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Background: Esophageal cancer (EC) often occurs in the elderly, and approximately 40% of patients are 70 years or older. To investigate the long‐term survival of EC in elderly patients, to provide a theoretical direction for better management and predicting survival of EC based on the hospital‐based multi‐center study in China. Methods: The study was conducted in 18 hospitals including 6 provincial hospitals, 8 municipal hospitals, and 4 county hospitals. We extracted information from medical record homepage, records of admission and discharge, and pathological diagnosis reports from the medical record department of the elderly patients at 70–84 years old to obtain the 3‐year and 5‐year overall survival (OS), and main associated factors, and to analyze the current therapeutic effect of different treatment options for elderly patients. Results: The 3‐year and 5‐year OS rate of the 1013 elderly patients was 44.8% and 32.8%, respectively. Their median survival was 28.00 months. The median survival of patients with squamous cell carcinoma was longer than that of other pathological type (squamous vs. other types: 31.00 vs. 20.00 months, p = 0.018). The median survival of patients with surgery only or combined therapy was longer than that of radiotherapy, chemotherapy, and no therapy (surgery only vs. combined therapy vs. radiotherapy vs. chemotherapy vs. no therapy: 56.00 vs. 33.00 vs. 26.00 vs.18.00 vs. 16.00 months, p < 0.001). The 5‐year OS rate of patients with highly differentiated cancer was higher than that of medium differentiated and poor differentiation/undifferentiated. In multivariate analysis, the older ages, pathological stage, were independent prognostic risk factors for poor EC survival. Treatment method was independent protective factors predictive of a good EC OS. Conclusions: The survival rate of the elderly EC patients was still low in China. Age, therapy method, and pathological stage were mainly associated with the survival rate of EC in elderly patients. [ABSTRACT FROM AUTHOR]

Background: We aimed to obtain a set of health state utility scores of patients with esophageal cancer (EC) and precancerous lesions in China, and to explore the influencing factors of health‐related quality of life (HRQoL). Methods: A hospital‐based multicenter cross‐sectional study was conducted. From 2013 to 2014, patients with EC or precancerous lesions were enrolled. HRQoL was assessed using a European quality of life‐5 dimension (EQ‐5D‐3L) instrument. Multivariable linear regression analysis was performed to explore the influencing factors of the EQ‐5D utility scores. Results: A total of 2090 EC patients and 156 precancer patients were included in the study. The dimension of pain/discomfort had the highest rate of self‐reported problems, 60.5% in EC and 51.3% in precancer patients. The mean visual analog scale (VAS) score for EC and precancer patients were 68.4 ± 0.7 and 64.5 ± 3.1, respectively. The EQ‐5D utility scores for EC and precancer patients were estimated as 0.748 ± 0.009 and 0.852 ± 0.022, and the scores of EC at stage I, stage II, stage III, and stage IV were 0.693 ± 0.031, 0.747 ± 0.014, 0.762 ± 0.015, and 0.750 ± 0.023, respectively. According to the multivariable analyses, the factors of region, occupation, household income in 2012, health care insurance type, pathological type, type of therapy, and time points of the survey were statistically associated with the EQ‐5D utility scores of EC patients. Conclusions: There were remarkable decrements of utility scores among esophageal cancer patients, compared with precancer patients. The specific utility scores of EC would support further cost‐utility analysis in populations in China. [ABSTRACT FROM AUTHOR]

FAT4 plays a crucial role in carcinogenesis as a key component of the Hippo signaling pathway. We hypothesized that potential functional polymorphisms in the FAT4 gene may modify the risk of esophageal cancer. To test this hypothesis, we evaluated the association between four nonsynonymous polymorphisms (rs1039808, rs12508222, rs1567047 and rs1014867) in FAT4 and esophageal cancer risk in a case-control study of 2,139 esophageal cancer cases and 2,273 controls in a Chinese population. We found that the T allele of rs1014867 (Pro4972Ser) was significantly associated with a decreased risk of esophageal cancer (odds ratio [OR]=0.77, 95% confidence interval [95% CI]=0.66-0.90; p=1.42 × 10−3). We also observed a borderline significant association between rs1039808 (Ala807Val) and esophageal cancer risk (OR=0.90, 95% CI=0.82-1.00; p=0.050), which was more prominent in non-drinkers (OR=0.82, 95% CI=0.71-0.94; p=6.53 × 10−3). Furthermore, we detected a significant interaction between rs1039808 genotypes and alcohol drinking on esophageal cancer risk ( p=0.013). These findings indicate that the nonsynonymous variants rs1014867 (Pro4972Ser) and rs1039808 (Ala807Val) of FAT4 may contribute to esophageal cancer susceptibility. [ABSTRACT FROM AUTHOR]

Introduction Methods Results Conclusions Plain Language Summary Breast cancer is a significant contributor to female mortality, exerting a public health burden worldwide, especially in China, where risk‐prediction models with good discriminating accuracy for breast cancer are still scarce.A multicenter screening cohort study was conducted as part of the Cancer Screening Program in Urban China. Dwellers aged 40–74 years were recruited between 2014 and 2019 and prospectively followed up until June 30, 2021. The entire data set was divided by year of enrollment to develop a prediction model and validate it internally. Multivariate Cox regression was used to ascertain predictors and develop a risk‐prediction model. Model performance at 1, 3, and 5 years was evaluated using the area under the curve, nomogram, and calibration curves and subsequently validated internally. The prediction model incorporates selected factors that are assigned appropriate weights to establish a risk‐scoring algorithm. Guided by the risk score, participants were categorized into low‐, medium‐, and high‐risk groups for breast cancer. The cutoff values were chosen using X‐tile plots. Sensitivity analysis was conducted by categorizing breast cancer risk into the low‐ and high‐risk groups. A decision curve analysis was used to assess the clinical utility of the model.Of the 70,520 women enrolled, 447 were diagnosed with breast cancer (median follow‐up, 6.43 [interquartile range, 3.99–7.12] years). The final prediction model included age and education level (high, hazard ratio [HR], 2.01 [95% CI, 1.31–3.09]), menopausal age (≥50 years, 1.34 [1.03–1.75]), previous benign breast disease (1.42 [1.09–1.83]), and reproductive surgery (1.28 [0.97–1.69]). The 1‐year area under the curve was 0.607 in the development set and 0.643 in the validation set. Moderate predictive discrimination and satisfactory calibration were observed for the validation set. The risk predictions demonstrated statistically significant differences between the low‐, medium‐, and high‐risk groups (p < .001). Compared with the low‐risk group, women in the high‐ and medium‐risk groups posed a 2.17‐fold and 1.62‐fold elevated risk of breast cancer, respectively. Similar results were obtained in the sensitivity analyses. A web‐based calculator was developed to estimate risk stratification for women.This study developed and internally validated a risk‐adapted and user‐friendly risk‐prediction model by incorporating easily accessible variables and female factors. The personalized model demonstrated reliable calibration and moderate discriminative ability. Risk‐stratified screening strategies contribute to precisely distinguishing high‐risk individuals from asymptomatic individuals and prioritizing breast cancer screening. Breast cancer remains a burden in China. To enhance breast cancer screening, we need to incorporate population stratification in screening. Accurate risk‐prediction models for breast cancer remain scarce in China. We established and validated a risk‐adapted and user‐friendly risk‐prediction model by incorporating routinely available variables along with female factors. Using this risk‐stratified model helps accurately identify high‐risk individuals, which is of significant importance when considering integrating individual risk assessments into mass screening programs for breast cancer. Current clinical breast cancer screening lacks a constructive clinical pathway and guiding recommendations. Our findings can better guide clinicians and health care providers. Breast cancer remains a burden in China. To enhance breast cancer screening, we need to incorporate population stratification in screening.Accurate risk‐prediction models for breast cancer remain scarce in China. We established and validated a risk‐adapted and user‐friendly risk‐prediction model by incorporating routinely available variables along with female factors.Using this risk‐stratified model helps accurately identify high‐risk individuals, which is of significant importance when considering integrating individual risk assessments into mass screening programs for breast cancer.Current clinical breast cancer screening lacks a constructive clinical pathway and guiding recommendations. Our findings can better guide clinicians and health care providers. [ABSTRACT FROM AUTHOR]