Surveillance, Epidemiology, And End Results Cohort Research Articles

Development and validation of a nomogram integrating marital status for 5-year overall survival of chondrosarcoma: a population-based study.

The objective of this study was to evaluate the influence of marital status on overall survival (OS) and develop a nomogram for predicting 5-year OS in chondrosarcoma (CHS) patients. We utilized the Surveillance, Epidemiology, and End Results (SEER) database to identify CHS patients diagnosed between 2010 and 2018. Survival rates were calculated using Kaplan-Meier analysis. Prognostic factors were identified through univariate and multivariate analyses. An independent cohort was used for external validation of the nomogram. Performance evaluation of the nomogram was conducted using Harrell's concordance index (C-index), calibration plot, and decision curve analysis (DCA). In the SEER cohort, Kaplan-Meier analysis showed significant differences in OS among CHS patients with different marital statuses (P < 0.001), with widowed patients having the lowest OS. In terms of gender, there were significant survival differences based on marital status in females (P < 0.001), but not in males (P = 0.067). The OS of married and single females is significantly higher than that of married (P < 0.001) and single male (P = 0.006), respectively. Kaplan-Meier curves showed no significant difference in OS between groups stratified by either gender or marital status in the external cohort. Univariate and multivariate analyses confirmed that age at diagnosis, gender, marital status, tumor size, histological type, tumor grade, SEER stage, and surgery were independent prognostic factors for OS. The nomogram demonstrated high internal and external validation C-indexes of 0.818 and 0.88, respectively. Calibration plots, DCA curve, and Kaplan-Meier curve (P < 0.001) confirmed the excellent performance and clinical utility of the nomogram. Marital status was an independent factor influencing OS in CHS patients, with widowed patients having the worst prognosis. The OS of both married and single females is significantly higher than that of their male counterparts. However, these findings require further validation in a large independent cohort. While the contribution of marital status on predicting OS appears modest, our nomogram accurately predicted 5-year OS and identified high-risk groups, providing a valuable tool for clinical decision-making.

A population study comparing tracheal and lung adenoid cystic carcinoma.

Thoracic adenoid cystic carcinoma (ACC) is rare, and the differences between tracheal and lung lesions have not been fully understood. Patients were identified from a Chinese cancer center (FUSCC) (2005-2022) and the Surveillance, Epidemiology, and End Results (SEER) database (2000-2019). Incidence was calculated and trends were quantified. Clinicopathological features and overall survival (OS) were analyzed. Nomograms predicting OS were constructed. Totally, 55 tracheal adenoid cystic carcinoma (TACC) and 25 lung and bronchus adenoid cystic carcinoma (LACC) were included in a Chinese cohort, 121 TACC and 162 LACC included in the SEER cohort. There were larger tumor sizes, more lymph nodes and distant metastases for LACC than TACC patients. TACC patients are more likely to get local treatments. Patients with LACC had significantly worse median OS than patients with TACC (SEER cohort: 68.0 months vs. 109.0 months, p = 0.001, Chinese cohort: 62.9 months vs. 124.8 months, p = 0.061). Age, lymph node metastasis, distant metastasis and local treatment were identified as independent prognostic factors for OS of TACC. Distant metastasis and local treatment were identified for LACC. Specifically, surgery alone or in combination with radiotherapy is crucial for improving survival in both TACC and LACC. Only TACC benefits from radiotherapy alone, while chemotherapy does not improve survival for either. The nomograms constructed using these factors revealed good prognostic accuracy. LACC is more aggressive and has a worse prognosis than TACC. TACC patients have more opportunities for local treatment, which is important for the prognosis of both TACC and LACC. Nomograms were created for TACC and LACC to aid in personalized survival predictions and clinical decisions.

Development and external validation of a machine learning model for prediction of survival in extremity leiomyosarcoma

PurposeMachine learning (ML) models have been used to predict cancer survival in several sarcoma subtypes. However, none have investigated extremity leiomyosarcoma (LMS). ML is a powerful tool that has the potential to better prognosticate extremity LMS. MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was queried for cases of histologic extremity LMS (n = 634). Patient, tumor, and treatment characteristics were recorded, and ML models were developed to predict 1-, 3-, and 5-year survival. The best performing ML model was externally validated using an institutional cohort of extremity LMS patients (n = 46). ResultsAll ML models performed best at the 1-year time point and worst at the 5-year time point. On internal validation within the SEER cohort, the best models had c-statistics of 0.75–0.76 at the 5-year time point. The Random Forest (RF) model was the best performing model and used for external validation. This model also performed best at 1-year and worst at 5-year on external validation with c-statistics of 0.90 and 0.87, respectively. The RF model was well calibrated on external validation. This model has been made publicly available at https://rachar.shinyapps.io/lms_app/ ConclusionsML models had excellent performance for survival prediction of extremity LMS. Future studies incorporating a larger institutional cohort may be needed to further validate the ML model for LMS prognostication.

Glioblastoma patients' survival and its relevant risk factors during the pre-COVID-19 and post-COVID-19 pandemic: real-world cohort study in the USA and China.

Although the COVID-19 pandemic has exerted potential impact on patients with glioblastomas (GBMs), it remains unclear whether the survival and its related risk factors of GBM patients would be altered or not during the period spanning from pre-COVID-19 to post-COVID-19 pandemic era. This study aimed to clarify the important issues above. Two observational cohorts were utilized, including the nationwide American cohort from the Surveillance, Epidemiology, and End-Results (SEER) and the Chinese glioblastoma cohort (CGC) at our institution during 2018-2020. Demographics, tumour features, treatment regimens and clinical outcomes were collected. Cox regression model, competing risk model, and subgroup and sensitivity analysis were used to dynamically estimate the survival and its relevant risk factors over different diagnosis years from the pre-COVID-19 (2018 and 2019) to post-COVID-19 (2020) pandemic. Causal mediation analysis was further adopted to explore the potential relationship between risk factors and mortality. This study included 11321 GBM cases in SEER and 226 GBM patients in CGC, respectively. Instead of the diagnostic years of 2018-2020, the prognostic risk factors, such as advanced age, bilateral tumour and absence of comprehensive therapy (surgery combined with chemoradiotherapy), were identified to persistently affect GBM survival independently during the period from 2018 to 2020 in the SEER cohort (all P < 0.05). In CGC, lack of comprehensive therapy for GBM patients were restated as survival risk factors during the same timeframe. Causal mediation analysis showed that the effect of comprehensive therapy on all-cause mortality played a determinant role (direct effect value -0.227, 95% CI -0.248 to -0.207), which was partially mediated by age (9.11%) rather than tumour laterality. As the timeframe shifted from pre-COVID-19 to post-COVID-19 pandemic, survival of GBM patients remained stable, yet advanced age, bilateral tumours, and passive treatment continuingly impacted GBM survival. It is necessary to optimize the comprehensive treatment for GBM patients even in the post-pandemic era.

The 31-Gene Expression Profile Test Outperforms AJCC in Stratifying Risk of Recurrence in Patients with Stage I Cutaneous Melanoma.

Patients with stage I cutaneous melanoma (CM) are considered at low risk for metastasis or melanoma specific death; however, because the majority of patients are diagnosed with stage I disease, they represent the largest number of melanoma deaths annually. The 31-gene expression profile (31-GEP) test has been prospectively validated to provide prognostic information independent of staging, classifying patients as low (Class 1A), intermediate (Class 1B/2A), or high (Class 2B) risk of poor outcomes. Patients enrolled in previous studies of the 31-GEP were combined and evaluated for recurrence-free (RFS) and melanoma-specific survival (MSS) (n = 1261, "combined"). A second large, unselected real-world cohort (n = 5651) comprising clinically tested patients diagnosed 2013-2018 who were linked to outcomes data from the NCI Surveillance, Epidemiology, and End Results (SEER) Program registries was evaluated for MSS. Combined cohort Class 1A patients had significantly higher RFS than Class 1B/2A or Class 2B patients (97.3%, 88.6%, 77.3%, p < 0.001)-better risk stratification than AJCC8 stage IA (97.5%) versus IB (89.3%). The SEER cohort showed better MSS stratification by the 31-GEP (Class 1A = 98.0%, Class 1B/2A = 97.5%, Class 2B = 92.3%; p < 0.001) than by AJCC8 staging (stage IA = 97.6%, stage IB = 97.9%; p < 0.001). The 31-GEP test significantly improved patient risk stratification, independent of AJCC8 staging in patients with stage I CM. The 31-GEP provided greater separation between high- (Class 2B) and low-risk (Class 1A) groups than seen between AJCC stage IA and IB. These data support integrating the 31-GEP into clinical decision making for more risk-aligned management plans.

Optimal treatment strategy and prognostic analysis for patients with non-metastatic pT4 colon adenocarcinoma.

This study endeavored to explore the optimal treatment strategy and conduct a prognostic analysis for patients diagnosed with pT4M0 (pathologic stage T4) colon adenocarcinoma (COAD). A total of 8,843 patients diagnosed with pT4M0 COAD between January 2010 and December 2015 were included in this study from the Surveillance, Epidemiology, and End Results (SEER) database. These patients were randomly divided into a training set and an internal validation set using a 7:3 ratio. Variables that demonstrated statistical significance (P<0.05) in univariate COX regression analysis or held clinical significance were incorporated into the multivariate COX regression model. Subsequently, this model was utilized to formulate a nomogram. The predictive accuracy and discriminability of the nomogram were assessed using the C-index, area under the curve (AUC), and calibration curves. Decision curve analysis (DCA) was conducted to confirm the clinical validity of the model. In the entire SEER cohort, the 3-year overall survival (OS) rate (74.22% vs. 63.20%, P<0.001) and the 3-year cancer-specific survival (CSS) rate (76.25% vs. 66.98%, P<0.001) in the surgery combined with postoperative adjuvant therapy (S+ADT) group surpassed those in the surgery (S) group. Multivariate COX regression analysis of the training set unveiled correlations between age, race, N stage, serum CEA (carcinoembryonic antigen), differentiation, number of resected lymph nodes, and treatment modalities with OS and CSS. Nomograms for OS and CSS were meticulously crafted based on these variables, achieving C-indexes of 0.692 and 0.690 in the training set, respectively. The robust predictive ability of the nomogram was further affirmed through receiver operating characteristic (ROC) and calibration curves in both the training and validation sets. In individuals diagnosed with pT4M0 COAD, the integration of surgery with adjuvant chemoradiotherapy demonstrated a substantial extension of long-term survival. The nomogram, which incorporated key factors such as age, race, differentiation, N stage, serum CEA level, tumor size, and the number of resected lymph nodes, stood as a dependable tool for predicting OS and CSS rates. This predictive model held promise in aiding clinicians by identifying high-risk patients and facilitating the development of personalized treatment plans.

Nomogram for predicting occurrence and prognosis of liver metastasis in elderly colorectal cancer patients: a population-based study.

This study aimed to explore independent risk and prognostic factors in elderly patients with colorectal cancer liver metastasis (ECRLM) and generate nomograms for predicting the occurrence and overall survival (OS) rates of such patients. Elderly colorectal cancer patients (ECRC) from 2010 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were included in this study. External validation relied on Chinese patients from the China-Japan Union Hospital of Jilin University. Univariate and multivariate logistic regression analyses were employed to identify liver metastasis (LM) risk variables, which were used to create a nomogram to estimate LM probabilities in patients with ECRC. Univariate and multivariable Cox analyses were performed to identify prognostic variables and further derive nomograms that could predict the OS of patients with ERCLM. Differences in lifespan were assessed using the Kaplan-Meier analysis. Finally, the quality of the nomograms was verified using decision curve analysis (DCA), calibration curves, and receiver operating characteristic curves (ROC). In the SEER cohort, 32,330 patients were selected, of those, 3,012 (9.32%) were diagnosed with LM. A total of 188 ECRLM cases from a Chinese medical center were assigned for external validation. LM occurrence can be affected by 13 factors, including age at diagnosis, marital status, race, bone metastases, lung metastases, CEA level, tumor size, Grade, histology, primary site, T stage, N stage and sex. Furthermore, in ECRLM patients, 10 variables, including age at diagnosis, CEA level, tumor size, lung metastasis, bone metastasis, chemotherapy, surgery, N stage, grade, and race, have been shown to be independent prognostic predictors. The results from both internal and external validation revealed a high level of accuracy in predicting outcomes, as well as significant clinical utility, for the two nomograms. We created two nomograms to predict the occurrence and prognosis of LM in patients with ECRC, which would contribute significantly to the improvement in disease detection accuracy and the formulation of personalized cures for that particular demographic.

Differences in Survival between Black and White Patients with Head and Neck Squamous Cell Carcinoma: Comparison of Data from the DOD Central Cancer Registry and SEER.

Barriers to health care access may contribute to the poorer survival of Black patients with head and neck squamous cell carcinoma (HNSCC) than their White counterparts in the U.S. general population. The Department of Defense's (DOD) Military Health System (MHS) provides universal health care access to all beneficiaries with various racial backgrounds. We compared overall survival of patients with HNSCC by race in the MHS and the general population, respectively, to assess whether there were differences in racial disparity between the two populations. The MHS patients were identified from the DOD's Central Cancer Registry (CCR) and the patients from the U.S. general population were identified from the NCI's Surveillance, Epidemiology and End Results (SEER) program. For each cohort, a retrospective study was conducted comparing survival by race. Black and White patients in the CCR cohort had similar survival in multivariable Cox regression models with a HR of 1.04 and 95% confidence interval (95% CI) of 0.81 to 1.33 after adjustment for the potential confounders. In contrast, Black patients in the SEER cohort exhibited significantly worse survival than White patients with an adjusted HR of 1.47 (95% CI = 1.43-1.51). These results remained similar in the subgroup analyses for oropharyngeal and non-oropharyngeal sites, respectively. There was no racial difference in survival among patients with HNSCC in the MHS system, while Black patients had significantly poorer survival than White patients in the general population. Equal access to health care could reduce racial disparity in overall survival among patients with HNSCC.

Development and validation of a predictive model associated with lymph node metastasis of gastric signet ring carcinoma patients.

The risk factors for lymph node metastasis (LNM) in patients with gastric signet ring cell carcinoma (GSRC) have not been well-defined. This study was designed to prognosticate LNM in patients with GSRC by constructing and verifying a nomogram. A total of 2789 patients with GSRC from the Surveillance, Epidemiology, and End Results (SEER) database and Yijishan Hospital of Wannan Medical College (YJS) were retrospectively reviewed. A predictive model was established using logistic regression based on the SEER cohort. The performance of the model was evaluated using the concordance index (C-index) and decision curve analysis (DCA). In addition, its robustness was validated using the YJS cohort. Four independent predictors of LNM were identified in the SEER cohort. Next, a nomogram was constructed by incorporating these predictors. The C-index were 0.800 (95% confidence interval [CI] = 0.781-0.819) and 0.837 (95% CI = 0.784-0.890) in the training and external validation cohorts, respectively. The outcomes of DCA supported good clinical benefits. The proposed model for evaluating the LNM in patients with GSRC can help to avoid the misdiagnosis risk of N-stage, assist to screen the population suitable for neoadjuvant therapy and help clinicians to optimize clinical decisions.

Establishment and validation of a nomogram to select patients with metastatic sarcomatoid renal cell carcinoma suitable for cytoreductive radical nephrectomy

IntroductionMetastatic renal cell carcinoma (mRCC) with sarcomatoid features has a poor prognosis. Cytoreductive radical nephrectomy (CRN) can improve prognosis, but patient selection is unclear. This study aimed to develop a prediction model for selecting patients suitable for CRN.Materials and methodsPatients with a diagnosis of mRCC with sarcomatoid features in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 were retrospectively reviewed. CRN benefit was defined as a survival time longer than the median overall survival (OS) in patients who did not receive CRN. A prediction nomogram was established and validated using the SEER cohort (training and internal validation) and an external validation cohort.ResultsOf 900 patients with sarcomatoid mRCC, 608 (67.6%) underwent CRN. OS was longer in the CRN group than in the non-CRN group (8 vs. 6 months, hazard ratio (HR) = 0.767, p = 0.0085). In the matched CRN group, 124 (57.7%) patients survived &amp;gt;6 months after the surgery and were considered to benefit from CRN. Age, T-stage, systematic therapy, metastatic site, and lymph nodes were identified as independent factors influencing OS after CRN, which were included in the prediction nomogram. The monogram performed well on the training set (area under the receiver operating characteristic (AUC) curve = 0.766, 95% confidence interval (CI): 0.687–0.845), internal validation set (AUC = 0.796, 95% CI: 0.684–0.908), and external validation set (AUC = 0.911, 95% CI: 0.831–0.991).ConclusionsA nomogram was constructed and validated with good accuracy for selecting patients with sarcomatoid mRCC suitable for CRN.

Elderly patients with stage II gastric cancer do not benefit from adjuvant chemotherapy

BackgroundWith the aging of the population, the burden of elderly gastric cancer (EGC) increases worldwide. However, there is no consensus on the definition of EGC and the efficacy of adjuvant chemotherapy in patients with stage II EGC. Here, we investigated the effectiveness of adjuvant chemotherapy in defined EGC patients.MethodsWe enrolled 5762 gastric cancer patients of three independent cohorts from the Sixth Affiliated Hospital of Sun Yat-sen University (local), the Surveillance, Epidemiology, and End Results (SEER), and the Asian Cancer Research Group (ACRG). The optimal age cutoff for EGC was determined using the K-adaptive partitioning algorithm. The defined EGC group and the efficacy of adjuvant chemotherapy for them were confirmed by Cox regression and Kaplan–Meier survival analyses. Furthermore, gene set variation analyses (GSVA) were performed to reveal pathway enrichment between groups.ResultsThe optimal age partition value for EGC patients was 75. In the local, SEER, and ACRG cohorts, the EGC group exhibited significantly worse overall survival and cancer-specific survival than the non-EGC group (P < 0.05) and was an independent risk factor. Stratified analyses based on chemotherapy showed that EGC patients derived little benefit from adjuvant chemotherapy. Furthermore, GSVA analysis revealed the activation of DNA repair-related pathways and downregulation of the p53 pathway, which may partially contribute to the observed findings.ConclusionIn this retrospective, international multi-center study, 75 years old was identified as the optimal age cutoff for EGC definition, and adjuvant chemotherapy proved to be unbeneficial for stage II EGC patients.

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.

Prognostic Value of Tumor Deposits in Stage III Colorectal Cancer Patients with Different N Stages: A Population-Based, Retrospective, Cohort Study.

Tumor deposits (TDs) seem to be associated with the prognosis of patients with colorectal cancer (CRC). The goal of this study was to investigate the prognostic value of TDs among patients with stage III CRC at different N stages. A retrospective analysis was performed on two independent cohorts of stage III CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database (n = 8232) and the First Affiliated Hospital of Wenzhou Medical University (n = 423). Primary outcomes were overall survival (OS) and cancer-specific survival (CSS). Of 8232 patients in the SEER cohort, the presence of TDs revealed poorer 5-year OS rates and 5-year CSS rates in all N-stage subgroups. X-tile software identified 5 (5-year OS: P = 0.004; 5-year CSS: P < 0.001) as the optimal cutoff value for TD count in the TD-positive subgroup at the N2 stage. The OS (5-year OS: 62.0% vs. 42.0%, P < 0.001) and CSS (5-year CSS: 66.0% vs. 43.8%, P < 0.001) of patients with five or more TDs were significantly worse than those with one to four TDs in the N2 stage subgroups. Of 423 patients in the Wenzhou cohort, the 3-year OS rate for patients in the positive group was worse than that for patients in the negative group (88.7% vs. 94.3%, P = 0.015). TD count should be considered when evaluating the prognosis of patients with the N2 stage. Those with higher TD counts (≥5) might have a worse prognosis.

A Comparative Population-Based Study of Tracheal and Lung Adenoid Cystic Carcinoma

Thoracic adenoid cystic carcinoma (ACC) is very rare, and its clinicopathological characteristics, treatment and prognosis have not been fully elucidated. Previous studies did not differentiate between tracheal and lung lesions. We identified tracheal ACC (TACC) and lung and bronchus ACC (LACC) patients from our cancer center (from 2005 to 2022) and the Surveillance, Epidemiology, and End Results (SEER) database (from 2000 to 2009). Incidence was calculated and trends were quantified. Significant prognostic factors for overall survival (OS) were reviewed and analyzed by using Cox proportional hazards regression. Then, two nomograms predicting OS of TACC and LACC were constructed based on the SEER database and validated externally by using the separate cohort. There was an upward trend from 2000 to 2019 for LACC while a downward trend from 2000 to 2009 was shown for TACC. Totally, 55 TACC and 25 LACC were included in our cohort, 121 TACC and 162 LACC included in the SEER cohort. There were larger tumor sizes, more lymph nodes and distant metastases for LACC patients than TACC patients. The proportion of patients receiving radiotherapy were higher for TACC than LACC. More patients with TACC received surgery and perioperative radiotherapy than those with LACC. Patients with LACC had significantly worse OS than patients with TACC (SEER cohort: 93.7 mons vs. 127.0 mons, p = 0.001, our cohort: 72.2 months vs. 130.8months, p = 0.061). Age, lymph node metastasis, distant metastasis and radiation and/or surgery were identified as independent prognostic factors for OS of TACC. Laterality, distant metastasis and surgery were identified for LACC. The discrimination of the nomogram revealed good prognostic accuracy and clinical applicability as indicated by C-index values of 0.753 and 0.833 for the training cohort and the external validation cohort for TACC, and 0.739 and 0.786 for LACC. TACC and LACC are different in incidence, clinical features, prognosis. Compared with LACC, radiotherapy combined with surgery is more important for TACC. Two nomograms were established for TACC and LACC respectively to help physicians make more individualized survival predictions and clinical decisions.

Subsite-specific metastatic organotropism and risk in gastric cancer: A population-based cohort study of the US SEER database and a Chinese single-institutional registry.

Studies exploring whether metastatic organotropism and risk in gastric cancer (GC) differ by primary anatomical site are scarce. This study included 15,260 and 1623 patients diagnosed with GC from the Surveillance, Epidemiology, and End Results (SEER) registry database and the Nanfang Hospital in China, respectively. Patients were stratified according to primary site of GC, and the incidence of metastasis to different organs was used to determine the metastatic organotropism for each GC subsite. Finally, the metastatic organotropism and risk were compared among the different subsite groups. Liver metastasis was the most common metastasis site in cardia GC, whereas other-site metastases were more common in the body, antrum, overlapping lesions, and unspecified GCs. Liver and other-site metastases were also frequently observed in the fundus, pylorus, lesser curvature, and greater curvature GCs. Patients with GC with definite primary tumor sites in the SEER and validation Nanfang hospital cohorts were compared by grouping as proximal and distal GCs for further analysis. In the SEER cohort, the top three metastatic sites of proximal GC were liver (21.4%), distant lymph node (LN) (14.6%), and other-site (mainly peritoneum, 11.9%), whereas those of distal GC were other-site (mainly peritoneum, 19.5%), liver (11.8%), and distant LN (9.5%). The incidence of metastasis to the liver, distant LN, lung, and brain was significantly higher in patients with proximal GC than in those with distal GC in both the SEER and Nanfang cohorts (p < 0.05). However, metastasis to other-site/peritoneum was significantly lower in patients with proximal GC compared to those with distal GC in the Nanfang Hospital and SEER cohorts, respectively (p < 0.05). Liver and distant LN are the preferred metastatic sites for proximal GC, whereas peritoneal metastasis is more common in distal GC. Proximal GC has a higher risk of lymphatic and hematogenous metastases, and a lower risk of transcoelomic metastasis than distal GC. Our findings highlight the need to stratify GC by its primary subsite to aid in planning and decision-making related to metastatic management in clinical practice.

Development and external validation of a machine learning model for prediction of survival in undifferentiated pleomorphic sarcoma.

Machine learning (ML) algorithms to predict cancer survival have recently been reported for a number of sarcoma subtypes, but none have investigated undifferentiated pleomorphic sarcoma (UPS). ML is a powerful tool that has the potential to better prognosticate UPS. The Surveillance, Epidemiology, and End Results (SEER) database was queried for cases of histologically confirmed undifferentiated pleomorphic sarcoma (UPS) (n = 665). Patient, tumor, and treatment characteristics were recorded, and ML models were developed to predict 1-, 3-, and 5-year survival. The best performing ML model was externally validated using an institutional cohort of UPS patients (n = 151). All ML models performed best at the 1-year time point and worst at the 5-year time point. On internal validation within the SEER cohort, the best models had c-statistics of 0.67-0.69 at the 5-year time point. The Multi-Layer Perceptron Neural Network (MLP) model was the best performing model and used for external validation. Similarly, the MLP model performed best at 1-year and worst at 5-year on external validation with c-statistics of 0.85 and 0.81, respectively. The MLP model was well calibrated on external validation. The MLP model has been made publicly available at https://rachar.shinyapps.io/ups_app/ . Machine learning models perform well for survival prediction in UPS, though this sarcoma subtype may be more difficult to prognosticate than other subtypes. Future studies are needed to further validate the machine learning approach for UPS prognostication.

Sarcomatoid Urothelial Carcinoma Is Associated With Limited Response to Neoadjuvant Chemotherapy and Poor Oncologic Outcomes After Radical Cystectomy.

To examine oncologic outcomes and response to neoadjuvant chemotherapy (NAC) in patients with sarcomatoid urothelial carcinoma (SUC) treated with radical cystectomy (RC). We retrospectively queried our institutional database (2003-18) and Surveillance, Epidemiology, and End Results (SEER)-Medicare (2004-2015) for patients with cT2-4, N0-2, M0 SUC and conventional UC (CUC) treated with RC. Clinicopathologic characteristics were described using descriptive statistics (t test, χ2-test and log-rank-test for group comparison). Overall (OS) and recurrence-free-survival (RFS) after RC were estimated with the Kaplan Meier method and associations with OS were evaluated with Cox proportional hazards models. We identified 38 patients with SUC and 287 patients with CUC in our database, and 190 patients with SUC in SEER-Medicare. In the institutional cohort, patients with SUC versus CUC had higher rates of pT3/4 stage (66% vs. 35%, P < 0.001), lower rates of ypT0N0 (6% vs. 35%, P=.02), and worse median OS (17.5 vs. 120 months, P < .001). Further, patients with SUC in the institutional versus SEER-Medicare cohort had similar median OS (17.5 vs. 21 months). In both cohorts, OS was comparable between patients with SUC undergoing NAC+RC vs. RC alone (17.5 vs. 18.4 months, P=.98, institutional cohort; 24 vs. 20 months, P=.56, SEER cohort). In Cox proportional hazards models for the institutional RC cohort, SUC was independently associated with worse OS (HR 2.3, CI 1.4-3.8, P=.001). SUC demonstrates poor pathologic response to NAC and worse OS compared with CUC, with no OS benefit associated with NAC. A unique pattern of rapid abdominopelvic cystic recurrence was identified.

Survival benefit of active surveillance for papillary thyroid carcinoma: a propensity score matching analysis based on SEER database.

Over-treatment of papillary thyroid microcarcinoma (PTMC) has become a common issue. Although active surveillance (AS) has been proposed as an alternative treatment to immediate surgery for PTMC, its inclusion criteria and mortality risk have not been clearly defined. The purpose of this study was to investigate whether surgery can achieve significant survival benefits in patients with larger tumor diameter of papillary thyroid carcinoma (PTC), in order to evaluate the feasibility of expanding the threshold for active surveillance. This study retrospectively collected data of patients with papillary thyroid carcinoma from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2019. The propensity score matching (PSM) method was used to minimize confounding factors and selection bias between the surgery and non-surgery groups, and to compare the clinical and pathological characteristics between the two groups based on the SEER cohort. Meanwhile, the impact of surgery on prognosis was compared using Kaplan-Meier estimates and Cox proportional hazard models. A total of 175,195 patients were extracted from the database, including 686 patients who received non-surgical treatment, and were matched 1:1 with patients who received surgical treatment using propensity score matching. The Cox proportional hazard forest plot showed that age was the most important factor affecting overall survival (OS) of patients, while tumor size was the most important factor affecting disease-specific survival (DSS) of patients. In terms of tumor size, there was no significant difference in DSS between PTC patients with tumor size of 0-1.0cm who underwent surgical treatment and those who underwent non-surgical treatment, and the relative survival risk began to increase after the tumor size exceeded 2.0cm. Additionally, the Cox proportional hazard forest plot showed that chemotherapy, radioactive iodine, and multifocality were negative factors affecting DSS. Moreover, the risk of death increased over time, and no plateau phase was observed. For patients with papillary thyroid carcinoma (PTC) staged as T1N0M0, AS is a feasible management strategy. As the tumor diameter increases, the risk of death without surgical treatment gradually increases, but there may be a threshold. Within this range, a non-surgical approach may be a potentially viable management strategy. However, beyond this range, surgery may be more beneficial for patient survival. Therefore, it is necessary to conduct more large-scale prospective randomized controlled trials to further confirm these findings.

Clinical and treatment characteristics of secondary bladder malignancies following low dose rate brachytherapy for prostate cancer.

To characterize the clinical course and prognosis of bladder malignancies associated with prior prostate brachytherapy SUBJECTS/PATIENTS AND METHODS: We queried our institutional database for patients with bladder cancer (BC) diagnosed between January 2005 and April 2019 who had previously undergone low dose rate (LDR) prostate brachytherapy. Patients diagnosed with BC at least 1 year following LDR prostate brachytherapy with or without external beam radiation therapy were included. Clinical and disease-specific characteristics were abstracted from chart review and survival outcomes were estimated using Kaplan-Meier estimates. We compared the pathologic characteristics and prognosis of secondary BCs in our study cohort to those of BCs diagnosed after prostate cancer managed without radiation reported by the Surveillance, Epidemiology, and End Results (SEER) populational database from 2005 to 2018. Three hundred seventy-five patients were identified with combined diagnosis of prostate cancer and BC, 51 of whom met inclusion criteria in the study cohort. Median times from brachytherapy to BC diagnosis for the study and SEER cohort were 9.5 ± 4.5 and 6.3 ± 4.1 years, respectively. Compared to the SEER cohort, significantly greater proportion of BC from the study cohort presented with high-grade (study: 78.4%, SEER: 52.3%, P = 0.0008) and with MIBC (Study BC 35.3%, SEER BC: 17.5%, P = 0.0009). The study and the SEER cohort had similar 5-year overall survival (study: 67.9%, SEER: 58.0%, P = 0.1099), and 5-year cancer-specific survival (study: 81.0%, SEER: 82.8%, P = 0.5559). The 5-year progression-free survival for the study cohort was 43.7% (95% CI: 28.8-57.7). Compared to bladder cancers following prostate cancer managed without radiation, bladder malignancies following prostate LDR brachytherapy present with higher grade and are more likely to be muscle invasive. Despite the aggressive presenting features of postprostate brachytherapy BC, there were no differences in overall and cancer-specific survival between the groups.

Evaluation of the prognostic value of negative to positive lymph node ratio in gastric cancer: results from multi-institutional cohorts from western and eastern datasets - Cohort study.

The authors evaluated the clinical significance of the Rnp stage in 7660 GC patients from three high-volume institutions in China. Meanwhile, the authors verified the value of the Rnp stage in 11234 GC patients from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were stratified into different subgroups based on the N stage of the eighth edition of the TNM staging system, the ratio of positive to detected LNs (Rpd) and Rnp. The survival analysis showed clear differences between the three LN stages in both the China and Surveillance, Epidemiology, and End Results cohorts. In univariate and multivariate analyses, the Rnp stage provided smaller Akaike information criterion or Bayesian information criterion values and a larger likelihood ratio χ2 than the N or Rpd stages in both two cohorts. For patients with inadequate examined LNs (<16), the Rnp stage showed better prognostic evaluation performance than the other two stages. In addition, the 5-year disease-specific survival of GC patients showed a slight variation with increasing LNs in the same subgroup classified by the Rnp or Rpd stages compared to the N stage. Along with the higher prognostic value, the Rnp stage has excellent universality with GC patients compared to the N or Rpd stages. Studies with larger sample sizes are needed to predict the prognosis and provide more precise treatment for GC patients.