People over 60 years old had higher cancer morbidity and mortality. We aimed to explore the factors associated with the choice of first treatment institution among elderly cancer patients in China and to provide evidence for the development of healthcare policies. We designed a cross-sectional study. 9 hospitals in Shandong Province of China were selected as sample institutions and a questionnaire survey was conducted on cancer patients from these hospitals. The chi-square test and binary logistic regression were used to assess the factors that influence elderly patients’ choice of first treatment institution. 537 respondents(97.64

The objective of this study was to investigate the relationship between the age of menarche and the prevalence of malignancies of the uterus and ovaries. A total of 5540 women were screened from those who participated in the National Health And Nutrition Examination Survey (NHANES) questionnaire from 2007 to 2020, and their variable factors of age, race, education level, Poverty Impact Ratio (PIR), marital status, Body Mass Index (BMI), waist circumference, duration of moderate exercise, smoking habits, hypertension status, energy intake, diabetes and alcohol consumption habits were analysed statistically and by logistic regression. Univariate and multivariate logistic regression analysis of the relationship between age at menarche and gynaecological cancer (uterus/cervix/ovary cancer, the following gynecologic cancers in the article refer to having at least one of these three cancers) prevalence showed a negative association between age at menarche and malignancies of the uterus and ovaries prevalence (OR: 0.82, 95

Background: Depressed mood affects a significant number of patients with cancer, and can impair their quality of life and interfere with successful treatment. Our study aims to create a predictive model for identifying high-risk groups of depressed mood in cancer patients, offering a theoretical support for preventing depressed mood in these individuals. Methods: The China Health and Retirement Longitudinal Study (CHARLS) provided the data for this research, which used CES-D as a tool to identify individuals with depressed mood. Influencing factors of depressed mood in cancer patients was analyzed using a binary logistic regression model. Using the Harvard Cancer Index, we classified the high-risk patients for depressed mood. Results: In present study, 52.96 % of cancer patients met criteria for depressed mood based on the CES-D. Significant correlations were found between depressed mood and factors such as gender, self-rated health, sleep duration, exercise, satisfaction with family, residence, education, life satisfaction, and medical insurance. Utilizing the Harvard Cancer Index, we classified patients into five risk levels for depressed mood, revealing a significant variation in the number of depressive patients across these levels (x(2)=99.82, P < 0.05). Notably, the incidence of depressed mood increased with the risk level among cancer patients (x(2)=103.40, P < 0.05). Limitations: Lack of data on tumor typing and subgroups makes it unlikely to explore the specifics of depressed mood in patients with various types of cancer. Conclusion: The determinants of depressed mood in cancer patients are multi-dimensional. The Harvard Cancer Index may be helpful in identifying high-risk populations.

Esophageal squamous cell carcinoma (ESCC) remains an important health concern in developing countries. Patients with advanced ESCC have a poor prognosis and survival rate, and achieving early diagnosis remains a challenge. Metabolic biomarkers are gradually gaining attention as early diagnostic biomarkers. Hence, this multicenter study comprehensively evaluated metabolism dysregulation in ESCC through an integrated research strategy to identify key metabolite biomarkers of ESCC. First, the metabolic profiles were examined in tissue and serum samples from the discovery cohort (n = 162; ESCC patients, n = 81; healthy volunteers, n = 81), and ESCC tissue-induced metabolite alterations were observed in the serum. Afterward, RNA sequencing of tissue samples (n = 46) was performed, followed by an integrated analysis of metabolomics and transcriptomics. The potential biomarkers for ESCC were further identified by censoring gene-metabolite regulatory networks. The diagnostic value of the identified biomarkers was validated in a validation cohort (n = 220), and the biological function was verified. A total of 457 dysregulated metabolites were identified in the serum, of which 36 were induced by tumor tissues. The integrated analyses revealed significant alterations in the purine salvage pathway, wherein the abundance of hypoxanthine/xanthine exhibited a positive correlation with HPRT1 expression and tumor size. A diagnostic model was developed using two purine salvage–associated metabolites. This model could accurately discriminate patients with ESCC from normal individuals, with an area under the curve (AUC) (95% confidence interval (CI): 0.680–0.843) of 0.765 in the external cohort. Hypoxanthine and HPRT1 exerted a synergistic effect in terms of promoting ESCC progression. These findings are anticipated to provide valuable support in developing novel diagnostic approaches for early ESCC and enhance our comprehension of the metabolic mechanisms underlying this disease.

Health literacy is closely related to the incidence of major chronic diseases and its related behaviors such as cancer-related behaviors. This study explored how the cancer health literacy level affects cancer-related behaviors. About one to two villages from six cities of Shandong province were selected as sample areas. Professionals conducted face-to-face interviews with the participants. Finally, 1200 residents completed 1085 effective questionnaires. Data were analysed from a cross-sectional survey in 2019, which included 1085 residents in six cities/counties of Shandong province, China. The result showed that residents with high cancer health literacy were more likely to eat fruits and vegetables frequently, avoid eating moldy food and take exercise. Besides, they were more likely to engage in health education and have a higher willingness to pay for cancer screenings. Most residents in Shandong province have a basic level of cancer health literacy. Improving the cancer health literacy of the population can be an effective strategy to promote a healthier lifestyle, thereby reducing the incidence rates related to cancers.

Objectives The objective of this study was to investigate the relationship between the age of menarche and the prevalence of gynecological cancer. Methods A total of 5540 women were screened from those who participated in the National Health And Nutrition Examination Survey (NHANES) questionnaire from 2007–2020, and their variable factors of age, race, education level, Poverty Impact Ratio (PIR), marital status, Body Mass Index (BMI), waist circumference, duration of moderate exercise, smoking habits, hypertension status, energy intake, diabetes and alcohol consumption habits were analysed statistically and by logistic regression. Results Univariate and multivariate logistic regression analysis of the relationship between age at menarche and gynaecological cancer (Uterus / Cervix / Ovary Cancer, the following gynecologic cancers in the article refer to having at least one of these three cancers) prevalence showed a negative association between age at menarche and gynaecological cancer prevalence (OR: 0.82, 95%CI: 0.69–0.97), with a statistically significant difference (p = 0.02). Regression results of the association between age at menarche and different types of gynaecological cancers found a negative association between age at menarche and prevalence in uterine cancers (P = 0.03) and no association between age at menarche and prevalence in cervical and ovarian cancers (P = 0.17, P = 0.29). Those with a younger age at menarche were more likely to develop uterine cancer (OR: 0.72, 95%CI: 0.54–0.98). Conclusions There was a correlation between age at menarche and gynaecological cancer, with those who had menarche at an earlier age being at a higher risk of gynaecological cancer. More obviously, the younger the age of first menstruation, the higher the risk of uterine cancer.

Medulloblastoma (MB), a common and heterogeneous posterior fossa tumor in pediatric patients, presents diverse prognostic outcomes. To advance our understanding of MB’s intricate biology, the development of novel patient tumor-derived culture MB models with necessary data is still an essential requirement. We continuously passaged PUMC-MB1 in vitro in order to establish a continuous cell line. We examined the in vitro growth using Cell Counting Kit-8 (CCK-8) and in vivo growth with subcutaneous and intracranial xenograft models. The xenografts were investigated histopathologically with Hematoxylin and Eosin (HE) staining and immunohistochemistry (IHC). Concurrently, we explored its molecular features using Whole Genome Sequencing (WGS), targeted sequencing, and RNA sequecing. Guided by bioinformatics analysis, we validated PUMC-MB1’s drug sensitivity in vitro and in vivo. PUMC-MB1, derived from a high-risk MB patient, displayed a population doubling time (PDT) of 48.18 h and achieved 100

Previous metabolomics studies have highlighted the predictive value of metabolites on upper gastrointestinal (UGI) cancer, while most of them ignored the potential effects of lifestyle and genetic risk on plasma metabolites. This study aimed to evaluate the role of lifestyle and genetic risk in the metabolic mechanism of UGI cancer. Differential metabolites of UGI cancer were identified using partial least-squares discriminant analysis and the Wilcoxon test. Then, we calculated the healthy lifestyle index (HLI) score and polygenic risk score (PRS) and divided them into three groups, respectively. A total of 15 metabolites were identified as UGI-cancer-related differential metabolites. The metabolite model (AUC = 0.699) exhibited superior discrimination ability compared to those of the HLI model (AUC = 0.615) and the PRS model (AUC = 0.593). Moreover, subgroup analysis revealed that the metabolite model showed higher discrimination ability for individuals with unhealthy lifestyles compared to that with healthy individuals (AUC = 0.783 vs 0.684). Furthermore, in the genetic risk subgroup analysis, individuals with a genetic predisposition to UGI cancer exhibited the best discriminative performance in the metabolite model (AUC = 0.770). These findings demonstrated the clinical significance of metabolic biomarkers in UGI cancer discrimination, especially in individuals with unhealthy lifestyles and a high genetic risk.

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Pin1, a peptide prolyl cis-trans isomerase, is overexpressed and/or overactivated in many human malignancies. However, whether Pin1 regulates the immunosuppressive TME has not been well defined. In this study, we detected the effect of Pin1 on immune cells and immune checkpoint PD-L1 in the TME of CRC and explored the anti-tumor efficacy of Pin1 inhibitor ATRA combined with PD-1 antibody. We found that Pin1 facilitated the immunosuppressive TME by raising the proportion of myeloid-derived suppressor cells (MDSCs) and declining the percentage of CD8+ T cells and CD4+ T cells. Pin1 restrained PD-L1 protein expression in CRC cells and the effect was tempered by endoplasmic reticulum (ER) stress inducers. Mechanically, Pin1 overexpression decreased the stability of PD-L1 and promoted its degradation by mitigating ER stress. Silencing or inhibiting Pin1 promoted PD-L1 protein expression by inducing ER stress. Hence, Pin1 inhibitor ATRA enhanced the anti-tumor efficacy of PD-1 antibody in the CRC allograft by upregulating PD-L1. Our results reveal the critical and pleiotropic effects of Pin1 on managing the immune cells and immune checkpoint PD-L1 in the TME of CRC, providing a new promising candidate for combination with immunotherapy.

The presence of a poly(A) tail is indispensable for the post-transcriptional regulation of gene expression in cancer. This dynamic and modifiable feature of transcripts is under the control of various nuclear and cytoplasmic proteins. This study aimed to develop a novel cytoplasmic poly(A)-related signature for predicting prognosis, clinical attributes, tumor immune microenvironment (TIME), and treatment response in hepatocellular carcinoma (HCC). Utilizing RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA), non-negative matrix factorization (NMF), and principal-component analysis (PCA) were employed to categorize HCC patients into three clusters, thus demonstrating the pivotal prognostic role of cytoplasmic poly(A) tail regulators. Furthermore, machine learning algorithms such as least absolute shrinkage and selection operator (LASSO), survival analysis, and Cox proportional hazards modeling were able to distinguish distinct cytoplasmic poly(A) subtypes. As a result, a 5-gene signature derived from TCGA was developed and validated using International Cancer Genome Consortium (ICGC) HCC datasets. This novel classification based on cytoplasmic poly(A) regulators has the potential to improve prognostic predictions and provide guidance for chemotherapy, immunotherapy, and transarterial chemoembolization (TACE) in HCC.

目的 通过测量医学专业硕士、博士毕业生对公立医院人才引进政策的偏好,为同类医疗机构设计政策吸引人才提供参考依据.方法 基于离散选择实验设计问卷,在线调查388名医学专业硕士、博士毕业生对科研经费、子女教育福利(幼、小、初阶段)、住房福利、编制、职称晋升减免年限和工作薪酬外的一次性补贴等人才引进政策属性的偏好程度,通过Stata 16.0软件运用混合logit模型进行数据分析.结果 除职称晋升减免年限外,其余纳入的5项人才引进政策属性差异均有统计学意义(P＜0.05).效用最大的属性是编制(β= 2.473),医学专业毕业生愿意放弃335272.5元的一次性补贴来换取编制,职称晋升减免年限的属性效用最小.亚组分析显示,未婚人群更关注住房福利,博士毕业生更在乎科研经费.结论 编制和子女教育福利是最吸引医学专业硕士、博士毕业生的人才引进政策.政策制定者应综合考虑政策属性和毕业生背景,制定更为有效的人才引进政策.

目的 了解影响癌症患者参与医患共同决策行为意愿的行为因素,为进一步促进癌症患者参与医患共同决策提供参考依据.方法 本文基于计划行为理论模型,从行为控制、行为态度、主观规范3个维度构建癌症患者参与医患共同决策的理论分析框架,采取分层随机抽样的方法,选取2023-03-01-2023-03-10山东省肿瘤医院收治的453例癌症患者进行问卷调查,运用结构方程模型分析其参与医患共同决策行为意愿驱动机制.结果 在癌症患者参与医患共同决策的行为意向方面,行为控制对行为意向有显著的正向影响,P＜0.001;而行为态度(P=0.176)和主观规范(P=0.282)对行为意向无显著影响;行为态度,行为控制和主观规范三者之间两两相关,并最终共同作用于行为意向,均P＜0.001.结论 在今后的工作中应进一步加强对癌症相关知识的宣传教育,降低患者参与决策的专业壁垒,以促进癌症患者更好的参与到医患共同决策中.

[目的]分析山东省样本地区肺癌防控资源和能力现状,为更好开展肺癌防控工作提供科学依据.[方法]基于世界卫生组织-国家癌症控制计划核心能力自我评估工具,通过德尔菲专家咨询法设计调查问卷,问卷共4个方面26个条目,包括肺癌防控资源情况,烟草控制政策、法规及相关行动,肺癌筛查/早诊早治以及肺癌诊疗情况等,总分30分;在山东省范围内根据地理位置和经济发展水平分层随机抽取3个地级市,每个市随机抽取3个县(市、区),开展问卷调查.[结果]27个样本县(市、区)肺癌防控资源情况,烟草控制政策、法规及相关行动,肺癌筛查/早诊早治和肺癌诊疗情况的平均得分分别为6.35、4.67、2.17和3.07分,占对应总分的42.35％、77.83％、43.40％和76.75％;西部地区肺癌防控能力低于东部和中部地区,东、中部地区间差异则较小.[结论]山东省样本地区肺癌防控能力总体较低,肺癌防控资源配置不均衡,区域间防控能力差异大.各地应针对自身特点和薄弱环节有重点地采取措施,促进肺癌防治能力和水平的持续提升.

Abstract Background: The prognosis of patients with small cell lung cancer (SCLC) is poor. We aim to figure out the survival rate of SCLC and construct a nomogram survival prediction for SCLC patients in Shandong. Methods: We collected the clinical data of 2219 SCLC patients in various tumor hospitals and general hospitals in fifteen cities in Shandong province from 2010-2014, and the data were randomly divided into a training set and a validation set according to 7:3. We used univariate and multivariate to determine the independent prognostic factors of SCLC, and developed a prognostic nomogram model based on these factors. The predictive discriminatory and accuracy performance of this model was evaluated by the area under the receiver operator characteristic (ROC) curve (AUC), and calibration curves. Results: The overall 5-year survival rate of Shandong SCLC patients was 14.27% with the median survival time being 15.77 months. Multivariate analysis showed that region, sex, age, year of diagnosis, TNM stage (assigned according to the AJCC 8th edition), and treatment type (surgery, chemotherapy, and radiotherapy) were independent prognostic factors and were included in the prognostic nomogram model. The AUC of the training set was 0.724, 0.710, and 0.704 for 1-year, 3-year, and 5-year; the AUC of the validation set was 0.678, 0.670, and 0.683 for 1-year, 3-year, and 5-year. The calibration curves of the prediction are consistent with the ideal curve. Conclusion: We construct a nomogram prognostic model to predict SCLC prognosis with certain discrimination which can provide both clinicians and patients with an effective tool for predicting outcomes and guiding treatment decisions.

目的 通过比较肥城市上消化道癌内镜筛查区病例与未筛查区病例的生存差异,探讨上消化道癌症内镜筛查的效果.方法 以2011-2013年进行内镜筛查村庄在筛查当年及筛查年前2年的503例新发病例为研究对象,其中男368例,女135例.借鉴类阶梯式试验原理,对人群进行回顾性队列研究.以进行内镜筛查的村庄在筛查当年的全部新发病病例为筛查组病例;筛查年之前2年登记的40～69岁的新发病例为未筛查组病例.采用寿命表法描述筛查组与未筛查组3和5年生存率及95％CI值;log-rank检验比较筛查组与未筛查组上消化道癌症病例的生存曲线差异;Cox回归分析内镜筛查对上消化道癌症患者生存状况的影响.结果 筛查组共纳入病例368例,未筛查组共纳入135例.筛查组和未筛查组的3年生存率分别为75.3％(95％CI:70.5～79.4)和31.85％(95％CI:24.2～39.8);5年生存率分别为38.0％(95％CI:33.1～43.0)和26.7％(95％CI:19.5～34.3).整体筛查组的生存分布优于未筛查组,χ2=100.000,P<0.001.多因素Cox回归结果显示,参与内镜筛查(HR=0.26,95％CI:0.20～0.35)和女性(HR=0.56,95％CI:0.40～0.79)是上消化道癌症的保护因素.结论 开展内镜筛查可以有效的发现早期病例,延长了筛查区上消化道癌症患者的生存时间,对减轻当地上消化道癌症疾病负担有重要意义.

Importance Assessment tools are lacking for screening of esophageal squamous cell cancer (ESCC) in China, especially for the follow-up stage. Risk prediction to optimize the screening procedure is urgently needed. Objective To develop and validate ESCC prediction models for identifying people at high risk for follow-up decision-making. Design, Setting, and Participants This open, prospective multicenter diagnostic study has been performed since September 1, 2006, in Shandong Province, China. This study used baseline and follow-up data until December 31, 2021. The data were analyzed between April 6 and May 31, 2022. Eligibility criteria consisted of rural residents aged 40 to 69 years who had no contraindications for endoscopy. Among 161 212 eligible participants, those diagnosed with cancer or who had cancer at baseline, did not complete the questionnaire, were younger than 40 years or older than 69 years, or were detected with severe dysplasia or worse lesions were eliminated from the analysis. Exposures Risk factors obtained by questionnaire and endoscopy. Main Outcomes and Measures Pathological diagnosis of ESCC and confirmation by cancer registry data. Results In this diagnostic study of 104 129 participants (56.39% women; mean [SD] age, 54.31 [7.64] years), 59 481 (mean [SD] age, 53.83 [7.64] years; 58.55% women) formed the derivation set while 44 648 (mean [SD] age, 54.95 [7.60] years; 53.51% women) formed the validation set. A total of 252 new cases of ESCC were diagnosed during 424 903.50 person-years of follow-up in the derivation cohort and 61 new cases from 177 094.10 person-years follow-up in the validation cohort. Model A included the covariates age, sex, and number of lesions; model B included age, sex, smoking status, alcohol use status, body mass index, annual household income, history of gastrointestinal tract diseases, consumption of pickled food, number of lesions, distinct lesions, and mild or moderate dysplasia. The Harrell C statistic of model A was 0.80 (95% CI, 0.77-0.83) in the derivation set and 0.90 (95% CI, 0.87-0.93) in the validation set; the Harrell C statistic of model B was 0.83 (95% CI, 0.81-0.86) and 0.91 (95% CI, 0.88-0.95), respectively. The models also had good calibration performance and clinical usefulness. Conclusions and Relevance The findings of this diagnostic study suggest that the models developed are suitable for selecting high-risk populations for follow-up decision-making and optimizing the cancer screening process.