American Joint Committee On Cancer Staging System Research Articles

Advantage of Log Odds of Metastatic Lymph Nodes After Curative-Intent Resection of Gallbladder Cancer.

Lymph node metastasis (LNM) is among the most important predictors of poor prognosis after surgery for gallbladder cancer (GBC). Traditionally, staging has been based on the raw count of LNM, with a high risk of understaging patients who undergo inadequate lymph node dissection (LND). The log odds of metastatic lymph nodes (LODDS) may represent an alternative staging approach to stratify patients more accurately after resection of GBC. In this cross-sectional study, patients who underwent curative-intent surgery with LND for GBC were identified from an international database. Two predictive models were built and compared, each integrating a different lymph nodes status indicator [i.e., American Joint Committee on Cancer (AJCC) and LODDS]. Among 199 patients, the median number of lymph nodes examined was 5 [interquartile range (IQR): 3.0, 8.0]; most patients had T1 (n = 26, 13.1%) or T2 (n = 97, 48.7%) disease, and a subset had LNM (n = 87, 44.0%). Multivariable Cox analysis demonstrated LODDS was an independent predictor of overall survival [hazard ratio (HR) 1.84, 95% confidence interval (CI) 1.5-2.3; p < 0.001]. The LODDS model demonstrated better performance compared with a traditional model that utilized the AJCC N category [concordance (C) index: 0.814 versus 0.763; p < 0.001]. Patients classified as high- versus low-risk based on LODDS had much worse overall survival (OS) (4.9% versus 83.7%, respectively; p < 0.001). The LODDS model performance remained high even among patients with inadequateLND (< 6 LN) (C index: 0.87). An online calculator was developed ( https://catalano-giovanni.shinyapps.io/LoddsGBC/ ). A novel prognostic model based on LODDS may overcome the inherent limitations of the current AJCC staging system, reducing understaging among patients with fewer than six total lymph nodes evaluated.

Prognostic Value and Clinical Implication of Lymph Node-to-Primary Tumor SUV Ratio in Node-Positive Hypopharyngeal Squamous Cell Carcinoma Treated With Radiotherapy With or Without Chemotherapy.

The aim of this was to evaluate the prognostic significance of the nodal-to-primary tumor SUVmax ratio (NTR) in patients with node-positive hypopharyngeal squamous cell carcinoma (HPSCC) treated with radiotherapy with or without concurrent chemotherapy. The study aims to enhance prognostic accuracy by incorporating NTR into the American Joint Committee on Cancer (AJCC) staging system. This retrospective study included 191 patients with biopsy-proven node-positive HPSCC treated from 2005 to 2013. NTR was calculated as the ratio of SUVmax of metastatic lymph nodes to the primary tumor's SUVmax. Survival analyses were conducted using Cox regression models and Kaplan-Meier analysis. Receiver operating characteristic analysis compared the prognostic performance of the modified and AJCC staging systems. The median follow-up was 8.27 years, with 135 deaths (70.7%). High NTR (≥0.63) was significantly associated with worse overall survival (OS) and was an independent prognostic factor in multivariable analysis (adjusted hazards ratio [HR] = 1.63, P = 0.007). Median OS for high NTR was 17.4 months, compared with 75.2 months for low NTR. High NTR significantly predicted worse OS within AJCC stage IVA patients (HR = 6.09, P = 0.014). Patients in modified stage IVA (AJCC stage IVA with low NTR) had significantly longer OS than those in modified stage IVB (AJCC stage IVA with high NTR and AJCC stage IVB) (HR = 8.62, P = 0.003). The modified staging system incorporating NTR showed superior prognostic performance compared with the AJCC staging system. NTR is a significant independent prognostic factor for OS in node-positive HPSCC patients. Integrating NTR into the AJCC staging system improves prognostic accuracy.

Development of a staging system for hepatoid adenocarcinoma of the stomach based on multicenter data: A retrospective cohort study: A Staging System for Hepatoid Adenocarcinoma of the Stomach.

Hepatoid adenocarcinoma of the stomach (HAS) is a rare subtype of gastric cancer (GC) with a poor prognosis. Furthermore, the current pathological staging system for HAS does not distinguish it from that for common gastric cancer (CGC). The clinicopathological data of 251 patients with primary HAS who underwent radical surgery at 14 centers in China from April 2004 to December 2019 and 5082 patients with primary CGC who underwent radical surgery at 2 centers during the same period were retrospectively analyzed. A modified staging system was established based on the differences in survival. After 1:4 propensity score matching (PSM), 228 patients with HAS and 828 patients with CGC were analyzed. Kaplan-Meier (K-M) analysis showed patients with HAS had a poorer prognosis compared with CGC. Multivariate analysis identified pN stage, CEA level, and perineural invasion (PNI) as independent prognostic factors in patients with HAS. A modified pT (mpT) staging was derived using recursive partitioning analysis (RPA) incorporating PNI and pT staging. The modified pathological staging system (mpTNM) integrated the mpT and the 8th American Joint Committee on Cancer (AJCC) pN definitions. Multivariate analysis showed that mpTNM stage outperformed other pathological variables as independent predictors of OS and RFS in patients with HAS. The mpTNM staging system exhibited significantly higher predictive accuracy for 3-year OS in patients with HAS (0.707, 95% CI: 0.650-0.763) compared to that of the 8th AJCC staging system (0.667, 95% CI: 0.610-0.723, P<0.05). Analysis using the Akaike information criterion favored the mpTNM staging system over the 8th AJCC staging system (824.69 vs. 835.94) regarding the goodness of fit. The mpTNM stages showed improved homogeneity in survival prediction (likelihood ratio: 41.51 vs. 27.10). Comparatively the mpTNM staging system outperformed the 8th AJCC staging system in survival prediction, supported by improvements in the net reclassification index (NRI: 47.7%) and integrated discrimination improvement (IDI: 0.083, P<0.05). Time-dependent ROC curve showed that the mpTNM staging system consistently outperformed the 8th AJCC staging system with increasing observation time. The mpTNM staging system exhibited superior postoperative prognostic accuracy for patients with HAS compared to the 8th AJCC staging system.

Construction and validation of a nomogram for predicting cancer-specific survival in middle-aged patients with advanced hepatocellular carcinoma: A SEER-based study.

Hepatocellular carcinoma is the predominant form of primary liver cancer and is the leading cause of cancer-related death. The aim of this study was to construct a nomogram to predict cancer-specific survival (CSS) in middle-aged patients with advanced hepatocellular carcinoma. Clinical data were downloaded from the Surveillance, Epidemiology and End Results (SEER) database for middle-aged patients diagnosed with advanced hepatocellular carcinoma (AJCC stage III and IV) from 2000 to 2019. The patients were randomized in a 7:3 ratio into training cohort and validation cohort. Univariate and multivariate Cox regression analyses were performed in the training cohort to screen for independent risk factors associated with cancer-specific survival for the construction of nomogram. The nomogram was examined and evaluated using the consistency index (C-index), area under the curve (AUC), and calibration plots. The clinical application value of the model was evaluated using decision curve analysis (DCA). A total of 3026 patients were selected, including 2244 in the training cohort and 962 in the validation cohort. Multivariate analysis revealed gender, marital status, American Joint Committee on Cancer (AJCC) stage, tumor size, bone metastasis, lung metastasis, alpha-fetoprotein (AFP) level, surgery, radiotherapy, chemotherapy as independent risk factors, which were all included in the construction of the nomogram. In the training cohort, the AUC values were 0.74 (95% CI: 0.76-0.72), 0.78 (95% CI: 0.82-0.75), and 0.82 (95% CI: 0.86-0.78) at 1-, 3-, and 5-year CSS, respectively. The calibration plots showed good consistency between the actual and predicted values. The DCA curves indicated that the nomogram model could more accurately predict CSS at 1-, 3-, and 5-year in middle-aged patients with advanced hepatocellular carcinoma compared with the AJCC staging system. Highly similar results to the training cohort were also observed in the validation cohort. In the risk stratification system, good differentiation was shown between the 2 groups, and Kaplan-Meier survival analysis indicated that surgery could prolong patient survival. In this study, we developed a nomogram and risk stratification system for predicting CSS in middle-aged patients with advanced hepatocellular carcinoma. The prediction model has good predictive performance and can help clinicians in judging prognosis and clinical decision making.

BAUSSS biomarker improves melanoma survival risk assessment.

The American Joint Committee on Cancer (AJCC) method of staging melanoma is dated and inaccurate. It ignores important prognostic melanoma features, especially the patient's age. BAUSSS is more accurate in determining survival risk for primary cutaneous melanoma patients who have no clinical or imaging evidence of nodal or distant metastases. BAUSSS is an algorithm incorporating analysis of Breslow thickness, Age, Ulceration, Subtype of melanoma, Sex and Site. These are the six features from the patient history along with the details from the melanoma pathology report that are most predictive of mortality outcome. To develop a single-page document that allows the clinician to determine BAUSSS biomarker-predicted prognosis in consultation with the patient. From various data sources, we developed an algorithm to predict melanoma mortality using the BAUSSS biomarker system. The single-page algorithm was made available to download at https://globalmelanoma.net/bausss-survival-chart, thus being readily available without charge to all clinicians and their patients. BAUSSS method of determining melanoma prognosis is more accurate and less costly than the AJCC staging system. The only surgery the patient requires is wide local excision of the primary tumour. This method of ascertaining melanoma risk does not require added surgery, costs, hospitalization, tests and anaesthesia, such as would be required if sentinel lymph node biopsy was undertaken. BAUSSS can be a useful tool in determining which primary melanoma patients are at sufficiently high risk to be considered for adjuvant drug therapy. We encourage clinicians to download and print in colour this single-page BAUSSS mortality prediction tool, laminate it, and use it face to face with the patient in consultations. Not only will the patient be able to recognize his/her long-term prognosis but will also be able to see how their tumour severity compares with others.

Key updates and interpretation of the ninth version of AJCC staging system for neuroendocrine tumors of the stomach

The cancer staging system of the American Joint Committee on Cancer (AJCC) is the most widely used clinical basis for tumor staging. In October 2023, AJCC released the staging system (ninth version) for the neuroendocrine tumors of stomach (NET), which has been implemented in January 2024. The ninth version of NET staging system mainly updated the histopathologic classification, diagnosis and staging methods, clinical and pathological staging, prognosis grade, tumor and non-tumor prognostic features. The update and implementation of the staging system provide a more detailed reference for the accurate diagnosis, staging and precise treatment of gastric neuroendocrine tumors. Moreover, it is convenient for clinicians to carry out clinical practice. The purpose of our article is to provide a high-level overview of the major changes in AJCC staging system (version 9) for gastric NET based on the latest evidence-based medical research.

A machine learning clinic scoring system for hepatocellular carcinoma based on the Surveillance, Epidemiology, and End Results database.

Hepatocellular carcinoma (HCC) poses a global threat to life; however, numerical tools to predict the clinical prognosis of these patients remain scarce. The primary objective of this study is to establish a clinical scoring system for evaluating the overall survival (OS) rate and cancer-specific survival (CSS) rate in HCC patients. From the Surveillance, Epidemiology, and End Results (SEER) Program, we identified 45,827 primary HCC patients. These cases were randomly allocated to a training cohort (22,914 patients) and a validation cohort (22,913 patients). Univariate and multivariate Cox regression analyses, coupled with Kaplan-Meier methods, were employed to evaluate prognosis-related clinical and demographic features. Factors demonstrating prognostic significance were used to construct the model. The model's stability and accuracy were assessed through C-index, receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curve analysis (DCA), while comparisons were made with the American Joint Committee on Cancer (AJCC) staging. Ultimately, machine learning (ML) quantified the variables in the model to establish a clinical scoring system. Univariate and multivariate Cox regression analyses identified 11 demographic and clinical-pathological features as independent prognostic indicators for both CSS and OS using. Two models, each incorporating the 11 features, were developed, both of which demonstrated significant prognostic relevance. The C-index for predicting CSS and OS surpassed that of the AJCC staging system. The area under the curve (AUC) in time-dependent ROC consistently exceeded 0.74 in both the training and validation sets. Furthermore, internal and external calibration plots indicated that the model predictions aligned closely with observed outcomes. Additionally, DCA demonstrated the superiority of the model over the AJCC staging system, yielding greater clinical net benefit. Ultimately, the quantified clinical scoring system could efficiently discriminate between high and low-risk patients. A ML clinical scoring system trained on a large-scale dataset exhibits good predictive and risk stratification performance in the cohorts. Such a clinical scoring system is readily integrable into clinical practice and will be valuable in enhancing the accuracy and efficiency of HCC management.

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

BackgroundSmall 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.MethodsWe 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).ResultsMultivariate 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.ConclusionThe 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.

A prognostic nomogram for the cancer-specific survival rate of choroidal melanoma using the Surveillance, Epidemiology, and End Results database.

This study was conducted to develop a comprehensive nomogram for individuals with choroidal melanoma (CM) to determine their cancer-specific survival (CSS). Data of individuals with CM, diagnosed between 2004 and 2015, were accessed at the Surveillance, Epidemiology, and End Results (SEER) database. The selected individuals were randomly categorized into a training and validation cohort. Multivariate Cox regression analysis was applied to screen the relevant variables. Followed by the development of a nomogram based on independent variables. Ultimately, the net reclassification index (NRI), concordance index (C-index), calibration charts, integrated discrimination improvement (IDI), receiver operating characteristic curves (ROC), area under the curve (AUC), and decision-curve analysis (DCA), were utilized to evaluate the discrimination, accuracy, and effectiveness of the model. This study enrolled 3,782 patients. Seven independent factors linked to prognosis were screened via multivariate Cox regression analysis, encompassing age at diagnosis; race; AJCC (American Joint Committee on Cancer) stage; histologic type; and therapy method of radiotherapy, surgery, and chemotherapy. The respective C-indexes of the training and validation cohorts were 0.709 and 0.726, indicative of the excellent accuracy of the nomogram. Furthermore, the AUCs of the training and validation cohorts across 3, 5, and 8 years were 0.767, 0.744, and 0.722 as well as 0.772, 0.770, and 0.753, respectively. Evident of the superiority of the established nomogram over the AJCC staging, both the NRI and IDI values exhibited improvement. The favorable clinical impact and good performance of the nomogram were evident via decision curve analyses (DCAs) and calibration plots, respectively. This research dealt with establishing and validating a nomogram as a prognostic tool for assessing the prognosis of adult patients with CM utilizing the SEER database. A comprehensive assessment of the nomogram via diverse variables demonstrated its accuracy in predicting the CSS probabilities of CM patients across 3, 5, and 8 years in clinical settings. Notably, its performance surpassed that of the AJCC staging system.

Abstract PO5-27-01: Comparison between the 7th and the 8th edition of TNM Staging System of American joint committee on Cancer(AJCC) for Breast Cancer Patients, diagnosed and treated at King Abdulaziz Medical City

Abstract Breast cancer is a heterogeneous disease with different biological and molecular characteristics that affect local recurrence, metastases, prognoses, and response to available therapies. The 8th edition of the American Joint Committee on Cancer (AJCC) staging system for breast cancer has incorporated the biological and molecular characteristics, tumor grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor status(Her-2)and tumor grade, into the traditional anatomical 7th edition that only considers tumor size, lymph nodes status, and distant metastases. The aim of this study is to compare the 7th to 8th editions of the AJCC staging system for prognostic impact, assess the effect of the new edition on the treatment and treatment outcome Method A retrospective cohort study was performed for all breast cancer patients, diagnosed between (2013 -2019) and underwent upfront surgery at King Abdulaziz Medical City (KAMC).Patients’ clinicopathological, immunohistochemical, surgical, therapeutic, and follow-up data were retrieved. Overall survival (OS) and breast cancer-specific survival (BCSS) were estimated using the Kaplan–Meier method. Univariate analysis using Fisher's exact test was used to compare staging systems' prognostic accuracy. Multivariable analysis using Cox proportional hazards regression analysis was performed to identify factors independently associated with disease outcome Results A total of 169 female patients were included, the 8th AJCC staging system resulted in a reallocation of 108 (63.9%) of the patients to a different stage group. The majority were downstaged(60.9%) while only 3% were upstaged, most of the upstaged patients had a triple-negative subtype (80%). The change in overall stage for the 8th edition was most significant in stage I (an increase by 140.3%), followed by stage II (downstaged by 74.3%) and stage III (downstaged by 49.7%) compared to the 7th edition. Critically 42.8% of all downstaged patients treated with adjuvant chemotherapy were found to have received unnecessary chemotherapy after applying the 8th AJCC staging system as per National Comprehensive Cancer Network (NCCN) clinical practice guidelines recommendations. The 8th AJCC staging system was a better prognostic predictor of disease survival, patients in 8th AJCC stage 3 had a higher tendency to develop metastases and die because of their disease (P-value 0.03, 0.051, respectively). Conclusions: Our comparison revealed that the AJCC 8th edition staging system is superior and more comprehensive than the 7th, in term of prognostic value, and in defining the precise adjuvant therapy Figure 1 Comparison of the 7th AJCC and the 8th AJCC staging system Citation Format: Nafisa Abdelhafiez, Abdulmohsen Alkushi, Lolwah Alriyees, Mohammad Arabi, Faris Alsalamah, Emad Masuadi, Ahmad Omair, Mohammad Alkaiyat, Hussam Shehata. Comparison between the 7th and the 8th edition of TNM Staging System of American joint committee on Cancer(AJCC) for Breast Cancer Patients, diagnosed and treated at King Abdulaziz Medical City [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-27-01.

A nomogram incorporating treatment data for predicting overall survival in gastroenteropancreatic neuroendocrine tumors: a population-based cohort study.

Over the last few decades, the annual global incidence of gastroenteropancreatic neuroendocrine tumours (GEP-NETs) has steadily increased. Because of the complex and inconsistent treatment of GEP-NETs, the prognosis of patients with GEP-NETs is still difficult to assess. The study aimed to construct and validate the nomograms included treatment data for prediction overall survival (OS) in GEP-NETs patients. GEP-NETs patients determined from the Surveillance, Epidemiology, and End Results (SEER)-13 registry database (1992-2018) and with additional treatment data from the SEER-18 registry database (1975-2016). In order to select independent prognostic factors that contribute significantly to patient survival and can be included in the nomogram, multivariate Cox regression analysis was performed using the minimum value of Akaike information criterion (AIC) and we analyzed the relationship of variables with OS by calculating hazard ratios (HRs) and 95% CIs. In addition, we also comprehensively compared the nomogram using to predict OS with the current 7th American Joint Committee on Cancer (AJCC) staging system. From 2004 to 2015, a total of 42662 patients at diagnosis years with GEP-NETs were determined from the SEER database. The results indicated that the increasing incidence of GEP-NETs per year and the highest incidence is in patients aged 50-54. After removing cases lacking adequate clinicopathologic characteristics, the remaining eligible patients ( n =7564) were randomly divided into training (3782 patients) and testing sets (3782 patients). In the univariate analysis, sex, age, race, tumour location, SEER historic stage, pathology type, TNM, stage, surgery, radiation, chemotherapy, and CS tumour size were found to be significantly related to OS. Ultimately, the key factors for predicting OS were determined, involving sex, age, race, tumour location, SEER historic stage, M, N, grade, surgery, radiation, and chemotherapy. For internal validation, the C-index of the nomogram used to estimate OS in the training set was 0.816 (0.804-0.828). For external validation, the concordance index (C-index) of the nomogram used to predict OS was 0.822 (0.812-0.832). In the training and testing sets, our nomogram produced minimum AIC values and C-index of OS compared with AJCC stage. Decision curve analysis (DCA) indicated that the nomogram was better than the AJCC staging system because more clinical net benefits were obtained within a wider threshold probability range. A nomogram combined treatment data may be better discrimination in predicting overall survival than AJCC staging system. The authors highly recommend to use their nomogram to evaluate individual risks based on different clinical features of GEP-NETs, which can improve the diagnosis and treatment outcomes of GEP-NETs patients and improve their quality of life.

Evaluation of AJCC staging system and proposal of a novel stage grouping system in retroperitoneal liposarcoma: the Fudan Zhongshan experience.

Overall survival (OS) varies significantly among individuals with heterogeneous retroperitoneal liposarcoma (RPLS), even among those with the same clinical stage. Improved staging of RPLS is a critical unmet need, given the disappointing results of external validations of the 8th American Joint Committee on Cancer (AJCC) TNM staging system. The cohort study included 220 consecutive patients who underwent surgical resection for primary RPLS at the largest sarcoma centre of Fudan University in China from September 2009 to August 2021, combined with 277 adult patients with RPLS in the SEER database from 1975 to 2020. Data analysis was performed from December 2021 to December 2022. Patients were retrospectively restaged according to the 8th and 7th editions of the TNM staging system as well as the new TNM (nTNM) staging system. The primary endpoint was overall survival (OS). Comparative analysis of postoperative survival was performed using the Kaplan-Meier method, and differences between subgroups were tested using the log-rank test. The OS prediction nomogram was generated based on baseline variables and tumour characteristics. Harrell's consistency index (C-index), area under the curve (AUC) of receiver operating characteristic curves (ROC), and calibration curves were used to evaluate the performance of the nomogram. A total of 497 patients were enrolled in the study, including 282 (56.7%) male patients. The median follow-up was 51 months (interquartile range, IQR, 23-83), and the OS rates at 1, 3, and 5 years were 87.9%, 75.3%, and 64.9%, respectively. According to the staging distribution of the AJCC 7th edition, 6 patients were stage IA (1.2%), 189 patients were stage IB (38%), 12 patients were stage IIA (2.4%), 150 patients were stage IIB (30.1%), 131 patients were stage III (26.3%), and 9 patients were stage IV (1.8%). With the 8th edition staging, this distribution changed: 6 patients (1.2%) were stage IA, 189 patients (38%) were stage IB, 12 patients (2.4%) were stage II, 24 patients (4.8%) were stage IIIA, 257 patients (51.7%) were stage IIIB, and 9 patients (1.8%) were stage IV. 182 patients (36.6%) were reclassified according to the nTNM staging system with the new T stage classification. The C-index and log-rank score improved after implementation of nTNM implementation. The nTNM system was associated with improved identification of high-risk patients compared with the AJCC 7th and 8th TNM. The FNCLCC stage proved to be highly prognostic with significant intergroup differences in OS. The calibration curve shows a high degree of agreement between the actual OS rate and the nomogram estimated OS rate. Compared with 8th AJCC TNM, 7th AJCC TNM staging system showed a more homogeneous staging distribution and a slight improvement in the prognostic accuracy of RPLS. The revised T-stage and nTNM systems showed better risk stratification performance. The FNCLCC stage was found to have high prognostic value, further emphasising histological grade is the least negligible prognostic factor in predicting patient survival. The constructed nomogram model enables individualized prognostic analysis and helps to develop risk-adapted therapy for RPLS patients.

Prognostic nomograms for predicting long-term overall survival in spindle cell melanoma: a population-based study.

There are few research findings on the survival prognosis of spindle cell melanoma (SCM), which is an unusual kind of melanoma. The purpose of this study was to develop a thorough nomogram for predicting the overall survival (OS) of patients with SCM and to assess its validity by comparing it with the conventional American Joint Committee on Cancer (AJCC) staging system. The Surveillance, Epidemiology, and End Results database was searched, and 2,015 patients with SCM were selected for the analysis. The patients were randomly divided into training (n = 1,410) and validation (n = 605) cohorts by using R software. Multivariate Cox regression was performed to identify predictive factors. A nomogram was established based on these characteristics to predict OS in SCM. The calibration curve, concordance index (C-index), area under the receiver operating characteristic curve, and decision-curve analysis were utilized to assess the accuracy and reliability of the model. The net reclassification improvement and integrated discrimination improvement were also applied in this model to evaluate its differences with the AJCC model. The developed nomogram suggests that race, AJCC stage, chemotherapy status, regional node examination status, marital status, and sex have the greatest effects on OS in SCM. The nomogram had a higher C-index than the AJCC staging system (0.751 versus 0.633 in the training cohort and 0.747 versus 0.650 in the validation cohort). Calibration plots illustrated that the model was capable of being calibrated. These criteria demonstrated that the nomogram outperforms the AJCC staging system alone. The nomogram developed in this study is sufficiently reliable for forecasting the risk and prognosis of SCM, which may facilitate personalized treatment recommendations in upcoming clinical trials.

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

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. 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). 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. 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.

Development and validation of web-based nomograms for predicting survival status in patients with intrahepatic cholangiocarcinoma depending on the surgical status: a SEER database analysis

This study aimed to develop and validate prognostic nomograms that can estimate the probability of 1-, 3- and 5-year overall survival (OS) as well as cancer-specific survival (CSS) for Intrahepatic cholangiocarcinoma (ICCA) patients. Clinical data of 1446 patients diagnosed with ICCA between 2010 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database were analyzed. In both the OS and the CSS group, the training cohort and validation cohort were divided into a 7:3 ratio. Age, sex, AJCC T stage, AJCC N stage, AJCC M stage, surgical status, and tumor grade were selected as independent prognostic risk factors to build the nomograms. To compare the efficacy of predicting 1-, 3-, and 5-year OS and CSS rates of the nomogram with the 8th edition of the American Joint Committee on Cancer (AJCC) staging system, we evaluated the Harrell’s index of concordance (C-index), area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) in both cohorts. The results showed the nomogram for 1-, 3-, and 5-year OS and CSS prediction performed better than the AJCC staging system. In the subgroup analysis for patients could not receive surgery as the primary treatment. We developed two nomograms for predicting the 1-, and 2-year OS and CSS rates following the same analysis procedure. Results indicate that the performance of both nomograms, which contained sex, AJCC T stage, AJCC M stage, chemotherapy, and tumor grade and prognostic factors, was also superior to the AJCC staging system. Meanwhile, four dynamic network-based nomograms were published. The survival analysis showed the survival rate of patients classified as high-risk based on the nomogram score was significantly lower compared to those categorized as low-risk (P < 0.0001). Finally, accurate and convenient nomograms were established to assist clinicians in making more personalized prognosis predictions for ICCA patients.

LASSO-derived prognostic model predicts cancer-specific survival in advanced pancreatic ductal adenocarcinoma over 50 years of age: a retrospective study of SEER database research.

This study aimed to develop a prognostic model for patients with advanced ductal adenocarcinoma aged ≥50 years. Patient information was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to screen the model variables. Cases from Nanchang Central Hospital were collected for external validation. The new nomogram and the American Joint Committee on Cancer (AJCC) criteria were evaluated using integrated discrimination improvement (IDI) and net reclassification index (NRI) indicators. Survival curves presented the prognosis of the new classification system and AJCC criteria. In total, 17,621 eligible patients were included. Lasso Cox regression selected 4 variables including age, chemotherapy, radiotherapy and AJCC stage. The C-index of the training cohort was 0.721. The C-index value of the validation cohort was 0.729. The AUCs for the training cohorts at 1, 2, and 3 years were 0.749, 0.729, and 0.715, respectively. The calibration curves showed that the predicted and actual probabilities at 1, 2, and 3 years matched. External validation confirmed the model's outstanding predictive power. Decision curve analysis indicated that the clinical benefit of the nomogram was higher than that of the AJCC staging system. The model evaluation indices preceded the AJCC staging with NRI (1-year: 0.88, 2-year: 0.94, 3-year: 0.72) and IDI (1-year: 0.24, 2-year: 0.23, 3-year: 0.22). The Kaplan-Meier curves implied that the new classification system was more capable of distinguishing between patients at different risks. This study established a prognostic nomogram and risk classification system for advanced pancreatic cancer in patients aged ≥50 years to provide a practical tool for the clinical management of patients with pancreatic ductal adenocarcinoma.

Development and Validation of Nomograms to Predict Risk and Prognosis in Salivary Gland Carcinoma Patient with Distant Metastases.

Background: Salivary gland carcinoma (SGC) patients with distant metastasis (DM) are rare, and understanding this disease is insufficient. Nomograms can predict the prognostic probability of patients, while few studies have examined diagnostic and prognostic factors in SGC patients with DM. The purpose of this study was to establish and validate the risk and prognostic nomograms of SGC patients with DM. Methods: Based on the SEER database, we analyzed the data of SGC patients between 2004 and 2015. Logistic regression analyses and Cox proportional hazards regression analyses were used to identify risk and prognostic factors for DM in SGC patients. Based on the Akaike information criterion (AIC) value and likelihood ratio test, the best-fitting model was selected to build risk and prognostic nomograms, and the results were evaluated by receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and Kaplan-Meier (K-M) survival curves. ROC curves were also used to compare the nomograms with the American Joint Committee on Cancer (AJCC) staging system. Results: 7418 SGC patients were included in the study, and 307 (4.14%) of them were diagnosed with DM. This study identified that there are variables (age ≥ 80, no-parotid gland primary site, histologic type of mucoepidermoid carcinoma and squamous cell carcinoma, T stage ≥ T2, N staged ≥ N1, histologic grade ≥ III, and tumor size ≥ 41 mm) associated with the occurrence of DM in SGC patients. Therefore, we constructed diagnostic and prognostic nomograms after incorporating these variables. ROC curves illustrated the better predictive efficacy of 2 nomograms over the AJCC staging system. DCA curves, calibration curves, and K-M survival curves showed that 2 nomograms can accurately predict the occurrence and prognosis of DM among SGC patients in training and validation sets. Conclusion: It was shown that the nomograms were highly discriminative in predicting the diagnosis and prognosis of SGC patients with DM, and could identify high-risk patients, thereby providing SGC patients with individualized treatment plans.

Prediction of postoperative recurrence in resectable pancreatic body/tail adenocarcinoma: a novel risk stratification approach using a CT-based nomogram.

To identify prognostic CT features that predict recurrence in patients with resectable pancreatic body/tail adenocarcinoma (PBTA) and construct a CT-based nomogram for preoperative risk stratification. A total of 258 patients with resectable PBTA who underwent upfront surgery were retrospectively enrolled (development cohort, n = 172; validation cohort, n = 86), and their clinical and CT features were analyzed. Stepwise Cox proportional hazard analysis was performed to identify prognostic features and construct a predictive nomogram for recurrence-free survival (RFS). The prognostic performance of the CT-based nomogram was validated and compared to the 8th American Joint Committee on Cancer (AJCC) pathological staging system. In the development cohort, the following five CT features for predicting recurrence were identified to construct the nomogram: tumor density in the venous phase, tumor necrosis, adjacent organ invasion, splenic vein invasion, and superior mesenteric vein/portal vein abutment. In the validation cohort, the CT-based nomogram showed a concordance index of 0.65 (95% confidence interval: 0.58-0.73), which was higher than the 8th AJCC staging system. The area under the curves of the nomogram for predicting recurrence at 0.5, 1, and 2years were 0.66, 0.71, and 0.72, respectively. Patients were categorized into high- and low-risk groups with 1-year recurrence probabilities of 0.73 and 0.43, respectively. The proposed nomogram provided accurate recurrence risk stratification for patients with resectable PBTA in a preoperative setting and may be used to facilitate clinical decision-making. The proposed CT-based nomogram, based on easily available CT features, may serve as an effective and convenient tool for stratifying further the recurrence risk of patients with pancreatic body/tail adenocarcinoma. • The CT-based nomogram, incorporating five commonly used CT features, successfully preoperatively stratified patients with resectable PBTA into distinct prognosis groups. • Tumor density in the venous phase, tumor necrosis, splenic vein invasion, adjacent organ invasion, and superior mesenteric vein/portal vein abutment were associated with RFS in patients with resectable PBTA. • The CT-based nomogram exhibited better predictive performance for recurrence than the 8th AJCC staging system.

The prognostic value of 11th Japanese classification and 8th AJCC staging systems in Chinese patients with esophageal squamous cell carcinoma

BackgroundTwo staging systems, the 8th staging system by the American Joint Committee on Cancer (AJCC) and the 11th Japanese classification by Japan Esophageal Society (JES), are currently applied in the clinic for predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC). The differences between the two staging systems have been widely researched. However, little studies focus on the differences in specific staging between the two systems. Therefore, we aimed to compare the performance of different staging in predicting overall survival (OS) of Chinese patients with ESCC.MethodsThis retrospective study included 268 patients who underwent radical esophagectomy and mediastinal lymph node dissection for ESCC between January 2008 and December 2013. Patients were staged by the 8th AJCC and 11th JES staging systems. OS was estimated using the Kaplan–Meier method and compared between N stages and between stage groupings using the log-rank test. Cox proportional hazards regression analysis was performed to identify factors independently related to outcome. Further, we compared the concordance indexes (C-indexes) of the two staging systems.ResultsThe mean age was 61.25 ± 7.056 years, median follow-up was 44.82 months, and 5-year OS rate was 47%. The OS was well predicted by the 8th AJCC N staging (P < 0.001) and the 11th JES N staging (P < 0.001), with a c-index of 0.638 (95% CI: 0.592–0.683) for AJCC N staging and 0.627 (95% CI: 0.583–0.670) for JES N staging (P = 0.13). In addition, the OS was also well predicted by stage groupings of the 8th AJCC (P < 0.001) and the 11th JES systems (P < 0.001), with a c-index of 0.658 (95% CI: 0.616–0.699) for 8th AJCC stage grouping and 0.629 (95% CI: 0.589–0.668) for the11th JES stage grouping (P = 0.211).ConclusionsThe prognostic effect of 11th JES staging system is comparable with that of AJCC 8th staging system for patients with ESCC. Therefore, both systems are applicable to clinical practice.

Proposal for a new N-stage classification system for intrahepatic cholangiocarcinoma.

The number of metastatic lymph nodes (MLNs) is not considered in the nodal status (N classification) of intrahepatic cholangiocarcinoma (ICC) in the current 8thEdition of the American Joint Committee on Cancer (AJCC) staging system. The aim of this study was to find out the optimal cut-off point based on the number of MLNs and establish a modified AJCC staging system for ICC according to the new N category. A total of 675 ICC patients diagnosed between 2004 and 2015 were retrieved from the Surveillance, Epidemiology and End Results (SEER) database. The optimal cut-off value of MLNs affecting survival was determined by X-tile software. The relative discriminative power was assessed by Harrell's concordance index (C-index) and Akaike information criterion (AIC). The proposed new nodal category subdivided patients into three groups (N0, no MLN; N1, 1-3 MLNs; and N2, ≥ 4 MLNs) with significantly different overall survival (P < 0.001). Multivariable analysis revealed that the new nodal category was an independent prognostic factor (P < 0.001). Both the C-index and AIC for our modified staging system were better than those for the 8th AJCC edition (0.574 [95% confidence interval 0.533-0.615] versus 0.570 [95% confidence interval 0.527-0.613], and 853.30 versus 854.21, respectively). The modified AJCC staging system based on the number of MLNs may prove to be a useful alternative for predicting survival of ICC patients in clinical practice.