-stratified multi-round PSA screening strategy integrating the screening reference level and the optimal subgroup-specific progression indicator of PSA could be recommended as a fundamental strategy to reduce missed diagnosis and improve the detection of high-grade PCa cases.

Comparisons of clinical characteristics, prognosis, epidemiological factors, and genetic susceptibility between HER2-low and HER2-zero breast cancer among Chinese females.

BACKGROUND: Traditional human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC) is recommended to be divided into HER2-low and HER2-zero subtypes due to different prognosis. However, few studies investigated their differences in clinical characteristics and prognosis among Chinese HER2-negative BC and their stratified differences by hormone receptor (HR), while fewer studies investigated their differences in epidemiological factors and genetic susceptibility. METHODS: A total of 11,911 HER2-negative BC were included to compare the clinical characteristics and prognosis between HER2-zero and HER2-low BC, and 4227 of the 11,911 HER2-negative BC were further compared to 5653 controls to investigate subtype-specific epidemiological factors and single nucleotide polymorphisms(SNPs). RESULTS: Overall, 64.2% of HER2-negative BC were HER2-low BC, and the stratified proportions of HER2-low BC were 61.9% and 75.2% for HR-positive and HR-negative BC, respectively. Compared to HER2-zero BC, HER2-low BC among HR-positive BC showed younger age at diagnosis, later stage, poorer differentiation, and higher Ki-67, while elder age at diagnosis and lower mortality were observed for HER2-low BC among HR-negative BC (all p values <0.05). Compared to healthy controls, both HER2-low and HER2-zero BC are associated with similar epidemiological factors and SNPs. However, stronger interaction between epidemiological factors and polygenic risk scores were observed for HER2-zero BC than HER2-low BC among either HR-positive [odds ratios: 10.71 (7.55-15.17) and 8.84 (6.19-12.62) for the highest risk group compared to the lowest risk group] or HR-negative BC [7.00 (3.14-15.63) and 5.70 (3.26-9.98)]. CONCLUSIONS: HER2-low BC should deserve more attention than HER2-zero BC, especially in HR-negative BC, due to larger proportion, less clinical heterogeneity, better prognosis, and less susceptibility to risk factors.

The changes of subtype markers between first and second primary breast cancers.

BACKGROUND: Previous studies investigated the changes of subtype markers [estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2)] in several clinical settings, but not for second primary breast cancer (SPBC) after first primary breast cancer (FPBC). METHODS: A total of 15,390 patients with SPBC were preliminarily selected from the Surveillance, Epidemiology, and End Results Program, and 3777 patients with complete information on three subtype markers in both FPBC and SPBC were included in the final analyses. The changes of subtype markers and their prognostic implications and potential influential factors were well investigated. RESULTS: The overall change rates of ER, PR, and HER2 between FPBC and SPBC were 23.0% (867/3777), 35.0% (1322/3777), and 18.3% (691/3777), respectively. Gains of ER, PR, and HER2 after negative index markers were 48.7% (364/748), 37.9% (418/1103), and 11.5% (370/3211), while losses of markers after positive index markers were 16.6% (503/3029), 33.8%(904/2674), and 56.7%(321/566). Loss of ER was significantly associated with increased mortality (18.1% vs. 7.9%, p < 0.001), while gain of ER was significantly associated with decreased mortality (11.5% vs. 23.2%, p < 0.001). Similar results were observed for changes of PR status. However, loss of HER2 was significantly associated with decreased mortality (8.7% vs. 16.3%, p = 0.014), and no significant association was observed between the gain of HER2 and the prognosis of SPBC. Multivariate competing risk analyses showed similar results. HER2 status in FPBC, chemotherapy, and radiotherapy was significantly associated with changes of ER/PR (all p < 0.05), and no available therapies associated with HER2 change. CONCLUSION: The changes of subtype markers are observed in a considerable proportion of patients and has statistically significant prognostic implications. Biopsies should be taken as a routine procedure for better therapy management.

Simple Prediction Model for Colorectal Serrated Polyps: Development and External Validation Study in U.S. Prospective Cohorts.

Serrated polyps (SP) are precursors for colorectal cancer and contribute disproportionately to postcolonoscopy cancers. Leveraging three U.S. cohorts (43,974 women and 5,322 men), we developed prediction models for high-risk SPs (sized ≥10 mm or ≥3) among individuals undergoing their first colonoscopy screening. We then validated the model in the Partners Colonoscopy Cohort (51,203 women and 39,077 men). We evaluated discrimination and calibration using the C-statistic and Hosmer-Lemeshow test, respectively. The age and family history model generated a C-statistic [95% confidence interval (CI)] of 0.57 (0.56-0.58) in women and 0.58 (0.55-0.61) in men. Further inclusion of smoking, alcohol, and body mass index (the simple model) increased the C-statistic (95% CI) to 0.68 (0.67-0.69) in women and 0.68 (0.66-0.71) in men (all P < 0.001). Adding more predictors did not provide much incremental predictivity. In the validation cohort, moderate discrimination was observed in both women (0.60, 0.58-0.61) and men (0.60, 0.59-0.62). Notably, the simple model also yielded similar C-statistics for a composite endpoint of SPs and high-risk conventional adenomas (women, 0.62, 0.62-0.63; men, 0.63, 0.61-0.64). The model was adequately calibrated in both sets of cohorts. In summary, we developed and externally validated a simple prediction model based on five major risk factors for high-risk SPs that may be useful for healthy lifestyle recommendations and tailored colorectal cancer screening. PREVENTION RELEVANCE: On the basis of four prospective studies in the United States, we developed and externally validated a simple risk prediction model for high-risk SPs in the setting of colonoscopy screening. Our model showed moderate discriminatory accuracy and has potential utility for individualized risk assessment, healthy lifestyle recommendations, and tailored colorectal cancer prevention.

Development of a modified ABC method among Helicobacter pylori infected but serum pepsinogen test-negative individuals.

BACKGROUND: Although the ABC method for gastric cancer (GC) screening has been widely adopted in Japan, it may not be suitable for other countries due to population heterogeneity and different tumor histology. We aim to develop a modified ABC method to improve GC screening performance, especially among Helicobacter pylori (Hp) infected but serum pepsinogen (sPG) test-negative individuals. METHODS: A total of 4745 participants were recruited from Tianjin, China, and were classified into four groups by combined assay for Hp infection and sPG concentrations: Group A (Hp [-], PG [-]), Group B (Hp [+], PG [-]), Group C (Hp [+], PG [+]), and Group D (Hp [-], PG [+]). We used receiver-operating characteristic (ROC) curves analysis and minimum p value method to determine the optimal cutoff point for PG II in Group B. We performed logistic regressions to examine the risk of GC across different subgroups. In addition to the derivation set, the performance of the modified ABC method was also evaluated in an external set involving 16,292 participants from Liaoning, China. RESULTS: In the modified ABC method, we further classified Group B as low-risk (Group B1) and high-risk subgroups (Group B2) using optimal sPG II cutoff point (20.0 ng/mL) by ROC curves analysis and minimum p value method. Compared with Group B1, Group B2 had a significantly higher risk of GC (adjusted OR = 2.54, 95% CI = 1.94-3.33). The modified ABC method showed good discrimination for GC (AUC = 0.61, 95% CI = 0.59-0.63) and improved risk reclassification (NRI = 0.11, p < .01). Similar results were observed in the validation dataset. CONCLUSIONS: The modified ABC method can effectively identify high-risk population for GC among Hp-infected but sPG test-negative participants in China.

Association Between Baseline C-Reactive Protein and the Risk of Lung Cancer: A Prospective Population-Based Cohort Study.

C-reactive protein (CRP), a systemic marker of diagnosing chronic inflammation, has been associated with the incidence of multiple types of cancer. However, little is known about the impact of CRP on lung cancer incidence in Chinese population. A total of 97,950 participants without cancer at baseline (2006-2007) of the Kailuan Cohort Study were followed up. The concentration of plasma high-sensitivity CRP (hsCRP) was tested for all participants at baseline interview. Multivariable Cox proportional hazards regression models were used to assess the association between levels of hsCRP and incident lung cancer. During 8.7-year follow-up, 890 incident lung cancer cases occurred and were divided into three groups according to the level of hsCRP. The risk of incident lung cancer was significantly increased with elevated levels of hsCRP [HRMedium/Low, 1.21; 95% confidence interval (CI), 1.03-1.42; HRHigh/Low, 1.42, 95% CI, 1.20-1.68; Ptrend < 0.001], compared with the low group after adjusting confounders. Moreover, after stratifying by BMI, the significantly positive associations between the hsCRP level and the risk of lung cancer were found among those with BMI < 24 (HRHigh/Low, 1.51; 95% CI, 1.18-1.94; Ptrend = 0.001) and BMI = 24-28 (HRHigh/Low, 1.47; 95% CI, 1.13-1.92; Ptrend = 0.003), but not among those with BMI ≥ 28 (HRHigh/Low, 1.01; 95% CI, 0.64-1.57; Ptrend = 0.991). There was an antagonistic interaction between hsCRP levels and BMI that contributed to development of lung cancer (Pinteraction = 0.049). In conclusion, these findings indicate a dose-dependent relationship between hsCRP and lung cancer risk among Chinese population, especially in nonobese participants, suggesting that CRP could serve as a potential biomarker for prediction of lung cancer risk and identification of high-risk population. PREVENTION RELEVANCE: In this prospective population-based cohort study, we found an association between higher plasma hsCRP and an increased risk of developing lung cancer, with stronger associations observed among nonobese participants.

A new risk stratification strategy for fatty liver disease by incorporating MAFLD and fibrosis score in a large US population.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a newly proposed definition of fatty liver disease (FLD) independent of excessive alcohol consumption (EAC) and hepatitis viral infection. Evidence on the mortality risk in different types of FLD [nonalcoholic FLD (NAFLD), alcoholic FLD (AFLD), and MAFLD] is sparse, hindering the identification of high-risk populations for preferential clinical surveillance. METHODS: A total of 11,000 participants in the Third National Health and Nutrition Examination Survey were enrolled. Participants were categorized into three groups [FLD( - ), MAFLD( - ), and MAFLD( +)] according to FLD and MAFLD criteria, and further categorized into six groups by EAC. Multivariate Cox proportional hazard model was used to estimate the risk of all-cause, cardiovascular-related, and cancer-related mortality. RESULTS: During a median follow-up of 23.2 years, a total of 3240 deaths were identified. Compared with FLD( - )/EAC( - ) participants, MAFLD( +) individuals had higher all-cause mortality risk [hazard ratio (HR) = 1.28, 95% confidence interval (CI) = 1.18-1.39] regardless of EAC status [MAFLD( +)/NAFLD: HR = 1.22, 95%CI = 1.11-1.34; MAFLD( +)/AFLD: HR = 1.83, 95%CI = 1.46-2.28], while not for MAFLD( - ) individuals. Furthermore, diabetes-driven-MAFLD had higher mortality risk (HR = 2.00, 95%CI = 1.77-2.27) followed by metabolic dysregulation-driven-MAFLD (HR = 1.30, 95%CI = 1.06-1.60) and overweight/obesity-driven-MAFLD (HR = 1.11, 95%CI = 1.00-1.22). Additionally, MAFLD( - ) participants with elevated fibrosis score were also associated with statistically significantly higher mortality risk (HR = 3.23, 95%CI = 1.63-6.40). CONCLUSIONS: Utilizing a representative sample of the US population, we proved the validity of MAFLD subtype and fibrosis score, rather than the traditional definition (NAFLD and AFLD), in the risk stratification of FLD patients. These findings may be applied to guide the determination of surveillance options for FLD patients.

Corrigendum: Construction and Validation of a Lung Cancer Risk Prediction Model for Non-Smokers in China.

[This corrects the article DOI: 10.3389/fonc.2021.766939.].

A risk prediction model for selecting high-risk population for computed tomography lung cancer screening in China.

OBJECTIVE: Two large randomized controlled trials (RCTs) have demonstrated that low dose computed tomography (LDCT) screening reduces lung cancer mortality. Risk-prediction models have been proved to select individuals for lung cancer screening effectively. With the focus on established risk factors for lung cancer routinely available in general cancer screening settings, we aimed to develop and internally validated a risk prediction model for lung cancer. MATERIALS AND METHODS: Using data from the Cancer Screening Program in Urban China (CanSPUC) in Henan province, China between 2013 and 2019, we conducted a prospective cohort study consisting of 282,254 participants including 126,445 males and 155,809 females. Detailed questionnaire, physical assessment and follow-up were completed for all participants. Using Cox proportional risk regression analysis, we developed the Henan Lung Cancer Risk Models based on simplified questionnaire. Model discrimination was evaluated by concordance statistics (C-statistics), and model calibration was evaluated by the bootstrap sampling, respectively. RESULTS: By 2020, a total of 589 lung cancer cases occurred in the follow-up yielding an incident density of 64.91/100,000 person-years (pyrs). Age, gender, smoking, history of tuberculosis and history of emphysema were included into the model. The C-index of the model for 1-year lung cancer risk was 0.766 and 0.741 in the training set and validation set, respectively. In stratified analysis, the model showed better predictive power in males, younger participants, and former or current smoking participants. The model calibrated well across the deciles of predicted risk in both the overall population and all subgroups. CONCLUSIONS: We developed and internally validated a simple risk prediction model for lung cancer, which may be useful to identify high-risk individuals for more intensive screening for cancer prevention.

Relationship of sleep duration and annual changes in sleep duration with the incidence of gastrointestinal cancers: a prospective cohort study.

BACKGROUND: Prospective analyses have yet to identify a consistent relationship between sleep duration and the incidence of gastrointestinal (GI) cancers. The effect of changes in sleep duration on GI cancer incidence has scarcely been studied. Therefore, we aimed to examine the association between baseline sleep duration and annual changes in sleep duration and GI cancer risk in a large population-based cohort study. METHODS: A total of 123,495 participants with baseline information and 83,511 participants with annual changes in sleep duration information were prospectively observed from 2006 to 2015 for cancer incidence. Cox proportional-hazards models were used to calculate hazard ratios (HRs) and their confidence intervals (CIs) for GI cancers according to sleep duration and annual changes in sleep duration. RESULTS: In baseline sleep duration analyses, short sleep duration (≤5 h) was significantly associated with a lower risk of GI cancer in females (HR: 0.31, 95% CI: 0.10-0.90), and a linear relationship between baseline sleep duration and GI cancer was observed (P = 0.010), especially in males and in the >50-year-old group. In the annual changes in sleep duration analyses, with stable category (0 to -15 min/year) as the control group, decreased sleep duration (≤-15 min/year) was significantly associated with the development of GI cancer (HR: 1.29; 95% CI: 1.04-1.61), especially in the >50-year-old group (HR: 1.32; 95% CI: 1.01-1.71), and increased sleep duration (>0 min/year) was significantly associated with GI cancer in females (HR: 2.89; 95% CI: 1.14-7.30). CONCLUSIONS: Both sleep duration and annual changes in sleep duration were associated with the incidence of GI cancer.

Association Between Genetically Proxied Lipid-Lowering Drug Targets and Renal Cell Carcinoma: A Mendelian Randomization Study.

Observational studies suggested inconsistent associations between lipid-lowering drugs, such as statins, and renal cell carcinoma (RCC) risk. In a two-sample Mendelian randomization (MR) framework, we assessed the causal influence of lipid-lowering agents and circulating lipid traits on overall and sex-specific RCC risk. Genetic variants of six drug-target genes were selected to proxy the effects of low-density lipoprotein cholesterol (LDL-C) lowering therapies. Instrumental variables for circulating lipid traits were constructed from two large genome-wide association studies. We used endpoints for RCC from summary statistics of two studies [International Agency for Research on Cancer [IARC], N = 13,230; National Cancer Institute [NCI], N = 4,735]. The robustness of results was assessed through conventional MR sensitivity analyses. Overall, there was no significant association between genetically proxied HMG-CoA reductase (HMGCR) inhibition and RCC risk [Odds ratio [OR] = 1.42, 95% CI, 0.29-6.99]. In the sex-stratified analysis, we observed a positive association for genetically proxied drug targets with RCC risk. Specifically, genetically proxied proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition was associated with a higher risk of RCC in men [OR = 2.20 [95% CI, 1.24-3.89]], and the difference by sex was moderate. This study suggested genetically proxied inhibition of HMGCR was not associated with RCC risk, while genetically proxied PCSK9 inhibition might be associated with a higher risk of RCC in male.

Development and evaluation of the screening performance of a low-cost high-risk screening strategy for breast cancer.

OBJECTIVE: To develop and evaluate the screening performance of a low-cost high-risk screening strategy for breast cancer in low resource areas. METHODS: Based on the Multi-modality Independent Screening Trial, 6 questionnaire-based risk factors of breast cancer (age at menarche, age at menopause, age at first live birth, oral contraceptive, obesity, family history of breast cancer) were used to determine the women with high risk of breast cancer. The screening performance of clinical breast examination (CBE), breast ultrasonography (BUS), and mammography (MAM) were calculated and compared to determine the optimal screening method for these high risk women. RESULTS: A total of 94 breast cancers were detected among 31,720 asymptomatic Chinese women aged 45-65 years. Due to significantly higher detection rates (DRs) and suitable coverage of the population, high risk women were defined as those with any of 6 risk factors. Among high risk women, the DR for BUS [3.09/1,000 (33/10,694)] was similar to that for MAM [3.18/1,000 (34/10,696)], while it was significantly higher than that for the CBE [1.73/1,000 (19/10,959), P = 0.002]. Compared with MAM, BUS showed significantly higher specificity [98.64% (10,501/10,646) vs. 98.06% (10,443/10,650), P = 0.001], but no significant differences in sensitivity [68.75% (33/48) vs. 73.91% (34/46)], positive prediction values [18.54% (33/178) vs. 14.11% (34/241)], and negative prediction values [99.86% (10,501/10,516) vs. 99.89% (10,443/10,455)]. Further analyses showed no significant difference in the percentages of early stage breast cancer [53.57% (15/28) vs. 50.00% (15/30)], lymph node involvement [22.73% (5/22) vs. 28.00% (7/25)], and tumor size ≥ 2 cm [37.04% (10/27) vs. 29.03% (9/31)] between BUS and MAM. Subgroup analyses stratified by breast densities or age at enrollment showed similar results. CONCLUSIONS: The low-cost high-risk screening strategy based on 6 questionnaire-based risk factors was an easy-to-use method to identify women with high risk of breast cancer. Moreover, BUS and MAM had comparable screening performances among high risk women.

Construction and Validation of a Lung Cancer Risk Prediction Model for Non-Smokers in China.

BACKGROUND: About 15% of lung cancers in men and 53% in women are not attributable to smoking worldwide. The aim was to develop and validate a simple and non-invasive model which could assess and stratify lung cancer risk in non-smokers in China. METHODS: A large-sample size, population-based study was conducted under the framework of the Cancer Screening Program in Urban China (CanSPUC). Data on the lung cancer screening in Henan province, China, from October 2013 to October 2019 were used and randomly divided into the training and validation sets. Related risk factors were identified through multivariable Cox regression analysis, followed by establishment of risk prediction nomogram. Discrimination [area under the curve (AUC)] and calibration were further performed to assess the validation of risk prediction nomogram in the training set, and then validated by the validation set. RESULTS: A total of 214,764 eligible subjects were included, with a mean age of 55.19 years. Subjects were randomly divided into the training (107,382) and validation (107,382) sets. Elder age, being male, a low education level, family history of lung cancer, history of tuberculosis, and without a history of hyperlipidemia were the independent risk factors for lung cancer. Using these six variables, we plotted 1-year, 3-year, and 5-year lung cancer risk prediction nomogram. The AUC was 0.753, 0.752, and 0.755 for the 1-, 3- and 5-year lung cancer risk in the training set, respectively. In the validation set, the model showed a moderate predictive discrimination, with the AUC was 0.668, 0.678, and 0.685 for the 1-, 3- and 5-year lung cancer risk. CONCLUSIONS: We developed and validated a simple and non-invasive lung cancer risk model in non-smokers. This model can be applied to identify and triage patients at high risk for developing lung cancers in non-smokers.

Mitochondrial DNA copy number in cervical exfoliated cells and risk of cervical cancer among HPV-positive women.

BACKGROUND: Although human papillomavirus (HPV) infection has been regarded as the cause of cervical cancer in over 99% of cases, only a small fraction of HPV-infected women develop this malignancy. Emerging evidence suggests that alterations of mitochondrial DNA copy number (mtCN) may contribute to carcinogenesis. However, the relationship between mtCN and cervical cancer remains undetermined. METHODS: The current study included 591 cervical cancer cases and 373 cancer-free controls, all of whom were infected with high-risk HPV. Relative mtCN in cervical cancer exfoliated cells was measured by qRT-PCR assays, and logistic regression analysis was performed to compute odds ratios (ORs) and 95% confidence intervals (CIs). Interaction between mtCN and HPV types was assessed by using the Wald test in logistic regression models. RESULTS: HPV16, 18, 52, and 58 were the most common types in both case and control groups. Median mtCN in cases was significantly higher than that in controls (1.63 vs. 1.23, P = 0.03). After adjustment for age and HPV types, the highest quartile of mtCN was associated with increased odds of having cervical cancer (OR = 1.77, 95% CI = 1.19, 2.62; P < 0.01), as compared to the lowest quartile. A dose-response effect of mtCN on cervical cancer was also observed (Ptrend < 0.001). The interaction between mtCN and HPV types was statistically nonsignificant. CONCLUSIONS: In women who test HPV positive, the increase of mtCN in cervical exfoliated cells is associated with cervical cancer. This suggests a potential role of mtCN in cervical carcinogenesis.

Risk prediction model for lung cancer incorporating metabolic markers: Development and internal validation in a Chinese population.

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 Pentry  = .15 and Pstay  = .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 (PHL  = .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.

The association between fasting blood glucose trajectory and cancer risk in Chinese population without diabetes.

To examine the associations between fasting blood glucose (FBG) trajectories, the changes in FBG over time and the risk of cancer, particularly for gastrointestinal cancer, we enrolled 69,742 participants without diabetes from the Kailuan cohort. FBG trajectories (2006-2010) were modeled by group-based trajectory modeling, and five trajectories were identified: low-increasing (n = 6,275), moderate-stable (n = 44,120), moderate-increasing (n = 10,149), elevated-decreasing (n = 5,244) and elevated-stable (n = 3,954). A total of 1,364 cancer cases were accumulated between 2010 and 2015, including 472 gastrointestinal cancer cases. We used Cox proportional hazards regression models to evaluate the associations between FBG trajectory patterns and the risk of cancer. We further assessed the associations while carefully controlling for initial body mass index (BMI) in 2006 and for changes in BMI during 2006-2010. Relative to the moderate-stable group, we found a higher hazard ratio (HR) for overall cancer in the low-increasing group (HR = 1.26, 95% confidence interval (CI) 1.06-1.50); and for gastrointestinal cancer in the elevated-stable group (HR = 1.66, 95% CI 1.22-2.26). Moreover, among participants with an initial BMI ≥25 kg/m2 , a positive association with the low-increasing group was observed for both overall cancer and gastrointestinal cancer (HR = 1.54, 95% CI 1.17-2.04; HR = 1.65, 95% CI 1.02-2.66; respectively); among participants with a stable BMI (4.40% loss-5.15% gain), a positive association with the elevated-stable group was observed both for overall cancer and gastrointestinal cancer (HR = 1.43, 95% CI 1.10-1.87; HR = 1.95, 95% CI 1.33-2.86; respectively). Our study observed that FBG trajectories were associated with cancer risk among participants without diabetes, and BMI may modify the associations.

Development of a risk score for colorectal cancer in Chinese males: A prospective cohort study.

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.