Construction and Validation of a Nomogram Based on the Log Odds of Positive Lymph Nodes to Predict the Prognosis of Medullary Thyroid Carcinoma After Surgery

Ultrasonic radiomics in predicting pathologic type for thyroid cancer: a preliminary study using radiomics features for predicting medullary thyroid carcinoma

Introduction

Medullary thyroid carcinoma (MTC) is aggressive and difficult to distinguish from papillary thyroid carcinoma (PTC) using traditional ultrasound. Objective to establish a standard-based ultrasound imaging model for preoperative differentiation of MTC from PTC.

Methods

A retrospective study was conducted on the case data of 213 thyroid cancer patients (82 MTC, 90 lesions; 131 PTC, 135 lesions) from the Department of Diagnostic and Therapeutic Ultrasonography, Tianjin Medical University Cancer Institute and Hospital. We constructed clinical model, radiomics model and comprehensive model by executing machine learning algorithms based on baseline clinical, pathological characteristics and ultrasound image data, respectively.

Results

The study showed that the comprehensive model observed the highest diagnostic efficacy in differentiating MTC from PTC with AUC, sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 0.93, 0.88, 0.82, 0.77, 0.91, 85.8%. Delong test results showed that the comprehensive model was significantly better than the clinical model (Z=-3.791, P<0.001) and the radiomics model (Z=-2.017, P=0.044). Calibration curves indicated the comprehensive model and the radiomics model exhibited better stability than the clinical model. Decision curves analysis (DCA) demonstrated that the comprehensive model had the highest clinical net benefit.

Discussions

Radiomics model is effective in identifying MTC and PTC preoperatively, and the comprehensive model is better. This approach can aid in identifying the pathologic types of thyroid nodule before clinical operation, supporting personalized medicine in the decision-making process.

A prognostic nomogram for distant metastasis in thyroid cancer patients without lymph node metastasis

Background

Despite having negative lymph node (N0) status, thyroid cancer (TC) patients can still experience distant metastasis (DM), which significantly impacts their survival. This study aimed to investigate the prognostic factors for DM in TC patients (N0) and develop a predictive nomogram model for analyzing the prognosis of TC N0 patients with DM.

Methods

Data collected from the Surveillance, Epidemiology, and End Results (SEER) database for 18,504 TC patients (N0) between 2004 and 2015 were analyzed. Univariate and multivariate analyses were used to identify independent prognostic factors for DM in TC N0. These independent factors were used to build a nomogram model to predict overall survival (OS) at 1, 3, and 5 years for TC patients (N0) with DM.

Results and conclusion

This study examined the clinicopathological features associated with the risk and prognosis of DM in TC patients (N0), and successfully established and validated a nomogram capable of predicting OS in individual patients with DM. The nomogram is highly useful for the timely identification of TC patients (N0) at high risk of DM by physicians, enabling individualized survival evaluations and treatment for TC patients with DM (N0).

Development and Validation of a Prognostic Nomogram for Breast Cancer Patients With Multi-Organ Metastases: An Analysis of the Surveillance, Epidemiology, and End Results Program Database

BACKGROUND

Multi-organ metastases represent a substantial life-threatening risk for breast cancer (BC) patients. Nonetheless, the current dearth of assessment tools for patients with multi-organ metastatic BC adversely impacts their evaluation.

METHODS

We conducted a retrospective analysis of BC patients with multi-organ metastases using data from the SEER database from 2010 to 2019. The patients were randomly allocated into a training cohort and a validation cohort in a 7:3 ratio. Univariate COX regression analysis, the LASSO, and multivariate Cox regression analyses were performed to identify independent prognostic factors in the training set. Based on these factors, a nomogram was constructed to estimate overall survival (OS) probability for BC patients with multi-organ metastases. The performance of the nomogram was evaluated using C-indexes, ROC curves, calibration curves, decision curve analysis (DCA) curves, and the risk classification system for validation.

RESULTS

A total of 3626 BC patients with multi-organ metastases were included in the study, with 2538 patients in the training cohort and 1088 patients in the validation cohort. Age, grade, metastasis location, surgery, chemotherapy, and subtype were identified as significant independent prognostic factors for OS in BC patients with multi-organ metastases. A nomogram for predicting 1-year, 3-year, and 5-year OS was constructed. The evaluation metrics, including C-indexes, ROC curves, calibration curves, and DCA curves, demonstrated the excellent predictive performance of the nomogram. Additionally, the risk grouping system effectively stratified BC patients with multi-organ metastases into distinct prognostic categories.

CONCLUSION

The developed nomogram showed high accuracy in predicting the survival probability of BC patients with multi-organ metastases, providing valuable information for patient counseling and treatment decision making.

Application and subgroup analysis of competing risks model based on different lymph node staging systems in differentiated thyroid cancer

Differentiated thyroid cancer (DTC) is the most common endocrine malignancy, with a rising incidence worldwide. Accurate prognostic models are essential for effective patient management. This study evaluates the prognostic value of various lymph node staging systems in DTC using a competing risks model. We used SEER database records (1998-2016) of 16,527 DTC patients, analyzing N stage, positive lymph node numbers (PLNNs), metastatic lymph node ratio (MLNR), log odds of positive lymph nodes (LODDS), and log odds of the negative lymph node (NLN)/T stage ratio (LONT). Univariate and multivariate analyses in a competing risks model were performed, along with subgroup analyses based on demographic and clinical characteristics. In this study of 16,527 patients with DTC, different lymph node staging systems showed different prognostic correlations in univariate and multivariate analyses. In particular, PLNNs showed significant prognostic correlations in several subgroups. Additionally, PLNNs were more suitable as a lymph node staging system for DTC than LODDS and MLNR in N1 stage subgroups, with an optimal cut-off of 13. Receiver operating characteristic curves, calibration curves and nomograms improved the clinical utility of the prognostic model based on PLNNs. Using competing risks model and subgroup analyses, we found that PLNNs had the best prognostic discriminatory efficacy for patients with DTC, especially those with N1 stage disease, and had an optimal cut-off value of 13.

Prognostic nomogram for predicting the overall survival rate of patients with uterine clear-cell carcinoma: Based on SEER database

OBJECTIVE

To evaluate the risk factors for uterine clear-cell carcinoma (UCCC) and construct nomograms predicting 1-, 3-, and 5-year overall survival rates of patients with UCCC.

METHODS

The demographic and clinical information of 1674 patients diagnosed with UCCC between 2004 and 2015, including age, race, marital status, tumor size, American Joint Committee on Cancer (AJCC) stage, and details of surgery and radiotherapy/chemotherapy, was collected from the Surveillance, Epidemiology, and End Results (SEER) database. After excluding patients with unknown AJCC stage, race, marital status, or lymph node information, 1469 patients remained. Risk factors were determined using univariate and multivariate analyses, and nomograms were developed to predict 1-, 3-, and 5-year overall survival of UCCC. Various indicators were used to evaluate the performance of the nomogram, such as the C-index, net classification improvement (NRI) and decision curve analysis (DCA).

RESULTS

Age, log odds of positive lymph nodes, AJCC stage, surgery status, and chemotherapy status were independent risk factors for UCCC. The C-indexes of the training group and AJCC stage groups were 0.771 and 0.697, respectively. The results for the area under the receiver operating characteristics curve, NRI, and calibration curves indicated that the nomogram had good predictive ability. DCA revealed that the nomogram had greater clinical applicability than AJCC stage alone. Internal validation using the validation cohort also demonstrated that this nomogram had good predictive performance.

CONCLUSION

A new nomogram comprising a combination of demographic and clinical characteristics provided better survival predictions than the AJCC staging system alone, which will facilitate prognostic assessments and clinical decision-making.

Construction of a novel nomogram for predicting overall survival in patients with Siewert type II AEG based on LODDS: a study based on the seer database and external validation

Background

In recent years, the incidence of adenocarcinoma of the esophagogastric junction (AEG) has been rapidly increasing globally. Despite advances in the diagnosis and treatment of AEG, the overall prognosis for AEG patients remains concerning. Therefore, analyzing prognostic factors for AEG patients of Siewert type II and constructing a prognostic model for AEG patients is important.

Methods

Data of primary Siewert type II AEG patients from the SEER database from 2004 to 2015 were obtained and randomly divided into training and internal validation cohort. Additionally, data of primary Siewert type II AEG patients from the China Medical University Dandong Central Hospital from 2012 to 2018 were collected for external validation. Each variable in the training set underwent univariate Cox analysis, and variables with statistical significance (p < 0.05) were added to the LASSO equation for feature selection. Multivariate Cox analysis was then conducted to determine the independent predictive factors. A nomogram for predicting overall survival (OS) was developed, and its performance was evaluated using ROC curves, calibration curves, and decision curves. NRI and IDI were calculated to assess the improvement of the new prediction model relative to TNM staging. Patients were stratified into high-risk and low-risk groups based on the risk scores from the nomogram.

Results

Age, Differentiation grade, T stage, M stage, and LODDS (Log Odds of Positive Lymph Nodes)were independent prognostic factors for OS. The AUC values of the ROC curves for the nomogram in the training set, internal validation set, and external validation set were all greater than 0.7 and higher than those of TNM staging alone. Calibration curves indicated consistency between the predicted and actual outcomes. Decision curve analysis showed moderate net benefit. The NRI and IDI values of the nomogram were greater than 0 in the training, internal validation, and external validation sets. Risk stratification based on the nomogram's risk score demonstrated significant differences in survival rates between the high-risk and low-risk groups.

Conclusion

We developed and validated a nomogram for predicting overall survival (OS) in patients with Siewert type II AEG, which assists clinicians in accurately predicting mortality risk and recommending personalized treatment strategies.

Different lymph node staging systems for predicting the prognosis of colorectal neuroendocrine neoplasms

BACKGROUND

Colorectal neuroendocrine neoplasms (NENs) are a rare malignancy that primarily arises from the diffuse distribution of neuroendocrine cells in the colon and rectum. Previous studies have pointed out that the status of lymph node may be used to predict the prognosis.

AIM

To investigate the predictive values of lymph node ratio (LNR), positive lymph node (PLN), and log odds of PLNs (LODDS) staging systems on the prognosis of colorectal NENs treated surgically, and compare their predictive values.

METHODS

This cohort study included 895 patients with colorectal NENs treated surgically from the Surveillance, Epidemiology, and End Results database. The endpoint was mortality of patients with colorectal NENs treated surgically. X-tile software was utilized to identify most suitable thresholds for categorizing the LNR, PLN, and LODDS. Participants were selected in a random manner to form training and testing sets. The prognosis of surgically treating colorectal NENs was examined using multivariate cox analysis to assess the associations of LNR, PLN, and LODDS with the prognosis of colorectal NENs. C-index was used for assessing the predictive effectiveness. We conducted a subgroup analysis to explore the different lymph node staging systems' predictive values.

RESULTS

After adjusting all confounding factors, PLN, LNR and LODDS staging systems were linked with mortality in patients with colorectal NENs treated surgically (P < 0.05). We found that LODDS staging had a higher prognostic value for patients with colorectal NENs treated surgically than PLN and LNR staging systems. Similar results were obtained in the different G staging subgroup analyses. Furthermore, the area under the receiver operating characteristic curve values for LODDS staging system remained consistently higher than those of PLN or LNR, even at the 1-, 2-, 3-, 4-, 5- and 6-year follow-up periods.

CONCLUSION

LNR, PLN, and LODDS were found to significantly predict the prognosis of patients with colorectal NENs treated surgically.

The potential value of ultrasound in predicting local refractory/relapse events in primary thyroid lymphoma patients

BACKGROUND

Primary thyroid lymphoma (PTL) is a rare malignant disorder, and ultrasound plays an important role in PTL diagnosis and follow-up surveillance. Prediction of refractory/relapse events in PTL patients is an essential issue, yet no ultrasonic PTL features have been discovered to be related to refractory/local relapse events.

METHODS

From January 2008 to September 2022, newly diagnosed PTL patients in our center who underwent standard first-line treatment and received an ultrasound examination before treatment were enrolled. Data regarding patients' clinical and sonographic features, as well as their therapeutic responses were collected. Subjects with an ideal prognosis were compared to those with refractory/relapse events.

RESULTS

In total, 37 PTL patients were analyzed, including 26 with diffuse large B-cell lymphoma, 2 with follicular lymphoma and 9 with mucosa-associated lymphoid tissue lymphoma. During the median follow-up of 25 months, 30 patients obtained a complete response, 4 were refractory patients, and 3 experienced local relapse. No significant difference was detected in the baseline clinical characteristics between patients with an ideal prognosis and those with refractory/local relapse events. In terms of sonographic features, however, an event-free survival (EFS) curve comparison revealed that patients with bilobar enlargement (defined as an anterior-posterior diameter > 2.5 cm on both sides of thyroid lobes) had a poorer EFS than those without (P < 0.0001), and patients with diffuse type had a poorer EFS than those with mixed/nodular types (P = 0.043). No significant difference was observed in EFS between patients with or without signs of suspicious cervical lymph node metastasis, rich blood signal distribution or symptoms of trachea compression.

CONCLUSIONS

PTL patients with an anterior-posterior diameter > 2.5 cm for both thyroid lobes or PTL patients of the diffuse ultrasound type could be prone to refractory/local relapse events.

Machine Learning for Predicting Distant Metastasis of Medullary Thyroid Carcinoma Using the SEER Database

Objectives

We aimed to establish an effective machine learning (ML) model for predicting the risk of distant metastasis (DM) in medullary thyroid carcinoma (MTC).

Methods

Demographic data of MTC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database of the National Institutes of Health between 2004 and 2015 to develop six ML algorithm models. Models were evaluated based on accuracy, precision, recall rate, F1-score, and area under the receiver operating characteristic curve (AUC). The association between clinicopathological characteristics and target variables was interpreted. Analyses were performed using traditional logistic regression (LR).

Results

In total, 2049 patients were included and 138 developed DM. Multivariable LR showed that age, sex, tumor size, extrathyroidal extension, and lymph node metastasis were predictive features for DM in MTC. Among the six ML models, the random forest (RF) had the best predictability in assessing the risk of DM in MTC, with an accuracy, precision, recall rate, F1-score, and AUC higher than those of the traditional binary LR model.

Conclusion

RF was superior to traditional LR in predicting the risk of DM in MTC and can provide a valuable reference for clinicians in decision-making.

Comparison of alternative N-staging models in patients with oral cancer. Is nodal yield or burden the most critical parameter?

BACKGROUND

There is increasing evidence in the literature that alternative N-classification systems offer a simpler and more precise risk stratification than the current N- classification in patients with oral squamous cell carcinoma. The purpose of this study is to compare three broadly proposed models incorporating lymph node ratio, log odds of positive lymph nodes and number of positive lymph nodes regarding disease-free and overall survival.

METHODS

This is a retrospective study of patients treated in a single center between 2013 and 2019. Cox proportional hazard models, Kaplan Meier curves, the long rank test and the area under the curve were implemented to compare the risk-stratification ability of the three models. Moreover, a hazard ratio plot was calculated to investigate the association between nodal yield and disease-free survival.

RESULTS

231 patients were included. All three proposed N-models were significantly correlated to the patient's prognosis in the multivariate analysis. Pairwise comparisons between the groups showed that the current pN classification offers the worst stratification and that the model incorporating the number of positive lymph nodes had a better performance for predicting both endpoints. Finally, a decrease in hazard ratio was observed with each additional lymph node removed up to the number of 39 lymph nodes.

CONCLUSIONS

The model incorporating the nodal burden offered a better predictive ability. The current N-classification cannot adequately identify patients with different prognosis. A non-linear relationship was found between nodal yield and survival, which could be the disadvantage of the lymph node ratio and log odds models.

Construction and validation of a nomogram based on the log odds of positive lymph nodes to predict cancer-specific survival in patients with small cell lung cancer after surgery

Background

The lymph node ratio (LNR) is useful for predicting survival in patients with small cell lung cancer (SCLC). The present study compared the effectiveness of the N stage, number of positive LNs (NPLNs), LNR, and log odds of positive LNs (LODDS) to predict cancer-specific survival (CSS) in patients with SCLC.

Materials and methods

674 patients were screened using the Surveillance Epidemiology and End Results database. The Kaplan-Meier survival and receiver operating characteristic (ROC) curves were performed to address optimal estimation of the N stage, NPLNs, LNR, and LODDS to predict CSS. The optimal LN status group was incorporated into a nomogram to estimate CSS in SCLC patients. The ROC curve, decision curve analysis, and calibration plots were utilized to test the discriminatory ability and accuracy of this nomogram.

Results

The LODDS model showed the highest accuracy compared to the N stage, NPLNs, and LNR in predicting CSS for SCLC patients. LODDS, age, sex, tumor size, and radiotherapy status were included in the nomogram. The results of calibration plots provided evidences of nice consistency. The ROC and DCA plots suggested a better discriminatory ability and clinical applicability of this nomogram than the 8th TNM and SEER staging systems.

Conclusions

LODDS demonstrated a better predictive power than other LN schemes in SCLC patients after surgery. A novel LODDS-incorporating nomogram was built to predict CSS in SCLC patients after surgery, proving to be more precise than the 8th TNM and SEER staging.

A practical nomogram and risk stratification system predicting the cancer-specific survival for patients aged >50 with advanced melanoma

Objective

To investigate risk factors for advanced melanoma over 50 years of age and to develop and validate a new line chart and classification system.

Methods

The SEER database was screened for patients diagnosed with advanced melanoma from 2010 to 2019 and Cox regression analysis was applied to select variables affecting patient prognosis. The area under curve (AUC), relative operating characteristic curve (ROC), Consistency index (C-index), decision curve analysis (DCA), and survival calibration curves were used to verify the accuracy and utility of the model and to compare it with traditional AJCC tumor staging. The Kaplan-Meier curve was applied to compare the risk stratification between the model and traditional AJCC tumor staging.

Results

A total of 5166 patients were included in the study. Surgery, age, gender, tumor thickness, ulceration, the number of primary melanomas, M stage and N stage were the independent prognostic factors of CSS in patients with advanced melanoma (P<0.05). The predictive nomogram model was constructed and validated. The C-index values obtained from the training and validation cohorts were 0.732 (95%CI: 0.717-0.742) and 0.741 (95%CI: 0.732-0.751). Based on the observation and analysis results of the ROC curve, survival calibration curve, NRI, and IDI, the constructed prognosis model can accurately predict the prognosis of advanced melanoma and performs well in internal verification. The DCA curve verifies the practicability of the model. Compared with the traditional AJCC staging, the risk stratification in the model has a better identification ability for patients in different risk groups.

Conclusion

The nomogram of advanced melanoma and the new classification system were successfully established and verified, which can provide a practical tool for individualized clinical management of patients.

Prognostic nomogram based on the lymph node metastasis indicators for patients with bladder cancer: A SEER population-based study and external validation

PURPOSE

This study aimed to compare the prognostic value of multiple lymph node metastasis (LNM) indicators and to develop optimal prognostic nomograms for bladder cancer (BC) patients.

METHODS

BC patients were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and randomly partitioned into training and internal validation cohorts. Genomic and clinical data were collected from The Cancer Genome Atlas (TCGA) as external validation cohort. The predictive efficiency of LNM indicators was compared by constructing multivariate Cox regression models. We constructed nomograms on basis of the optimal models selected for overall survival (OS) and cause-specific survival (CSS). The performance of nomograms was evaluated with calibration plot, time-dependent area under the curve (AUC) and decision curve analysis (DCA) in three cohorts. We subsequently estimated the difference of biological function and tumor immunity between two risk groups stratified by nomograms in TCGA cohort.

RESULTS

Totally, 10,093 and 107 BC patients were screened from the SEER and TCGA databases. N classification, positive lymph nodes (PLNs), lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) were all independent predictors for OS and CSS. The filtered models containing LODDS had minimal Akaike Information Criterion, maximal concordance indexes and AUCs. Age, LODDS, T and M classification were integrated into nomogram for OS, while nomogram for CSS included gender, tumor grade, LODDS, T and M classification. The nomograms were successfully validated in predictive accuracy and clinical utility in three cohorts. Additionally, the tumor microenvironment was different between two risk groups.

CONCLUSIONS

LODDS demonstrated superior prognostic performance over N classification, PLN and LNR for OS and CSS of BC patients. The nomograms incorporating LODDS provided appropriate prediction of BC, which could contribute to the tumor assessment and clinical decision-making.

Update on C-Cell Neuroendocrine Neoplasm: Prognostic and Predictive Histopathologic and Molecular Features of Medullary Thyroid Carcinoma

Medullary thyroid carcinoma (MTC) is a C-cell-derived epithelial neuroendocrine neoplasm. With the exception of rare examples, most are well-differentiated epithelial neuroendocrine neoplasms (also known as neuroendocrine tumors in the taxonomy of the International Agency for Research on Cancer [IARC] of the World Health Organization [WHO]). This review provides an overview and recent evidence-based data on the molecular genetics, disease risk stratification based on clinicopathologic variables including molecular profiling and histopathologic variables, and targeted molecular therapies in patients with advanced MTC. While MTC is not the only neuroendocrine neoplasm in the thyroid gland, other neuroendocrine neoplasms in the thyroid include intrathyroidal thymic neuroendocrine neoplasms, intrathyroidal parathyroid neoplasms, and primary thyroid paragangliomas as well as metastatic neuroendocrine neoplasms. Therefore, the first responsibility of a pathologist is to distinguish MTC from other mimics using appropriate biomarkers. The second responsibility includes meticulous assessment of the status of angioinvasion (defined as tumor cells invading through a vessel wall and forming tumor-fibrin complexes, or intravascular tumor cells admixed with fibrin/thrombus), tumor necrosis, proliferative rate (mitotic count and Ki67 labeling index), and tumor grade (low- or high-grade) along with the tumor stage and the resection margins. Given the morphologic and proliferative heterogeneity in these neoplasms, an exhaustive sampling is strongly recommended. Routine molecular testing for pathogenic germline RET variants is typically performed in all patients with a diagnosis of MTC; however, multifocal C-cell hyperplasia in association with at least a single focus of MTC and/or multifocal C-cell neoplasia are morphological harbingers of germline RET alterations. It is of interest to assess the status of pathogenic molecular alterations involving genes other than RET like the MET variants in MTC families with no pathogenic germline RET variants. Furthermore, the status of somatic RET alterations should be determined in all advanced/progressive or metastatic diseases, especially when selective RET inhibitor therapy (e.g., selpercatinib or pralsetinib) is considered. While the role of routine SSTR2/5 immunohistochemistry remains to be further clarified, evidence suggests that patients with somatostatin receptor (SSTR)-avid metastatic disease may also benefit from the option of ¹⁷⁷Lu-DOTATATE peptide radionuclide receptor therapy. Finally, the authors of this review make a call to support the nomenclature change of MTC to C-cell neuroendocrine neoplasm to align this entity with the IARC/WHO taxonomy since MTCs represent epithelial neuroendocrine neoplasms of endoderm-derived C-cells.

Establishment and validation of a nomogram model for predicting distant metastasis in medullary thyroid carcinoma: An analysis of the SEER database based on the AJCC 8th TNM staging system

OBJECTIVE

Medullary thyroid carcinoma (MTC) patients with distant metastases frequently present a relatively poor survival prognosis. Our main purpose was developing a nomogram model to predict distant metastases in MTC patients.

METHODS

This was a retrospective study based on the Surveillance, Epidemiology, and End Results (SEER) database. Data of 807 MTC patients diagnosed from 2004 to 2015 who undergone total thyroidectomy and neck lymph nodes dissection was included in our study. Independent risk factors were screened by univariate and multivariate logistic regression analysis successively, which were used to develop a nomogram model predicting for distant metastasis risk. Further, the log-rank test was used to compare the differences of Kaplan-Meier curves of cancer-specific survival (CSS) in different M stage and each independent risk factor groups.

RESULTS

Four clinical parameters including age > 55 years, higher T stage (T3/T4), higher N stage (N1b) and lymph node ratio (LNR) > 0.4 were significant for distant metastases at the time of diagnosis in MTC patients, and were selected to develop a nomogram model. This model had satisfied discrimination with the AUC and C-index of 0.894, and C-index was confirmed to be 0.878 through bootstrapping validation. A decision curve analysis (DCA) was subsequently made to evaluate the feasibility of this nomogram for predicting distant metastasis. In addition, CSS differed by different M stage, T stage, N stage, age and LNR groups.

CONCLUSIONS

Age, T stage, N stage and LNR were extracted to develop a nomogram model for predicting the risk of distant metastases in MTC patients. The model is of great significance for clinicians to timely identify patients with high risk of distant metastases and make further clinical decisions.

A prognostic nomogram based on log odds of positive lymph nodes to predict the overall survival in biliary neuroendocrine neoplasms (NENs) patients after surgery

BACKGROUND

The prognosis of biliary neuroendocrine neoplasms (NENs) patients is affected by the status of metastatic lymph nodes. The purpose of this study was to explore the prognostic value of the log odds of positive lymph nodes (LODDS) and develop a novel nomogram to predict the overall survival (OS) in biliary NENs patients.

METHODS

A total of 125 patients with histologically confirmed biliary NENs were selected from the Surveillance, Epidemiology and End Results (SEER) database and further divided into training and validation cohorts. The discrimination and calibration of the nomogram were evaluated using the concordance index (C-index), the area under the time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration plots. The net benefits and clinical utility of the nomogram were quantified and compared with those of the SEER staging system using decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI). The risk stratifications of the nomogram and the SEER staging system were compared.

RESULTS

LODDS showed the highest accuracy in predicting OS for biliary NENs. The C-index (0.789 for the training cohort and 0.890 for the validation cohort) and the time-dependent AUC (> 0.7) indicated the satisfactory discriminative ability of the nomogram. The calibration plots showed a high degree of consistency. The DCA, NRI, and IDI indicated that the nomogram performed significantly better than the SEER staging system.

CONCLUSION

A novel LODDS-incorporated nomogram was developed and validated to assist clinicians in evaluating the prognosis of biliary NENs patients.

A novel prognostic model based on log odds of positive lymph nodes to predict outcomes of patients with anaplastic thyroid carcinoma after surgery

OBJECTIVE

The eighth version of the American Joint Committee on Cancer (8th AJCC) system for anaplastic thyroid carcinoma (ATC) added lymph node (LN) metastasis as the staging element. This study aimed to explore the association between LN status and ATC's prognosis, identify the optimal LN index and establish a novel prognostic model.

DESIGN AND PATIENTS

Data of 199 ATC patients after surgery were collected from the Surveillance, Epidemiology and End Results (SEER) database, then randomly divided into training and validation cohorts.

MEASUREMENTS

We compared the prognostic value of AJCC N status, number of positive LN (PLNN), ratio of LN (LNR) and log odds of positive LN (LODDS). We conducted univariate and multivariate Cox analyses to determine the independent prognostic factors for ATC, and constructed a novel prognostic model. The concordance index (C-index), area under the receiver-operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA) were used to assess the nomogram's predictive performance.

RESULTS

LODDS showed the highest accuracy among four LN systems to predict overall survival (OS) for ATC. In the training cohort, the C-index of the LODDS-based nomogram was 0.738. The AUCs were 0.813, 0.850 and 0.869 for predicting 1-, 2- and 3-year OS, respectively. The calibration plots and DCA indicated the great clinical applicability of the model. The above results were verified in the validation cohort.

CONCLUSIONS

LODDS showed better predictive performance than other LN schemes in ATC. The LODDS-incorporated nomogram has the potential to more precisely predict the prognosis for ATC patients than the AJCC system.

Lymph Node Ratio Nomogram-Based Prognostic Model for Resected Distal Cholangiocarcinoma

BACKGROUND

Several variables have been described as prognostic factors for resected distal cholangiocarcinoma (dCC), including lymph node metastases (N status) and lymph node ratio (LNR). The present study aimed to evaluate the prognostic value of LNR on survival and to establish a novel prognostic nomogram to predict the cancer-specific recurrence-free survival (RFS) of dCC.

STUDY DESIGN

Between December 2006 and September 2020, 415 consecutive patients who underwent pancreaticoduodenectomy (PD) for dCC in 10 centers were identified. Multivariate Cox analysis was used to identify all independent risk factors among several prognostic factors. A nomogram was then developed and assessed by integrating the independent prognostic factors into the model, and the concordance index (C-index) was used to evaluate its performance.

RESULTS

According to Cox regression multivariate analysis, a nomogram based on independent prognostic factor for RFS was performed including LNR 15 (hazard ratio [HR] 2.442, 95% CI 1.348-4.425, p = 0.003), perineural invasion (HR 3.100, 95% CI 1.183-8.122, p = 0.025), differentiation grade (HR 2.100, 95% CI 1.172-4.143, p = 0.021), and radicality of PD (HR 2.276, 95% CI 1.223-4.234, p = 0.009). The C-index of the nomogram, tailored based on the previous significant factors, was 0.8.

CONCLUSIONS

LNR15 yields a high prognostic efficiency for RFS. The nomogram based on LNR can provide an accurate prognosis assessment for patients with resected dCC.

Establishment and validation of a postoperative predictive model for patients with colorectal mucinous adenocarcinoma

BACKGROUND

The aim of this study was to develop comprehensive and effective nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) rates in patients with colorectal mucinous adenocarcinoma (CRMA).

METHODS

A total of 4711 CRMA patients who underwent radical surgery between 2010 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database were collected and randomized into development (n=3299) and validation (n=1412) cohorts at a ratio of 7:3 for model development and validation. OS and CSS nomograms were developed using the prognostic factors from the development cohort after multivariable Cox regression analysis. The performance of the nomograms was evaluated using Harrell's concordance index (C-index), calibration diagrams, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

RESULTS

The study included 4711 patients. Multivariate Cox regression analysis demonstrated that age, tumor size, grade, pT stage, pN stage, M stage, carcinoembryonic antigen, perineural invasion, tumor deposits, regional nodes examined, and chemotherapy were correlated with OS and CSS. Marital status was independently related to OS. In the development and validation cohorts, the C-index of OS was 0.766 and 0.744, respectively, and the C-index of CSS was 0.826 and 0.809, respectively. Calibration curves and ROC curves showed predictive accuracy. DCA showed that the nomograms had excellent potency over the 8th edition of the TNM staging system with higher clinical net benefits. Significant differences in OS and CSS were observed among low-, medium-, and high-risk groups.

CONCLUSIONS

Nomograms were developed for the first time to predict personalized 1-, 3-, and 5-year OS and CSS in CRMA postoperative patients. External and internal validation confirmed the excellent discrimination and calibration ability of the nomograms. The nomograms can help clinicians design personalized treatment strategies and assist with clinical decisions.

Metastatic Risk Stratification of 2526 Medullary Thyroid Carcinoma Patients: A Study Based on Surveillance, Epidemiology, and End Results Database

The risk of distant metastasis in medullary thyroid carcinoma (MTC) has not been well studied. Additional evaluation of MTC metastatic risk can be helpful for improving the quality of medical management. Therefore, we conducted a large population study to develop a method to stratify the risk of metastasis at the initial presentation of MTC patients. We collected 3612 MTC patients from the Surveillance, Epidemiology, and End Results (SEER) database, and included 2526 MTC patients in the study after applying exclusion criteria. We selected the most informative variables from a learning cohort of 2019 patients to obtain 1000 models by repetitive random data splicing into training and regularization cohorts. We selected the optimal model and developed a risk table from that model. Our risk table variables consist of age, gender, tumor size, extrathyroidal extension, and lymph node metastasis. The final model showed good calibration when metastatic risk was < 25% and good performance with areas under the curve (AUCs) of 0.81, 0.84, and 0.84 in the training, regularization, and test cohorts, respectively. We performed K-means clustering analysis on the model's metastatic estimation and determined three risk groups of patients with significant survival differences (p < 0.001). Low-risk patients had 0.88%, 1.3%, and 0.5% while high-risk patients had 19.7%, 15.8%, and 17.8% risk of metastasis in the three cohorts, respectively. The incorporation of our table into the International MTC Grading System (IMTCGS) requires more comprehensive clinicopathological studies.

Prognostic value of LODDS in medullary thyroid carcinoma based on competing risk model and propensity score matching analysis

Log odds of positive lymph nodes (LODDS) is an independent prognostic factor for patients with medullary thyroid carcinoma (MTC). However, the optimal cutoff value for LODDS needs to be further confirmed, and previous studies have ignored the prevalent competing events of non-cancer deaths among patients with MTC, thus possibly overestimating the risk of death from cancer. The information of patients with MTC who underwent total thyroidectomy was collected from SEER database. Restricted cubic splines (RCS) were used to determine the optimal cutoff for LODDS. Moreover, patients' overall survival (OS) and disease-specific survival (DSS) were determined using Kaplan-Meier and Cox proportional-hazards model. The competing risk models (CRM) were used to reduce the effect of competing events, and propensity score matching was performed to balance the confounding factors between groups. The cutoff value of LODDS determined by RCS was - 1.004, and a total of 2314 patients with MTC were recruited. In the CRM after PSM, factors such as age over 55 years at diagnosis, being male, treatment with chemotherapy or radiotherapy, unknown tumor size, and LODDS > - 1.004 were significantly associated with poor prognosis of patients both in univariate and multivariate analyses, while the presence of multifocal tumor indicated better prognosis. Patients with MTC who were over 55 years old at diagnosis, were male, received chemotherapy or radiation, had an unclear initial tumor size, and had LODDS > - 1.004 had a worse prognosis than patients with multifocal tumor.

Nomogram Predicts Overall Survival in Patients With Stage IV Thyroid Cancer (TC): A Population-Based Analysis From the SEER Database

Background

Stage IV Thyroid cancer (TC) has a relatively poor prognosis and lacks a precise and efficient instrument to forecast prognosis. Our study aimed to construct a nomogram for predicting the prognosis of patients with stage IV TC based on data from the SEER programme.

Methods

We enrolled patients diagnosed with TC from 2004 to 2015 in the study. Furthermore, the median survival time (MST) for the patients equalled 25 months. The patients were split into two groups: the training group and validation group. We used descriptive statistics to calculate demographic and clinical variables, Student’s t test was used to describe continuous variables, and the chi-square test was used to describe classified variables. We used the concordance index (C-index) to evaluate discrimination ability and calibration plots to evaluate calibration ability. The improvement of the nomogram compared with the AJCC TNM system was evaluated by the net weight classification index (NRI), comprehensive discriminant rate improvement (IDI) and decision curve analysis (DCA).

Results

There were 3501 patients contained within our cohort, and the median follow-up was 25 months [quartile range (IQR): 6-60] in the whole population, 25 months (IQR: 6-60) in the training cohort, and 25 months (IQR: 5-59) in the validation cohort. The C-index value of the training cohort equalled 0.86 (95% CI: 0.85-0.87), and the value of the validation cohort equalled 0.85 (95% CI: 0.84-0.86). The NRI values were as follows: training queue: 1.16 for three-year and 1.12 for five-year OS prediction; authentication group: 1.22 for three-year and 1.21 for five-year OS prediction. The IDI values were as follows: training cohort: 0.25 for three-year and 0.21 for five-year OS prediction; validation cohort: 0.27 for three-year and 0.21 for five-year OS prediction. The DCA diagram showed that the nomogram was superior in predicting the three-year and five-year trends.

Conclusions

Our nomogram can be used to forecast the survival of patients with stage IV TC.

Inclusion of the Number of Metastatic Lymph Nodes in the Staging System for Medullary Thyroid Cancer: Validating a Modified American Joint Committee on Cancer Tumor-Node-Metastasis Staging System

Background: The current American Joint Committee on Cancer (AJCC) staging system (8th edition) for medullary thyroid cancer (MTC) was originally extrapolated from the staging system for differentiated thyroid cancer. However, the current staging system does not accurately predict the prognosis of patients with MTC. Patients and Methods: The present study was based on data from the Surveillance, Epidemiology, and End Results (SEER) database and validated by multicenter data from the Shanghai Tenth People's Hospital, Tongji University School of Medicine, Xuzhou City Central Hospital, and Suzhou Ninth People's Hospital. Hazard ratio with its 95% confidence interval [CI] was estimated by Cox proportional hazards regression analysis. The concordance index (C-index) was used to evaluate the discrimination accuracy of the current AJCC tumor-node-metastasis (TNM) staging system and the modified AJCC (mAJCC) TNM staging system. Results: A total of 1175 MTC patients were selected from the SEER database and 312 from the three hospitals in China. We redefined the N category according to the number of metastatic lymph nodes (LNs) as follows: N'0 category (0 metastatic LNs), N'1 category (1-9 metastatic LNs), and N'2 category (≥10 metastatic LNs). The four distinct tumor stages were reclassified in the mAJCC staging system as follows: stage I (T1-4N'0M0, T1N'1M0), stage II (T2-3N'1M0, T1N'2M0), stage III (T4N'1M0, T2-4N'2M0), and stage IV (TanyN'anyM1). The C-index of the current AJCC staging system and the mAJCC staging system was 0.72 [CI, 0.67-0.78] and 0.78 [CI, 0.73-0.84], respectively. Similar results were observed in the survival analysis of the multicenter data set. Conclusions: The mAJCC staging system could discriminate the prognosis of MTC patients more effectively than the current AJCC staging system, indicating that it is feasible and appropriate to modify the current AJCC staging system by introducing the number of metastatic LNs instead of the location of LNs. These findings might be adopted in the next edition of the AJCC staging system and be used to guide clinical practice.

Log odds of positive lymph nodes as a novel prognostic predictor for colorectal cancer: a systematic review and meta-analysis

BACKGROUND

Colorectal cancer (CRC) is the third most prevalent cancer in the world, which remains one of the leading causes of cancer-related deaths. Accurate prognosis prediction of CRC is pivotal to reduce the mortality and disease burden. Lymph node (LN) metastasis is one of the most commonly used criteria to predict prognosis in CRC patients. However, inaccurate surgical dissection and pathological evaluation may lead to inaccurate nodal staging, affecting the effectiveness of pathological N (pN) classification in survival prediction among patients with CRC. In this meta-analysis, we aimed to estimate the prognostic value of the log odds of positive lymph nodes (LODDS) in patients with CRC.

METHODS

PubMed, Medline, Embase, Web of Science and the Cochrane Library were systematically searched for relevant studies from inception to July 3, 2021. Statistical analyses were performed on Stata statistical software Version 16.0 software. To statistically assess the prognostic effects of LODDS, we extracted the hazard ratio (HR) and 95% confidence interval (CI) of overall survival (OS) and disease-free survival (DFS) from the included studies.

RESULTS

Ten eligible articles published in English involving 3523 cases were analyzed in this study. The results showed that LODDS1 and LODDS2 in CRC patients was correlated with poor OS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.77, 95% CI (1.38, 2.28); LODDS2 vs. LODDS0: HR = 3.49, 95% CI (2.88, 4.23)). Meanwhile, LODDS1 and LODDS2 in CRC patients was correlated with poor DFS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.82, 95% CI (1.23, 2.68); LODDS2 vs. LODDS0: HR =3.30, 95% CI (1.74, 6.27)).

CONCLUSIONS

The results demonstrated that the LODDS stage was associated with prognosis of CRC patients and could accurately predict the prognosis of patients with CRC.

Construction and Validation of a Prediction Model for Identifying Clinical Risk Factors of Lateral Lymph Node Metastasis in Medullary Thyroid Carcinoma

PURPOSE

Medullary thyroid carcinoma (MTC) is a rare but highly invasive malignancy, especially in terms of cervical lymph node metastasis. However, the role of prophylactic lateral lymph node dissection (LLND) is still controversial. We hereby aim to explore the risk factors of lateral lymph node metastasis (LLNM) in patients with MTC to guide clinical practice.

PATIENTS AND METHODS

The clinicopathological characteristics of patients with MTC from the Surveillance, Epidemiology, and End Results (SEER) Program and the Second Affiliated Hospital of Chongqing Medical University were reviewed and analyzed. Univariate and multivariate logistics regression analyses were used to screen the risk factors of LLNM in patients with MTC.

RESULTS

Four variables, including male gender, multifocality, extrathyroidal invasion (EI), and large tumor size (all p < 0.05), were identified as potential independent factors of LLNM in patients with MTC. Based on these results, an individualized prediction model was subsequently developed with a satisfied C-index of 0.798, supported by both internal and external validation with a C-index of 0.816 and 0.896, respectively. We also performed the decision curve analysis (DCA) and calibration curve, which indicated a remarkable agreement in our model for predicting the risk of LLNM.

CONCLUSION

We determined that various clinical characteristics, male gender, multifocality, EI, and large tumor size, were significantly associated with LLNM in patients with MTC. Thus, a validated prediction model utilizing readily available variables was successfully established to help clinicians make individualized clinical decisions on MTC management, especially regarding whether the LLND is necessary for patients with clinical negative lateral lymph node involvement and the frequency of follow-up without LLND.

Comparison of Four Lymph Node Stage Methods for Predicting the Prognosis of Distal Cholangiocarcinoma Patients After Surgery

Background

The metastatic status of regional lymph nodes is an effective risk factor for the prognosis of distal cholangiocarcinoma (dCCA). But existing lymph node staging is not accurate enough and is susceptible to interference. This study aims to explore the predictive ability of the log odds of positive lymph nodes (LODDS) staging system of dCCA compared with existing lymph node staging systems.

Methods

A total of 928 dCCA patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database as the training cohort, and 207 dCCA patients from West China Hospital who underwent surgery were reviewed as the validation cohort. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were conducted to identify the most meaningful factors relevant to prognosis. The performance of four lymph node stage systems was compared by a model-based approach.

Result

Age at diagnosis, pathological grade, American Joint Committee on Cancer (AJCC) tumor 7th T stage, tumor size, radiotherapy, chemotherapy, and lymph node stage system were independent prognostic factors. The model with the LODDS system had a better model fit with the highest C-index (0.679) and 1-/3-/5- area under the receiver operating characteristic curve (AUC) (0.739/0.671/0.658) as well as the lowest Akaike information criterion (AIC) (5,020.52). External validation results from 207 dCCA patients showed a C-index of 0.647 and 1-/3-/5-AUC of 0.740/0.683/0.589. Compared with the lymph node ratio (LNR), AJCC 8th N system, and 7th N system, the 5-year net reclassification improvement (NRI) of the LODDS system was 0.030 (95% CI: -0.079 to 0.147), 0.042 (95% CI: -0.062 to 0.139), and 0.040 (95% CI: -0.057 to 0.146), respectively. The integrated discrimination improvement (IDI) of LODDS improved compared with the LNR model (0.016; 95% CI: -0.001 to 0.036), AJCC 8th N system (0.020; 95% CI: 0.003-0.037), and AJCC 7th N system (0.019; 95% CI: 0.002-0.036). Decision curve analysis (DCA) also shows a greater net benefit of LODDS. In lymph node-negative patients, LODDS reveals a positive linear relationship with the hazard ratio (HR). The stage capacity of LODDS in a subgroup analysis stratified by examined lymph node number (ELNN) was consistent.

Conclusions

The LODDS lymph node stage system has superior predictive performance as compared with the LNR, AJCC 7th, and 8th lymph node stage systems. Meanwhile, LODDS has a more detailed staging ability and good stability.

Prognostic Performance of Alternative Lymph Node Classification Systems for Patients with Medullary Thyroid Cancer: A Single Center Cohort Study

BACKGROUND

Lymph node ratio (LNR) and the log odds of positive lymph nodes (LODDS) have been proposed as alternative lymph node (LN) classification schemes. Various cut-off values have been defined for each system, with the question of the most appropriate for patients with medullary thyroid cancer (MTC) still remaining open. We aimed to retrospectively compare the predictive impact of different LN classification systems and to define the most appropriate set of cut-off values regarding accurate evaluation of overall survival (OS) in patients with MTC.

METHODS

182 patients with MTC who were operated on between 1985 and 2018 were extracted from our medical database. Cox proportional hazards regression models and C-statistics were performed to assess the discriminative power of 28 LNR and 28 LODDS classifications and compare them with the N category according to the 8th edition of the AJCC/UICC TNM classification in terms of discriminative power. Regression models were adjusted for age, sex, T category, focality, and genetic predisposition.

RESULTS

High LNR and LODDS are associated with advanced T categories, distant metastasis, sporadic disease, and male gender. In addition, among 56 alternative LN classifications, only one LNR and one LODDS classification were independently associated with OS, regardless of the presence of metastatic disease. The C-statistic demonstrated comparable results for all classification systems showing no clear superiority over the N category.

CONCLUSION

Two distinct alternative LN classification systems demonstrated a better prognostic performance in MTC patients than the N category. However, larger scale studies are needed to further verify our findings.

Metastatic Lymph Node Ratio for Predicting Recurrence in Medullary Thyroid Cancer

Simple Summary

The anatomical staging system for thyroid cancer only contains categories for lymph node compartments. The metastatic lymph node ratio (LNR), which is the ratio of metastasized lymph nodes to the total number of evaluated lymph nodes, is suggested as a quantitative evaluation tool for lymph node metastasis in patients with medullary thyroid cancer in this study. The initial stratification implemented in this study was helpful in predicting structural recurrence, and LNR was identified as a predictor of disease-free survival.

Abstract

The lymph node ratio (LNR) has been investigated as a prognostic factor in many different types of cancers, including differentiated thyroid cancer; however, reports regarding medullary thyroid cancer (MTC) are limited. Therefore, this study aims to evaluate LNR as a risk factor for structural recurrence in patients with MTC. Medical records of patients treated for MTC in a single tertiary center between 1995 and 2017 were retrospectively reviewed. LNR is defined as the number of metastatic lymph nodes or lymph node metastases (LNM) divided by the number of retrieved lymph nodes or lymph node yield (LNY). In the survival analysis, recurrence-free survival was defined as the time from the date of total thyroidectomy to recurrence or last follow-up. To identify risk factors influencing structural recurrence, univariable and multivariable Cox proportional hazard models were used. A total of 132 patients were enrolled. The mean age of study participants was 49.7 years, and 86 patients (65%) were women. Structural recurrence was identified in 39 patients at the end of the study period, and the median follow-up period was 8.7 years. In univariable analyses, gross extra thyroidal extension, N stage, postoperative serum calcitonin and carcinoembryonic antigen (CEA) levels, and LNR were significant (p < 0.05) predictors of structural recurrence. In multivariable analysis, postoperative serum calcitonin, postoperative serum CEA, and LNR were identified as a predictor of disease-free survival (p < 0.05). LNR can potentially predict structural recurrence as a quantitative evaluation tool for lymph node metastasis in patients with MTC.

A Nomogram Based on the Log Odds of Positive Lymph Nodes Predicts the Prognosis of Patients With Distal Cholangiocarcinoma After Surgery

Background: Lymph node (LN) metastasis is considered one of the most important risk factors affecting the prognosis of distal cholangiocarcinoma (DCC). This study aimed to demonstrate the superiority of log odds of positive lymph nodes (LODDS) compared with other LN stages, and to establish a novel prognostic nomogram to predict the cancer-specific survival (CSS) of DCC.

Methods: From the Surveillance, Epidemiology and End Results (SEER) database, the data of 676 patients after DCC radical operation were screened, and patients were randomly divided into training (n = 474) and validation sets (n = 474). The prognostic evaluation performance of the LODDS and American Joint Commission on Cancer (AJCC) N stage and lymph node ratio (LNR) were compared using the Akaike information criteria, receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was used to screen independent risk factors, and a LODDS-based nomogram prognostic staging model was established. The nomogram's precision was verified by C-index, calibration curves, and AUC, and the results were compared with those of the AJCC TNM staging system.

Results:Compared with the other two stages of LN metastasis, LODDS was most effective in predicting CSS in patients with DCC. Multivariate analysis proved that LODDS, histologic grade, SEER historic stage, and tumor size were independent risk factors for DCC. The C-index of the nomogram, based on the above factors, in the validation set was 0.663. The 1-, 3-, and 5-y AUCs were 0.735, 0.679, and 0.745, respectively. Its good performance was also verified by calibration curves. In addition, the C-index and Kaplan-Meier analysis showed that the nomogram performed better than the AJCC TNM staging system.

Conclusion:For postoperative patients with DCC, the LODDS stage yielded better prognostic efficiency than the AJCC N and LNR stages. Compared with the AJCC TNM staging system, the nomogram, based on the LODDS, demonstrated superior performance.

A novel risk score system for prognostic evaluation in adenocarcinoma of the oesophagogastric junction: a large population study from the SEER database and our center

Background

The incidence rate of adenocarcinoma of the oesophagogastric junction (AEG) has significantly increased over the past decades, with a steady increase in morbidity. The aim of this study was to explore a variety of clinical factors to judge the survival outcomes of AEG patients.

Methods

We first obtained the clinical data of AEG patients from the Surveillance, Epidemiology, and End Results Program (SEER) database. Univariate and least absolute shrinkage and selection operator (LASSO) regression models were used to build a risk score system. Patient survival was analysed using the Kaplan-Meier method and the log-rank test. The specificity and sensitivity of the risk score were determined by receiver operating characteristic (ROC) curves. Finally, the internal validation set from the SEER database and external validation sets from our center were used to validate the prognostic power of this model.

Results

We identified a risk score system consisting of six clinical features that can be a good predictor of AEG patient survival. Patients with high risk scores had a significantly worse prognosis than those with low risk scores (log-rank test, P-value < 0.0001). Furthermore, the areas under ROC for 3-year and 5-year survival were 0.74 and 0.75, respectively. We also found that the benefits of chemotherapy and radiotherapy were limited to stage III/IV AEG patients in the high-risk group. Using the validation sets, our novel risk score system was proven to have strong prognostic value for AEG patients.

Conclusions

Our results may provide new insights into the prognostic evaluation of AEG.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08558-1.

Nomograms for Differentiated Thyroid Carcinoma Patients Based on the Eighth AJCC Staging and Competing Risks Model

BACKGROUND

Differentiated thyroid carcinoma (DTC) patients have a long survival period and good prognosis, so they are easily affected by competing risk events. The purpose of this study was to use the competing risks model to identify prognostic factors for cause-specific death (CSD) and death due to other causes (DOC) in patients with DTC.

METHODS

Our screening process identified 34 585 DTC patients in the Surveillance, Epidemiology, and End Results database and randomly divided them into a training cohort and a validation cohort. We used the Fine and Gray subdistribution hazards model to establish the CSD and DOC nomograms. The distinguishing ability and consistency of the nomograms were evaluated using the consistency indexes and calibration plots.

RESULTS

Our analysis of a competing risks model revealed that pathological grade, tumor size, histological type, American Joint Committee on Cancer (AJCC)-8 stage, surgery status, adjuvant radiotherapy status, adjuvant chemotherapy status, and log odds of positive lymph nodes are prognostic factors for CSD, and age at diagnosis, year of diagnosis, sex, pathological grade, tumor size, AJCC-8 stage, surgery status, adjuvant radiotherapy status, and lymph node ratio are prognostic factors for DOC. The 1-year, 3-year, and 5-year concordance indexes in the validation cohorts were 0.942, 0.931, and 0.913 for the CSD nomogram and 0.813, 0.746, and 0.776 for the DOC nomogram. The calibration plots showed good consistency in both nomograms.

CONCLUSIONS

Our nomograms can be used as a tool to help clinicians individually predict the probability of CSD and DOC in DTC patients at 1 year, 3 years, and 5 years, which has certain guiding value in clinical applications.