American Joint Committee On Cancer Staging System Research Articles

Nomogram-Based Prognostic Evaluation of Gastric Cancer Patients with Low Counts of Examined Lymph Nodes Outperforms the Predictive Ability of the 7th and 8th Editions of the American Joint Committee on Cancer Staging System

BackgroundThe American Joint Committee on Cancer (AJCC) staging system has limited accuracy in predicting survival of gastric cancer patients with inadequate counts of evaluated lymph nodes (LNs). We therefore aimed to develop a prognostic nomogram suitable for clinical applications in such cases. MethodsA total of 1511 noncardia gastric cancer patients treated between 1990 and 2010 in the academic surgical center were reviewed to compare the 7th and 8th editions of the AJCC staging system. A nomogram was developed for the prediction of 5-year survival in patients with less than 16 LNs evaluated (n = 546). External validation was performed using datasets derived from the Polish Gastric Cancer Study Group (n = 668) and the SEER database (n = 11,225). ResultsThe 8th edition of AJCC staging showed better overall discriminatory power compared to the previous version, but no improvement was found for patients with < 16 evaluated LNs. The developed nomogram had better concordance index (0.695) than the former (0.682) or latest (0.680) staging editions, including patients subject to neoadjuvant treatment, and calibration curves showed excellent agreement between the nomogram-predicted and actual survival. High discriminatory power was also demonstrated for both validation cohorts. Subsequently, the nomogram showed the best accuracy for the prediction of 5-year survival through the time-dependent ROC curve analysis in the training and validation cohorts. ConclusionsA clinically relevant nomogram was built for the prediction of 5-year survival in patients with inadequate numbers of LNs evaluated in surgical specimens. The predictive accuracy of the nomogram was validated in two Western populations.

Clinical features and prognostic factors in patients with microvascular infiltration of hepatocellular carcinoma: Development and validation of a nomogram and risk stratification based on the SEER database.

BackgroundThe goal is to establish and validate an innovative prognostic risk stratification and nomogram in patients of hepatocellular carcinoma (HCC) with microvascular invasion (MVI) for predicting the cancer-specific survival (CSS).Methods1487 qualified patients were selected from the Surveillance, Epidemiology and End Results (SEER) database and randomly assigned to the training cohort and validation cohort in a ratio of 7:3. Concordance index (C-index), area under curve (AUC) and calibration plots were adopted to evaluate the discrimination and calibration of the nomogram. Decision curve analysis (DCA) was used to quantify the net benefit of the nomogram at different threshold probabilities and compare it to the American Joint Committee on Cancer (AJCC) tumor staging system. C-index, net reclassification index (NRI) and integrated discrimination improvement (IDI) were applied to evaluate the improvement of the new model over the AJCC tumor staging system. The new risk stratifications based on the nomogram and the AJCC tumor staging system were compared.ResultsEight prognostic factors were used to construct the nomogram for HCC patients with MVI. The C-index for the training and validation cohorts was 0.785 and 0.776 respectively. The AUC values were higher than 0.7 both in the training cohort and validation cohort. The calibration plots showed good consistency between the actual observation and the nomogram prediction. The IDI values of 1-, 3-, 5-year CSS in the training cohort were 0.17, 0.16, 0.15, and in the validation cohort were 0.17, 0.17, 0.17 (P<0.05). The NRI values of the training cohort were 0.75 at 1-year, 0.68 at 3-year and 0.67 at 5-year. The DCA curves indicated that the new model more accurately predicted 1-year, 3-year, and 5-year CSS in both training and validation cohort, because it added more net benefit than the AJCC staging system. Furthermore, the risk stratification system showed the CSS in different groups had a good regional division.ConclusionsA comprehensive risk stratification system and nomogram were established to forecast CSS for patients of HCC with MVI.

Prognostic nomograms for lung neuroendocrine carcinomas based on lymph node ratio: a SEER database analysis.

ObjectiveThe current study aimed to explore the prognostic value of the lymph node ratio (LNR) in patients with lung neuroendocrine carcinomas (LNECs).MethodsData for 1564 elderly patients with LNECs between 1998 and 2016 were obtained from the Surveillance, Epidemiology, and End Results database. The cases were assigned randomly to training (n = 1086) and internal validation (n = 478) sets. The association between LNR and survival was investigated by Cox regression.ResultsMultivariate analyses identified age, tumor grade, summary stage, M stage, surgery, and LNR as independent prognostic factors for both overall survival (OS) and lung cancer-specific survival (LCSS). Tumor size was also a prognostic determinant for LCSS. Prognostic nomograms combining LNR with other informative variables showed good discrimination and calibration abilities in both the training and validation sets. In addition, the C-index of the nomograms was statistically superior to the American Joint Committee on Cancer (AJCC) staging system in both the training and validation cohorts.ConclusionsThese nomograms, based on LNR, showed superior prognostic predictive accuracy compared with the AJCC staging system for predicting OS and LCSS in patients with LNECs.

Construction of a new clinical staging system for colorectal cancer based on the lymph node ratio: A validation study.

AimThis study aims to construct a new staging system for colorectal cancer (CRC) based on the lymph node ratio (LNR) as a supplement to the American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging system for predicting the prognosis of CRC patients with <12 lymph nodes.MethodsThe data of 26,695 CRC patients with <12 lymph nodes were extracted from the Surveillance, Epidemiology, and End Results (SEER) database as a training set. A total of 635 CRC patients were also enrolled from Northern Jiangsu People's Hospital affiliated with Yangzhou University as an independent validation set. Classification and regression tree analysis was used to obtain the LNR cutoff value. Survival curves were estimated using the Kaplan–Meier method, and the log-rank test was used for comparisons of differences among the survival curves. The monotonic decreasing trend of the overall survival curve in the staging system was expressed by the linear correlation degree R.ResultsThe 5-year survival rates of patients in the training set based on the AJCC staging system from stage I to stage IV were 75.6% (95%CI: 74.4–76.8), 59.8% (95%CI: 58.6–61.0), 42.1% (95%CI: 34.5–49.7), 33.2% (95%CI: 24.6–41.8), 72.0% (95%CI: 69.1–74.9), 48.8% (95%CI: 47.4–50.2), 26.5% (95%CI: 23.0–30.0), and 11.3% (95%CI: 10.3–12.3). The 5-year survival rates of patients in the training set from stage I to stage IIIC were 80.4%, 72.9%, 59.8%, 48.4%, 32.5%, and 15.0%, according to the TNM + LNR (TNRM) staging system. According to the AJCC staging system, the 5-year survival rates of patients in the validation set from stage I to stage IIIC were 91.3%, 90.8%, 72.6%, 61.3%, 72.4%, 58.1%, and 32.8%. Based on the TNRM staging system, the 5-year survival rates of patients in the validation set from stage I to stage IIIC were 99.2%, 90.5%, 81.4%, 78.6%, 60.2%, and 35.8%.ConclusionThe TNRM staging system successfully eliminated “survival paradox” in the AJCC staging system, which might be superior to the AJCC staging system.

A Practical Nomogram and Risk Stratification System Predicting Cancer-Specific Survival for Hepatocellular Carcinoma Patients With Severe Liver Fibrosis.

ObjectiveHepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths worldwide. This study aims to construct a novel practical nomogram and risk stratification system to predict cancer-specific survival (CSS) in HCC patients with severe liver fibrosis.MethodsData on 1,878 HCC patients with severe liver fibrosis in the period 1975 to 2017 were extracted from the Surveillance, Epidemiology, and End Results database (SEER). Patients were block-randomized (1,316 training cohort, 562 validation cohort) by setting random seed. Univariate and multivariate COX regression analyses were employed to select variables for the nomogram. The consistency index (C-index), the area under time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration curves were used to evaluate the performance of the nomogram. Decision curve analysis (DCA), the C-index, the net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to compare the nomogram with the AJCC tumor staging system. We also compared the risk stratification of the nomogram with the American Joint Committee on Cancer (AJCC) staging system.ResultsSeven variables were selected to establish the nomogram. The C-index (training cohort: 0.781, 95%CI: 0.767–0.793; validation cohort: 0.793, 95%CI = 95%CI: 0.779–0.798) and the time-dependent AUCs (the training cohort: the values of 1-, 3-, and 5 years were 0.845, 0.835, and 0.842, respectively; the validation cohort: the values of 1-, 3-, and 5 years were 0.861, 0.870, and 0.876, respectively) showed satisfactory discrimination. The calibration plots also revealed that the nomogram was consistent with the actual observations. NRI (training cohort: 1-, 2-, and 3-year CSS: 0.42, 0.61, and 0.67; validation cohort: 1-, 2-, and 3-year CSS: 0.26, 0.52, and 0.72) and IDI (training cohort: 1-, 3-, and 5-year CSS:0.16, 0.20, and 0.22; validation cohort: 1-, 3-, and 5-year CSS: 0.17, 0.26, and 0.30) indicated that the established nomogram significantly outperformed the AJCC staging system (P < 0.001). Moreover, DCA also showed that the nomogram was more practical and had better recognition.ConclusionA nomogram for predicting CSS for HCC patients with severe liver fibrosis was established and validated, which provided a new system of risk stratification as a practical tool for individualized treatment and management.

Predicting survival after surgery for pancreatic adenocarcinoma: Testing accuracy of current models.

e16286 Background: Pancreatic adenocarcinoma (PDAC) remains highly morbid, and outcomes are difficult to prognosticate. Multiple models have also been developed to predict survival following surgical resection of PDAC, but their clinical utility remains unclear. This study aims to determine the accuracy of these algorithms for predicting PDAC survival. Methods: We performed a retrospective analysis using a de-identified dataset of patients who received neoadjuvant chemotherapy and underwent surgical resection of PDAC at four academic medical centers across the United States between 2010 and 2020. For this analysis the prognostic accuracy of the Memorial Sloan Kettering Cancer Center Pancreatic Adenocarcinoma Nomogram (MSKCCPAN) and the American Joint Committee on Cancer (AJCC) staging system were evaluated. For the MSKCCPAN, the prognostic index (PI) for each patient was calculated using the nomogram’s underlying Cox model. The PI was then used as input for the model’s survival function, which calculates the probability of DSS at 12-, 24-, and 36-month intervals. For the AJCC staging system, we assessed statistical discrimination between stage and DSS. We evaluated the concordance between predicted and actual DSS of both algorithms using the Uno C-statistic. Results: A total of 303 patients with complete information were included in the study, with 155 (51.2%) female patients and a mean age of 65.0 years (SD, 9.2 years). At the time of surgery, 47 (15.5%) patients had AJCC Stage IA disease, 45 (14.9%) had Stage IB, 49 (16.2%) had Stage IIA, 105 (34.6%) had Stage IIB, and 57 (18.8%) had Stage III. The median follow-up time of the cohort was 37.7 months (IQR, 16.4-70.7). One hundred eleven (36.6%) patients were alive at last follow-up, while 155 (51.2%) patients had died of disease. Thirty-seven (12.2%) patients died of another cause. The Kaplan-Meier estimated 12-, 24-, and 36-month DSS of the cohort was 74.3% (95% CI, 69.1-79.9), 46.6% (95% CI, 40.3-53.9) and 39.3% (95% CI, 32.9-46.9), respectively. The MSKCCPAN-predicted DSS at 12, 24, and 36 months was 78.1% (95% CI, 76.1-80.0), 56.4% (95% CI, 53.7-59.0), and 45.0% (95%0.781 CI, 42.3-47.6). For the MSKCCPAN, the calculated Uno C-statistic was 0.61 at 12 months and 0.62 at both 24 and 36 months. For the AJCC staging system, the Uno C-statistic was 0.61 at 12 months and 0.60 at both 24 months and 36 months. Conclusions: The present analysis suggests that concordance of current predictive models and staging systems with real world survival in patients with PDAC undergoing surgical resection after neoadjuvant chemotherapy has limited accuracy. Improving risk stratification of patients with PDAC will afford greater opportunities for tailoring patient selection, precision medicine initiatives, and trial design. There is an urgent need to develop novel models that better prognosticate outcomes following surgical resection of PDAC.

Prognostic Significance of Growth Pattern in Predicting Outcome of Opisthorchis viverrini-Associated Distal Cholangiocarcinoma in Thailand

Distal cholangiocarcinoma (dCCA) is a rare type of CCA in Asia, even in Opisthorchis viverrini-prevalent Northeastern Thailand. The clinical ambiguity and imprecision of diagnosis surrounding this malignancy result in high mortality due often to advanced/metastatic disease on presentation. We aim to identify a prognostic factor that can improve the performance stratification and influence the outcome of dCCA patients after curative resection. A total of 79 patients who underwent curative-intended surgery for dCCA was enrolled. Possible risk factors for survival were analyzed with log-rank test, and independent factors with Cox regression model. dCCA patients were staged and classified according to the 8th edition the American Joint Committee on Cancer (AJCC) Staging Manual. Results were then compared with the revised classification employing the prognostic factor identified from multivariate analysis. Multivariate analysis revealed that growth pattern (p < 0.01) and distant metastasis (p = 0.012) were independent factors. Growth patterns comprise intraductal (ID), periductal infiltrating (PI), mass-forming (MF), and mixed types. When dCCA patients were grouped into those having good and poor outcomes (with and without ID components, respectively). The survival outcomes significantly differed among patients with and without ID components, which was better than with the 8th AJCC staging system in our cohort. Furthermore, Chi-square test showed that patterns without ID components (PI, MF, PI + MF) correlated with lymph node and distant metastasis. Therefore, classification of dCCA patients after curative-intended surgical resection based on growth pattern provides additional beneficial information for the prediction of survival in dCCA patients.

Utilization of the lymph node-to-primary tumor ratio of PET standardized uptake value and circulating Epstein–Barr virus DNA to predict distant metastasis in nasopharyngeal carcinoma

Background and purposeTo determine the clinical impact of integrating Epstein–Barr virus (EBV) DNA and lymph node-to-primary tumor ratio (NTR) of positron emission tomography (PET) standardized uptake value (SUV) in predicting distant metastasis, such as distant metastasis-free survival (DMFS), in patients with nasopharyngeal carcinoma (NPC). Materials and methodsWe retrospectively reviewed patients diagnosed with non-disseminated NPC between 2010 and 2017. The optimal cut-off values of EBV DNA and SUV NTR were determined using receiver operating characteristic analysis. The prognostic values of SUV NTR and EBV DNA on DMFS and overall survival were evaluated using the Kaplan–Meier method. Univariate and multivariable analyses were performed using the Wald Chi-squared test and Cox proportional hazards regression, respectively. ResultsA total of 488 patients were included in the analysis. The median follow-up period was 61.6 months. The optimal cut-off values of EBV DNA and SUV NTR were 3377.5 copies per mL and 0.64, respectively. The five-year DMFS for patients with high vs low EBV DNA and SUV NTR levels were 64.9% vs 86.6% (p < 0.001) and 78.7% vs 87.4% (p = 0.021), respectively. In subgroup analysis, the high-risk group with high levels of pretreatment EBV DNA and SUV NTR had worse DMFS in either American Joint Committee on Cancer (AJCC) stage I–III or IVA–B (p = 0.001 and <0.001, respectively). Univariate and multivariable analyses showed the statistical significance of EBV DNA, SUV NTR, and their composite in DMFS (p < 0.001 for EBV DNA; p = 0.022 for SUV NTR; p < 0.001 for their composite). ConclusionThis study showed that EBV DNA and SUV NTR have independent and additive values as prognosticators for distant metastasis in patients with NPC, suggesting that these two individual factors, except the AJCC staging system, should be included in future studies.

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.

Validation of the Memorial Sloan Kettering Gastric Cancer Post-Resection Survival Nomogram: Does It Stand the Test of Time?

The Memorial Sloan Kettering Cancer Center (MSK) nomogram combined both gastroesophageal junction (GEJ) and gastric cancer patients and was created in an era from patients who generally did not receive neoadjuvant chemotherapy. We sought to reevaluate the MSK nomogram in the era of multidisciplinary treatment for GEJ and gastric cancer. Using data on patients who underwent R0 resection for GEJ or gastric cancer between 2002 and 2016, the C-index of prediction for disease-specific survival (DSS) was compared between the MSK nomogram and the American Joint Committee on Cancer (AJCC) 8th edition staging system after segregating patients by tumor location (GEJ or gastric cancer) and neoadjuvant treatment. A new nomogram was created for the group for which both systems poorly predicted prognosis. During the study period, 886 patients (645 gastric and 241 GEJ cancer) underwent up-front surgery, and 999 patients (323 gastric and 676 GEJ) received neoadjuvant treatment. Compared with the AJCC staging system, the MSK nomogram demonstrated a comparable C-index in gastric cancer patients undergoing up-front surgery (0.786 vs 0.753) and a better C-index in gastric cancer patients receiving neoadjuvant treatment (0.796 vs 0.698). In GEJ cancer patients receiving neoadjuvant chemotherapy, neither the MSK nomogram nor the AJCC staging system performed well (C-indices 0.647 and 0.646). A new GEJ nomogram was created based on multivariable Cox regression analysis and was validated with a C-index of 0.718. The MSK gastric cancer nomogram's predictive accuracy remains high. We developed a new GEJ nomogram that can effectively predict DSS in patients receiving neoadjuvant treatment.

Does Albumin Level Change the Strength of the Memorial Sloan Kettering Cancer Center Nomogram Used to Predict 5-year Survival in Patients with Colon Cancer?

To test the efficacy of including albumin in the Memorial Sloan Kettering Cancer Center (MKSCC) nomogram (MSKCC+A) on predicting the overall survival. Descriptive study. Ankara Training and Research Hospital & Ataturk Training and Research Hospital, Turkey, in 2020, on patients who were operated between 2009 and 2014 to confirm the 5-year survival results. Patients who underwent R0 resection for colon cancer were evaluated. For each patient in the cohort, the 5-year probability of survival was calculated and compared with actual, using the AJCC (American Joint Committee on Cancer), MSKCC and MSKCC+A estimation systems obtained using logistic regression. The performance of the estimation methods was evaluated by the ROC analysis. Two hundred and thirty-nine patients were studied. When the patients with more than 5-year overall survival were compared, the AJCC, MSKCC, and enhanced MSKCC survival scores were significantly higher. AUC = 0.699 for the AJCC staging system, AUC = 0.702 for the MKSCC nomogram, and AUC = 0.777 when the albumin level was added to the MKSCC system. The use of the MSKCC overall survival nomogram in patients with colon cancer appears useful for both clinicians and patients. The prognostic power of this calculator was found to be further enhanced by including the preoperative serum albumin level as an extra variable in the nomogram. Nomograms, Neoplasm grading, Survival, Colon cancer, Serum albumin.

Development and Validation of the Nomograms for Predicting Overall Survival and Cancer-Specific Survival in Patients With Synovial Sarcoma.

BackgroundThe study aimed to build and validate practical nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with synovial sarcoma (SyS).MethodsA total of 893 eligible patients confirmed to have SyS between 2007 and 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided into the training cohort (n = 448) and validation cohort (n = 445). Clinically independent prognostic and important factors were determined according to the Akaike information criterion in multivariate Cox regression models when developing the nomograms with the training cohort. The predictive accuracy of nomograms was bootstrapped validated internally and externally with the concordance index (C-index) and calibration curve. Decision curve analysis (DCA) was performed to compare the clinical usefulness between nomograms and American Joint Commission on Cancer (AJCC) staging system.ResultsTwo nomograms shared common indicators including age, insurance status, tumor site, tumor size, SEER stage, surgery, and radiation, while marital status and tumor site were only included into the OS nomogram. The C-index of nomograms for predicting OS and CSS was 0.819 (0.873–0.764) and 0.821 (0.876–0.766), respectively, suggesting satisfactory predictive performance. Internal and external calibration curves exhibited optimal agreement between the nomogram prediction and the actual survival. Additionally, DCA demonstrated that our nomograms had obvious superiority over the AJCC staging system with more clinical net benefits.ConclusionsTwo nomograms predicting 3- and 5-year OS and CSS of SyS patients were successfully constructed and validated for the first time, with higher predictive accuracy and clinical values than the AJCC staging system regarding OS and CSS.

Proposed modification of the eighth edition of the AJCC-ypTNM staging system of esophageal squamous cell cancer treated with neoadjuvant chemotherapy: Unification of the AJCC staging system and the Japanese classification

BackgroundThe eighth edition of the American Joint Committee on Cancer (AJCC) tumor node metastasis (AJCC-TNM 8th) system adopted the newly separate post-neoadjuvant pathologic stage group (ypTNM). However, it is not compatible with the Japanese pathologic classification after neoadjuvant chemotherapy (JPN-CT-pTNM). The aim of this study is to clarify the subjects of the AJCC-ypTNM 8th and propose a unification of the AJCC and Japanese systems to create novel AJCC-CT-pTNM 8th. MethodsParticipants were 304 esophageal squamous cell carcinoma (ESCC) patients who underwent neoadjuvant chemotherapy followed by 3 stage esophagectomy between 2010 and 2019. Predictive probabilities of pN, pM in AJCC-ypTNM 8th and JPN-CT-pTNM 11th systems were evaluated to propose novel system. ResultsIn training data from 234 patients, the overall survival rate was statistically better for ypStage IIIA than ypStage II (P = 0.040) resulting in staging inversion in AJCC-ypTNM 8th. Predictive probability of pathological N status in AJCC-ypTNM 8th (Akaike Information Criterion: AIC = 979.53) was superior to that in JPN-CT-pTNM 11th (AIC = 999.07). In AJCC-ypTNM 8th, 71% (15/21) of ypM1 diseases were supraclavicular lymph nodes (No. 104 L/N as regional in JPN-CT-pTNM 11th) metastases with considerably good prognosis. The predictive probability of the novel AJCC-CT-pTNM 8th [unification of ypStage II and IIIA, conversion of supraclavicular L/Ns metastases from ypM to ypN] (AIC = 1054.24) was superior to that of the existing AJCC-ypTNM 8th (AIC = 1070.74). The feasibility of novel system was validated using test data from 70 patients. ConclusionsUnification of the AJCC and Japanese systems yields a simpler and more precise predictive system after neoadjuvant chemotherapy.

A model for predicting the overall survival of gastroenteropancreatic neuroendocrine neoplasms after surgery

Background The increase in the incidence of gastroenteropancreatic neuroendocrine tumors (GEP-NENs) and refined morphological imaging techniques have led to a rise in the number of patients undergoing surgery. However, there is still a paucity of objective, clinically reliable and personalized tools to evaluate patient prognosis. Materials and methods We identified patients from the Surveillance, Epidemiology, and End Results (SEER) database who underwent surgery for GEP-NEN from 1975 to 2018. The predictors associated with OS were investigated by Multivariate Cox proportional hazards (PHs) regression analysis in the primary cohort; a prognostic nomogram was then built based on the multivariate analysis results. The performance of the nomogram was assessed by Harrell's concordance index (C-index) and calibration curve and compared with the eighth edition of the American Joint Committee on Cancer (AJCC) staging system. Results A total of 45,889 patients were enrolled in our study; 32,321 were included in the primary cohort, and 13,568 were included in the validation cohort. A nomogram incorporating Age, Differentiation, M staging, and AJCC staging was subsequently built based on the multivariate analysis. The C-index (0.833 for the primary cohort and 0.845 for the validation cohort) and calibration curves indicated good discriminative ability and calibration of the nomogram. Further analysis demonstrated that the nomogram had superior discriminatory ability than the AJCC staging system (C-index= 0.706). Conclusion The proposed nomogram showed excellent prediction with good calibration and discrimination, which can be used to make well-informed and individualized clinical decisions regarding the clinical management of GEP-NENs.

Establishment and validation of a novel nomogram for survival prediction of ovarian carcinosarcoma.

BackgroundOvarian carcinosarcoma (OCS) is a rare and aggressive histological type of ovarian cancer. Current prognostic methods for OCS are insufficient. This study was undertaken to establish and validate a novel nomogram for predicting the overall survival (OS) of OCS patients.MethodsWe extracted 820 patients with OCS from the Surveillance, Epidemiology, and End Results (SEER) database and further randomly assigned them to a training set (n=574) and a validation set (n=246) at a ratio of 7-to-3. Univariate and multivariate regression analyses were utilized to verity independent prognostic factors, and a prognostic nomogram was constructed based on the results. The performance of the new model was compared with that of the AJCC staging system using the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA).ResultsCox regression analysis suggested that age, grade, tumor size, the American Joint Committee on Cancer (AJCC) stage, surgery, and chemotherapy were the independent prognostic factors. These factors were integrated into a prognostic nomogram to determine the 1-, 3-, and 5-year OS of OCS patients. The AUC, NRI, IDI, calibration curves, and DCA data demonstrated that our nomogram had better discriminative ability than the AJCC staging system alone. The calibration curves indicate that the nomogram was well-calibrated. The DCA verified the clinical applicability of the nomogram.ConclusionsOur current study is the first to establish and internally validate a novel nomogram for predicting the 1-, 3-, and 5-year OS probabilities of OCS patients. Our prognostic nomogram was of good performance and can be an accurate tool to predict individualized survival time of OCS in clinical work.

Validation of the Eighth Edition of the American Joint Committee on Cancer (AJCC) TNM Staging System in Patients with Resected Ampullary Adenocarcinoma

Introduction: The purpose of this study is to assess the prognostic accuracy of the 7th and 8th AJCC staging system for ampullary cancer(AAC) and externally validate the 8th edition for resected AAC in an international cohort.

Effects of Total Pancreatectomy on Survival of Patients With Pancreatic Ductal Adenocarcinoma: A Population-Based Study.

Background: Total pancreatectomy (TP) seems to be experiencing a renaissance in recent years. In this study, we aimed to determine the long-term survival of pancreatic ductal adenocarcinoma (PDAC) patients who underwent TP by comparing with pancreaticoduodenectomy (PD), and formulate a nomogram to predict overall survival (OS) for PDAC individuals following TP.Methods: Patients who were diagnosed with PDAC and received PD (n = 5,619) or TP (n = 1,248) between 2004 and 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. OS and cancer-specific survival (CSS) of the PD and TP groups were compared using Kaplan-Meier method and log-rank test. Furthermore, Patients receiving TP were randomly divided into the training and validation cohorts. Univariate and multivariate Cox regression were applied to identify the independent factors affecting OS to construct the nomogram. The performance of the nomogram was measured according to concordance index (C-index), calibration plots, and decision curve analysis (DCA).Results: There were no significant differences in OS and CSS between TP and PD groups. Age, differentiation, AJCC T stage, radiotherapy, chemotherapy, and lymph node ratio (LNR) were identified as independent prognostic indicators to construct the nomogram. The C-indexes were 0.67 and 0.69 in the training and validation cohorts, while 0.59 and 0.60 of the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system. The calibration curves showed good uniformity between the nomogram prediction and actual observation. DCA curves indicated the nomogram was preferable to the AJCC staging system in terms of the clinical utility. A new risk stratification system was constructed which could distinguish patients with different survival risks.Conclusions: For PDAC patients following TP, the OS and CSS are similar to those who following PD. We developed a practical nomogram to predict the prognosis of PDAC patients treated with TP, which showed superiority over the conventional AJCC staging system.

Nomogram for predicting postoperative cancer-specific early death in patients with epithelial ovarian cancer based on the SEER database: a large cohort study

PurposeOvarian cancer is a common gynecological malignant tumor. Poor prognosis is strongly associated with early death, but there is no effective tool to predict this. This study aimed to construct a nomogram for predicting cancer-specific early death in patients with ovarian cancer.MethodsWe used data from the Surveillance, Epidemiology, and End Results database of patients with ovarian cancer registered from 1988 to 2016. Important independent prognostic factors were determined by univariate and multivariate logistic regression and LASSO Cox regression. Several risk factors were considered in constructing the nomogram. Nomogram discrimination and calibration were evaluated using C-index, internal validation, and receiver operating characteristic (ROC) curves.ResultsA total of 4769 patients were included. Patients were assigned to the training set (n = 3340; 70%) and validation set (n = 1429; 30%). Based on the training set, eight variables were shown to be significant factors for early death and were incorporated in the nomogram: American Joint Committee on Cancer (AJCC) stage, residual lesion size, chemotherapy, serum CA125 level, tumor size, number of lymph nodes examined, surgery of primary site, and age. The concordance indices and ROC curves showed that the nomogram had better predictive ability than the AJCC staging system and good clinical practicability. Internal validation based on validation set showed good consistency between predicted and observed values for early death.ConclusionCompared with predictions made based on AJCC stage or residual lesion size, the nomogram could provide more robust predictions for early death in patients with ovarian cancer.

Development and Assessment of a Clinical Calculator for Estimating the Likelihood of Recurrence and Survival Among Patients With Locally Advanced Rectal Cancer Treated With Chemotherapy, Radiotherapy, and Surgery

Predicting outcomes in patients receiving neoadjuvant therapy for rectal cancer is challenging because of tumor downstaging. Validated clinical calculators that can estimate recurrence-free survival (RFS) and overall survival (OS) among patients with rectal cancer who have received multimodal therapy are needed. To develop and validate clinical calculators providing estimates of rectal cancer recurrence and survival that are better for individualized decision-making than the American Joint Committee on Cancer (AJCC) staging system or the neoadjuvant rectal (NAR) score. This prognostic study developed risk models, graphically represented as nomograms, for patients with incomplete pathological response using Cox proportional hazards and multivariable regression analyses with restricted cubic splines. Because patients with complete pathological response to neoadjuvant therapy had uniformly favorable outcomes, their predictions were obtained separately. The study included 1400 patients with stage II or III rectal cancer who received treatment with chemotherapy, radiotherapy, and surgery at 2 comprehensive cancer centers (Memorial Sloan Kettering [MSK] Cancer Center and Siteman Cancer Center [SCC]) between January 1, 1998, and December 31, 2017. Patients from the MSK cohort received chemoradiation, surgery, and adjuvant chemotherapy from January 1, 1998, to December 31, 2014; these patients were randomly assigned to either a model training group or an internal validation group. Models were externally validated using data from the SCC cohort, who received either chemoradiation, surgery, and adjuvant chemotherapy (chemoradiotherapy group) or short-course radiotherapy, consolidation chemotherapy, and surgery (total neoadjuvant therapy with short-course radiotherapy group) from January 1, 2009, to December 31, 2017. Data were analyzed from March 1, 2020, to January 10, 2021. Chemotherapy, radiotherapy, chemoradiotherapy, and surgery. Recurrence-free survival and OS were the outcome measures, and the discriminatory performance of the clinical calculators was measured with concordance index and calibration plots. The ability of the clinical calculators to predict RFS and OS was compared with that of the AJCC staging system and the NAR score. The models for RFS and OS among patients with incomplete pathological response included postoperative pathological tumor category, number of positive lymph nodes, tumor distance from anal verge, and large- and small-vessel venous and perineural invasion; age was included in the risk model for OS. The final clinical calculators provided RFS and OS estimates derived from Kaplan-Meier curves for patients with complete pathological response and from risk models for patients with incomplete pathological response. Among 1400 total patients with locally advanced rectal cancer, the median age was 57.8 years (range, 18.0-91.9 years), and 863 patients (61.6%) were male, with tumors at a median distance of 6.7 cm (range, 0-15.0 cm) from the anal verge. The MSK cohort comprised 1069 patients; of those, 710 were assigned to the model training group and 359 were assigned to the internal validation group. The SCC cohort comprised 331 patients; of those, 200 were assigned to the chemoradiotherapy group and 131 were assigned to the total neoadjuvant therapy with short-course radiotherapy group. The concordance indices in the MSK validation data set were 0.70 (95% CI, 0.65-0.76) for RFS and 0.73 (95% CI, 0.65-0.80) for OS. In the external SCC data set, the concordance indices in the chemoradiotherapy group were 0.71 (95% CI, 0.62-0.81) for RFS and 0.72 (95% CI, 0.59-0.85) for OS; the concordance indices in the total neoadjuvant therapy with short-course radiotherapy group were 0.62 (95% CI, 0.49-0.75) for RFS and 0.67 (95% CI, 0.46-0.84) for OS. Calibration plots confirmed good agreement between predicted and observed events. These results compared favorably with predictions based on the AJCC staging system (concordance indices for MSK validation: RFS = 0.69 [95% CI, 0.64-0.74]; OS = 0.67 [95% CI, 0.58-0.75]) and the NAR score (concordance indices for MSK validation: RFS = 0.56 [95% CI, 0.50-0.63]; OS = 0.56 [95% CI, 0.46-0.66]). Furthermore, the clinical calculators provided more individualized outcome estimates compared with the categorical schemas (eg, estimated RFS for patients with AJCC stage IIIB disease ranged from 7% to 68%). In this prognostic study, clinical calculators were developed and validated; these calculators provided more individualized estimates of the likelihood of RFS and OS than the AJCC staging system or the NAR score among patients with rectal cancer who received multimodal treatment. The calculators were easy to use and applicable to both short- and long-course radiotherapy regimens, and they may be used to inform surveillance strategies and facilitate future clinical trials and statistical power calculations.

Analysis of the effect of ipsilateral supraclavicular lymph node metastasis on the prognosis of N3 breast cancer

Objective: The 6th edition American Joint Committee on Cancer (AJCC) staging system for breast cancer classifies ipsilateral supraclavicular lymph node metastasis (ISLM) downing stage from M1 to N3, suggesting more patients might receive radical treatment. The aim of this study was to analyze the effect of ISLM on the prognosis of N3 breast cancer and verify the rationality of modified staging. Methods: A total of 321 breast cancer patients with N3 according to the 6th edition AJCC staging system were retrospectively analyzed. Propensity Score Matching (PSM) was used to pair the different subgroups of N3. The primary end point was disease-free survival (DFS), the secondary end point was overall survival (OS). Kaplan-Meier method was used to calculate the DFS and OS. The differences between two groups were analyzed by the Log-rank test. Results: After PSM pairing twice, 78 patients with none-ISLM and 78 patients with ISLM were enrolled in the first group; 51 patients with none-ISLM was compared patients with isolated ISLM in the second group. The results of the two groups showed that patients with none-ISLM have a prolonged DFS (the first group: 58.9 months vs 32.1 months, P=0.101; the second group: 59.0 months vs 44.0 months, P=0.533), while the OS was opposite (the first group: 87.4 months vs 140.4 months, P=0.289; the second group: 87.4 months vs 137.1 months, P=0.289). Conclusions: The prognosis of breast cancer patients with ISLM is similar to that of patients with none-ISLM in stage N3. It is reasonable to include ISLM in N3 in the 6th edition AJCC staging system. Yet, prospective studies with larger sample size are needed to further confirmation.