A nomogram for screening esophageal squamous cell carcinoma based on environmental risk factors in a high-incidence area of China: a population-based case-control study

Performance of Prediction Models for Esophageal Squamous Cell Carcinoma in General Population: A Systematic Review and External Validation Study

INTRODUCTION

Prediction models for esophageal squamous cell carcinoma (ESCC) need to be proven effective in the target population before they can be applied to population-based endoscopic screening to improve cost-effectiveness. We have systematically reviewed ESCC prediction models applicable to the general population and performed external validation and head-to-head comparisons in a large multicenter prospective cohort including 5 high-risk areas of China (Fei Cheng, Lin Zhou, Ci Xian, Yang Zhong, and Yan Ting).

METHODS

Models were identified through a systematic review and validated in a large population-based multicenter prospective cohort that included 89,753 participants aged 40-69 years who underwent their first endoscopic examination between April 2017 and March 2021 and were followed up until December 31, 2022. Model performance in external validation was estimated based on discrimination and calibration. Discrimination was assessed by C-statistic (concordance statistic), and calibration was assessed by calibration plot and Hosmer-Lemeshow test.

RESULTS

The systematic review identified 15 prediction models that predicted severe dysplasia and above lesion (SDA) or ESCC in the general population, of which 11 models (4 SDA and 7 ESCC) were externally validated. The C-statistics ranged from 0.67 (95% confidence interval 0.66-0.69) to 0.70 (0.68-0.71) of the SDA models, and the highest was achieved by Liu et al (2020) and Liu et al (2022). The C-statistics ranged from 0.51 (0.48-0.54) to 0.74 (0.71-0.77), and Han et al (2023) had the best discrimination of the ESCC models. Most models were well calibrated after recalibration because the calibration plots coincided with the x = y line.

DISCUSSION

Several prediction models showed moderate performance in external validation, and the prediction models may be useful in screening for ESCC. Further research is needed on model optimization, generalization, implementation, and health economic evaluation.

Genetic and molecular characterization of metabolic pathway-based clusters in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive types of squamous cell carcinoma and represents a significant proportion of esophageal cancer. Metabolic reprogramming plays a key role in the occurrence and development of ESCC. Unsupervised clustering analysis was employed to stratify ESCC samples into three clusters: MPC1-lipid type, MPC2-amino acid type, and MPC3-energy type, based on the enrichment scores of metabolic pathways extracted from the Reactome database. The MPC3 cluster exhibited characteristics of energy metabolism, with heightened glycolysis, cofactors, and nucleotide metabolism, showing a trend toward increased aggressiveness and poorer survival rates. On the other hand, MPC1 and MPC2 primarily involved lipid and amino acid metabolism, respectively. In addition, liquid chromatography‒mass spectrometry-based metabolite profiles and potential therapeutic agents were explored and compared among ESCC cell lines with different MPCs. MPC3 amplified energy metabolism markers, especially carnitines. In contrast, MPC1 and MPC2 predominantly had elevated levels of lipids (primarily triacylglycerol) and amino acids, respectively. Furthermore, MPC3 demonstrated a suboptimal clinical response to PD-L1 immunotherapy but showed increased sensitivity to the doramapimod chemotherapy regimen, as evident from drug sensitivity evaluations. These insights pave the way for a more personalized therapeutic approach, potentially enhancing treatment precision for ESCC patients.

Association of interleukin-10 rs1800896, rs1800872, and interleukin-6 rs1800795 polymorphisms with squamous cell carcinoma risk: A meta-analysis

The relationship between interleukin (IL)-10 and IL-6 gene polymorphisms and squamous cell carcinoma (SCC) has been demonstrated but with inconsistent conclusions. The aim of this study was to evaluate the potential associations of IL gene polymorphisms and the SCC risk. PubMed, Cochrane Library, Web of Science, China National Knowledge Infrastructure, China Biomedical Database, WanFang, and China Science and Technology Journal Database databases were searched for articles reporting the correlations of IL-10 and IL-6 gene polymorphisms with the SCC risk. Odds ratio and 95% confidence interval were calculated using Stata Version 11.2. Meta-regression, sensitivity, and publication bias were analyzed. False-positive reporting probability and Bayesian measure of the false-discovery probability were used to explore the credibility of the calculation. Twenty-three articles were included. The IL-10 rs1800872 polymorphism showed a significant correlation with the SCC risk in the overall analysis. Studies pooled by ethnicity revealed that the IL-10 rs1800872 polymorphism reduced the SCC risk in the Caucasian population. The results of this study suggest that the IL-10 rs1800872 polymorphism may confer a genetic susceptibility to SCC, particularly oral SCC, in Caucasians. However, the IL-10 rs1800896 or IL-6 rs1800795 polymorphism was not significantly associated with the SCC risk.

Cancer situation in China: what does the China cancer map indicate from the first national death survey to the latest cancer registration?

BACKGROUND

Over the past four decades, the Chinese government has conducted three surveys on the distribution of causes of death and built cancer registration. In order to shine a new light on better cancer prevention strategies in China, we evaluated the profile of cancer mortality over the forty years and analyzed the policies that have been implemented.

METHODS

We described spatial and temporal changes in both cancer mortality and the ranking of major cancer types in China based on the data collected from three national surveys during 1973-1975, 1990-1992, 2004-2005, and the latest cancer registration data published by National Central Cancer Registry of China. The mortality data were compared after conversion to age-standardized mortality rates based on the world standard population (Segi's population). The geographical distribution characteristics were explored by marking hot spots of different cancers on the map of China.

RESULTS

From 1973 to 2016, China witnessed an evident decrease in mortality rate of stomach, esophageal, and cervical cancer, while a gradual increase was recorded in lung, colorectal, and female breast cancer. A slight decrease of mortality rate has been observed in liver cancer since 2004. Lung and liver cancer, however, have become the top two leading causes of cancer death for the last twenty years. From the three national surveys, similar profiles of leading causes of cancer death were observed among both urban and rural areas. Lower mortality rates from esophageal and stomach cancer, however, have been demonstrated in urban than in rural areas. Rural areas had similar mortality rates of the five leading causes of cancer death with the small urban areas in 1973-1975. Additionally, rural areas in 2016 also had approximate mortality rates of the five leading causes with urban areas in 2004-2005. Moreover, stomach, esophageal, and liver cancer showed specific geographical distributions. Although mortality rates have decreased at most of the hotspots of these cancers, they were still higher than the national average levels during the same time periods.

CONCLUSIONS

Building up a strong primary public health system especially among rural areas may be one critical step to reduce cancer burden in China.

Dietary habits, nutrition and esophageal cancer: A case-control study on Kazakhs in Xinjiang

OBJECTIVE

To explore associations between dietary habits and esophageal epithelial cell carcinoma (ESCC) and provide a potential direction for exploring how different dietary habits and nutrient intake might affect ESCC development.

METHODS

198 ESCC cases and 200 controls on Kazakhs were recruited in Xinjiang from 2010 to 2019 for a group-matched case-control study. The case group were recruited from the First Affiliated Hospital of Xinjiang Medical University and Affiliated Cancer Hospital of Xinjiang Medical University. The control population were recruited from two parts: hospital-based control and population-based control. The diagnosis was confirmed by histological examination. The food frequency questionnaire was used to investigate the dietary nutrients intake. Folic acid, vitamin B12, and DNA-methyltransferase 1(DNMT1) levels were measured in serum samples obtained from cases and controls.

RESULTS

The cholesterol intake of ESCC group was significantly higher than that of the control group while the intakes of protein, thiamin, riboflavin, folic acid, vitamin A, B6, C and E were significantly lower than the control group. Factors including lacking fresh vegetables and fruits, low educational level, low income, alcohol drinking, eating solid and dry food and smoked meat, dieting irregularly, salty taste preference, low serum folic acid level and high serum DNMT1 level were associated with increased risk of ESCC in Kazakhs.

CONCLUSION

Dietary habits and nutrient intake were associated with increased risk of ESCC in Kazakhs that may provide a potential direction for further studies.

Study protocol for artificial intelligence-assisted sponge cytology as pre-endoscopy screening for early esophegeal squmaous epithelial lesions in China

Background

Endoscopic screening is the widely accepted screening strategy for esophageal squmaous cell carcinoma (ESCC). However, massive endoscopic screening is expensive and not cost-efficient, and novel pre-endoscopy detection used as a preliminary screening method arouses new concerns. We are planning to launch an artificial intelligence (AI) assisted sponge cytology for detecting esophageal squmaous high-grade intraepithelial neoplasia (HGIN) and above lesions. The aim of this trail is to investigate the efficiency of AI-assisted sponge cytology in population-based screening of early esophageal squmaous epithelial lesions.

Methods

The study will be prospectively conducted in five regions with a high prevalence of ESCC. AI-assisted sponge cytology and endoscopic examination will be sequentially performed. Based on our previous data, at least 864 patients with esophageal HGIN and above lesions are needed to achieve enough statistical power. And, a calculated 112,500 individuals with high risks of ESCC will be recruited. In the first stage, each 24,000 participants who meet the inclusion criteria will be recruited on a voluntary basis. Setting pathological results as standard reference, diagnostic threshold and according performance of AI-assisted detection will be evaluated. A prediction model will be constructed by co-analyzing cytological results and relevant risk factors. Then, an external validation cohort will be used for validation of the model efficiency. Also, cost-efficiency analysis will be performed. This study protocol was registered on chineseclinicaltrial.gov (ChiCTR1900028524).

Discussion

Our study will determine whether this AI-assisted sponge cytology can be used as an effective pre-endoscopy detection tool for large-scale screening for ESCC in high-risk areas.

Burden of All Cancers Along With Attributable Risk Factors in China From 1990 to 2019: Comparison With Japan, European Union, and USA

Background

Understanding the epidemiological characteristics of various cancers can optimize the prevention and control strategies in the national cancer control plan. This study aimed to report the burden differences, pattern trend, and potential risk factors of all neoplasm types in China in recent 30 years, and further compared with top economies in the world.

Methods

The disability-adjusted life-years (DALYs) and age-standardized DALY rate (ASDR) of all neoplasms with the attributable risk factors from 1990 to 2019 in China, Japan, European Union, USA, and the world were extracted from the Global Burden of Disease Study 2019. The temporal trend analysis was estimated using the joinpoint regression model.

Results

In 2019, about 251.4 million DALYs worldwide were caused by all neoplasms, and nearly 26.9% (67.5 million DALYs) occurred in China with the ASDR in 2019 of 342.09/10 000, which was higher than European Union (334.25/10 000), USA (322.94/10 000), and Japan (250.36/10 000). Although the cancer burden of the colorectum, non-Hodgkin lymphoma, oral cavity, ovary, and kidney in China was lower than in Japan, European Union and USA, the corresponding ASDR gradually increased in China over the past 30 years, but declined in the three developed areas. Around 46.29% of overall neoplasms DALYs in China in 2019 were attributed to 22 identified risk factors, and the specific risk attributable-fraction for several neoplasm types varied greatly in these regions.

Conclusion

The ASDR of cancers of the lung, colorectum, pancreas, non-Hodgkin lymphoma, oral cavity, ovary, kidney, and chronic lymphoid leukemia increased in China compared to 30 years ago. With the population aging and the social transformation in China, the increasing burden of neoplasms and the changing spectrum of neoplasms suggest that effective comprehensive prevention and treatment measures should be adopted to reduce the burden, including public health education, strict tobacco-control policy, healthier lifestyles, along with expanding vaccination programs and early cancer screening.

Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review

Objective: The risk prediction model is an effective tool for risk stratification and is expected to play an important role in the early detection and prevention of esophageal cancer. This study sought to summarize the available evidence of esophageal cancer risk predictions models and provide references for their development, validation, and application. Methods: We searched PubMed, EMBASE, and Cochrane Library databases for original articles published in English up to October 22, 2021. Studies that developed or validated a risk prediction model of esophageal cancer and its precancerous lesions were included. Two reviewers independently extracted study characteristics including predictors, model performance and methodology, and assessed risk of bias and applicability with PROBAST (Prediction model Risk Of Bias Assessment Tool). Results: A total of 20 studies including 30 original models were identified. The median area under the receiver operating characteristic curve of risk prediction models was 0.78, ranging from 0.68 to 0.94. Age, smoking, body mass index, sex, upper gastrointestinal symptoms, and family history were the most commonly included predictors. None of the models were assessed as low risk of bias based on PROBST. The major methodological deficiencies were inappropriate date sources, inconsistent definition of predictors and outcomes, and the insufficient number of participants with the outcome. Conclusions: This study systematically reviewed available evidence on risk prediction models for esophageal cancer in general populations. The findings indicate a high risk of bias due to several methodological pitfalls in model development and validation, which limit their application in practice.

Risk prediction models for esophageal cancer: A systematic review and critical appraisal

BACKGROUND AND AIMS

Esophageal cancer risk prediction models allow for risk-stratified endoscopic screening. We aimed to assess the quality of these models developed in the general population.

METHODS

A systematic search of the PubMed and Embase databases from January 2000 through May 2021 was performed. Studies that developed or validated a model of esophageal cancer in the general population were included. Screening, data extraction, and risk of bias (ROB) assessment by the Prediction model Risk Of Bias Assessment Tool (PROBAST) were performed independently by two reviewers.

RESULTS

Of the 13 models included in the qualitative analysis, 8 were developed for esophageal squamous cell carcinoma (ESCC) and the other 5 were developed for esophageal adenocarcinoma (EAC). Only two models conducted external validation. In the ESCC models, cigarette smoking was included in each model, followed by age, sex, and alcohol consumption. For EAC models, cigarette smoking and body mass index were included in each model, and gastroesophageal reflux disease, uses of acid-suppressant medicine, and nonsteroidal anti-inflammatory drug were exclusively included. The discriminative performance was reported in all studies, with C statistics ranging from 0.71 to 0.88, whereas only six models reported calibration. For ROB, all the models had a low risk in participant and outcome, but all models showed high risk in analysis, and 60% of models showed a high risk in predictors, which resulted in all models being classified as having overall high ROB. For model applicability, about 60% of these models had an overall low risk, with 30% of models of high risk and 10% of models of unclear risk, concerning the assessment of participants, predictors, and outcomes.

CONCLUSIONS

Most current risk prediction models of esophageal cancer have a high ROB. Prediction models need further improvement in their quality and applicability to benefit esophageal cancer screening.

Development and Validation of an Esophageal Squamous Cell Carcinoma Risk Prediction Model for Rural Chinese: Multicenter Cohort Study

BACKGROUND

There are rare prediction models for esophageal squamous cell carcinoma (ESCC) for rural Chinese population. We aimed to develop and validate a prediction model for ESCC based on a cohort study for the population.

METHODS

Data of 115,686 participants were collected from esophageal cancer (EC) early diagnosis and treatment of cancer program as derivation cohort while data of 54,750 participants were collected as validation cohort. Risk factors considered included age, sex, smoking status, alcohol drinking status, body mass index (BMI), tea drinking status, marital status, annual household income, source of drinking water, education level, and diet habit. Cox proportional hazards model was used to develop ESCC prediction model at 5 years. Calibration ability, discrimination ability, and decision curve analysis were analyzed in both derivation and validation cohort. A score model was developed based on prediction model.

RESULTS

One hundred eighty-six cases were diagnosed during 556,949.40 person-years follow-up in the derivation cohort while 120 cases from 277,302.70 in the validation cohort. Prediction model included the following variables: age, sex, alcohol drinking status, BMI, tea drinking status, and fresh fruit. The model had good discrimination and calibration performance: R 2, D statistic, and Harrell's C statistic of prediction model were 43.56%, 1.70, and 0.798 in derivation cohort and 45.19%, 1.62, and 0.787 in validation cohort. The calibration analysis showed good coherence between predicted probabilities and observed probabilities while decision curve analysis showed clinical usefulness. The score model was as follows: age (3 for 45-49 years old; 4 for 50-54 years old; 7 for 55-59 years old; 9 for 60-64 years; 10 for 65-69 years), sex (5 for men), BMI (1 for ≤25), alcohol drinking status (2 for alcohol drinkers), tea drinking status (2 for tea drinkers), and fresh fruit (2 for never) and showed good discrimination ability with area under the curve and its 95% confidence interval of 0.792 (0.761,0.822) in the deviation cohort and 0.773 (0.736,0.811) in the validation cohort. The calibration analysis showed great coherence between predicted probabilities and observed probabilities.

CONCLUSIONS

We developed and validated an ESCC prediction model using cohort study with good discrimination and calibration capability which can be used for EC screening for rural Chinese population.