Surveillance, Epidemiology, And End Results Population-based Study Research Articles

Prognostic factors of tongue cancer in children and adolescents: A SEER population-based study.

This study aims to analyze the clinicopathological characteristics and survival outcomes of tongue cancer in the pediatric population, a topic with limited existing data, using a population-based cohort. Pediatric patients diagnosed with tongue cancer from 1975 to 2018 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Survival rates were assessed using Kaplan-Meier analysis. Univariate survival analysis was conducted with the log-rank test, while multivariate analysis involved Cox proportional-hazards regression to identify factors influencing overall survival (OS). A predictive nomogram was developed based on Cox regression findings. In total, 97 pediatric patients with tongue cancer were identified, with a median age at diagnosis of 15 years (range: 1-19 years). Tumors were classified as squamous cell carcinoma (45.4%), rhabdomyosarcoma (RMS) (13.4%), and others (41.2%). Of the patients, squamous cell carcinoma was more common in older children, whereas rhabdomyosarcoma was more common in younger children. The Cox proportional hazard regression revealed that histology and surgery were significant independent predictors of overall survival. The chance of death increased with no surgery. Moreover, patients with squamous cell carcinoma or rhabdomyosarcoma have a poorer survival percentage than patients with other subtypes. Tongue cancer in children is rare and associated with poor survival outcomes. This study highlights the significance of tumor histology and surgical intervention in determining overall survival, offering valuable insights for clinical decision-making in pediatric tongue cancer.

Development and validation of a nomogram for predicting lymph node metastasis in ductal carcinoma in situ with microinvasion: A SEER population-based study.

Ductal carcinoma in situ with microinvasion (DCIS-MI) is a special type of breast cancer. It is an invasive lesion less than 1.0 mm in size related to simple ductal carcinoma in situ (DCIS). Lymph node metastasis (LNM) in DCIS-MI often indicates a poor prognosis. Therefore, the management of lymph nodes plays a vital role in the treatment strategy of DCIS-MI. Since DCIS-MI is often diagnosed by postoperative paraffin section and immunohistochemical detection, to obtain the best clinical benefits for such patients, we aim to establish and verify a nomogram to predict the possibility of lymph node metastasis in DCIS-MI patients and help preoperative or intraoperative clinical decision-making. A retrospective analysis of patients with DCIS-MI in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2019 was performed. The study cohort was randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The risk factors were determined by univariate and multivariate logistic regression analyses in the training cohort, and a nomogram was constructed. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram in the training set and validation set. An independent data cohort was obtained from the Shanghai Jiao Tong University Breast Cancer Database (SJTU-BCDB) for external validation. This study included 3951 female patients from SEER with DCIS-MI, including 244 patients with regional lymph node metastasis, accounting for 6.18% of the total. An independent test set of 323 patients from SJTU-BCDB was used for external validation. According to the multifactorial logistic regression analysis results, age at diagnosis, ethnicity, grade, and surgical modality were included in the prediction model. The areas under the ROC curves (AUCs) were 0.739 (95% CI: 0.702~0.775), 0.732 (95% CI: 0.675~0.788), and 0.707 (95%CI: 0.607-0.807) in the training, validation and external test groups, suggesting that the column line graphs had excellent differentiation. The calibration curves slope was close to 1, and the model's predicted values were in good agreement with the actual values. The DCA curves showed good clinical utility. In this study, we constructed accurate and practical columnar maps with some clinical benefit to predict the likelihood of lymph node metastasis in patients with postoperatively diagnosed DCIS-MI and provide a reference value for specifying treatment strategies.

A novel log odds of positive lymph nodes–based nomogram for predicting overall survival in patients with colorectal signet ring cell carcinoma: a SEER population-based study

PurposeConsidering the poor prognosis and high lymph node (LN) involvement rate of colorectal signet ring cell carcinoma (SRCC), this study aimed to construct a prognostic nomogram to predict overall survival (OS) with satisfactory accuracy and utility, based on LN status indicators with superior predictability.MethodsUsing the Surveillance, Epidemiology, and End Results (SEER) database, we obtained cases of colorectal SRCC patients and employed univariate and multivariate Cox analyses to determine independent prognostic factors. Kaplan–Meier curves were utilized to visualize survival differences among these factors. Receiver operating characteristic curves were generated to assess predictive performances of models incorporating various LN status indicators. A novel nomogram, containing optimal LN status indicators and other prognostic factors, was developed to predict OS, whose discriminatory ability and accuracy were evaluated using calibration curves and decision curve analysis.ResultsA total of 1663 SRCC patients were screened from SEER database. Older patients and those with grades III–IV, tumor sizes > 39 mm, T3/T4 stage, N1/N2 stage, M1 stage, and higher log odds of positive lymph nodes (LODDS) values exhibited poorer prognoses. Age, grade, tumor size, TNM stage, and LODDS were independent prognostic factors. The model containing N stage and LODDS outperformed the one relying solely on N stage as LN status indicator, resulting in a validated nomogram for accurately predicting OS in SRCC patients.ConclusionThe integration of LODDS, N stage, and other risk factors into a nomogram offered precise OS predictions, enhancing therapeutic decision-making and tailored follow-up management for colorectal SRCC patients.

Multiple primary tumors in patients with surgically treated pancreatic cancer: a SEER population-based study.

With improving survival after pancreatic cancer (PC) resection, questions emerge concerning risk and patterns of metachronous tumors. We aimed to determine the incidence of multiple primary cancers among postoperative PC survivors. Patients undergoing PC surgery from 1975 to 2020 were identified in the Surveillance, Epidemiology, and End Results (SEER) registry. Standardized incidence ratios (SIRs) compared observed-to-expected cancers based on U.S. population rates. Cumulative incidence of secondary tumors was analyzed with Cox regression and cancer-specific survival with Kaplan-Meier curves. Of 6,100 resected PC patients, 267 (4.38%) developed multiple cancers over 6.2 years median follow-up period. Subsequent malignancies showed a rising cumulative incidence extending beyond 5 years. Lung cancer was the predominant second primary in both males (n=36, SIR 1.87) and females (n=32, SIR 2.17). Prostate (n=33) and breast (n=25) cancers were also common. Risk varied by latency period and gender. Postoperative PC patients face a measurable risk for secondary cancers. Enhanced long-term surveillance has the potential to improve early detection and outcomes in this survivor population. Our data provides real-world evidence which could help inform surveillance guidelines in the future.

Nomograms predict survival in elderly women with triple-negative breast cancer: A SEER population-based study.

The effective treatment of breast cancer in elderly patients remains a major challenge. To construct a nomogram affecting the overall survival of triple-negative breast cancer (TNBC) and establish a survival risk prediction model. A total of 5317 TPBC patients with negative expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) who were diagnosed and received systematic treatment from 2010 to 2015 were collected from the American Cancer Surveillance, Epidemiology and End Results (SEER) database. They were randomly divided into training set (n= 3721) and validation set (n= 1596). Univariate and multivariate Cox regression analysis were used to identify prognostic features, and a nomogram was established to predict the probability of 1-year, 3-year and 5-year OS and BCSS. We used consistency index (C-index), calibration curve, area under the curve (AUC) and decision curve analysis (DCA) to evaluate the predictive performance and clinical utility of the nomogram. The C-indices of the nomograms for OS and BCSS in the training cohort were 0.797 and 0.825, respectively, whereas those in the validation cohort were 0.795 and 0.818, respectively. The receiver operating characteristic (ROC) curves had higher sensitivity at all specificity values as compared with the Tumor Node Metastasis (TNM) system. The calibration plot revealed a satisfactory relationship between survival rates and predicted outcomes in both the training and validation cohorts. DCA demonstrated that the nomogram had clinical utility when compared with the TNM staging system. This study provides information on population-based clinical characteristics and prognostic factors for patients with triple-negative breast cancer, and constructs a reliable and accurate prognostic nomogram.

Development and validation of prognostic models for small cell lung cancer patients with liver metastasis: a SEER population-based study

BackgroundThis study was to establish and validate prediction models to predict the cancer-specific survival (CSS) and overall survival (OS) of small-cell lung cancer (SCLC) patients with liver metastasis.MethodsIn the retrospective cohort study, SCLC patients with liver metastasis between 2010 and 2015 were retrospectively retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided into the training group and testing group (3: 1 ratio). The Cox proportional hazards model was used to determine the predictive factors for CSS and OS in SCLC with liver metastasis. The prediction models were conducted based on the predictive factors. The performances of the prediction models were evaluated by concordance indexes (C-index), and calibration plots. The clinical value of the models was evaluated by decision curve analysis (DCA).ResultsIn total, 8,587 patients were included, with 154 patients experiencing CSS and 154 patients experiencing OS. The median follow-up was 3 months. Age, gender, marital status, N stage, lung metastases, multiple metastases surgery of metastatic site, chemotherapy, and radiotherapy were independent predictive factors for the CSS and OS of SCLC patients with liver metastasis. The prediction models presented good performances of CSS and OS among patients with liver metastasis, with the C-index for CSS being 0.724, whereas the C-index for OS was 0.732, in the training set. The calibration curve showed a high degree of consistency between the actual and predicted CSS and OS. DCA suggested that the prediction models provided greater net clinical benefit to these patients.ConclusionOur prediction models showed good predictive performance for the CSS and OS among SCLC patients with liver metastasis. Our developed nomograms may help clinicians predict CSS and OS in SCLC patients with liver metastasis.

Development and validation of a nomogram for predicting the early death of anaplastic thyroid cancer: a SEER population-based study.

Anaplastic thyroid cancer (ATC) is a highly aggressive malignancy with dismal prognosis. This study aimed to identify the independent risk factors and construct a readily-to-use nomogram to predict the probability of early death in ATC patients. Patients diagnosed with ATC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in this study for model development and internal validation. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for early death of ATC. Nomograms for predicting the probability of all-cause early death (ACED) and cancer-specific early death (CSED) of ATC were subsequently developed. The performance of the nomograms was comprehensively evaluated and validated in an internal cohort. A total of 696 ATC patients were included in this study, of which 488 patients in the training cohort and 208 patients in the validation cohort. The univariate and multivariate logistic regression analyses identified five independent factors (tumor size, M stage, surgery, radiotherapy and chemotherapy) in the ACED model and six variables in the CSED (gender, tumor size, M stage, surgery, radiotherapy and chemotherapy) model for the establishment of the nomograms. Calibration curves and receiver operating characteristic (ROC) curves showed satisfactory efficacy and consistency both in the training (ACED: AUC values: 0.814 (0.776-0.852); CSED: 0.778 (0.736-0.820)) and validation sets (ACED: 0.762 (0.696-0.827); CSED: 0.745 (0.678-0.812)). In addition, the decision curve analysis (DCA) demonstrated the favorable potential of the two nomograms in clinical application. The two nomograms assist clinicians to identify risk factors and predict the early death probability among ATC patients, thus guide individualized treatment to improve the prognosis.

Incidence, survival, and prognostic factors for patients with gastrointestinal mixed neuroendocrine non-neuroendocrine neoplasms: a SEER population-based study.

Mixed neuroendocrine non-neuroendocrine neoplasms (MiNENs) are a group of rare tumors with limited research currently available. This study aimed to analyze the incidence, survival, and prognostic factors of gastrointestinal MiNENs. We included data from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2019. We compared the clinicopathologic characteristics and survival rates between MiNENs and neuroendocrine tumors (NETs), and calculated the incidence of MiNENs. We utilized univariate and multivariate Cox analysis to assess independent factors of prognosis and established a nomogram to predict 1-, 2-, and 3-year cancer-specific survival (CSS). Calibration and receiver operating characteristic (ROC) curves were drawn to validate the accuracy and reliability of the model. Decision curve analysis (DCA) was used to assess the clinical utility of the model. Patients with gastrointestinal MiNENs had a poorer prognosis than those with NETs. The overall incidence of gastrointestinal MiNENs has been increasing annually. Multivariate Cox regression analysis revealed that tumor size, lymph node metastasis, distant metastasis, and surgery were independent risk factors for CSS in MiNENs patients. Based on these risk factors, the 1-, 2-, and 3-year CSS nomogram model for MiNENs patients was established. Calibration, ROC, and DCA curves of the training and validation sets demonstrated that this model had good accuracy and clinical utility. Gastrointestinal MiNENs are rare tumors with an increasing incidence rate. The nomogram model is expected to be an effective tool for personalized prognosis prediction in MiNENs patients, which may benefit clinical decision-making.

Prognostic factors for competing risk in patients with AIDS-related Kaposi's sarcoma: A SEER population-based study.

Despite the improved survival of patients with AIDS and Kaposi's sarcoma (KS), competing events are a non-negligible issue affecting the survival of such patients. In this study, we explored the prognostic factors of KS-specific and non-KS-specific mortality in patients with AIDS-related KS (AIDS-KS), accounting for competing risk. We identified 17 103 patients with AIDS-KS aged 18-65 years between 1980 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) 18 registry database. Prognostic factors for KS-specific and non-KS-specific mortality were determined by the Fine and Grey proportional subdistribution hazard model. We built competing risk nomograms and assessed their predictive performance based on the identified prognostic factors. In total, 12 943 (75.68%) patients died, 1965 (15.50%) of whom died from competing events. The KS-specific mortality rate was 14 835 per 100 000 person-years, and the non-KS specific mortality rate was 2719 per 100 000 person-years. Specifically, age >44 years was associated with an 11% decrease in the subdistribution hazard of KS-specific mortality compared with age <43 years but a 50% increase in the subdistribution hazard of non-KS-specific mortality. Being male was associated with a 26% increase in the subdistribution hazard of KS-specific mortality compared with being female but a 32% decrease in the subdistribution hazard of non-KS-specific mortality. Notably, being in the antiretroviral therapy (ART) era consistently showed a decrease in the subdistribution hazard of both KS-specific and non-KS-specific mortality than being in the pre-ART era. Competing events commonly occurred among patients with AIDS-KS, which deserves further attention to improve the prognosis of these patients.

A practical nomogram and risk stratification system for predicting survival outcomes in neuroblastoma patients: a SEER population-based study

BackgroundNeuroblastoma (NB) is a childhood malignancy with marked heterogeneity, resulting in highly variable outcomes among patients. This study aims to establish a novel nomogram and risk stratification system to predict the overall survival (OS) for patients with NB.MethodsWe analyzed neuroblastoma patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. The nomogram was constructed using independent risk factors for OS, identified through univariate and multivariate Cox regression analyses. The accuracy of this nomogram was evaluated with the concordance index, receiver operating characteristic curve, calibration curve, and decision curve analysis. In addition, we developed a risk stratification system based on the total score of each patient in the nomogram.ResultsA total of 2185 patients were randomly assigned to the training group and the testing group. Six risk factors, including age, chemotherapy, brain metastases, primary site, tumor stage, and tumor size, were identified in the training group. Using these factors, a nomogram was constructed to predict 1-, 3-, and 5-year OS of NB patients. This model exhibited superior accuracy in the training and testing groups, exceeding traditional tumor stage prediction. Subgroup analysis suggested worse prognosis for retroperitoneal origin in the intermediate-risk group and adrenal gland origin in the high-risk group compared to other sites. Additionally, the prognosis for high-risk patients significantly improved after surgery. We also developed a web application to make the nomogram more user-friendly in clinical practices.ConclusionThis nomogram demonstrates excellent accuracy and reliability, offering more precise personalized prognostic predictions to clinical patients.

Prediction of distant organ metastasis and overall survival of lung cancer patients: a SEER population-based cohort study.

Distant organ metastasis is a common event in lung cancer (LC). However, the preferential metastatic pattern of different pathological types of LC and its effect on prognosis have not been comprehensively elucidated. This study aimed to explore the distant metastasis pattern and construct nomograms predicting the metastasis and survival of LC patients using the Surveillance, Epidemiology, and End Results (SEER) database. LC data were downloaded from the SEER database to conduct logistic regression and investigate risk factors for developing organ metastasis. A Cox regression analysis was conducted to investigate prognostic factors of LC. A Kaplan-Meier analysis was used to estimate overall survival outcomes. Nomograms were constructed to predict the probability of organ metastasis and the 1-, 3- and 5-year survival probability of LC patients. Receiver operating characteristic curves were used to evaluate the diagnostic accuracy of the nomograms. All statistical analyses were conducted within R software. The liver is the most common metastatic organ of small cell carcinoma. The brain is the most likely metastasis site of large cell carcinoma, and bone is the most likely metastasis site for squamous cell carcinoma and adenocarcinoma. Patients with triple metastases (brain-bone-liver) have the worst prognosis, and for nonsquamous carcinoma with single organ metastasis, liver metastases conferred the worst prognosis. Our nomograms based on clinical factors could predict the metastasis and prognosis of LC patients. Different pathological types of LC have different preferential metastatic sites. Our nomograms showed good performance in predicting distant metastasis and overall survival. These results will provide a reference for clinicians and contribute to clinical evaluations and individualized therapeutic strategies.

Clinical subtypes and survival outcomes in invasive breast cancer with Paget’s disease: A SEER population-based study.

e12564 Background: The objective of this study was to investigate the clinicopathological characteristics, especially subtypes and survival outcomes of Invasive breast cancer with Paget's disease. Methods: 4930 patients were identified using the histopathology codes from the International Classification of Disease for Oncology third edition (ICD-O-3), from 2000 to 2019 in the Surveillance, Epidemiology, and End Results (SEER) database. Excluding 787 patients whose ICD-O-3 and TNM stages did not match, there were 663 patients with '8540/3, Paget disease, mammary', 976 patients with ‘8543/3, Paget disease and intraductal carcinoma(DCIS)’ and 2540 patients with ‘8541/3, and ‘8541/3, Paget disease and infiltrating ductal carcinoma (IDC) of breast’. ER and PR status have been available since 1990, and HER2 status since 2010. Results: Among patients with IDC and Paget's disease, 24.6% were under the age of 50 and 2.7% were male, which was higher than the other two groups. Expressions of ER and PR were higher than both groups, and HER2 expression was lower. The ratio of HR-/HER2+ subtype was also lower than the other two groups at 29.6%. ER+, Paget 43.7%, DCIS with Paget 36.4%, IDC with Paget 53.6%. PR+ Paget 21.6%, DCIS with Paget 21.7%, IDC with Paget 40.1%. HER2+ Paget 69.2%, DCIS with Paget 83.1 %, IDC with Paget 58.3%. HR-/HER2+subtype, Paget 40.7%, DCIS with Paget 49.2%, IDC with Paget 29.6%. As a result of survival analysis in patients with IDC and Paget's disease, the HR-/HER2+ subtype had shown the best prognosis in Overall Survival (OS) analysis (5year OS, HR+/HER2- 70.8%, HR+/HER2+ 74.9%, HR-/HER2- 63.7%, HR-/HER2+ 80.7% P=0.010) In the BCSS analysis, the 5-year BCSS was the best at 87.0% in the HR-HER2+ subtype, but there was no statistically significant difference. Conclusions: In IDC with Paget's disease, the distribution of subtypes is different from that of DCIS with Paget's, and HER2 expression can be considered as a favor prognostic factor. It is considered necessary to study the relationship between the loss of HER2 overexpression and invasion/progression in invasive breast cancer with Paget's disease.

Identification of Populations at Risk for "Choosing Un-Wisely": A SEER Population-Based Study.

Since 2016, the Choosing Wisely campaign has recommended against routine axillary surgery in elderly patients with early stage, hormone receptor positive (ER+) breast cancer. The objective was to evaluate factors associated with axillary surgery in breast cancer patients meeting criteria for sentinel lymph node biopsy (SLNB) omission and identify potential disparities. Female patients age ≥70years with cT1-2N0M0, ER+, HER2-negative breast cancer diagnosed after publication of the Choosing Wisely recommendations, between 2016 and 2019, were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Patient demographics and tumor characteristics associated with axillary surgery were analyzed. Of the 31756 patients meeting omission criteria, 25771 (81.2%) underwent axillary surgery. Hispanic ethnicity, median household income between $35,000 and $70,000, treatment in rural areas, poor differentiation, lobular and mixed lobular with ductal histology, T2 tumors, radiation therapy, and systemic therapy were factors associated with receiving axillary surgery on multivariable analysis. In the axillary surgery cohort, a median of 2 (IQR = 2) nodes were examined and 529 (2.1%) patients were found to have 1 or more positive lymph nodes. Among elderly patients meeting Choosing Wisely criteria for SLNB omission, particular racial, ethnic, socioeconomic, and geographic populations may be at increased risk for potential over treatment. Identification of these factors provides specific opportunities for education and implementation of de-escalation of unnecessary procedures.

Development and validation of a clinical survival model for young-onset colorectal cancer with synchronous liver-only metastases: a SEER population-based study and external validation.

The morbidity and mortality of young-onset colorectal cancer (YO-CRC) patients have been increasing in recent years. Moreover, YO-CRC patients with synchronous liver-only metastases (YO-CRCSLM) have various survival outcomes. Therefore, the purpose of this study was to construct and validate a prognostic nomogram for patients with YO-CRCSLM. The YO-CRCSLM patients were rigorously screened from the Surveillance, Epidemiology, and End Results (SEER) database in January 2010 and December 2018 and then assigned to a training and validation cohort randomly (1488 and 639 patients, respectively). Moreover, the 122 YO-CRCSLM patients who were enrolled in The First Affiliated Hospital of Nanchang University were served as a testing cohort. The variables were selected using the multivariable Cox model based on the training cohort and then developed a nomogram. The validation and testing cohort were used to validate the model's predictive accuracy. The calibration plots were used to determine the Nomogram's discriminative capabilities and precision, and the decision analysis (DCA) was performed to evaluate the Nomogram's net benefit. Finally, the Kaplan-Meier survival analyses were performed for the stratified patients based on total nomogram scores classified by the X-tile software. The Nomogram was constructed including ten variables: marital status, primary site, grade, metastatic lymph nodes ratio (LNR), T stage, N stage, carcinoembryonic antigen (CEA), Surgery, and chemotherapy. The Nomogram performed admirably in the validation and testing group according to the calibration curves. The DCA analyses showed good clinical utility values. Low-risk patients (score<234) had significantly better survival outcomes than middle-risk (234-318) and high-risk (>318) patients (P < 0.001). A nomogram predicting the survival outcomes for patients with YO-CRCSLM was developed. In addition to facilitating personalized survival prediction, this nomogram may assist in developing clinical treatment strategies for patients with YO-CRCSLM who are undergoing treatment.

Nomogram for predicting preoperative axillary lymph node status in male breast carcinoma: a SEER population-based study.

Sentinel lymph node biopsy (SLNB) has been recommended as a replacement for axillary lymph node dissection (ALND) in male breast carcinoma (MBC) with clinical axillary lymph node-negative (ALN-negative) as in the case of female. However, the morbidity after SLNB may also have short-term or long-term complications. To avoid unnecessary surgery, building a model which is able to assess the risk of lymph node metastasis is vitally significant. A retrospective review of the clinical and pathology data were carried out for patients diagnosed with MBC between 2010 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database. The cohort was divided into training and validation cohorts. A logistic regression model was used to construct the nomogram in the training cohort and then verified in the validation cohort. The receiver operating characteristic (ROC) curve, C-index, and calibration were used to evaluate the predictive ability of the nomogram. Overall, 2,610 patients diagnosed with MBC were included in the study, of which 1,740 were in the training cohort and 870 were in the validation cohort. Logistic regression analysis indicated age at diagnosis, tumor location, tumor stage, pathological type, and histologic grade, were significantly related to axillary lymph node metastasis (ALNM). The area under the curve (AUC) of the nomogram was 0.846 (95% CI: 0.825-0.867) and C-index was 0.848 (95% CI: 0.807-0.889), demonstrating a notable prediction performance. The calibration curve for the nomogram was plotted and the slope was close to 1. The prognostic value of the nomogram was further validated in the validation cohort, with an AUC of 0.848 (95% CI: 0.819-0.877). A nomogram to predict ALNM was successfully established, especially for those who were of advanced age at diagnosis, had small tumor size, displayed low malignancy, and showed clinical ALN-negative, to avoid unnecessary axillary operation. The quality of life for patients is enhanced without conceding the overall survival rate.

Survival Nomogram for Patients With Locally Advanced Breast Cancer Undergoing Immediate Breast Reconstruction: A SEER Population-Based Study

Introduction/BackgroundThis study aimed to construct a nomogram to provide prognostic references for patients with locally advanced breast cancer (LABC) to receive immediate breast reconstruction (IBR). Materials and MethodsAll data were obtained from the Surveillance, Epidemiology and End Results (SEER) database. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and best subset regression (BSR), separately followed by backward stepwise multivariable Cox, were used to construct the nomogram. Risk stratification was established after validation. ResultsA total of 6,285 patients were enrolled to generate the training group (n = 3,466) and the test group (n = 2,819) by geographical split. Age, marital status, grade, T staging, N staging, radiotherapy, chemotherapy, estrogen receptor status (ER), progesterone receptor status (PR) and human epidermal growth factor receptor type 2 status (HER2) were used to fit the nomogram. The overall Harrell's concordance index (C-index) was 0.772 in the training group and 0.762 in the test group. The area under the receiver operator characteristic curves (AUC) at 3-year and 5-year were respectively 0.824 and 0.720 in the training group, 0.792 and 0.733 in the test group. The calibration curves showed great consistency in both groups. A dynamic nomogram (https://dcpanfromsh.shinyapps.io/NomforLABCafterIBR/) was developed. ConclusionA nomogram was developed and validated that predicts prognosis more accurately than the AJCC 7th stage and can be used as a reference for decision-making in LABC patients receiving IBR.

Validation of the Prognostic Role for Surgical Treatment in Stage II Intrahepatic Cholangiocarcinoma: A SEER Population-Based Study.

Background: This study aimed to determine the role of surgical treatment in patients with stage II intrahepatic cholangiocarcinoma (iCCA). Methods: Data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We divided stage II iCCAs into solitary tumors with vascular invasion (T2sN0M0) and multiple tumors with/without vascular invasion (T2mN0M0) according to the criteria of AJCC v.8. The Kaplan−Meier method and log-rank test were used to evaluate differences in overall survival (OS). We performed two propensity score-matching analyses with (PSM2) or without (PSM1) surgical treatment. Results: 667 and 778 iCCA patients with stage II and IIIB were recruited. After PSM2, there was no survival difference in stage II iCCA patients in hypothetical conditions with similar surgical proportions (p = 0.079). However, OS was significantly worse in patients with T2mN0M0 than T2sN0M0 when the actual surgical proportion existed after PSM1 (p < 0.001). OS was similar between T2mN0M0 and IIIB regardless of whether PSM1 (p = 0.907) or PSM2 (p = 0.699) was performed. The surgical treatment was verified to associate with prognosis. Conclusions: The survival benefit by surgical treatment was existed in Stage II but not in Stage IIIB iCCA patients. The OS for T2mN0M0 will approach that of T2sN0M0 if the surgical proportion is gradually increased.

Competitive Risk Model Nomogram to Predict Prognosis in Patients Aged Over 65 Years with nonmetastatic Cervical Cancer: A SEER Population-Based Study.

Objective: The prognostic factors for elderly patients with cervical cancer differ from those of younger patients. Competitive risk events could cause biases in the Cox proportional hazards (PH) model. This study aimed to construct a competitive risk model (CRM) nomogram for patients aged > 65 years with nonmetastatic cervical cancer. Methods: We retrospectively analyzed data extracted from the Surveillance, Epidemiology, and End Results (SEER) database and a total of 1856 patients from 18 cancer registries across the United States diagnosed between 2010 and 2015 were included. Kaplan-Meier analysis and log-rank tests were used to compare intergroup survival. Univariate and multivariate Cox proportional regression analyses were performed to identify independent prognostic factors. The cumulative incidence function (CIF) and Fine and Gray's test were used to determine the impact of competitive risk events on prognosis. The CRM nomogram was internally and externally validated using time-dependent receiver operator characteristic (ROC) curve (time-AUC), Brier scores, Harrell's concordance index (C-index), calibration curve, and decision curve analysis (DCA). Results: Analyses revealed that histology, age, the International Federation of Gynaecologists and Obstetricians (FIGO) stage, number of in situ malignancies, chemotherapy, radiotherapy (RT), and surgery were independent prognostic factors. The CRM nomogram accurately predicted 1-year, 3-year, and 5-year disease-specific survival (DSS). The C-indexes and Brier scores of the CRM nomogram were 0.641 and 0.094, respectively, at the 1-year cut-off in the training set. The time-AUC of the CRM nomogram at the 1-year, 3-year, and 5-year intervals in the training set were 77.6%, 77.3%, and 74.5%, respectively. The calibration curve demonstrated a favorable concordance. DCA suggested that the nomogram had a good net benefit. Therefore, the Cox model underestimated the weight of risk factors compared to CRM. Conclusions: This study presents the CRM nomogram to predict DSS in patients aged > 65 years with nonmetastatic cervical cancer. It can help clinicians implement more accurate personalized diagnostic and treatment modalities for elderly patients with cervical cancer.

Comparative analysis of the prognosis of external beam radiation therapy (EBRT) and EBRT plus brachytherapy for glioblastoma multiforme: a SEER population-based study

ObjectiveRadiotherapy is one of the effective ways to treat glioblastoma multiforme (GBM). We aimed to explore the prognostic difference between external beam radiotherapy (EBRT) and EBRT combined with brachytherapy (EBRT + BT).MethodsThe GBM patients from the Surveillance, Epidemiology, and End Results (SEER) database were divided into two cohorts: the EBRT cohort and the EBRT + BT cohort. Kaplan–Meier (KM) analysis and Cox proportional hazards regression were used to determine the underlying risk factors for overall survival (OS) and disease-specific survival (DSS). And the competing risk model and propensity score matching (PSM) was adopted to eliminate potential biases. We also conducted subgroup analyses and interaction tests as well.ResultsThere was a total of 41,010 eligible GBM patients. The median OS (15 months) and DSS (17 months) of the EBRT + BT cohort were significantly longer than that of the EBRT cohort (OS = 11 months, DSS = 12 months). After using the competing risk model and PSM, we found that only advanced age was the independent risk factor, while only EBRT + BT was the independent protective factor (HR = 0.84, 95%CI [0.74,0.96], p = 0.01). EBRT had universal effects in the treatment of GBM, and EBRT + BT had a more pronounced protective effect in the subgroups of males (HR = 0.81, 95%CI [0.68,0.97], p = 0.02) and local excision (HR = 0.82, 95%CI [0.34,0.95], p = 0.01).ConclusionsThe therapeutical effect of EBRT + BT treatment is better than that of EBRT alone, especially in male patients or patients who have undergone local resection. Our findings may provide novel evidence to develop a better radiotherapy strategy for GBM patients.

Development and validation of nomograms for predicting overall survival and cancer specific survival in locally advanced breast cancer patients: A SEER population-based study.

BackgroundFor patients with locally advanced breast cancer (LABC), conventional TNM staging is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making.MethodsA retrospective analysis of 22,842 LABC patients was performed from 2010 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. An additional cohort of 200 patients from the Binzhou Medical University Hospital (BMUH) was analyzed. The least absolute shrinkage and selection operator (LASSO) regression was used to screen for variables. The identified variables were used to build a survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).ResultsThe LASSO analysis identified 9 variables in patients with LABC, including age, marital status, Grade, histological type, T-stage, N-stage, surgery, radiotherapy, and chemotherapy. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.767 [95% confidence intervals (95% CI): 0.751–0.775], cancer specific survival (CSS) was 0.765 (95% CI: 0.756–0.774). In the external validation cohort, the C-index of the nomogram in predicting the OS was 0.858 (95% CI: 0.812–0.904), the CSS was 0.866 (95% CI: 0.817–0.915). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1, 3, and 5-year OS were 0.836 (95% CI: 0.821–0.851), 0.769 (95% CI: 0.759–0.780), and 0.750 (95% CI: 0.738–0.762), respectively. The AUC values for prediction of the 1, 3, and 5-year CSS were 0.829 (95% CI: 0.811–0.847), 0.769 (95% CI: 0.757–0.780), and 0.745 (95% CI: 0.732–0.758), respectively. Results of the C-index, ROC curve, and DCA demonstrated that the nomogram was more accurate in predicting the OS and CSS of patients compared with conventional TNM staging.ConclusionTwo prediction models were developed and validated in this study which provided more accurate prediction of the OS and CSS in LABC patients than the TNM staging. The constructed models can be used for predicting survival outcomes and guide treatment plans for LABC patients.