Nomograms predict survival of patients with small bowel adenocarcinoma: a SEER-based study

Development and validation of a nomogram for predicting cancer-specific survival in small-bowel adenocarcinoma patients using the SEER database

BACKGROUND

Small bowel adenocarcinoma (SBA) is a rare gastrointestinal malignancy forwhich survival is hampered by late diagnosis, complex responses to treatment, and poor prognosis. Accurate prognostic tools are crucial for optimizing treatment strategies and improving patient outcomes. This study aimed to develop and validate a nomogram based on the Surveillance, Epidemiology, and End Results (SEER) database to predict cancer-specific survival (CSS) in patients with SBA and compare it to traditional American Joint Committee on Cancer (AJCC) staging.

METHODS

We analyzed data from 2,064 patients diagnosed with SBA between 2010 and 2020 from the SEER database. Patients were randomly assigned to training and validation cohorts (7:3 ratio). Kaplan‒Meier survival analysis, Cox multivariate regression, and nomograms were constructed for analysis of 3-year and 5-year CSS. The performance of the nomograms was evaluated using Harrell's concordance index (C-index), the area under the receiver operating characteristic (ROC) curve, calibration curves, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

RESULTS

Multivariate Cox regression identified sex, age at diagnosis, marital status, tumor site, pathological grade, T stage, N stage, M stage, surgery, retrieval of regional lymph nodes (RORLN), and chemotherapy as independent covariates associated with CSS. In both the training and validation cohorts, the developed nomograms demonstrated superior performance to that of the AJCC staging system, with C-indices of 0.764 and 0.759, respectively. The area under the curve (AUC) values obtained by ROC analysis for 3-year and 5-year CSS prediction significantly surpassed those of the AJCC model. The nomograms were validated using calibration and decision curves, confirming their clinical utility and superior predictive accuracy. The NRI and IDI indicated the enhanced predictive capability of the nomogram model.

CONCLUSION

The SEER-based nomogram offers a significantly superior ability to predict CSS in SBA patients, supporting its potential application in clinical decision-making and personalized approaches to managing SBA to improve survival outcomes.

Clinicopathological Characteristics, Treatment and Prognosis in Duodenal Adenocarcinoma with Liver Metastasis: A SEER-Based Study

Background and Objectives

Duodenal adenocarcinoma (DAC) is a rare tumor that is often accompanied by liver metastasis in advanced stages. The aim of this study was to evaluate the correlation between clinicopathological characteristics and survival in DAC patients with liver metastasis, and to explore appropriate treatment options.

Methods

482 DAC patients with liver metastasis were retrospectively identified from the Surveillance, Epidemiology and End Results (SEER) database (2011-2020). Univariate and multivariate Cox regression analyses were performed to explore the clinicopathological factors related to survival. The Kaplan-Meier method was used to identify the independent risk factors associated with survival.

Results

The 1-year overall survival (OS) and cancer-specific survival (CSS) rates for the entire cohort were 25.4% and 28.3%, and the 5-year OS and CSS rates were 2.4% and 2.9% respectively. Univariable analysis and multivariate analysis identified chemotherapy and surgery as the independent risk factors for OS and CSS. Patients who underwent chemotherapy and surgery had better CSS and OS rates, whereas radiotherapy failed to improve outcomes.

Conclusion

We identified several prognostic factors of DAC with liver metastasis. Chemotherapy and surgery can prolong the survival of DAC patients with liver metastasis, which lays the foundation for identifying the optimal treatment strategy.

Progress of the application clinical prediction model in polycystic ovary syndrome

Clinical prediction models play an important role in the field of medicine. These can help predict the probability of an individual suffering from disease, complications, and treatment outcomes by applying specific methodologies. Polycystic ovary syndrome (PCOS) is a common disease with a high incidence rate, huge heterogeneity, short- and long-term complications, and complex treatments. In this systematic review study, we reviewed the progress of clinical prediction models in PCOS patients, including diagnosis and prediction models for PCOS complications and treatment outcomes. We aimed to provide ideas for medical researchers and clues for the management of PCOS. In the future, models with poor accuracy can be greatly improved by adding well-known parameters and validations, which will further expand our understanding of PCOS in terms of precision medicine. By developing a series of predictive models, we can make the definition of PCOS more accurate, which can improve the diagnosis of PCOS and reduce the likelihood of false positives and false negatives. It will also help discover complications earlier and treatment outcomes being known earlier, which can result in better outcomes for women with PCOS.

Mismatch repair deficiency as prognostic factor for stage III small bowel adenocarcinoma: A multicentric international study

BACKGROUND

Small bowel adenocarcinoma (SBA) is a rare cancer with an aggressive behavior. No study has specifically addressed the putative prognostic role of mismatch repair status in stage III SBAs.

AIMS

We aimed to investigate whether mismatch repair deficiency is associated with cancer-specific survival in a Western cohort of patients with stage III SBAs.

METHODS

In this retrospective multicentric international cohort study, we enrolled 70 patients who underwent surgically resection for stage III SBAs and we analyzed the frequency of mismatch repair deficiency, tested by immunohistochemistry for mismatch repair proteins and by polymerase chain reaction for microsatellite instability, and its association with cancer-specific survival and other clinic-pathologic factors.

RESULTS

We found sixteen (23%) patients with mismatch repair deficient adenocarcinoma, without discordance between immunohistochemical and polymerase chain reaction for microsatellite instability analyses. Mismatch repair deficiency proved to be associated with a better outcome both at univariable analysis (hazard ratio: 0.28, 95% confidence interval: 0.08-0.91, p: 0.035) and in bivariable models adjusted for patient age or gender, tumor site, pT4 stage, tumor budding, and perineural invasion.

CONCLUSION

This study highlights the importance of testing mismatch repair status to improve prognostic stratification in stage III SBAs.

Prediction of distant metastasis and specific survival prediction of small intestine cancer patients with metastasis: A population-based study

BACKGROUND

Small intestine cancer (SIC) is difficult to diagnose early and presents a poor prognosis due to distant metastasis. This study aimed to develop nomograms for diagnosing and assessing the prognosis of SIC with distant metastasis.

METHODS

Patients diagnosed with SIC between 2010 and 2015 were included from the Surveillance, Epidemiology and End Results database. Univariate and multifactor analysis determined independent risk factors for distant metastasis and prognostic factors for overall and cancer-specific survival. We then constructed the corresponding three nomograms and assessed the diagnostic accuracy of the nomograms by net reclassification improvement, receiver operating characteristic curves and calibration curves, assessed the clinical utility by decision curve analysis.

RESULTS

The cohort consisted of 6697 patients, of whom 1299 had distant metastasis at diagnosis. Tstage, Nstage, age, tumor size, grade, and histological type were independent risk factors for distant metastasis. Age, histological type, T stage, N stage, grade, tumor size, whether receiving surgery, number of lymph nodes removed, and the presence of bone or lung metastases were predictors of both overall survival and cancer-specific survival. The nomograms showed excellent accuracy in predicting distant metastasis and prognosis.

CONCLUSION

Nomograms were developed and validated for SIC patients with distant metastasis, aiding physicians in making rational and personalized clinical decisions.

Incidence and risk factors of cardiovascular mortality in patients with gastrointestinal adenocarcinoma

BACKGROUND

Gastrointestinal (GI) cancers are common and fatal. Improved cancer-directed therapies, with thier substantial role in improving cancer-specific survival, may increase non-cancer mortality-including cardiovascular mortality-in these patients.

AIM

To identify the risk factors of cardiovascular mortality in GI adenocarcinoma patients.

METHODS

Data of GI adenocarcinoma patients were gathered from the Surveillance, Epidemiology, and End Results database. We used Pearson's chi-square test to assess the relationships between categorical variables. We used the Kaplan-Meyer test in the univariate analysis and Cox regression test for the multivariate analysis.

RESULTS

Among 556,350 included patients, 275,118 (49.6%) died due to adenocarcinoma, 64,079 (11.5%) died due to cardiovascular causes, and 83,161 (14.9%) died due to other causes. Higher rates of cardiovascular mortality were found in patients ≥ 50 years (HR, 8.476; 95% CI, 7.91-9.083), separated (HR, 1.27; 95% CI, 1.184-1.361) and widowed (HR, 1.867; 95% CI, 1.812-1.924), patients with gastric (HR, 1.18; 95% CI, 1.1-1.265) or colorectal AC (HR, 1.123; 95% CI, 1.053-1.198), and patients not undergone surgery (HR, 2.04; 95% CI, 1.958-2.126). Lower risk patients include females (HR, 0.729; 95% CI, 0.717-0.742), blacks (HR, 0.95; 95% CI, 0.924-0.978), married (HR, 0.77; 95% CI, 0.749-0.792), divorced (HR, 0.841; 95% CI, 0.807-0.877), patients with pancreatic AC (HR, 0.83; 95% CI, 0.757-0.91), and patients treated with chemotherapy (HR, 0.416; 95% CI, 0.406-0.427).

CONCLUSIONS

Risk factors for cardiovascular mortality in GI adenocarcinoma include advanced age, males, whites, separated and widowed, gastric or colorectal adenocarcinoma, advanced grade or advanced stage of the disease, no chemotherapy, and no surgery. Married and divorced, and patients with pancreatic adenocarcinoma have a lower risk.

Clinicopathological characteristics and prognostic factors of elderly small intestine adenocarcinoma using propensity score matching analysis: a study based on SEER database

BACKGROUND

Small intestine adenocarcinoma (SIA) is a scant disease that has no adequate clinical trials, so its prognostic factors are still unclear, especially in elderly patients. In this article, we aimed to explore the clinicopathology presentation, treatments, outcomes, and predictors of small intestine adenocarcinoma patients aged 65 years or older.

METHODS

We retrieved clinicopathology data of small intestine adenocarcinoma patients diagnosed between 2004 and 2015 from the Surveillance Epidemiology and End Results (SEER) database. We clarified patients into two groups: the surgery and the non-surgery group and conducted propensity score matching (PSM) to compare survival outcoming. We identified the prognostic indicators for cancer-specific survival (CSS) and overall survival (OS) by the Cox proportional hazards model.

RESULTS

In total, 1018 eligible cases were enrolled, with a median survival of 16 months; the 3-year OS and CSS rates were 36% and 41.7%, and the 5-year OS and CSS rates were 26.5% and 33.3%. Multivariate analyses revealed that age, grade, tumor stage, surgery, and chemotherapy were independent prognostic factors for OS, while grade, tumor stage, surgery, radiation, and chemotherapy were independent factors for CSS. After PSM, only surgery and tumor stage (AJCC 6th) were independent prognostic factors for OS and CSS.

CONCLUSION

Surgery could bring benefit to survival for elderly SIA patients, and the early stage of the disease was another significant prognostic factor.

Localized Small Bowel Adenocarcinoma Management: Evidence Summary

Small bowel cancers are rare diseases whose prognosis is poorer than that of colon cancers. Due to disease rarity, there is little data on small bowel adenocarcinoma (SBA) treatment, and most recommendations come from expert agreements or analogies to the management of colon cancer. Although relatively high rates of local recurrence are observed for duodenal malignancies, distant metastatic relapse remains common and requires adjuvant systemic therapy. Given the similarities between SBA and colorectal cancer, radiotherapy and chemotherapy strategies used for the latter disease are frequently pursued for the former disease, specifically for tumors located in the duodenum. However, no previous randomized study has evaluated the benefit of adjuvant chemotherapy on the overall survival of SBA patients. Most previous studies on treatment outcomes and prognostic factors in this context were based on large international databases, such as the Surveillance, Epidemiology, and End Results or the National Cancer Database. Studies are required to establish and validate prognostic and predictive markers relevant in this context to inform the use of (neo) adjuvant treatment. Among those, deficient mismatch repair tumors represent 20% of SBAs, but their impact on chemosensitivity remains unknown. Herein, we summarize the current evidence on the management of localized SBA, including future perspectives.

Outcomes of Patients with Small Intestine Adenocarcinoma in a Canadian Province: A Retrospective Multi-Center Population-Based Cohort Study

Background: Small intestine adenocarcinoma is a rare cancer. The current study aims to determine the outcomes of patients with small intestine adenocarcinoma in a Canadian province. Methods: This retrospective population-based cohort study assessed patients with small intestine adenocarcinoma who were diagnosed from 2008 to 2017 in Saskatchewan. A Cox proportional multivariate regression analysis was performed to determine the correlation between survival and exploratory factors. Results: 112 eligible patients with a median age of 73 years and M:F of 47:53 were identified. Overall, 75% had a comorbid illness, and 45% had a WHO performance status >1. Of the 112 patients, 51 (46%) had early-stage disease and 61 (54%) had advanced-stage disease. The median overall survival (mOS) was as follows: stage one, 59 months; stage two, 30 months; stage three, 20 months; and stage four, 3 months (p < 0.001). The median disease-free survival of patients with stage three disease who received adjuvant chemotherapy was 26 months (95% CI:23.1−28.9) vs. 4 months (0.0−9.1) with observation (p = 0.04). Patients who received chemotherapy for advanced disease had a mOS of 10 months (3.5−16.5) vs. 2 months (0.45−3.6) without chemotherapy (p < 0.001). In the multivariate analysis, stage four disease, hazard ratio (HR), 3.20 (1.84−5.40); WHO performance status >1, HR, 2.22 (1.42−3.45); lack of surgery, HR, 2.10 (1.25−3.50); and a neutrophil:lymphocyte ratio of >4.5, HR, 1.72 (1.10−2.71) were significantly correlated with inferior survival. Conclusions: Most patients with small intestine adenocarcinoma were diagnosed with advanced-stage disease. Advanced-stage disease, poor performance status, lack of surgery and a baseline neutrophil:lymphocyte ratio >4.5 were correlated with inferior survival.

Development of a Deep Learning Model for Malignant Small Bowel Tumors Survival: A SEER-Based Study

Background This study aims to explore a deep learning (DL) algorithm for developing a prognostic model and perform survival analyses in SBT patients. Methods The demographic and clinical features of patients with SBTs were extracted from the Surveillance, Epidemiology and End Results (SEER) database. We randomly split the samples into the training set and the validation set at 7:3. Cox proportional hazards (Cox-PH) analysis and the DeepSurv algorithm were used to develop models. The performance of the Cox-PH and DeepSurv models was evaluated using receiver operating characteristic curves, calibration curves, C-statistics and decision-curve analysis (DCA). A Kaplan−Meier (K−M) survival analysis was performed for further explanation on prognostic effect of the Cox-PH model. Results The multivariate analysis demonstrated that seven variables were associated with cancer-specific survival (CSS) (all p < 0.05). The DeepSurv model showed better performance than the Cox-PH model (C-index: 0.871 vs. 0.866). The calibration curves and DCA revealed that the two models had good discrimination and calibration. Moreover, patients with ileac malignancy and N2 stage disease were not responding to surgery according to the K−M analysis. Conclusions This study reported a DeepSurv model that performed well in CSS in SBT patients. It might offer insights into future research to explore more DL algorithms in cohort studies.

Development and validation of a nomogram for primary duodenal carcinoma: a multicenter, population-based study

Aim: This study aimed to develop a predictive model for patients with duodenal carcinoma. Methods: Duodenal carcinoma patients from the Surveillance, Epidemiology, and End Results database (2010-2015) and the First Affiliated Hospital of Nanchang University (2010-2021) were enrolled. A nomogram was constructed according to least absolute shrinkage and selection operator regression analysis, the Akaike information criterion approach and Cox regression analysis. Results: Five independent prognostic factors were significantly associated with the prognosis of the duodenal carcinoma patients. A nomogram was constructed with a C-index in the training and validation cohorts of 0.671 (95% CI: 0.578-0.716) and 0.662 (95% CI: 0.529-0.773), respectively. Conclusion: The established nomogram model provided visualization of the risk of each prognostic factor.

Metastasis Pattern and Survival Analysis in Primary Small Bowel Adenocarcinoma: A SEER-Based Study

Background: Small bowel adenocarcinoma (SBA) is a rare gastrointestinal tumor with high malignancy. The aim of this study was to comprehensively evaluate the distant metastasis pattern and establish nomograms predicting survival for SBA. Methods: From 2010 to 2015, patients diagnosed with SBA were identified based on the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier survival analysis was applied to compare survival differences between metastasis patterns. Then, univariate and multivariate cox analyses were applied to screened out independent prognostic factors of cancer-specific survival (CSS) and overall survival (OS), and identify the risk factors for metastasis of SBA. To assess the discrimination and calibration of nomograms, the concordance index (C-index), calibration curves, receiver-operating characteristic curve (ROC), and decision curve analysis (DCA) were calculated. Results: Kaplan-Meier curves revealed that metastasis patterns were significantly correlated with CSS (p < 0.001) and OS (p < 0.001). Then, the metastasis pattern was showed to be an independent prognostic factor of OS and CSS in patients with SBA, as well as age, grade, T stage, N stage, surgery, retrieval of regional lymph nodes, and chemotherapy. Combining these factors, we constructed prognostic nomograms, which suggested that the metastasis pattern made the greatest contribution to the survival of patients with SBA. Nomograms for OS and CSS had a C-index of 0.787 and 0.793, respectively. Calibration curves showed an excellent agreement between probability and actual observation in the training and validation cohort. Decision curve analysis also exhibited its clinical value with an improved net benefit. In addition, the models we constructed had better prognostic accuracy and clinical utility than traditional TNM staging based on C-index and ROC. Further, Cox regression analysis showed that old age, poor differentiation, N2, and not receiving chemotherapy were the risk factors for prognosis in patients with metastatic SBA. Conclusion: As an independent prognostic factor, the metastasis pattern exhibited the greatest predictive effect on OS and CSS for patients with SBA. Adjuvant chemotherapy had a positive effect on the survival of patients with SBA. Nomograms for predicting 3-and 5-year OS and CSS of patients with SBA were constructed, which could identify patients with higher risk and might be superior in predicting the survival of patients with SBA than TNM staging.