Users can access data about cancer statistics in the United States including but not limited to searches by type of cancer and race, sex, ethnicity, age at diagnosis, and age at death. Background Surveillance Epidemiology and End Results (SEER) database’s mission is to provide information on cancer statistics to help reduce the burden of disease in the U.S. population. The SEER database is a project to the National Cancer Institute. The SEER database collects information on incidence, prevalence, and survival from specific geographic areas representing 28 percent of the United States population. User functionality Users can access a variety of reso urces. Cancer Stat Fact Sheets allow users to look at summaries of statistics by major cancer type. Cancer Statistic Reviews are available from 1975-2008 in table format. Users are also able to build their own tables and graphs using Fast Stats. The Cancer Query system provides more flexibility and a larger set of cancer statistics than F ast Stats but requires more input from the user. State Cancer Profiles include dynamic maps and graphs enabling the investigation of cancer trends at the county, state, and national levels. SEER research data files and SEER*Stat software are available to download through your Internet connection (SEER*Stat’s client-server mode) or via discs shipped directly to you. A signed data agreement form is required to access the SEER data Data Notes Data is available in different formats depending on which type of data is accessed. Some data is available in table, PDF, and html formats. Detailed information about the data is available under “Data Documentation and Variable Recodes”.

The county population estimates currently used in the SEER*Stat software to calculate cancer incidence and mortality rates are available for download (see Download U.S. Population Data). They represent a modification of the intercensal and Vintage 2019 annual time series of July 1, county population estimates by age, sex, race, and Hispanic origin produced by the U.S. Census Bureau's Population Estimates Program, in collaboration with the National Center for Health Statistics, and with support from the NCI through an interagency agreement. The files were downloaded and archived on July 28, 2021 by the American Economic Association's Data Editor.

ObjectivePulmonary enteric adenocarcinoma (PEAC) is a rare subtype of pulmonary adenocarcinoma that lacks effective treatment. The purpose of this research was to investigate the clinical characteristics, treatment, and prognosis of PEAC, as well as the impact of relevant factors on survival, thus providing a reference for the clinical management of patients with this disease.MethodsFor this study, we gathered clinical data from 26 patients with PEAC in the Affiliated Cancer Hospital of Zhengzhou University from June 2014 to June 2021. We used SEER*Stat software V8.3.5 to download the PEAC patients from the Surveillance, Epidemiology, and End Results (SEER) database. In total, 20 patients were identified. Clinical data, including general information, imaging findings, and treatment protocols, were obtained, together with a follow-up of disease regression. The relevant clinical data were then analyzed.ResultsIt included 12 males and 14 females out of 26 patients from China, whose mean age was (62.73 ± 11.89) years; 20 were in the lower lung, 11 were stage I-II, and 15 were stage III-IV. Five had EGFR mutations, and four had KRAS mutations. In terms of treatment, patients with stage I-II were primarily treated by surgery, and patients with stage III-IV were treated mostly by chemotherapy. We extended the follow-up date to January 2022. On completion of the follow-up visit, 11 patients died, and the remaining 15 patients survived. The overall survival (OS) of 26 patients was 2.0-76.0 months, while the mean was 53.1 months, and the median OS (mOS) was 38.0 months (95% CI:1.727-74.273). In the case of progression-free survival (PFS) times, it was 2.0-76.0 months, with a mean PFS of 31.0 months and a median PFS (mPFS) of 8.0 months (95% CI:4.333-11.667). The PFS of the 15 patients in stage III-IV was 2.0-17 months, while the mean PFS was 6.5 months and the mPFS was 6.0 months (95% CI:4.512-7.488). Out of the 20 patients identified in the SEER database, the average age was 69.9 years, with 14 males and 6 females. Of these patients, 8 were diagnosed with stage I-II, while the remaining 11 were diagnosed with stage III-IV. 10 underwent surgery, 4 received radiation therapy, and 9 received chemotherapy. The mean OS of the 20 patients was 67.5 months, mOS was 28.0 months (95% CI: 9.664- 46.336). For patients diagnosed with stage III-IV, the mean OS was 14.8 months and mOS was 20 months (95% CI: 4.713-35.287).ConclusionPEAC is rare, and the prognosis is determined mainly by the stage; patients who undergo surgery in stage I-II have a better prognosis.

BackgroundGastrointestinal neuroendocrine tumor (GI-net) is a rare heterogeneous tumor, and there is a lack of models to predict its prognosis. Our study aims to develop and validate two new nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of GI-net patients and investigate their application value.MethodsSEER*Stat 8.4.4 software was used to download clinicopathological information of GI-net patients between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. These patients were randomly divided into a training group (n=3007) and an internal-validation group (n=1289) at a 7:3 ratio. Patients from the Fourth Hospital of Hebei Medical University were enrolled in this study to form the external-validation group (n=86). Univariate and multivariate Cox analyses were performed to explore the independent prognostic factors and establish two nomograms. The concordance index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomograms. X-tile was used to divide GI-net patients into high-, medium-, and low-risk groups. Kaplan–Meier (KM) curves and log-rank tests were used to compare survival differences among the three groups.ResultsSeven variables (age, site, size, grade, M stage, surgery, and chemotherapy) were selected to establish the nomogram for OS, and 6 variables (age, size, grade, M stage, surgery, and chemotherapy) were selected for CSS. The C indices (0.785, 0.813, and 0.936 in the training, internal-validation, and external-validation groups for OS; 0.888, 0.893, and 0.930 for CSS, respectively) and AUCs (≥0.7) indicated that the nomograms had satisfactory discriminative ability. Calibration curve analysis and DCA revealed that the nomogram had a satisfactory ability to predict OS and CSS. KM curves indicated that each of the two nomograms clearly differentiated the high-, medium-, and low-risk groups. In addition, two online risk calculators were developed to predict the OS and CSS of these patients visually.ConclusionsOur nomograms may play an important role in predicting 3- and 5-year OS and CSS for GI-net patients. Risk stratification systems and online risk calculators can be utilized in clinical practice to help doctors create personalized treatment plans.