Distinct characteristics of distant metastasis in early-onset gastric cancer patients compared to late-onset patients: An observational study

Presently, there is limited understanding of the features of distant metastasis in early-onset gastric cancer (GC). To explore these disparities, a retrospective study utilizing the Surveillance, Epidemiology, and End Results (SEER) database was undertaken. The SEER database was utilized to extract patient data, and multivariate logistic regression analysis was employed to identify the risk factors associated with distant metastasis and liver metastasis. Propensity score matching (PSM) was used to compare the occurrence of liver metastasis among patients based on their age at diagnosis. The study included 2684 early-onset GC patients and 33,289 late-onset GC patients. Preliminary data analysis indicated that early-onset GC patients exhibited more aggressive characteristics such as poor cell differentiation, advanced T stage, and a higher incidence of distant metastasis, excluding liver metastasis. Multivariate logistic regression analysis identified younger age as an independent risk factor for distant metastasis, along with T stage, lymph node metastasis (LNM), and tumor size (>3 cm). Another regression analysis revealed that younger age, diffuse type, and female gender were protective factors against liver metastasis. Through PSM, 3276 early-onset GC patients were matched with an equal number of late-onset GC patients, revealing that patients with early-onset GC had fewer instances of liver metastasis but a higher prevalence of distant metastasis. Our findings suggest that early-onset serves as a protective factor against liver metastasis in GC, while it poses a risk for distant metastasis, likely influenced by the increased prevalence of diffuse-type GC in early-onset patients.

A practical nomogram for predicting early death in elderly small cell lung cancer patients: A SEER-based study

This study aimed to identify risk factors for early death in elderly small cell lung cancer (SCLC) patients and develop nomogram prediction models for all-cause and cancer-specific early death to improve patient management. Data of elderly patients diagnosed with SCLC were extracted from the SEER database, then randomly divided into training and validation cohorts. Univariate and stepwise multivariable Logistic regression analyses were performed on the training cohort to identify independent risk factors for early death in these patients. Nomograms were developed based on these factors to predict the overall risk of early death. The efficacy of the nomograms was validated using various methods, including ROC analysis, calibration curves, DCA, NRI, and IDI. Among 2077 elderly SCLC patients, 773 died within 3 months, 713 due to cancer-specific causes. Older age, higher AJCC staging, brain metastases, and lack of surgery, chemotherapy, or radiotherapy increase the risk of all-cause early death, while higher AJCC staging, brain metastases, lung metastases, and lack of surgery, chemotherapy, or radiotherapy increase the risk of cancer-specific death (P < .05). These identified factors were used to construct 2 nomograms to predict the risk of early death. The ROC indicated that the nomograms performed well in predicting both all-cause early death (AUC = 0.823 in the training cohort and AUC = 0.843 in the validation cohort) and cancer-specific early death (AUC = 0.814 in the training cohort and AUC = 0.841 in the validation cohort). The results of calibration curves, DCAs, NRI and IDI also showed that the 2 sets of nomograms had good predictive power and clinical utility and were superior to the commonly used TNM staging system. The nomogram prediction models constructed in this study can effectively assist clinicians in predicting the risk of early death in elderly SCLC patients, and can also help physicians screen patients at higher risk and develop personalized treatment plans for them.

Establishment and validation of nomograms to predict the overall survival and cancer-specific survival for non-metastatic bladder cancer patients: A large population-based cohort study and external validation

This study aimed to develop nomograms to accurately predict the overall survival (OS) and cancer-specific survival (CSS) of non-metastatic bladder cancer (BC) patients. Clinicopathological information of 260,412 non-metastatic BC patients was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2020. LASSO method and Cox proportional hazard regression analysis were utilized to discover the independent risk factors, which were used to develop nomograms. The accuracy and discrimination of models were tested by the consistency index (C-index), the area under the subject operating characteristic curve (AUC) and the calibration curve. Decision curve analysis (DCA) was used to test the clinical value of nomograms compared with the TNM staging system. Nomograms predicting OS and CSS were constructed after identifying independent prognostic factors. The C-index of the training, internal validation and external validation cohort for OS was 0.722 (95%CI: 0.720-0.724), 0.723 (95%CI: 0.721-0.725) and 0.744 (95%CI: 0.677-0.811). The C-index of the training, internal validation and external validation cohort for CSS was 0.794 (95%CI: 0.792-0.796), 0.793 (95%CI: 0.789-0.797) and 0.879 (95%CI: 0.814-0.944). The AUC and the calibration curves showed good accuracy and discriminability. The DCA showed favorable clinical potential value of nomograms. Kaplan-Meier curve and log-rank test uncovered statistically significance survival difference between high- and low-risk groups. We developed nomograms to predict OS and CSS for non-metastatic BC patients. The models have been internally and externally validated with accuracy and discrimination and can assist clinicians to make better clinical decisions.

Primary tumor resection improves prognosis of unresectable carcinomas of the transverse colon including flexures with pulmonary metastasis: a cohort study

PURPOSE

Studies of unresectable colorectal cancer pulmonary metastasis (CRPM) have rarely analyzed patient prognosis from the perspective of colonic subsites. This study aimed to evaluate the effects of primary tumor resection (PTR) on the prognosis of patients with unresectable pulmonary metastases of transverse colon cancer pulmonary metastasis (UTCPM), hepatic flexure cancer pulmonary metastasis (UHFPM), and splenic flexure cancer pulmonary metastasis (USFPM).

METHODS

Patients were identified from the Surveillance, Epidemiology, and End Results database between 2000 and 2018. The Cox proportional hazards regression models were used to identify prognostic factors of overall survival (OS) and cause-specific survival (CSS). The Kaplan-Meier analyses and log-rank tests were conducted to assess the effectiveness of PTR on survival.

RESULTS

This study included 1294 patients: 419 with UHFPM, 636 with UTCPM, and 239 with USFPM. Survival analysis for OS and CSS in the PTR groups, showed that there were no statistical differences in the the UHFPM, UTCPM, and USFPM patients. There were statistical differences in the UHFPM, UTCPM, and USFPM patients for OS and CSS. Three non-PTR subgroups showed significant statistical differences for OS and CSS.

CONCLUSION

We confirmed the different survival rates of patients with UTCPM, UHFPM, and USFPM and proved for the first time that PTR could provide survival benefits for patients with unresectable CRPM from the perspective of the colonic subsites of the transverse colon, hepatic flexure, and splenic flexure.

Epidemiology and survival of patients with spinal meningiomas: a large retrospective cohort study

INTRODUCTION

Spinal meningiomas (SMs) are relatively rare central nervous system tumors that usually trigger neurological symptoms. The prevalence of SMs is increasing with the aging of the global population. This study aimed to perform a systematic epidemiologic and survival prognostic analysis of SMs to evaluate their public health impact and to develop a novel method to estimate the overall survival at 3-year, 5-year, and 10-year in patients with SMs.

METHODS

Five thousand one hundred fifty eight patients with SMs were recruited from the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2019. Firstly, descriptive analysis was performed on the epidemiology of SMs. Secondly, these individuals were randomly allocated to the training and validation sets in a ratio of 7:3. Kaplan-Meier method and Cox regression analysis were utilized in the training set to identify independent prognostic factors and to construct a nomogram for survival prognosis. Subsequently, the discriminative power, predictive performance, and clinical utility of the nomogram were evaluated by receiver operating characteristic curve and decision curve analysis. Finally, a mortality risk stratification system and a web-based dynamic nomogram were constructed to quantify the risk of mortality in patients with SMs.

RESULTS

The annual age-adjusted incidence rates of SMs increased steadily since 2004, reaching a rate of 0.40 cases per 100 000 population in 2019, with a female-to-male ratio of ~4:1. The age groups of 50-59, 60-69, and 70-79 years old were the most prevalent ages for SMs, accounting for 19.08, 24.93, and 23.32%, respectively. In addition, seven independent prognostic factors were identified to establish a prognostic nomogram for patients with SMs. The decision curve analysis and receiver operating characteristic curve indicated that the nomogram had high clinical utility and favorable accuracy. Moreover, the mortality risk stratification system effectively divided patients into low-risk, middle-risk, and high-risk subgroups.

CONCLUSIONS

SMs are relatively rare benign spinal tumors prevalent in the white elderly female population. Clinicians could use the nomogram to personalize the prediction of the overall survival probability of patients with SMs, categorize these patients into different mortality risk subgroups, and develop personalized decision-making plans. Moreover, the web-based dynamic nomogram could help to further promote clinical application and assist clinicians in providing personalized counseling, timely monitoring, and clinical assessment for patients.

Clinical Characteristics and Prognostic Factors of Endometrial Cancer Patients With Liver Metastasis: A Surveillance, Epidemiology, and End Results Database (SEER)-Based Study of 1,034 Women

Background There are several patterns of metastatic spread from endometrial cancer (EC). Although studies have been conducted to study the EC population with distant metastasis in the bone and lungs, there is still a lack of studies on liver metastasis. This study aims to evaluate and assess the clinical features and prognostic factors of EC patients with liver metastasis. Methodology We conducted a retrospective cohort study adhering to the guidelines for reporting observational research. We utilized the Surveillance, Epidemiology, and End Results database to gather data on female patients diagnosed with EC and reported liver metastasis. We estimated survival curves using the Kaplan-Meier method and evaluated differences in survival using the log-rank test. We also conducted univariable and multivariable Cox proportional hazards regression analyses to determine the hazard ratios with 95% confidence intervals for overall survival (OS) and identify factors that impact survival. Results We analyzed data from 1,034 EC patients with liver metastasis. Median OS after liver metastasis was six months, and cancer-specific survival was seven months. Univariate Cox regression analysis revealed several factors associated with decreased OS in EC patients. These included age (≥60 years), non-endometrioid and sarcoma histological subtypes, absence of surgery, no chemotherapy, and the presence of distant metastasis to the lung, brain, and bone. Conversely, married marital status and white race were linked to a better prognosis. Subsequent multivariate Cox regression analysis identified age (≥60 years), non-endometrioid histological subtype, absence of surgery, no chemotherapy, and the presence of distant metastasis to lung, brain, and bone remaining as independent risk factors for decreased OS. In contrast, the white race still emerged as an independent prognostic factor for better OS. Conclusions Various risk factors, such as age, race, lung, bone, or brain metastasis, as well as chemotherapy and surgery, may influence the prognosis of individuals with primary EC liver metastases.

Construction and validation of a prognostic nomogram for ductal adenocarcinoma of the prostate: A population-based study

This study aimed to establish and validate a nomogram for ductal adenocarcinoma of the prostate (DAC) to accurately predict the prognosis of DAC patients. The data of 834 patients with confirmed DAC were obtained from the Surveillance, Epidemiology, and End Results database. The cases were randomly assigned to the training and internal validation cohorts. Data from patients attending our institution as an external validation cohort (n = 35). Nomogram and web-based dynamic nomogram were constructed based on Cox regression analysis, and their prediction accuracy was evaluated by concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis. Multivariate analyses identified age, T-stage, N-stage, M-stage, surgery, lymph node dissection, Gleason score, and PSA as independent prognostic factors for overall survival. The C-index and calibration curves demonstrate the good discriminative performance of the prediction model. The area under the curve further confirmed the accuracy of the nomogram in predicting survival. In addition, the area under the curve and decision curve analysis were better than the 7th tumor-node-metastasis staging system. The Kaplan-Meier curves of the nomogram-based risk groups showed significant differences (P < .001). We constructed and validated the first nomogram to predict patients with DAC.

Clinical features and demographic characteristics of gestational trophoblastic neoplasia: Single center experience and the SEER database

The aim of this study was to analyze the clinical features and demographic characteristics of gestational trophoblastic neoplasia (GTN) patients, specifically choriocarcinoma (CC), placental site trophoblastic tumour (PSTT), and epithelioid trophoblastic tumor (ETT). We utilized data from a local hospital and the SEER database, as well as survival outcomes of CC in SEER database. Additionally, we used multiple risk factors to create a prognostic nomogram model for CC patients. The study included GTN patients from the SEER database between 1975 and 2016 as well as those from the First Affiliated Hospital of Xi 'an Jiaotong University between January 2005 and May 2022. Related factors of patients were compared using the chi-square (χ2) or Fisher's exact test. For assessing overall survival we employed the Kaplan-Meier method and log-rank test. To construct the nomogram, we used Cox regression. Statistically significant differences were found between CC and PSTT/ETT patients in terms of surgery in local hospital, as well as age and year of diagnosis in the SEER database. Moreover, significant differences were observed between low and high (HR) /ultra-high risk (UHR) groups regarding FIGO stage, surgery and chief complaint at the local hospital, and FIGO stage, surgery and unemployment in the SEER database. The Cox regression analysis confirmed that age, race, surgery, marital status, FIGO stage, and unemployment were correlated with CC prognosis. Furthermore, the analysis showed that patients aged 40 years or older and those with FIGO Ⅲ/Ⅳ were independent prognostic factors of CC. The study indicates that atypical symptoms or signs may be the main reasons for HR /UHR patients to seek medical treatment. Therefore, providing multidisciplinary care is recommended for CC patients experiencing psychological distress due to unfavorable marital status or unemployment.

Demographic characteristics and prognosis of HHV8-positive diffuse large B-cell lymphoma, not otherwise specified: Insights from a population-based study with a 10-year follow-up

HHV8-positive diffuse large B-cell lymphoma, not otherwise specified (HDN) is a subtype of lymphoma that usually arises in association with HHV8-positive multicentric Castleman disease. However, the epidemiology, treatment patterns, and survival outcomes of HDN are poorly understood. A retrospective analysis was performed for 67 patients with HDN diagnosed from 2011 to 2020 using the SEER database. The demographic characteristics, treatment modalities, and survival outcomes of HDN patients were evaluated. Kaplan-Meier analysis and Cox regression analysis were employed to identify prognostic factors for overall survival (OS) and disease-specific survival (DSS). The age-adjusted incidence rate of HDN was 0.010 per 100,000 person-years. The median age at diagnosis was 51.8 years with male predominance. The primary site distribution was mainly nodal (79.1%), while the extranodal sites were rarely involved (20.9%). The majority of patients were white (65.7%). Only 3.0% of patients received radiotherapy, while 55.2% received chemotherapy. The 1-year, 3-year, and 5-year OS was 67.4%, 65.6%, 58.4%, and 56.3%, respectively, and the corresponding DSS was 73.1%, 73.1%, and 67.8%, respectively. The diagnosis year group of 2016-2020 had a significantly worse OS than the diagnosis year group of 2011-2015 (P = .040), but not for DSS (P = .074). No significant survival improvement was observed in patients underwent chemotherapy. Age and marital status were independent prognostic factors for OS, and age was an independent prognostic factor for DSS. In conclusion, HDN is a rare and aggressive disease, our study provides a comprehensive overview of the epidemiology, treatment patterns and survival outcomes of HDN patients for the first time. We revealed that older age and marital status of single were associated with worse survival of HDN, while chemotherapy was not associated with improved survival outcomes in HDN patients.

Comparison of survival between diffuse type and intestinal type early-onset gastric cancer patients: A large population-based study

Currently, little knowledge about the survival of early-onset gastric cancer and little evidence about the difference of survival based on Lauren type has been reported. In order to investigate the difference, we conducted a retrospective study using the Surveillance, Epidemiology, and End Results (SEER) database and compared it comprehensively. SEER database was used to extracted patients and multiple imputation was utilized to fill blank data. Multivariate cox regression analysis and competing risk model were used to identify the risk factors of survival. K-M survival curve and propensity score matching (PSM) was applied to compare the difference of survival of patients based on Lauren type. Totally, we extracted 3932 EOGC patients including 2086 diffused type and 1846 intestinal type. K-M survival curve showed patients aged 20 to 29 had worse survival compared to patients aged at 30 to 45 years. The survival of EOGC patients would be greatly improved after surgery. Multivariate cox regression analysis revealed diffused type was an independent risk factor, as well as T stage, lymph node metastasis, tumor size (>5 cm) and metastasis, while surgery treatment and examined lymph nodes were protective factors. Multivariate competing risk regression model also showed diffused type was risk factor. We performed PSM by matching 1433 diffused EOGC with 1433 intestinal EOGC patients, finding patients with diffused type had a poorer survival. our results revealed that compared to diffused type EOGC, intestinal type was characterized by a better survival. EOGC should be attached more attention by clinicians.

Development and validation of a nomogram to predict overall survival for cervical adenocarcinoma: A population-based study

This study aimed to develop and validate a nomogram for predicting the overall survival of cervical adenocarcinoma (CAC) patients using a large database comprising patients with different ethnicities. We enrolled primary CAC cases with complete clinicopathological and survival data from the Surveillance, Epidemiology, and End Results program during 2004 to 2015. For training set samples, this work applied the Cox regression model to obtain factors independently associated with patient prognosis, which could be incorporated in constructing the nomogram. Altogether 3096 qualified cases were enrolled, their survival ranged from 0 to 155 (median, 45.5) months. As revealed by multivariate regression, age, marital status, tumor size, grade, International Federation of Gynecology and Obstetrics (FIGO) classification, pelvic lymph node metastasis, surgery, and chemotherapy served as the factors to independently predict CAC (all P < .05). We later incorporated these factors for constructing the nomogram. According to the concordance index determined, this nomogram had superior discrimination over FIGO classification system (all P < .001). Based on calibration plot, the predicted value was consistent with actual measurement. As revealed by time-independent area under the curves, our constructed nomogram had superior 5-year overall survival over FIGO system. Additionally, according to decision curve analysis, our constructed nomogram showed high clinical usefulness as well as favorable discrimination. Our constructed nomogram attains favorable performances, indicating that it may be applied in predicting survival for CAC patients.

Prognostic factors of sarcomas occurring in bone and joint: A SEER based study

To clarify the epidemiology, treatment, and prognosis of sarcomas occurring in the bones and joints. The surveillance, epidemiology, and end results (SEER) 18 registries, comprising sarcoma diagnoses made between 2008 and 2014, were queried for sarcomas arising in bones or joints. Kaplan-Meier analysis, multivariate logistic regression analysis, Cox proportional hazards model, and nomograms were used to identify prognostic factors. 2794 patients aged from 1 to 99 (55.8% male) with microscopically confirmed diagnosed as sarcomas (including osteosarcoma, chondrosarcoma, Ewing sarcoma, and soft tissue sarcomas) which primary site limited to bone and joint were identified. Eight independent factors, including age, race, sex, tumor site, histology, pathology grade, tumor size, and total number of malignant tumors (TNOMT), were associated with tumor metastasis. Nine independent prognostic factors, including age (>=60 year, hazard ratio [HR] = 4.145, 95% confidence interval [CI], P < .001), sex (female, HR = 0.814, 95%CI, P = .007), tumor site (spine, HR = 2.527, 95%CI, P < .001), histology, pathology grade (undifferentiated, HR = 5.816, 95%CI, P < .001), tumor size (>=20 cm, HR = 3.043, 95%CI, P < .001), tumor extent (distant, HR = 4.145, 95%CI, P < .001), surgery (no performed, HR = 2.436, 95%CI, P < .001), and TNOMT (1, HR = 0.679, 95%CI, P < .001, were identified and incorporated to construct a nomogram for 2- and 5-year overall survival (OS). The calibration curve for the probability of survival showed good agreement between prediction by the nomogram and actual observation. The C-index of the nomogram for survival prediction was 0.814. Patients who received chemotherapy had a significantly decreased risk of death only for Ewing sarcoma, poorly differentiated tumors, undifferentiated tumors, and distant tumor invasion (P < .05). However, radiotherapy did not show significant differences in OS. This study presents population-based estimates of prognosis for patients with bone sarcomas and demonstrates the impact of age, race, sex, tumor site, histology, pathology grade, tumor size, tumor extent, surgery, radiotherapy, chemotherapy, and the TNOMT on OS. Moreover, the nomogram resulted in a more accurate prognostic prediction. However, in our study, radiotherapy showed no survival benefit, perhaps because detailed data on treatment factors were unavailable and which may have influenced the results.

Development and validation of prognostic nomogram for elderly patients with clear cell renal cell carcinoma based on the SEER database

This study sought to establish nomogram models of overall survival (OS) in patients with elderly clear cell renal cell carcinoma (ECCRCC). The Surveillance, Epidemiology, and End Results database provided data of the ECCRCC-afflicted patients diagnosed during the period from 2010 to 2015. This data was subsequently segregated into the training and validation sets randomly in a 7:3 ratio. The calibration curves, the receiver operating characteristic curves, the decision curve analysis and the Concordance index (C-index) were applied for the model evaluation. 9201 eligible cases from 2010 to 2015 were extracted; 6441 were included in the training cohort and 2760 in the validation cohort. The C-index for the training and validation sets were 0.710 and 0.709, respectively. The receiver operating characteristic and decision curve analysis curves demonstrated that nomograms outperformed the AJCC stage in predictive performance. Moreover, the nomogram was found to match closely with the actual observation, as indicated by the calibration plots. To make predictions with regard to the survival of the ECCRCC-afflicted individuals, and as a guide for treatment, the new nomogram could be used.

A web-based nomogram to predict overall survival for postresection leiomyosarcoma patients with lung metastasis

To investigate the overall survival of post-resection leiomyosarcoma (LMS) patients with lung metastasis, data of post-resection LMS patients with lung metastasis between 2010 and 2016 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The clinical characteristics and survival data for post-resection LMS patients with lung metastasis at Tianjin Medical University Cancer Hospital & Institute (TJMUCH) between October 2010 and July 2018 were collected. Patients derived from the SEER database and TJMUCH were divided into training and validation cohorts, respectively. Univariate and multivariate Cox regression analyses were performed and a nomogram was established. The area under the curve (AUC) and the calibration curve were used to evaluate the nomogram. A web-based nomogram was developed based on the established nomogram. Eventually, 226 patients from the SEER database who were diagnosed with LMS and underwent primary lesion resection combined with lung metastasis were enrolled in the training cohort, and 17 patients from TJMUCH were enrolled in the validation cohort. Sex, race, grade, tumor size, chemotherapy, and bone metastasis were correlated with overall survival in patients with LMS. The C-index were 0.65 and 0.75 in the SEER and Chinese set, respectively. Furthermore, the applicable AUC values of the ROC curve in the SEER cohort to predict the 1-, 3-, 5- years survival rate were 0.646, 0.682, and 0.689, respectively. The corresponding AUC values in the Chinese cohort were 0.970, 0.913, and 0.881, respectively. The calibration curve showed that the nomogram performed well in predicting the overall survival in post-resection LMS patients with lung metastasis. A web-based nomogram (https://weijunqiang.shinyapps.io/survival_lms_lungmet/) was established. The web-based nomogram (https://weijunqiang.shinyapps.io/survival_lms_lungmet/) is an accurate and personalized tool for predicting the overall survival of post-resection LMS with lung metastasis.

Pediatric retroperitoneal non-organ-originated malignancies: An analysis based on SEER database

Retroperitoneal non-organ-originated malignancies are rare pediatric tumors with challenging diagnosis and treatment. The present study aimed to analyze the clinicopathological characteristics, treatment, and prognosis of retroperitoneal non-organ-originated malignancies. In the study, we included the pathological diagnosis of pediatric retroperitoneal non-organ-originated malignant tumors between 2000 to 2019 through the updated Surveillance, Epidemiology, and End Results database. We use the Kaplan-Meier survival curve to calculate the overall survival (OS) and cancer-specific survival (CSS). The risk of all-cause death and disease-specific death were analyzed using Cox proportional hazard regression model and Fine-and-Grey competitive hazard model, respectively. In the study, a total of 443 pediatric retroperitoneal non-organ-originated malignancies were included. Of them, only 22.3% of patients had no metastatic disease, 42.9% had distant metastasis and 34.8% had locally advanced diseases. The primary pathological tumor was neuroblastoma followed by germ cell tumor. The overall 10-year OS and CSS were 70.7% and 73.1%, respectively, and the 10-year OS and CSS of metastatic diseases were 54.4% and 56.6%, respectively. Older children, worse tumor stage at diagnosis, incomplete resection, and prolonged time from diagnosis to treatment were significantly associated with worse survival outcomes. Radiotherapy and chemotherapy did not significantly improve the prognosis of patients without complete tumor resection. The study indicated that most pediatric retroperitoneal non-organ-originated malignancies diagnosed with metastatic diseases have plagued treatment. Radiotherapy and chemotherapy are the main treatment methods for children unable to undergo complete surgical treatment. However, these treatments do not reach the same therapeutic effect as complete tumor resection after early diagnosis. Hence, early diagnosis and surgery for complete tumor resection are of utmost importance.

Competing risk analysis of cardiovascular-specific mortality in typical carcinoid neoplasms of the lung: A SEER database analysis

Cardiovascular mortality (CVM) is a growing concern for cancer survivors. This study aimed to investigate the mortality patterns of individuals with typical carcinoid (TC) tumors, identify independent predictors of CVM, and compare these risk variables with those associated with TC deaths. The Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2019 was utilized for obtaining data on patients with TC. Standardized mortality rates were employed to evaluate the risk of CVM while multivariate competing risk models were used to determine the association between patient characteristics and the probability of CVM or TC-related deaths. Our findings show that TC patients had an increased risk of CVM, with an standardized mortality rates of 1.12 (95% CI:1.01-1.25). Furthermore, we discovered that age at diagnosis, marital status, year of diagnosis, SEER stage, site, year of diagnosis, surgery, radiotherapy, and chemotherapy all contributed independently to the risk of CVM in patients with TC, whereas age at diagnosis, sex, race, SEER stage, site, year of diagnosis, surgery, radiotherapy, and chemotherapy all contributed significantly to TC mortality. Compared to the general population in the United States, patients with TC are significantly more likely to acquire CVM. Timely introduction of cardioprotective treatments is critical for preventing CVM in patients with TC.

Prediction model of liver metastasis risk in patients with gastric cancer: A population-based study

Liver was the most common site of distant metastasis in patients with gastric cancer (GC). The prediction model of the risk of liver metastasis was rarely proposed. Therefore, we aimed to establish a prediction model for liver metastasis in patients with GC. In this retrospective cohort study, we extracted demographic and clinical data of all the GC patients from the Surveillance, Epidemiology, and End Results registration database from 2010 to 2015. Patients were divided into training set (n = 1691) for model development and testing set (n = 3943) for validation. Univariable and multivariable logistic regression analyses were carried out on the training set to screen potential predictors of liver metastasis and constructed a prediction model. The receiver operator characteristics curves with the area under curve values were used to assess the predictive performance of the liver metastasis prediction model. And a nomogram of the prediction model was also constructed. Of the total 5634 GC patients, 444 (7.88%) had liver metastasis. Variables including age, gender, N stage, T stage, Lauren classification, tumor size, histological type, and surgery were included in the liver metastasis prediction model. The study results indicated that the model had excellent discriminative ability with an area under curve of 0.851 (95% confidence interval: 0.829-0.873) in the training set, and that of 0.849 (95% confidence interval: 0.813-0.885) in the testing set. We have developed an effective prediction model with 8 easily acquired predictors of liver metastasis. The prediction model could predict the risk of liver metastasis in GC patients and performed well, which would assist clinicians to make individualized prediction of liver metastasis in GC patients and adjust treatment strategies in time to improve the prognosis.

Development and validation of a prognostic nomogram for predicting cancer-specific survival in lymph node-negative elderly esophageal cancer patients: A SEER-based study

In this study, we explored the prognostic risk factors of elderly patients (≥65 years old) with lymph node-negative esophageal cancer (EC) and established a nomogram to evaluate the cancer-specific survival of patients. The surveillance, epidemiology, and end results database was used to collect data on patients diagnosed with EC. Univariate and multivariate Cox analyses were used to determine independent prognostic factors, and the nomogram for predicting cancer-specific survival of EC patients was constructed based on the independent prognostic factors obtained from the multivariate Cox analysis. To evaluate the predictive ability of the nomogram, calibration curves, concordance index (C-index), receiver operating characteristic curves, and decision curve analysis were conducted. Kaplan-Meier method was used to analyze the long-term outcomes of EC patients with different risk stratifications. A total of 3050 cases with lymph node-negative EC were randomized into the training cohort (1525) and the validation cohort (1525). Cancer-specific mortality at 1, 3, and 5 years in the entire cohort was 30.7%, 41.8%, and 59.2%, respectively. In multivariate Cox analysis, age (P < .001), marital status (P < .001), tumor size (P < .001), Tumor-node-metastasis stage (P < .001), chemotherapy (P = .011), radiotherapy (P < .001), and surgery (P < .001) were independent prognostic factors. The C-index for the training cohort was 0.740 (95% confidence interval [CI]: 0.722-0.758), and the C-index for the validation cohort was 0.738 (95% CI: 0.722-0.754). The calibration curve demonstrated the great calibration ability of the nomogram. Based on the area under the receiver operating characteristic curve, the nomogram demonstrated a higher sensitivity than the tumor-node-metastasis stage. Decision curve analysis showed the good clinical utility of the nomogram. The risk stratification system was established using the Kaplan-Meier curve and verified by the log-rank test (P < .001). The nomogram and risk stratification system can improve the accuracy of prediction to help clinicians identify high-risk patients and make treatment decisions.

Clinicopathological features and correlation analysis of male breast cancer

To analyze and compare the clinicopathological characteristics of male breast cancer (MBC) among Chinese patients and those from East Asia and other regions. Clinicopathological data from 3 kinds of data sources, including 31 MBC patients in Jiangsu Provincial Hospital (JPH) from 2014 to 2021 in China, 20 literature data on East Asian MBC patients from 2014 to 2021, and 3102 MBC patients registered in the surveillance, epidemiology, and end results (SEER) database from 2014 to 2019, were collected and retrospectively analyzed. The average ages of first-diagnosis MBC patients in JPH and East Asian patients were 59.7 and 62.3 years old, respectively, which were younger than those of SEER patients (66.5 years old). Between East Asian and SEER patients, the status or rates of main breast cancer type, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, breast subtype, and TNM stage were relatively close, and their differences were not statistically significant (P > .05). Differences were observed in chemotherapy, surgery, pathological grade, and lymph node positivity (P < .01). Furthermore, no statistically significant difference was observed between the JPH and East Asian patients (all P > .05). In JPH and SEER, linear regression relationships were observed between the lymph node positivity rate, tumor size, and histological grade. JPH and East Asian MBC patients were younger than SEER patients. Between East Asian and SEER patients, the status of the main breast cancer type, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, breast subtype, and TNM stage were similar, but there were differences in chemotherapy, surgery, pathological grade, and lymph node positivity. The findings of this study should prove to be helpful to deepen our understanding of East Asian MBC.

Comparation between novel online models and the AJCC 8th TNM staging system in predicting cancer-specific and overall survival of small cell lung cancer

Background

Most of previous studies on predictive models for patients with small cell lung cancer (SCLC) were single institutional studies or showed relatively low Harrell concordance index (C-index) values. To build an optimal nomogram, we collected clinicopathological characteristics of SCLC patients from Surveillance, Epidemiology, and End Results (SEER) database.

Methods

24,055 samples with SCLC from 2010 to 2016 in the SEER database were analyzed. The samples were grouped into derivation cohort (n=20,075) and external validation cohort (n=3,980) based on America's different geographic regions. Cox regression analyses were used to construct nomograms predicting cancer-specific survival (CSS) and overall survival (OS) using derivation cohort. The nomograms were internally validated by bootstrapping technique and externally validated by calibration plots. C-index was computed to compare the accuracy and discrimination power of our nomograms with the 8th of version AJCC TNM staging system and nomograms built in previous studies. Decision curve analysis (DCA) was applied to explore whether the nomograms had better clinical efficiency than the 8th version of AJCC TNM staging system.

Results

Age, sex, race, marital status, primary site, differentiation, T classification, N classification, M classification, surgical type, lymph node ratio, radiotherapy, and chemotherapy were chosen as predictors of CSS and OS for SCLC by stepwise multivariable regression and were put into the nomograms. Internal and external validations confirmed the nomograms were accurate in prediction. C-indexes of the nomograms were relatively satisfactory in derivation cohort (CSS: 0.761, OS: 0.761) and external validation cohort (CSS: 0.764, OS: 0.764). The accuracy of the nomograms was superior to that of nomograms built in previous studies. DCA showed the nomograms conferred better clinical efficiency than 8th version of TNM staging system.

Conclusions

We developed practical nomograms for CSS (https://guowei2020.shinyapps.io/DynNom-CSS-SCLC/) and OS (https://drboidedwater.shinyapps.io/DynNom-OS-SCLC/) prediction of SCLC patients which may facilitate clinicians in individualized therapeutics.

Prognostic impact of metastatic patterns and treatment modalities on overall survival in lung squamous cell carcinoma: A population-based study

This study aimed to investigate the impact of distinct metastasis patterns on the overall survival (OS) of individuals diagnosed with organ metastatic lung squamous cell carcinoma (LUSC). OS was calculated using the Kaplan-Meier method, and univariate and multivariate Cox regression analyses were conducted to further assess prognostic factors. A total of 36,025 cases meeting the specified criteria were extracted from the Surveillance, Epidemiology, and End Results database. Among these patients, 30.60% (11,023/36,025) were initially diagnosed at stage IV, and 22.03% (7936/36,025) of these individuals exhibited metastasis in at least 1 organ, including the liver, bone, lung, and brain. Among the 4 types of single metastasis, patients with bone metastasis had the lowest mean OS, at 9.438 months (95% CI: 8.684-10.192). Furthermore, among patients with dual-organ metastases, those with both brain and liver metastases had the shortest mean OS, at 5.523 months (95% CI: 3.762-7.285). Multivariate Cox regression analysis revealed that metastatic site is an independent prognostic factor for OS in patients with single and dual-organ metastases. Chemotherapy was beneficial for patients with single and multiple-organ metastases; although surgery was advantageous for those with single and dual-organ metastases, it did not affect the long-term prognosis of patients with triple organ metastases. Radiotherapy only conferred benefits to patients with single-organ metastasis. LUSC patients exhibit a high incidence of metastasis at the time of initial diagnosis, with significant differences in long-term survival among patients with different patterns of metastasis. Among single-organ metastasis cases, lung metastasis is the most frequent and is associated with the longest mean OS. Regarding treatment options, patients with single-organ metastasis can benefit from chemotherapy, surgery, and radiotherapy, and those with metastasis in 2 organs can benefit from chemotherapy and surgery. Patients with metastasis in more than 2 organs, however, can only benefit from chemotherapy. Understanding the variations in metastasis patterns assists in guiding pretreatment assessments and in determining appropriate therapeutic interventions for LUSC.

Clinical Characteristics and Survival Analysis of Patients With Second Primary Malignancies After Hepatocellular Carcinoma Liver Transplantation: A SEER-based Analysis

BACKGROUND

Second primary malignancies (SPMs) after liver transplantation (LT) are becoming the leading causes of death in LT recipients. The purpose of this study was to explore prognostic factors for SPMs and to establish an overall survival nomogram.

METHODS

A retrospective analysis was conducted of data from the Surveillance, Epidemiology, and End Results (SEER) database on adult patients with primary hepatocellular carcinoma who had undergone LT between 2004 and 2015. Cox regression analysis was used to explore the independent prognostic factors for SPMs. Nomogram was constructed using R software to predict the overall survival at 2, 3, and 5 years. The concordance index, calibration curves, and decision curve analysis were used to evaluate the clinical prediction model.

RESULTS

Data from a total of 2078 patients were eligible, of whom 221 (10.64%) developed SPMs. A total of 221 patients were split into a training cohort (n=154) or a validation cohort (n=67) with a 7:3 ratio. The 3 most common SPMs were lung cancer, prostate cancer, and non-Hodgkin lymphoma. Age at initial diagnosis, marital status, year of diagnosis, T stage, and latency were the prognostic factors for SPMs. The C-index of the nomogram for overall survival in the training and validation cohorts were 0.713 and 0.729, respectively.

CONCLUSIONS

We analyzed the clinical characteristics of SPMs and developed a precise prediction nomogram, with a good predictive performance. The nomogram we developed may help clinicians provide personalized decisions and clinical treatment for LT recipients.

Pancreatic Diffuse Large B-cell Lymphoma in the US Population

BACKGROUND

Pancreatic lymphomas (PLs) represent <2% of all lymphomas and <0.5% of all pancreatic neoplasms. An accurate histologic diagnosis of PL is needed to predict prognosis and adequately treat the patient. This study aims to investigate the demographic, clinical, and pathological factors affecting the prognosis and survival of pancreatic diffuse large B-cell lymphoma (DLBCL).

METHODS

Demographic and clinical data from 493 cases of DLBCL of the pancreas were identified between 2000 and 2018 using the Surveillance, Epidemiology, and End Results (SEER) database.

RESULTS

The most common age group was between the ages of 70 and 79 years (27.0%). While 44% of cases involved distant sites (a proxy for secondary pancreatic DLBCL), regional and localized involvement was seen in 33%, with the most common cause of death being a primary pancreatic DLBCL. Most patients (71%) received only chemotherapy (systemic therapy). The overall five-year observed survival was 46% (95% CI, 43.5-48.3). The one-year and five-year survival with chemotherapy only was 68% (95% CI, 65.3-70.3) and 48% (95% CI, 44.7-50.5), respectively. The one-year and five-year survival with surgery and chemotherapy was 96% (95% CI, 91.3-99.9) and 80% (95% CI, 71.4-89.2), respectively. Surgery with chemotherapy (HR: 0.397 (95% CI, 0.197-0.803), p = 0.010) were both positive predictors in survival prognosis. Multivariable analysis identified age >55 years (HR: 2.475 (95% CI, 1.770-3.461), p < 0.001), distant stage (HR: 6.894 (95% CI, 4.121-11.535), p < 0.001), and undergoing no surgery (HR: 2.610 (95% CI, 1.307-5.215), p = 0.007) as negative predictors for survival.

CONCLUSION

PLs are rare malignant pancreatic neoplasms with DLBCL being the most common histological subtype. An accurate and timely diagnosis of pancreatic DLBCL is necessary to implement effective treatments and reduce mortality. Systemic therapy (chemotherapy) with or without surgical therapy improved survival. Increased age and regional and distant spread negatively impacted survival.

The impact of surgery and survival prediction in patients with gastroenteropancreatic neuroendocrine tumors: a population-based cohort study

OBJECTIVE

This study aimed at assessing the impact of surgical treatments in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs).

METHODS

A propensity score-matched analysis based on data in the Surveillance, Epidemiology, and End Results database was used to assess the efficacy of surgical treatment in patients with GEP-NETs.

RESULTS

A total of 7515 patients diagnosed with GEP-NETs from 2004 to 2015 were evaluated from the Surveillance, Epidemiology, and End Results database. There were 1483 patients in the surgery group and 6032 patients in the nonsurgery group. Compared with patients in the surgery group, patients in the nonsurgery group were inclined to receive chemotherapy (50.8 vs. 16.7%) and radiation (12.9 vs. 3.7%) as treatment options. Multivariate Cox regression analysis revealed higher rates of overall survival (OS) outcomes for GEP-NETs patients who had been subjected to surgery (hazard ratio=0.483, 95% CI=0.439-0.533, P <0.001). Then, to reduce the impact of bias, a 1 : 1 propensity score-matched analysis was performed for the two groups of patients. A total of 1760 patients were assessed and each subgroup included 880 patients. In the matched population, the patients exhibited the ability to significantly benefit from surgery (hazard ratio=0.455, 95% CI=0.439-0.533, P <0.001). The OS outcomes for radiation or chemotherapy patients who had been treated with surgery were better than those of patients who had not been treated with surgery ( P <0.001). In addition, it was found that the OS of patients was not significant after rectum and small intestine surgery, whereas there was a significant difference in OS after colon, pancreas, and stomach surgery on the patients. Patients who had been subjected to surgery in the rectum and small intestines exhibited better therapeutic benefits.

CONCLUSION

Patients with GEP-NETs who are treated with surgery have better OS outcomes. Therefore, surgery is recommended for specified selected patients with metastatic GEP-NETs.

Primary B-cell non-Hodgkin lymphoma of the parotid gland: An analysis based on the SEER database

Primary malignant lymphoma of the parotid gland is a rare entity. The disease is often misdiagnosed, and its survival factors remain unclear. This study included patients diagnosed with primary B-cell non-Hodgkin lymphoma of the parotid gland from 1987 to 2016 in the surveillance, epidemiology, and end results program. Univariate survival analysis was conducted using the Kaplan-Meier method, and multivariate analysis was performed using the Cox proportional hazards regression model. A competing risks regression model was applied to estimate the specific risks associated with parotid lymphoma mortality. A total of 1443 patients were identified. The overall survival of indolent primary B-cell lymphoma of the parotid gland was higher than that of aggressive lymphoma (hazard ratio 0.53, 95% confidence interval 0.44-0.64, P < .001), and older patients (≥70 years) exhibited inferior overall survival. Histological subtype and age are important prognostic factors in patients with primary B-cell non-Hodgkin lymphoma of the parotid gland.

Marital status is an independent prognostic factor for cervical adenocarcinoma: A population-based study

Marriage has been reported as a beneficial factor associated with improved survival among cancer patients, but conflicting results have been observed in cervical adenocarcinoma (AC). Thus, this study is aimed to examine the relationship between the prognosis of cervical AC and marital status. Eligible patients were selected from 2004 to 2015 using the surveillance, epidemiology and end results (SEER) database. Cancer-specific survival (CSS) and overall survival (OS) were compared between married and unmarried groups. A total of 3096 patients had been identified, with married ones accounting for 51.29% (n = 1588). Compared to unmarried groups, more patients in the married group were relatively younger (aged ≤ 45) and belonged to white race, with grade I/II, Federation of International of Gynecologists and Obstetricians (FIGO) stage I/II and tumor size ≤4 cm. Apart from that, more patients received surgery, whereas fewer patients received chemotherapy and radiotherapy (all P < 0.05). The 5-year CSS and OS rates were 80.16% and 78.26% in married patients, 68.58% and 64.62% in the unmarried group (P < .0001). Multivariate analysis showed that marital status was an independent prognostic factor, and the married group performed better CSS (hazard ratio [HR]: 0.770; 95% confidence interval [CI]: 0.663-0.895; P = .001) as well as OS (HR: 0.751; 95%CI: 0.653-0.863; P < .001). As demonstrated by the results of subgroup analysis, married patients had better CSS and OS survival than unmarried ones in nearly all the subgroups. Marital status was identified as an independent prognostic factor for improved survival in patients with cervical AC.

Prognostic disparities in young patients based on breast cancer subtype: A population-based study from the SEER database

Triple-negative breast cancer (TNBC) is associated with younger age and worse long-term survival. However, the characteristics and prognosis of different subtypes of breast cancer (BC) in young (<40 years) patients have not yet been elucidated. The present population-based study explored the clinical and pathological characteristics of young TNBC patients and investigated their long-term survival. We enrolled patients from the Surveillance, Epidemiology, and End Results database younger than 40 years of age with primary BC. Cases were defined as patients with TNBC (hormone receptor [HR]-/human epidermal growth factor receptor 2 [HER2]-), and controls were patients with other subtypes of BC (HR-/HER2+, HR+/HER2-, and HR+/HER2+). Demographic, pathological, and radiotherapy, chemotherapy, and surgery data were extracted and the overall survival was the primary endpoint. We enrolled 14,234 young patients with BC in the present study, of whom 2798 (19.7%) had TNBC and 11,436 (80.3%) had another BC subtype. A higher proportion of TNBC patients than non-TNBC patients had a more advanced tumor-node-metastasis stage (II-IV 80.5% vs 73.1%, P < .001), and smaller proportions underwent radiotherapy (50.0% vs 53.3%, P = .002) and surgery (91.8% vs 92.9%, P < .001). TNBC was associated with significantly lower 5-year survival rates than other subtypes among patients with regional node positivity (0, 1-3, 4-9, ≥10: 54.2% vs 57.7%, 44.2% vs 55.9%, 31.0% vs 52.0%, and 27.7% vs 38.8%, P < .001) and those with different lymph node ratios (low, intermediate, high: 50.9% vs 56.0%, 34.6% vs 53.6%, and 24.8% vs 44.8%, P < .001). Our research is the first to investigate the relevant characteristics of young TNBC patients in comparison with those of young non-TNBC patients based on the surveillance, epidemiology, and end results database. We found that young TNBC patients have a higher pathological stage and worse long-term survival than young patients with other BC subtypes. These findings have implications in identifying young patients with TNBC for aggressive therapy and further investigations should be performed to explore new multimodal treatments for such patients.

Prognostic factors and nomogram for the overall survival of bladder cancer bone metastasis: A SEER-based study

Bone metastasis has a poor prognosis in patients with bladder cancer (BC). This study aimed to construct a prognostic nomogram for predicting the overall survival of patients with bone-metastatic BC (BMBC). The Surveillance, Epidemiology, and End Results database was used to recruit patients with BMBC between 2010 and 2018. Univariate and multivariate analyses were performed to screen for prognostic factors and construct a nomogram. Harrell concordance index, receiver operating characteristic curve, and calibration curve were used to verify the prognostic nomograms. All statistical analyses and chart formation were performed using SPSS 23.0 and R software 4.1.2. A total of 1361 patients diagnosed with BMBC were identified in the Surveillance, Epidemiology, and End Results database. Six independent prognostic factors, including marital status, histological type, T stage, other metastases, surgery, and chemotherapy, were identified and included in the nomogram construction. Among them, chemotherapy contributed the most to the prognosis in the nomogram. The concordance index of the nomogram was 0.745 and 0.753 in the training and validation groups, respectively, and all values of the area under the curve were >0.77. The calibration curves showed perfect consistency between the observed and predicted survival rates. The prognostic nomogram developed in this study is expected to become an accurate and individualized tool for predicting overall survival in patients with BMBC and providing guidance for appropriate treatment or care.

Which model is better in predicting the survival of laryngeal squamous cell carcinoma?: Comparison of the random survival forest based on machine learning algorithms to Cox regression: analyses based on SEER database

Prediction of postoperative survival for laryngeal carcinoma patients is very important. This study attempts to demonstrate the utilization of the random survival forest (RSF) and Cox regression model to predict overall survival of laryngeal squamous cell carcinoma (LSCC) and compare their performance. A total of 8677 patients diagnosed with LSCC from 2004 to 2015 were obtained from surveillance, epidemiology, and end results database. Multivariate imputation by chained equations was applied to filling the missing data. Lasso regression algorithm was conducted to find potential predictors. RSF and Cox regression were used to develop the survival prediction models. Harrell's concordance index (C-index), area under the curve (AUC), Brier score, and calibration plot were used to evaluate the predictive performance of the 2 models. For 3-year survival prediction, the C-index in training set were 0.74 (0.011) and 0.84 (0.013) for Cox and RSF respectively. For 5-year survival prediction, the C-index in training set were 0.75 (0.022) and 0.80 (0.011) for Cox and RSF respectively. Similar results were found in validation set. The AUC were 0.795 for RSF and 0.715 for Cox in the training set while the AUC were 0.765 for RSF and 0.705 for Cox in the validation set. The prediction error curves for each model based on Brier score showed the RSF model had lower prediction errors both in training group and validation group. What's more, the calibration curve displayed similar results of 2 models both in training set and validation set. The performance of RSF model were better than Cox regression model. The RSF algorithms provide a relatively better alternatives to be of clinical use for estimating the survival probability of LSCC patients.

Development and validation of prognostic nomogram for patients with metastatic gastric adenocarcinoma based on the SEER database

The aim of this study was to investigate the prognostic factors affecting overall survival in patients with metastatic gastric adenocarcinoma and to establish a nomogram prediction model for comprehensive clinical application. Data from 2370 patients with metastatic gastric adenocarcinoma between 2010 and 2017 were retrieved from the surveillance, epidemiology, and end results database. They were randomly divided into a training set (70%) and a validation set (30%), univariate and multivariate Cox proportional hazards regressions were used to screen important variables that may affect overall survival and to establish the nomogram. The nomogram model was evaluated using a receiver operating characteristic curve, calibration plot, and decision curve analysis. Internal validation was performed to test the accuracy and validity of the nomogram. Univariate and multivariate Cox regression analyses revealed that, age, primary site, grade, and American joint committee on cancer. T, bone metastasis, liver metastasis, lung metastasis, tumor Size, and chemotherapy were identified as independent prognostic factors for overall survival and were included in the prognostic model to construct a nomogram. The prognostic nomogram showed good overall survival risk stratification ability for the area under the curve, calibration plots, and decision curve analysis in both the training and validation sets. Kaplan-Meier curves further showed that patients in the low-risk group had better overall survival. This study synthesizes the clinical, pathological, therapeutic characteristics of patients with metastatic gastric adenocarcinoma, establishes a clinically effective prognostic model, and that can help clinicians to better evaluate the patient's condition and provide accurate treatment.

Better survival and prognosis in SCLC survivors after combined second primary malignancies: A SEER database-based study

With recent advances in treatment modalities, the survival time for patients with small cell lung cancer (SCLC) has increased, along with the likelihood of recurrence of a second primary tumor. However, patient treatment options and prognosis remain uncertain. This research evaluated the survival rates of patients with SCLC with a second malignancy, aiming to provide new insights and statistics on whether to proceed with more active therapy. SCLC patients were selected based on the Surveillance, Epidemiology, and End Results (SEER) database, updated on April 15, 2021. We defined those with SCLC followed by other cancers (1st of 2 or more primaries) in the sequence number as S-second primary malignant cancer (S-SPM). Those who had other cancers followed by SCLC (2nd of 2 or more primaries) were defined as OC-SCLC. We performed Kaplan-Meier survival analysis, life table analysis, univariate analysis, stratified analysis, and multiple regression analysis of patient data. We considered the difference statistically meaningful at P < .05. After selection, data for 88,448 participants from the SEER database was included in our analysis. The mean survival time for patients with S-SPM was 69.349 months (95% confidence interval [CI]: 65.939, 72.759), and the medium duration of survival was 34 months (95% CI: 29.900, 38.100). Univariate analysis showed that for overall survival, the hazard ratio (HR) of S-SPM was 0.367 (95% CI: 0.351, 0.383), which was 0.633 lower than that of patients with solitary SCLC and 0.606 lower than that of patients with OC-SCLC. For cancer-specific survival (CSS), the HR of S-SPM was 0.285 (95% CI: 0.271, 0.301), which was 0.715 lower than for patients with solitary SCLC and 0.608 lower than that for patients with OC-SCLC. Multiple regression analysis showed that the HR values of S-SPM were lower than those of patients with single SCLC and those with OC-SCLC, before and after adjustment for variables. Kaplan-Meier survival curves showed that patients with S-SPM had significantly better survival times than the other groups. The survival time and prognosis of patients with S-SPM were clearly superior to those with single SCLC and OC-SCLC.

Neoadjuvant chemotherapy in advanced epithelial ovarian cancer by histology: A SEER based survival analysis

To evaluate the prognostic effect of neoadjuvant chemotherapy (NACT) in advanced epithelial ovarian cancer (EOC) patients with different histological subtype. Stage III/IV EOC patients diagnosed between 2010 and 2018 were identified from the surveillance, epidemiology, and end results database (SEER) database and stratified by histological subtype. Kaplan-Meier analysis was used for the assessment of overall survival (OS) cause-specific survival (CSS) before and after matching for baseline characteristics between NACT and primary debulking surgery (PDS) groups. Cox proportional risk model was conducted to identify independent prognostic factors. A total of 13,582 patients were included in the analysis. Of them, 9505 (74.50%) received PDS and 3253 (25.50%) received NACT. Overall, an inferior OS and CSS was observed among patients with high-grade serous carcinoma (HGSC) receiving NACT, while NACT served as a protective factor in clear cell carcinoma and carcinosarcoma in both original cohorts and adjusted cohorts. For other histo-subtypes, PDS showed survival benefit over NACT in certain cohorts of models. Prognostic effect of NACT in advanced EOC differed from pathological subtypes. Although it served as a risk factor for HGSC, patients with less common subtypes may benefit from NACT.

Elderly Pancreatic Adenocarcinoma Cancer Patients Could Benefit From Postoperative Chemotherapy

OBJECTIVES

The study aim to investigate whether elderly patients with resectable pancreatic ductal adenocarcinoma (PDAC) could benefit from postoperative chemotherapy.

METHODS

This study selects the data of PDAC patients who were diagnosed between 2004 and 2014 from the Surveillance, Epidemiology, and End Results program. Median overall survival (mOS) is determined by Kaplan-Meier survival curves. Multivariate logistic regression analysis and hazard ratio are employed to assess the association among potential prognostic factors. Propensity score matching evaluation is used to reduce bias.

RESULTS

In total, there are 11,865 PDAC patients selected from the Surveillance, Epidemiology, and End Results database. Elderly PDAC patients have poor prognoses compared with younger (mOS, 15 vs 21 months). The possible reason might be that the elderly patients are less likely to receive postoperative chemotherapy. After propensity score matching, it is found that, for those who receive postoperative chemotherapy, although the mOS of older group is not as good as that of the younger group (mOS, 20 vs 23 months; 18-month survival rate: 53.4% vs 61.3%), the mOS of older group prolonged by postoperative chemotherapy is similar to that of younger group (9 vs 9 months).

CONCLUSIONS

Elderly PDAC patients (≥70 years) might benefit from the currently used postoperative chemotherapy regimens.

Prognostic factors and survival prediction for patients with metastatic lung adenocarcinoma: A population-based study

The prognosis of metastatic lung adenocarcinoma (MLUAD) varies greatly. At present, no studies have constructed a satisfactory prognostic model for MLUAD. We identified 44,878 patients with MLUAD. The patients were randomized into the training and validation cohorts. Cox regression models were performed to identify independent prognostic factors. Then, R software was employed to construct a new nomogram for predicting overall survival (OS) of patients with MLUAD. Accuracy was assessed by the concordance index (C-index), receiver operating characteristic curves and calibration plots. Finally, clinical practicability was examined via decision curve analysis. The OS time range for the included populations was 0 to 107 months, and the median OS was 7.00 months. Nineteen variables were significantly associated with the prognosis, and the top 5 prognostic factors were chemotherapy, grade, age, race and surgery. The nomogram has excellent predictive accuracy and clinical applicability compared to the TNM system (C-index: 0.723 vs 0.534). The C-index values were 0.723 (95% confidence interval: 0.719-0.726) and 0.723 (95% confidence interval: 0.718-0.729) in the training and validation cohorts, respectively. The area under the curve for 6-, 12-, and 18-month OS was 0.799, 0.764, and 0.750, respectively, in the training cohort and 0.799, 0.762, and 0.746, respectively, in the validation cohort. The calibration plots show good accuracy, and the decision curve analysis values indicate good clinical applicability and effectiveness. The nomogram model constructed with the above 19 prognostic factors is suitable for predicting the OS of MLUAD and has good predictive accuracy and clinical applicability.

Risk and outcome of second primary malignancy in patients with classical Hodgkin lymphoma

BACKGROUND

Hodgkin lymphoma survivors demonstrated increased risk of secondary primary malignancies (SPMs), but comprehensive analysis of the risk and outcome of SPMs in classical Hodgkin lymphoma (cHL) patients has not yet been reported.

METHODS

Patients with cHL from 1975 to 2017 were identified from the Surveillance, Epidemiology and End Results (SEER) database. Standardized incidence ratios were calculated for the risk of solid and hematologic SPMs in cHL patients compared to the general population. The outcome of cHL patients developing SPMs were assessed by performing survival, competing risks regression, and cox proportional regression analyses.

RESULTS

In a follow-up of 26,493 cHL survivors for 365,156 person years, 3866 (14.59%) secondary cancers were identified, with an standardized incidence ratio of 2.09 (95% CI: 2.02-2.15). The increased risk was still notable after follow-up of 10 years or more, and the risk is more pronounced for patients with female gender, younger age, advanced stage, chemotherapy, and radiation therapy. The overall survival is worse for cHL patients with SPMs after 11 years of follow-up (P < .0001). The main cause of death for cHL patients with SPMs is not cHL but other causes including SPMs. Multivariate Cox regression analysis confirmed SPMs as an independently adverse prognostic factor for cHL survivors (hazard ratio, 1.13; 95% CI, 1.05-1.21, P = .001).

CONCLUSIONS

There is a significantly increased risk of developing SPMs for cHL survivors. The overall survival is worse for cHL patients and SPMs is an independent prognostic factor for cHL.

Short-term prognosis for hepatocellular carcinoma patients with lung metastasis: A retrospective cohort study based on the SEER database

Our study aimed to develop a prediction model to predict the short-term mortality of hepatocellular carcinoma (HCC) patients with lung metastasis. The retrospective data of HCC patients with lung metastasis was from the Surveillance, Epidemiology, and End Results registration database between 2010 and 2015. 1905 patients were randomly divided into training set (n = 1333) and validation set (n = 572). There were 1092 patients extracted from the Surveillance, Epidemiology, and End Results database 2015 to 2019 as the validation set. The variable importance was calculated to screen predictors. The constructed prediction models of logistic regression, random forest, broad learning system, deep neural network, support vector machine, and naïve Bayes were compared through the predictive performance. The mortality of HCC patients with lung metastasis was 51.65% within 1 month. The screened prognostic factors (age, N stage, T stage, tumor size, surgery, grade, radiation, and chemotherapy) and gender were used to construct prediction models. The area under curve (0.853 vs. 0.771) of random forest model was more optimized than that of logistic regression model in the training set. But, there were no significant differences in testing and validation sets between random forest and logistic regression models. The value of area under curve in the logistic regression model was significantly higher than that of the broad learning system model (0.763 vs. 0.745), support vector machine model (0.763 vs. 0.689) in the validation set, and higher than that of the naïve Bayes model (0.775 vs. 0.744) in the testing model. We further chose the logistic regression prediction model and built the prognostic nomogram. We have developed a prediction model for predicting short-term mortality with 9 easily acquired predictors of HCC patients with lung metastasis, which performed well in the internal and external validation. It could assist clinicians to adjust treatment strategies in time to improve the prognosis.

A nomogram model of postoperative prognosis for metastatic lung adenocarcinoma: A study based on the SEER database

We have observed that patients with metastatic lung adenocarcinoma can obtain survival benefits from surgical resection of the primary tumor. A model was developed to evaluate the prognosis of patients. The patients with metastatic lung adenocarcinoma were identified in the Surveillance, Epidemiology, and End Results database and divided into surgery group and non-surgical group. Through Kaplan-Meier analysis, the survival rate of the non-surgical group was found to be significantly lower no matter before or after propensity score matching. One thousand one hundred and seventy surgical patients were divided into a training group and a verification group. In the training group, univariate and multivariate Cox models were used to explore the prognostic factors, and logistic regression was used to establish a nomogram based on significant predictors. In total, 12,228 patients with metastatic lung adenocarcinoma were recognized; primary tumor surgery accounted for 9.5%. After propensity score matching, the median survival time of 2 groups was significantly different. For the training group, univariate and multivariate COX analysis was conducted, and a nomogram was constructed. Acceptable agreement has been achieved between the predicted and observed survival rates, and the nomogram can divide patients with metastatic lung adenocarcinoma into different risk groups and predict their prognostic survival rate.

Prognostic nomogram for female patients suffering from non-metastatic Her2 positive breast cancer: A SEER-based study

This paper aimed at constructing and validating a novel prognostic nomogram, so that physicians forecast the overall survival (OS) rates of female patients suffering from non-metastatic human epidermal growth element receptor-2 (HER2) positive breast. Information of primary female her2 positive breast cancer patients without metastasis was obtained from the Surveillance, Epidemiology, and End Results (SEER) database with given inclusion and exclusion standards. Independent variables were obtained greatly by performing univariable and multivariate analyses. Based on those independent predictors, a novel prognostic nomogram was constructed for predicting the survival of those with 3- and 5-year OS. Then, concordance index (C-index), receiver operating characteristic curve (ROC), and calibration plot were adopted for the assessment of the predictive power of the nomogram. A total of 36,083 eligible patients were classified into a training cohort (n = 25,259) and a verification cohort (n = 10,824) randomly. According to the identification of multivariate analysis, survival was predicted by age at diagnosis, marital status, race, site, T stage, N stage, progesterone receptor (PR) status, estrogen receptor (ER) status, surgery, radiation, and chemotherapy independently. A nomogram was established by applying the training cohort. The nomogram displayed excellent discrimination and performance as indicated by the C-index (0.764, 95% confidence interval: 0.756-0.772), and the 3- and 5-year area under the curve of ROC (AUC) values (0.760 and 0.692 respectively). The calibration plots for forecasting the 3- and 5-year OS were in great agreement. The OS for female her2 positive breast cancer patients without metastasis was predicted by constructing a nomogram on basis of the SEER database. A precise survival prediction could be offered for each patient.

Nomogram for predicting distant metastasis of male breast cancer: A SEER population-based study

The main purpose of this study was to build a prediction model for male breast cancer (MBC) patients to predict the possibility of distant metastasis. The Surveillance, Epidemiology, and End Results database was used to obtain data on patients with MBC. The patients were divided into a training set and a validation set at a ratio of 7:3. The risk variables of distant metastasis in the training set were determined by univariate and multivariate logistic regression analyses. And then we integrated those risk factors to construct the nomogram. The prediction nomogram was further verified in the verification set. The discrimination and calibration of the nomogram were evaluated by the area under the receiver operating characteristic curve, calibration plots, respectively. A total of 1974 patients (1381 in training set and 593 in validation set) were eligible for final inclusion, of whom 149 (7.55%) had distant metastasis at the diagnosed time. Multivariate logistic regression analyses presented that age, T stage, N stage, and hormone receptor status were independent risk factors for distant metastasis at initial diagnosis of male breast cancer. Finally, the 4 variables were combined to construct the nomogram. The area under the curve values for the nomogram established in the training set and validation set were 0.8224 (95%CI: 0.7796-0.8652) and 0.8631 (95%CI: 0.7937-0.9326), suggesting that the nomogram had good predictive power. The calibration plots illustrated an acceptable correlation between the prediction by nomogram and the actual observation, as the calibration curve was closed to the diagonal bisector line. An easy-to-use nomogram, being proven to be with reliable discrimination ability and accuracy, was established to predict distant metastasis for male patients with breast cancer using the easily available risk factors.

A nomogram for predicting overall survival rate in patients with brain metastatic non-small cell lung cancer

The purpose was to develop a nomogram for the prediction of the 1- and 2-year overall survival (OS) rates in patients with brain metastatic non-small cell lung cancer (BMNSCLC). Patients were collected from the Surveillance Epidemiology and End Results program (SEER) and classified into the training and validation groups. Several independent prognostic factors identified by statistical methods were incorporated to establish a predictive nomogram. The concordance index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration curve were applied to estimate predictive ability of the nomogram. To compare the clinical practicability of the nomogram and TNM staging system by decision curve analysis (DCA). A total of 24,164 eligible patients were collected and assigned into the training (n = 16,916) and validation groups (n = 7248). Based on the prognostic factors, we developed a nomogram with good discriminative ability. The C-indices for training and validation group were 0.727 and 0.728. The AUCs of 1- and 2-year OS rates were both 0.8, and the calibration curves also demonstrated good performance of the nomogram. DCA illustrated that the nomogram provided clinical net benefit compared with the TNM staging system. We developed a predictive nomogram for more accurate and comprehensive prediction of OS in BMNSCLC patients, which can be a useful and convenient tool for clinicians to make proper clinical decisions, and adjust follow-up management strategies.

The influence of marital status on survival in patients with nasopharyngeal carcinoma: A surveillance, epidemiology, and end results database analysis

BACKGROUND

To assess the influence of marital status on the survival of patients with nasopharyngeal carcinoma (NPC), we used the Surveillance, Epidemiology, and End Results (SEER) database to analyze 5477 patients who were diagnosed with NPC from 2004 to 2016.

METHODS

Kaplan-Meier survival analysis and Cox proportional hazard regression were used to analyze the influence of marital status on cause-specific survival (CSS) and overall survival (OS). Subgroup analyses was used to assess the influence of marital status on CSS based on different factors.

RESULTS

For the 5477 patients, 61.5%, 22.4%, and 16.1% were married, single/unmarried, and separated/widowed/divorced, respectively. The separated/widowed/divorced group was more likely to be female (P < .001), had the highest proportion of elderly subjects (P < .001), were mostly Caucasian (P < .001), had pathological grade I/II (P < .001), were likely to undergo surgery (P = .032), and were registered in the northeast, north-central, and south (P < .001) regions. The 5-year CSS rates were 92.6%, 92.4%, and 85.1% in the married, single/unmarried, and separated/widowed/divorced groups, respectively (P < .001), and the 5-year OS rates were 60.7%, 54.6%, and 40.1%, respectively (P < .001).

CONCLUSION

Marital status is an independent prognostic factor of NPC. Separated/widowed/divorced patients had a significantly increased risk of NPC-related death (hazard ratio [HR] = 2.180, 95% confidence interval [CI] 1.721-2.757, P < .001) compared to married patients. The single/unmarried (P = .355) group had a CSS similar to that of the unmarried group. Marital status is an independent prognostic factor of survival in NPC patients. Separated/widowed/divorced status increases the risk of NPC mortality.

Risk and prognosis of secondary bladder cancer after post-operative radiotherapy for gynecological cancer

The aim of this study was to investigate the impacts of radiation therapy (RT) on the occurrence risk of secondary bladder cancer (SBC) and on the patients' survival outcome after being diagnosed with gynecological cancer (EC). The data was obtained from the SEER database between 1973 and 2015. Chi-squared test was used to compare the clinicopathological characteristics among the different groups. Fine and Gray's competing risk model was used to assess the cumulative incidence and occurrence risk of SBC in GC survivors. Kaplan-Meier method was utilized for survival analysis. A total of 123,476 GC patients were included, among which 31,847 (25.8%) patients received RT while 91629 (74.2%) patients did not. The cumulative incidence of SBC was 1.59% or 0.73% among patients who had received prior GC specific RT or not, respectively. All EBRT (standardized incidence ratio (SIR) =2.49, 95% CI [2.17-2.86]), brachytherapy (SIR =1.96, 95% CI [1.60-2.38]), and combinational RT modality groups (SIR =2.73, 95% CI [2.24-3.28]) had dramatically higher SBC incidence as compared to the US general population. Receiving EBRT (HR = 2.83, 95% CI [2.34-3.43]), brachytherapy (HR = 2.17, 95% CI [1.67-2.82]), and combinational RT modality (HR = 2.97, 95% CI [2.34-3.77]) were independent risk factors for SBC development. Survival detriment was observed in SBC patients who received RT after GC diagnosis, as compared to those who did not receive RT. In conclusion, patients who underwent RT after GC had an increased risk of developing bladder as a secondary primary cancer. A long-term surveillance for SBC occurrence is necessary for GC patients who have received prior RT.

A Proposal to Modify the 8th IASLC System: Is it Suitable for T4N2M0 Lung Adenocarcinoma to Be Placed in Stage IIIB?

PURPOSE

The International Association for the Study of Lung Cancer (IASLC) of TNM staging system has been well accepted as a precise model. However, the latest American Joint Committee on Cancer (AJCC) staging system to solve the different survival and prognosis of lung adenocarcinoma in the same period is still controversial. Therefore, it is necessary to thoroughly explore the applicability between the new system and survival prediction in terms of lung adenocarcinoma.

METHODS

We recruited 52,517 patients with lung adenocarcinoma from the Surveillence, Epidemiology, and End Results database. Cox regression analysis was performed to determine survival related factors. The mortality rate per 1000 persons per year of the T4N2M0 lung adenocarcinoma stage and other stages were compared. Survival curves were obtained using the Kaplan-Meier analysis and log-rank test.

RESULTS

The results of Cox proportional hazards regression analysis showed that age at diagnosis, race, T stage, distant metastasis, extrathoracic extension, radiotherapy, chemotherapy, and surgery are independent factors related to cancer-specific survival (CSS) and all-cause survival. Furthermore, patients with stage IIIA disease (P<0.001) and IIIB disease (P<0.001) excluding stage at T4N2M0 had a significantly lower risk of CSS and all-cause survival than those staged with T4N2M0 disease. The mortality rates per 1000 person-years with patients staged at T4N2M0 lung adenocarcinoma had higher mortality than patients in the same period. The CSS curves of patients with stage T4N2M0 reflected an obvious decline compared with those of stages IIIA disease and IIIB excluding T4N2M0, and there is no significant difference between this curve and stage IIIC patients (P>0.05).

CONCLUSION

The survival rate of patients with T4N2M0 stage was significantly lower than that of patients with IIIA and IIIB stages excluding T4N2M0, there was no significant difference between T4N2M0 and IIIC. It was suggested that this group of patients with stage T4N2M0 were upgraded in the 8th IASLC system.

Postoperative radioiodine therapy impact on survival in poorly differentiated thyroid carcinoma: a population-based study

PURPOSE

The true impact of postoperative radioiodine therapy on survival has been controversial for patients with poorly differentiated thyroid carcinoma (PDTC). We aimed to determine the impact of postoperative radioiodine on survival in PDTC through a population-based study.

METHODS

Data on patients with PDTC were collected from the US SEER database (2004 to 2015). Patients were divided into the radioiodine group and nonradioiodine group. Survival comparison between groups was evaluated by Kaplan-Meier curves, log-rank test and multivariate Cox regression analysis. Akaike information criterion was used to select variables in the nomogram. The performance of the nomogram was assessed by discrimination (C-index) and calibration plots.

RESULTS

The radioiodine group had more aggressive features, such as advanced tumor node metastasis stage and radical surgery, compared to the nonradioiodine group. PDTC patients receiving radioiodine therapy had a significant survival advantage in terms of overall survival (OS) (P = 0.001) but not in terms of cancer-specific survival (P = 0.083). Multivariate analysis revealed radioiodine therapy was an independent favorable factor for OS in PDTC patients (hazard ratio = 0.57; 95% CI, 0.44-0.75, P < 0.001). Subgroup analysis identified patients' characteristics favoring radioiodine therapy. The nomogram (age, tumor size, extension, neck lymph nodes metastasis and radioiodine therapy) of OS for predicting 3-, 5- and 10-year OS probability showed good discrimination (C-index, 0.797) and calibration power.

CONCLUSION

Postoperative radioiodine therapy can prolong the long-term OS in patients with PDTC, and is an independent favorable prognostic factor for those patients. Further prospective studies are warranted.

Non-Cancer Causes of Death in Patients With Pancreatic Adenocarcinoma: A Surveillance, Epidemiology, and End Results (SEER)-Based Study

Background This study aimed to identify the most common causes of non-cancer mortality in patients with pancreatic adenocarcinoma (PAC) and compare their mortality risk with the general population. Methodology This study analyzed PAC patients' data registered in the Surveillance, Epidemiology, and End Results (SEER) database. We studied the causes of death and investigated their association with age, sex, race, tumor stage at presentation, and treatment modality according to the time interval from diagnosis during which death events occurred. We used the standardized mortality ratio (SMR). Results A total of 67,694 PAC patients' data were analyzed; of these patients, 64,347 (95.06%) died during the follow-up. Most deaths occurred due to cancer (61,685; 95.86% of deaths), while non-cancer mortality represented only 4.14%. The most common causes of non-cancer mortality were heart diseases (SMR = 2.79), cerebrovascular diseases (SMR = 3.11), and septicemia (SMR = 8.2). PAC patients had a higher mortality risk for all studied mortality causes except Alzheimer's disease (SMR = 0.5) and homicide and legal intervention (SMR = 2.29). Conclusions Approximately 96% of PAC patients' deaths are due to cancer. While the dominant non-cancer causes of death include heart diseases, cerebrovascular diseases, and septicemia, with a higher risk of mortality for most non-cancer causes than the general population.

Diagnostic and prognostic factors, and two nomograms for endometrial cancer patients with bone metastasis: A large cohort retrospective study

Patients with endometrial cancer (EC) who develop bone metastasis (BM) always imply a poorer prognosis. However, reliable predictive models associated with BM from EC are currently limited.We retrospectively analyzed data on 54,077 patients diagnosed with primary EC in the Surveillance, Epidemiology, and End Results database. Multivariate logistic regression analysis was used to determine independent predictors of BM from EC. Univariate and multivariate Cox regression analyses were used to determine independent prognostic factors for EC with BM. Based on independent predictors and prognostic factors, we constructed a diagnostic nomogram and prognostic nomogram separately. Besides, calibration curves, receiver operating characteristic curves, and decision curve analysis were used to evaluate the models.A total of 54,077 patients with EC from the Surveillance, Epidemiology, and End Results database were included in this study, 364 of whom had BM. Multivariate analysis in the logistic model showed that lung metastasis, liver metastasis, brain metastasis, N stage, T stage, histologic grade, and race were risk factors for BM from EC. Multivariate analysis in the Cox model showed that liver metastasis, brain metastasis, chemotherapy, surgery, and histologic type had a significant effect on overall survival. Moreover, the receiver operating characteristic curve, calibration curve, and decision curve analysis indicated the good performance of both diagnostic and prognostic nomograms.Two clinical prediction model was constructed and validated to predict individual risk and overall survival for EC with BM, respectively. Diagnostic nomogram and prognostic nomogram are complementary, improving the clinician's ability to assess the patient's prognosis and enhancing prognosis-based decision making.

Combined radiotherapy and chemotherapy versus radiotherapy alone in elderly patients with nasopharyngeal carcinoma: A SEER population-based study

Currently, the impact of chemotherapy (CT) on survival outcomes in elderly patients with nasopharyngeal carcinoma (NPC) receiving radiation therapy (RT) remains controversial. This retrospective study aims to investigate survival outcomes in a cohort of elderly NPC patients receiving RT alone or together with CT.Clinical data on 529 NPC patients aged 65 years and older extracted from the Surveillance, Epidemiology, and End Results registry (2004-2015) was collected and retrospectively reviewed. In this cohort, 74 patients were treated with RT alone and 455 individuals received RT and CT. We used propensity score matching with a 1:3 ratio to identify correlations between patients based on 6 different variables. Kaplan-Meier analysis was used to evaluate overall (OS) and cancer-specific survival (CSS). The differences in OS and CSS between the 2 treatment groups were compared using the Log-rank test and Cox proportional hazards models.The estimated 5-year OS and CSS rates for all patients were 49.5% and 59.3%, respectively. The combination of RT and CT provided longer OS than RT alone (53.7% vs 36.9%, P = .002), while no significant difference was observed in CSS (61.8% vs 51.7%, P = .074) between the 2 groups. Moreover, multivariate analysis demonstrated that the combination of CT and RT correlated favorably with OS and CSS. Subgroup analyses showed that the combination of RT and CT correlated better with both OS and CSS in patients with stage T3 or N2 or stage III.Among NPC patients aged 65 years and older, treatment with RT and CT provided longer OS than RT alone. Furthermore, the combination of RT and CT showed a better correlation with OS and CSS in NPC patients with stage T3 or N2 or stage III.

Comparison of Survival among Colon Cancer Patients in the U.S. Military Health System and Patients in the Surveillance, Epidemiology, and End Results (SEER) Program

BACKGROUND

Access to health care is associated with cancer survival. The U.S. military health system (MHS) provides universal health care to beneficiaries, reducing barriers to medical care access. However, it is unknown whether the universal care has translated into improved survival among patients with colon cancer. We compared survival of patients with colon cancer in the MHS to that in the U.S. general population and assessed whether stage at diagnosis differed between the two populations and thus could contribute to survival difference.

METHODS

The data were from Department of Defense's (DoD) Automated Central Tumor Registry (ACTUR) and the NCI's Surveillance, Epidemiology, and End Results (SEER) program, respectively. The ACTUR (N = 11,907) and SEER patients (N = 23,814) were matched to demographics and diagnosis year with a matching ratio of 1:2. Multivariable Cox regression model was used to estimate all-cause mortality for ACTUR compared with SEER.

RESULTS

ACTUR patients exhibited better survival than their SEER counterparts (HR, 0.82; 95% confidence interval, 0.79-0.87) overall and in most subgroups by age, in both men and women, and in whites and blacks. The better survival remained when the comparison was stratified by tumor stage.

CONCLUSIONS

Patients with colon cancer in a universal health care system had better survival than patients in the general population.

IMPACT

Universal care access is important to improve survival of patients with colon cancer.

Metastasis pattern and prognosis in men with esophageal cancer patients: A SEER-based study

Esophageal cancer (EC) is relatively common; at the time of diagnosis, 50% of cases present with distant metastases, and most patients are men. This study aimed to examine and compare the clinicopathological characteristics and metastatic patterns of male EC (MEC) and female EC (FEC). In addition, risk factors associated with MEC prognosis were evaluated.The present study population was extracted from the Surveillance Epidemiology and End Results database. MEC characteristics and factors associated with prognosis were evaluated using descriptive analysis, the Kaplan-Meier method, and the Cox regression model.A total of 12,558 MEC cases were included; among them, 3454 cases had distant organ metastases. Overall, 27.5% of the entire cohort were patients with distant organ metastases. Compared with patients with non-metastatic MEC, patients with metastatic MEC were more likely to be aged ≤60 years, of Black and White race, have a primary lesion in the overlapping esophagus segments, and have a diagnosis of adenocarcinoma of poorly differentiated and undifferentiated grade that was treated with radiotherapy and chemotherapy rather than surgery; moreover, they were also more likely to be married and insured. In addition, patients with MEC were more likely to be aged ≤60 years, White race, and diagnosed with a primary lesion in the lower third of the esophagus and overlapping esophagus segments, and treated without chemotherapy, compared with those with FEC. Patients in the former group were also more likely than those in the latter group to be unmarried and have bone metastasis only and lung metastasis only. Liver, lung, and bone metastases separately, and simultaneous liver and lung metastases were associated with poor survival in MEC patients.Metastatic MEC is associated with clinicopathological characteristics and metastatic patterns different from those associated with non-metastatic MEC and metastatic FEC. Metastatic MEC and FEC patients may have similar prognoses. Distant organ metastasis may be associated with poor prognosis in patients with MEC and FEC.

Establishment and Validation of a Nomogram for Tonsil Squamous Cell Carcinoma: A Retrospective Study Based on the SEER Database

This study aimed to establish and validate a comprehensive nomogram for predicting the cause-specific survival (CSS) probability in tonsillar squamous cell carcinoma (TSCC). We screened and extracted data from the SEER (Surveillance, Epidemiology, and End Results) database for the period 2004 to 2016. We randomly divided the 7243 identified patients into a training cohort (70%) for constructing the model and a validation cohort (30%) for evaluating the model using R software. Multivariate Cox stepwise regression was used to select predictive variables. The concordance index (C-index), the area under the time-dependent receiver operating characteristics curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the model. The multivariate Cox stepwise regression analysis successfully established a nomogram for the 1-, 3-, and 5-year CSS probabilities for TSCC patients. The C-index, AUC, NRI, and IDI were all showed that the model has good discrimination. The calibration plots were very close to the standard lines, indicating that the model has a good degree of calibration, and the DCA curve further illustrated that the model has good clinical validity. We have established the first nomogram for predicting the 1-, 3-, and 5-year CSS probabilities for TSCC based on a large retrospective sample. Our rigorous validation and evaluation indicated that the model can provide useful guidance to clinical workers making clinical decisions about individual patients.