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Background and purpose: Effective treatment for cervical cancer patients is one of the global strategies to eliminate cervical cancer. By analyzing the metastasis characteristics and survival status of patients with distant metastasis of cervical cancer from a hospital-based cancer registry data, our study provided real-world evidence for better survival of cervical cancer and finally eliminating cervical cancer. Methods: A total of 572 cervical cancer patients who had metastasis cancer at the initial diagnosis or developed distant metastasis during follow-up in Fudan University Shanghai Cancer Center from 2008 to 2017 were included in this study. Medical records review, telephone visits and death registry data linkage were applied in collecting endpoint data. The first follow-up date was the diagnose date of metastasis, and the last follow-up date was November 1, 2020. Kaplan-Meier method was applied in evaluating the 1-, 3- and 5-year overall survival (OS) rates for overall and site-specific patients. Results: The median follow-up time was 38.93 months, and 348 cases died during the follow-up. 72.55% were single site metastasis, and 27.45% were multiple metastases. Among all metastatic sites, the proportion of lung metastasis was the highest, 41.26%, 15.21% to bone, and 11.54% to liver. After metastasis, the 1-year, 3-year and 5-year OS rates were 62.29% (95% CI: 62.25-62.33), 33.13% (95% CI: 33.08-33.18) and 23.42% (95% CI: 23.37-23.47), respectively. In single site metastasis, 1-year OS was the highest after metastasis to the lung (72.52%). Besides, there was no significant difference among different metastatic sites, both in 3-year and 5-year OS. Conclusion: The most frequent distant metastatic sites of cervical cancer are lung, bone and liver. The survival rate after metastasis is poor. Further research with systematic treatment strategy is required for better survival.

Key Points: Question: Compared with the end point of cancer-specific mortality, is incidence of late-stage cancer a suitable alternative end point in randomized clinical trials of cancer screening? Findings: In this systematic review and meta-analysis that included 41 randomized clinical trials of cancer screening, correlation between the reduction in stage III and IV cancer and the reduction in cancer-specific mortality varied by cancer type. The correlation was high in trials that screened for ovarian (Pearson ρ = 0.99) and lung (Pearson ρ = 0.92) cancers, moderate for breast cancer (Pearson ρ = 0.70), and weak for colorectal (Pearson ρ = 0.39) and prostate (Pearson ρ = −0.69) cancers. Meaning: In randomized clinical trials of cancer screening, the correlation between reductions in late-stage cancer and cancer-specific mortality varied meaningfully by cancer type. The end point of late-stage cancer may be an appropriate alternative to cancer-specific mortality for randomized clinical trials of screening for some types of cancer, but not for others. Importance: Randomized clinical trials of cancer screening typically use cancer-specific mortality as the primary end point. The incidence of stage III-IV cancer is a potential alternative end point that may accelerate completion of randomized clinical trials of cancer screening. Objective: To compare cancer-specific mortality with stage III-IV cancer as end points in randomized clinical trials of cancer screening. Design, Setting, and Participants: This meta-analysis included 41 randomized clinical trials of cancer screening conducted in Europe, North America, and Asia published through February 19, 2024. Data extracted included numbers of participants, cancer diagnoses, and cancer deaths in the intervention and comparison groups. For each clinical trial, the effect of screening was calculated as the percentage reduction between the intervention and comparison groups in the incidence of participants with cancer-specific mortality and stage III-IV cancer. Exposures: Randomization to a cancer screening test or to a comparison group in a clinical trial of cancer screening. Main Outcomes and Measures: End points of cancer-specific mortality and incidence of stage III-IV cancer were compared using Pearson correlation coefficients with 95% CIs, linear regression, and fixed-effects meta-analysis. Results: The included randomized clinical trials tested benefits of screening for breast (n = 6), colorectal (n = 11), lung (n = 12), ovarian (n = 4), prostate (n = 4), and other cancers (n = 4). Correlation between reductions in cancer-specific mortality and stage III-IV cancer varied by cancer type (I2 = 65%; P =.02). Correlation was highest for trials that screened for ovarian (Pearson ρ = 0.99 [95% CI, 0.51-1.00]) and lung (Pearson ρ = 0.92 [95% CI, 0.72-0.98]) cancers, moderate for breast cancer (Pearson ρ = 0.70 [95% CI, −0.26 to 0.96]), and weak for colorectal (Pearson ρ = 0.39 [95% CI, −0.27 to 0.80]) and prostate (Pearson ρ = −0.69 [95% CI, −0.99 to 0.81]) cancers. Slopes from linear regression were estimated as 1.15 for ovarian cancer, 0.75 for lung cancer, 0.40 for colorectal cancer, 0.28 for breast cancer, and −3.58 for prostate cancer, suggesting that a given magnitude of reduction in incidence of stage III-IV cancer produced different magnitudes of change in incidence of cancer-specific mortality (P for heterogeneity =.004). Conclusions and Relevance: In randomized clinical trials of cancer screening, incidence of late-stage cancer may be a suitable alternative end point to cancer-specific mortality for some cancer types, but is not suitable for others. These results have implications for clinical trials of multicancer screening tests. This meta-analysis of 41 randomized clinical trials of cancer screening compares cancer-specific mortality with stage III-IV cancer as end points. [ABSTRACT FROM AUTHOR]

Background and purpose: We analyzed the distribution of metastatic sites and survival of lung cancer patients with metastases based on hospital registration to provide real-world data support for the treatment and survival management of lung cancer patients. Methods: A total of 1 490 lung cancer patients who developed metastasis during the follow-up in Fudan University Shanghai Cancer Center from 2008 to 2017 were enrolled in this study. Medical records review, telephone visits and death registry data linkage were applied in collecting endpoint data. The effects of age at diagnosis, gender and histological subtype on the distribution of metastases were studied. The Kaplan-Meier method was used to evaluate the overall survival (OS) rates of different metastatic sites. Results: The median follow-up time was 40.8 months. During the follow-up period, 937 cases died from all causes. 67.7% of patients only had single-site metastasis, while 32.3% of patients had multiple-site metastases. The common metastatic sites were bone (33.8%), brain (33.6%), lung (22.8%), liver (12.0%) and adrenal gland (3.7%). Female patients had more metastases to brain (37.8% vs 31.4%). Younger patients were more likely to develop multiple-site metastases, and small cell carcinomas patients had more brain metastases (47.2%) and liver metastases (20.9%). Lung metastasis featured relatively best survival (1-year OS rate: 78.3%, 3-year OS rate: 47.1%, 5-year OS rate: 29.5%), whereas liver metastasis had relatively the worst prognosis (1-year OS rate: 46.4%, 3-year OS rate: 15.2%, 5-year OS rate: 3.6%). Conclusion: The proportions of bone and brain metastases in lung cancer patients with metastasis are high. The distribution of metastatic sites is associated with gender, age at diagnosis and histological type. The prognosis of patient with different metastatic sites is different. Mechanisms or clinical treatment plans can be studied for different metastatic sites to improve the prognosis of late-stage lung cancer patients in future research.

Objective To analyze the literatures about artificial intelligence in cancer research in Web of Science (WOS) core collection database in 2010-2019 and summarize research hot spots and development trends. Methods Through bibliometrics methods and CiteSpace information visualization software, we applied the visual analysis of relevant literature on artificial intelligence in the field of cancer research retrieved from the Web of Science core collection database from 2010 to 2019. Results The number of published articles about artificial intelligence in the field of cancer research had been increasing year by year. The United States ranked first in the number of published articles in this field, the number of citations and cooperation capabilities. Although the number of published articles in China ranked the second, the number of citations was low. The hot spots of artificial intelligence in cancer research were mainly breast cancer and lung cancer. Machine learning, neural network and other methods were used to build models, which were used in basic cancer research, clinical diagnosis, treatment and prognosis prediction. The research frontiers were the methodological research of artificial intelligence, the research on the occurrence and classification of cancer and the research of protein in this field. Conclusion It will effectively promote the development of artificial intelligence in cancer research in China by learning the hot spots and cutting-edge technologies of international research, focusing on international cooperation and cooperation among national institutions and strengthening cross-disciplinary research.

Background and purpose: Metastasis remains the cause of 90% of death from cancer. By analyzing the distribution of metastatic sites and survival status of 20 000 metastatic cancer patients from a hospital-based cancer registry database, this study provides the real-world data for the cancer treatment and survival management in China. Methods: A total of 20 067 cancer patients who were diagnosed as having metastatic caner or developed metastasis during the follow-up in Fudan University Shanghai Cancer Center from 2008 to 2017 were included in this study. Medical records review, telephone visits and death registry data linkage were applied in collecting endpoint data. The first follow-up date was the diagnosis date of metastasis, and the last follow-up date was November 1, 2020. Kaplan-Meier method was applied in evaluating the 1-, 3- and 5-year overall survival (OS) rates for overall cancer and site-specific cancer patients. Results: The median follow-up time was 46.7 months, 13 170 cases died during the follow- up, 60.05% was single-site metastasis, and 39.95% was multiple-site metastasis. Among all metastable sites, the proportion of metastasis to liver was 33.82%, 26.25% to lung, 26.22% to bone, and 9.22% to brain. The incidence of brain metastasis was the highest in lung cancer patients among all cancer types (31.14%). Liver was the most frequent metastatic site in pancreatic cancer (77.85%), and bone was the most frequent metastatic site in patients with prostate cancer (83.20%). Subgroup analysis showed that liver metastasis was easier to be observed in males than in females (35.46% vs 31.89%, P

Differences in the average age at cancer diagnosis are observed across countries. We therefore aimed to assess international variation in the median age at diagnosis of common cancers worldwide, after adjusting for differences in population age structure. We used IARC's Cancer Incidence in Five Continents (CI5) Volume XI database, comprising cancer diagnoses between 2008 and 2012 from population‐based cancer registries in 65 countries. We calculated crude median ages at diagnosis for lung, colon, breast and prostate cancers in each country, then adjusted for population age differences using indirect standardization. We showed that median ages at diagnosis changed by up to 10 years after standardization, typically increasing in low‐ and middle‐income countries (LMICs) and decreasing in high‐income countries (HICs), given relatively younger and older populations, respectively. After standardization, the range of ages at diagnosis was 12 years for lung cancer (median age 61‐Bulgaria vs 73‐Bahrain), 12 years for colon cancer (60‐the Islamic Republic of Iran vs 72‐Peru), 10 years for female breast cancer (49‐Algeria, the Islamic Republic of Iran, Republic of Korea vs 59‐USA and others) and 10 years for prostate cancer (65‐USA, Lithuania vs 75‐Philippines). Compared to HICs, populations in LMICs were diagnosed with colon cancer at younger ages but with prostate cancer at older ages (both pLMICS‐vs‐HICs < 0.001). In countries with higher smoking prevalence, lung cancers were diagnosed at younger ages in both women and men (both pcorr < 0.001). Female breast cancer tended to be diagnosed at younger ages in East Asia, the Middle East and Africa. Our findings suggest that the differences in median ages at cancer diagnosis worldwide likely reflect population‐level variation in risk factors and cancer control measures, including screening. [ABSTRACT FROM AUTHOR]

Identification of risk biomarkers may enhance early detection of smoking-related lung cancer. We measured between 392 and 1,162 proteins in blood samples drawn at most three years before diagnosis in 731 smoking-matched case-control sets nested within six prospective cohorts from the US, Europe, Singapore, and Australia. We identify 36 proteins with independently reproducible associations with risk of imminent lung cancer diagnosis (all p < 4 × 10−5). These include a few markers (e.g. CA-125/MUC-16 and CEACAM5/CEA) that have previously been reported in studies using pre-diagnostic blood samples for lung cancer. The 36 proteins include several growth factors (e.g. HGF, IGFBP-1, IGFP-2), tumor necrosis factor-receptors (e.g. TNFRSF6B, TNFRSF13B), and chemokines and cytokines (e.g. CXL17, GDF-15, SCF). The odds ratio per standard deviation range from 1.31 for IGFBP-1 (95% CI: 1.17–1.47) to 2.43 for CEACAM5 (95% CI: 2.04–2.89). We map the 36 proteins to the hallmarks of cancer and find that activation of invasion and metastasis, proliferative signaling, tumor-promoting inflammation, and angiogenesis are most frequently implicated. Lung cancer screening could enhance early diagnosis and treatment. Here, the authors used proteomic analysis of pre-diagnosis samples across 6 cohorts to identify 36 proteins associated with imminent lung cancer diagnosis. [ABSTRACT FROM AUTHOR]

The EarlyCDT‐Lung test is a blood‐based autoantibody assay intended to identify high‐risk individuals for low‐dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT‐Lung test in ever‐smokers. We conducted a nested case‐control study within two prospective cohorts to evaluate the risk‐discriminatory performance of the EarlyCDT‐Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT‐Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT‐Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34‐2.30) for a moderate risk EarlyCDT‐Lung test result and 1.09 (95% CI: 0.48‐2.47) for a high‐risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6‐14) and overall specificity was 92% (95% CI: 87‐96) when considering a high‐risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2‐32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT‐Lung test in identifying the high‐risk subjects in ever‐smokers for lung cancer screening in the EPIC and NSHDS cohorts. [ABSTRACT FROM AUTHOR]