AJCC TNM Staging Research Articles

A Recurrence Predictive Model for Node-negative Esophageal Squamous Cell Carcinoma After Upfront Esophagectomy

The prognosis for pathologically node-negative (pN0) esophageal squamous cell carcinoma (ESCC) with surgery alone remains poor. We aimed to develop a model for a more precise prediction of recurrence, which will allow personalized management for pN0 ESCC after upfront complete resection. Clinical and pathological records of patients with completely resected pT1-3N0M0 ESCC were retrospectively analyzed between January 2014 and December 2019. A nomogram for the prediction of recurrence was established based on the Cox regression analysis and evaluated by C-index, AUC, and calibration curves. The model was further validated using bootstrap resampling and k-fold cross-validation and compared with the 8th edition of the AJCC TNM staging system using Td-ROC, NRI, IDI, and DCA. Two-hundred-and seventy cases were included in this study. The median follow-up was 45 months. Distant and/or loco-regional recurrences were noted in 89 (33.0%) patients. The predictive model revealed pT-category, differentiation, perineural invasion, examined lymph nodes (ELN), and prognostic nutritional index (PNI) as independent risk factors for recurrence, with a c-index of 0.725 in the bootstrapping cohort. Td-ROC, NRI, and IDI showed a better predictive ability than the AJCC 8th TNM staging system. Based on this model, patients in the low-risk group had a significantly lower recurrence incidence than those in the high-risk group (p < .001). The predictive model developed in this study may facilitate the precise prediction of recurrences for pN0 ESCC after upfront surgery. Stratifying management of those patients might bring significantly better survival benefits.

The prognostic value of machine learning techniques versus cox regression model for head and neck cancer.

Accurate prognostic prediction for head and neck cancer (HNC) is important for the improvement of clinical management. We aimed to compare the prognostic value of various machine learning techniques (MLTs) and statistical Cox regression model for different types of HNC. Clinical data of HNC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database from 1974 to 2016. The prediction performance of five ML models, including random forest (RF), gradient boosting decision tree (GBDT), support vector machine (SVM), neural network (NN) and deep learning (DL), were compared with the statistical Cox regression model by estimating the concordance index (C-index), integrated Brier score (IBS), time-dependent receiver operating characteristic (ROC) curve and the area under the curve (AUC). Our results showed that the RF model outperformed all other models in prognostic prediction for all tumor sites of HNC, particularly for major salivary gland cancer (MSGC, C-index: 88.730±0.8700, IBS: 7.680±0.4800), oral cavity cancer (OCC, C-index: 84.250±0.6700, IBS: 11.480±0.3300) and oropharyngeal cancer (OPC, C-index: 82.510±0.5400, IBS: 10.120±0.1400). Meanwhile, we analyzed the importance of each clinical variable in the RF model, in which age and tumor size presented the strongest positive prognostic effects. Additionally, similar results can be observed in the internal (6th edition of the AJCC TNM staging system cohort) and external validations (the TCGA HNC cohort). The RF model is a promising prognostic prediction tool for HNC patients, regardless of the anatomic subsites.

O088 Systematic review and meta-analysis of survival outcomes in T2a and T2b gallbladder cancers

Abstract Background The 8th edition of AJCC TNM staging of Gallbladder cancer subdivided T2 stage into T2a and T2b based on tumour location. This meta-analysis aimed to investigate the long-term outcomes in T2a and T2b gallbladder cancers. Methods Literature search of Medline, Web of science, Embase and Cochrane databases was performed. Study characteristics, survival and recurrence data were extracted for meta-analysis of effect estimates and of individual patient data. Results Fifteen retrospective studies (2531 patients, T2a = 1332, T2b = 199) were included in the meta-analysis. Overall survival (OS) was significantly worse in patients with T2b compared to T2a tumours (HR 2.18, 95% CI 1.67–2.86, p &amp;lt; 0.0001). Meta-analysis of individual patient data (n = 629) showed similar results (HR 1.92, 95% CI 1.43–2.58, p &amp;lt; 0.00001). Patients with T2b tumours had higher risk of recurrence compared to T2a (OR 3.19, 95% CI 1.40–7.28, p = 0.006) and were more likely to receive adjuvant chemotherapy (OR 1.76, 95% CI 1.12–2.84, p 0.014). Liver resection improved OS in T2b tumours (HR 2.99, CI 1.73–5.16, p &amp;lt; 0.0001). Conclusion T2b gallbladder tumours have worse overall survival and increase risk of recurrence compared to T2a. Liver resection appears to improve OS in patients with T2b tumours. However, high quality multicentre data is required to confirm these results. Take-home message T2b gallbladder tumours have worse overall survival and increase risk of recurrence compared to T2a. Liver resection appears to improve OS in patients with T2b tumours. However, high quality multicentre data is required to confirm these results.

Inclusion of Perineural Invasion with AJCC-TNM Staging: Outcomes from a South Asian Cohort of Curatively Treated Gastric Cancer Patients.

The incidence of perineural invasion (PNI) in patients with gastric cancer (GC) is high, and patients with PNI positive disease have a poor prognosis compared to PNI-negative disease. The present study aims to study the incidence and evaluate the impact of PNI on the survival outcome of a cohort of South Asian GC patients. All consecutive patients undergoing curative gastrectomy were included in the study. The incidence of PNI and correlation with different clinico-pathological features and overall survival was performed. A total of 59.54% had PNI-positive disease and the median OS of PNI + ve patients was 29.3months, while it was not reached in PNI-ve patients. The PNI positivity was a significant prognostic factor for overall survival both on univariate and multivariate analysis. On TNM-PNI staging, those with TNM stage I/II patients with PNI + ve disease had similar OS to all stage III patients (p = 0.835) and were worse than that of PNI-ve patients (p < 0.05). The incidence of PNI in gastric cancer is high. The inclusion of PNI with AJCC-TNM staging may better stratify prognostic staging in curatively treated gastric cancer patients.

Additional Postoperative Radiotherapy Prolonged the Survival of Patients with I-IIA Small Cell Lung Cancer: Analysis of the SEER Database.

Purpose Complete resection and adjuvant chemotherapy are recommended as the standard strategy for patients with stage I-IIA small cell lung cancer (SCLC). However, the role of additional postoperative radiotherapy (PORT) in treatment remains controversial. Methods Patients with stage I-IIA SCLC undergoing surgery and adjuvant chemotherapy were extracted from the Surveillance, Epidemiology, and End Results database. Stage I-IIA, defined as T1-2N0M0, was recalculated according to the 8th AJCC TNM staging system. Propensity score matching (PSM) was conducted to identify the therapeutic impact of PORT. Univariate Cox hazards regression and least absolute shrinkage and selection operator regression were utilized for primary screening of prognostic variables for I-IIA SCLC disease. A nomogram to predict overall survival (OS) was constructed based on the multivariate Cox proportional hazards model, evaluated with area under the curve, calibration curve, and decision curve analysis, and validated with bootstrap resampling. Results Our results demonstrated that compared with no PORT, PORT significantly prolonged the median OS (8.58 vs. 5.17 years, HR = 0.61 [0.39–0.96], P = 0.032) and median cancer-specific survival (11.33 vs. 8.08, HR = 0.47 [0.27–0.82], P = 0.0086) after PSM. The 5-year OS rate was 61.56% vs. 46.60%. Five variables including age at diagnosis, gender, T stage, surgical type, and PORT were elucidated to impact on prognosis and included in a nomogram to predict 3-/5-/10-year OS probability. The area under the curve values were 0.72, 0.71, and 0.81, respectively. The nomogram also exhibited satisfactory accuracy and clinical usefulness. Conclusion PORT was verified to improve the OS of patients with T1-2N0M0 SCLC after surgery and chemotherapy. A prognostic nomogram was developed and validated for OS prediction for these patients.

Real-world implications of nonbiological factors with staging, clinical management, and prognostic prediction in pancreatic ductal adenocarcinoma.

The American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system focuses on traditional biological factors (BFs). The present study incorporates nonbiological factors (NBFs) into the AJCC-TNM staging system in terms of the advanced clinical management and prognostic-prediction accuracy of pancreatic ductal adenocarcinoma (PDAC). Eight thousand three hundred and thirty eligible patients with PDAC were obtained from Surveillance, Epidemiology, and End Results database between January 1, 2011, and December 31, 2015. Multivariate Cox proportional hazards regression analysis and Kaplan-Meier curves were used to testify the feasibility of cancer-specific survival (CSS) prediction based on TNM-NBF stages. The large population-based study demonstrated that NBFs (insurance status, marital status, county-level median household income, and unemployment) were significant prognostic indicators (p< 0.005), and multivariate Cox regression analysis demonstrated that the NBF1 stage carried a 29.4% increased risk of cancer-specific mortality than NBF0 stage (p< 0.001). The concordance index of TNM-NBF stage was 0.755 (95% confidence interval: 0.740-0.769). The novel NBF stage was independently associated with CSS of PDAC. In addition, combining TNM with the NBF stage could provide better clinical management and prognostic-prediction accuracy.

Systematic review and meta-analysis of survival outcomes in T2a and T2b gallbladder cancers.

The 8th edition of AJCC TNM staging of Gallbladder cancer subdivided T2 stage into T2a and T2b based on tumour location. This meta-analysis aimed to investigate the long-term outcomes in T2a and T2b gallbladder cancers. Literature search of Medline, Web of science, Embase and Cochrane databases was performed. Study characteristics, survival and recurrence data were extracted for meta-analysis of effect estimates and of individual patient data. Fifteen retrospective studies (2531 patients, T2a=1332, T2b=199) were included in the meta-analysis. Overall survival (OS) was significantly worse in patients with T2b compared to T2a tumours (HR 2.18, 95% CI 1.67-2.86, p<0.0001). Meta-analysis of individual patient data (n=629) showed similar results (HR 1.92, 95% CI 1.43-2.58, p<0.00001). Patients with T2b tumours had higher risk of recurrence compared to T2a (OR 3.19, 95% CI 1.40-7.28, p=0.006) and were more likely to receive adjuvant chemotherapy (OR 1.76, 95% CI 1.12-2.84, p = 0.014). Liver resection improved OS in T2b tumours (HR 2.99, CI 1.73-5.16, p<0.0001). T2b gallbladder tumours have worse overall survival and increase risk of recurrence compared to T2a. Liver resection appears to improve OS in patients with T2b tumours. However, high quality multicenter data is required to confirm these results.

Micrometastasis in lymph nodes of colorectal cancer.

Colorectal cancer (CRC) is one of the most common cancers worldwide. Postoperative adjuvant chemotherapy is recommended for node‐positive stage III patients. A systematic meta‐analysis reported that the presence of micrometastases in regional lymph nodes (LNs) was associated with poor survival in patients with node‐negative CRC. Because most data employed in the meta‐analysis were based on retrospective studies, we conducted a prospective clinical trial and concluded that stage II is a transitional zone between stage I and stage III, where CRC tumors continuously increase the micrometastasis volume in LNs and proportionally raise the risk for tumor recurrence. The one‐step nucleic acid amplification (OSNA) assay is a simple and rapid technique to detect CK19 mRNA using the reverse‐transcription loop‐mediated isothermal amplification (RT‐LAMP) method. Using the OSNA assay, we and colleagues reported that the upstaging rates of pStages I, IIA, IIB, and IIC were 2.0%, 17.7%, 12.5%, and 25%, respectively, in 124 node‐negative patients. Survival analysis indicated that OSNA positive stage II CRC patients had a shorter 3‐y disease‐free survival rate than OSNA negative stage II CRC patients. In 2017, AJCC TNM staging (the 8th version) revised the definition of LN metastasis in colon cancer and it is stated that micrometastasis should be considered as a standard LN metastasis. To our surprise, this revision was based on a meta‐analysis to which our previous study on micrometastasis largely contributed. The remaining questions to be addressed are how to find micrometastases efficiently and whether postadjuvant chemotherapy is effective to prevent disease recurrence and to contribute to longer survival.

Predicting Disease-Specific Survival for Patients With Primary Cholangiocarcinoma Undergoing Curative Resection by Using a Decision Tree Model.

BackgroundThe aim of this study was to derive and validate a decision tree model to predict disease-specific survival after curative resection for primary cholangiocarcinoma (CCA).MethodTwenty-one clinical characteristics were collected from 482 patients after curative resection for primary CCA. A total of 289 patients were randomly allocated into a training cohort and 193 were randomly allocated into a validation cohort. We built three decision tree models based on 5, 12, and 21 variables, respectively. Area under curve (AUC), sensitivity, and specificity were used for comparison of the 0.5-, 1-, and 3-year decision tree models and regression models. AUC and decision curve analysis (DCA) were used to determine the predictive performances of the 0.5-, 1-, and 3-year decision tree models and AJCC TNM stage models.ResultsAccording to the fitting degree and the computational cost, the decision tree model derived from 12 variables displayed superior predictive efficacy to the other two models, with an accuracy of 0.938 in the training cohort and 0.751 in the validation cohort. Maximum tumor size, resection margin, lymph node status, histological differentiation, TB level, ALBI, AKP, AAPR, ALT, γ-GT, CA19-9, and Child-Pugh grade were involved in the model. The performances of 0.5-, 1-, and 3-year decision tree models were better than those of conventional models and AJCC TNM stage models.ConclusionWe developed a decision tree model to predict outcomes for CCA undergoing curative resection. The present decision tree model outperformed other clinical models, facilitating individual decision-making of adjuvant therapy after curative resection.

Comparison of treatment strategies and survival of early-onset gastric cancer: a population-based study

Treatments for early-onset gastric cancer (EOGC) patients are rarely included in clinical trials, resulting in an unclear impact on survival. This study aimed to investigate the treatment patterns of EOGC patients and their impact on survival. Based on the Surveillance, Epidemiology, and End Results database, we conducted a retrospective analysis of 1639 EOGC patients (< 50 years) diagnosed between 2010 and 2018. Patients with larger tumours, distant metastasis, and AJCC TNM stage in IV were prone to receive nonsurgical treatment. Patients treated with surgery alone had a better prognosis than those receiving SROC or SCRT or nonsurgical treatment. However, analyses stratified by histological type, tumour size and TNM stage showed that patients did not benefit more from SROC and SCRT than from surgery alone. Similar results were observed in the stratified Cox regression risk analysis. Patients who received nonsurgical treatment had the highest risk of overall death [hazard ratio (HR) = 2.443, 95% confidence interval (CI) 1.865–3.200, P < 0.001]. This study indicated that additional radiotherapy, chemotherapy or chemoradiotherapy did not provide a coordinated survival benefit to EOGC patients.

Breast Cancer Patients With Positive Apical or Infraclavicular/Ipsilateral Supraclavicular Lymph Nodes Should Be Excluded in the Application of the Lymph Node Ratio System.

Aim: Increasing studies have demonstrated lymph node ratio (LNR) to be an accurate prognostic indicator in breast cancer and an alternative to pN staging; however, the AJCC-TNM staging system classified apical or infraclavicular/ipsilateral supraclavicular lymph node-positive (APN(+)) patients with a worse prognosis as the pN3 stage. Until now, different reports on LNR in breast cancer have ignored this possibility. Consequently, it is necessary to discuss the role of APN(+) patients in the LNR system to obtain a precise LNR that predicts the prognosis accurately. Materials and Methods: We collected data on 10,120 breast cancer patients, including 3,936 lymph node-positive patients (3,283 APN(−) and 653 APN(+) patients), who visited our hospital from 2007 to 2012. Then we applied X-tile analysis to calculate cut-off values and conduct survival analysis and multivariate analysis to evaluate patients’ prognosis. Results: We confirmed that some APN(+) patients were mis-subgrouped according to previously reported LNR, indicating that APN(+) patients should be excluded in the application of LNR to predict prognosis. Then we applied X-tile analysis to calculate two cut-off values (0.15 and 0.34) for LNR-APN(−) patients and conducted survival analysis and found that LNR-APN(−) staging was superior to pN staging in predicting the prognosis of APN(−) breast cancer patients. Conclusion: From this study, we conclude that excluding APN(+) patients is the most necessary condition for effective implementation of the LNR system. LNR-APN(−) staging could be a more comprehensive approach in predicting prognosis and guiding clinicians to provide accurate and appropriate treatment.

Development and Validation of a Prediction Model for Predicting the Prognosis of Postoperative Patients with Hepatocellular Carcinoma.

PurposeThe aims of this study were to identify the prognosis-related risk factors for HCC patients after surgery and to develop a predictive model by analysing the medical records of 152 HCC patients in our hospital.Patients and MethodsUnivariate Cox regression analysis was applied to identify potential risk factors for HCC patients after surgery and to determine independent prognosis-related risk factors by multivariate analysis. Subsequently, a nomogram model was developed based on all independent factors and was validated by a validation set. Calibration and receiver operating characteristic curves were employed to evaluate the accuracy of the model. Finally, decision curve analyses were used to assess its clinical utility.ResultsThe univariate Cox regression analysis indicated that the patient’s age, sex, grade, different AJCC TNM stages, vascular invasion, lymphatic infiltration, and tumour size were potential prognostic-related risk factors for HCC patients (p < 0.2), and the findings of multivariate analysis revealed that grade, different AJCC TNM stages, vascular invasion, and lymphatic infiltration were independent prognostic-related risk factors for HCC patients (p < 0.05). Subsequently, we constructed a prognosis-related prediction model based on all independent prognostic predictors and validated it with internal and external validation sets. The validation results indicated that the prediction model showed good accuracy (AUC = 0.81, 0.728) and consistency. More importantly, decision curve analysis illustrated that the nomogram model is a practical tool for predicting prognosis.ConclusionThis study found that grade, different AJCC TNM stages, vascular invasion, and lymphatic infiltration were independent prognosis-related predictors for HCC patients after surgery, and a nomogram model built on these predictors exhibited great accuracy and clinical usefulness.

A novel hematological classifier predicting chemotherapy benefit and recurrence hazard for locally advanced gastric cancer A multicenter IPTW analysis

BackgroundEffective classifiers for the prediction of individual adjuvant chemotherapy (AC) benefits are scarce. PurposeThis study aimed to construct a useful classifier to predict the AC benefit and recurrence hazard based on preoperative hematological indices through a multicenter database. Methods and resultsMultivariate analysis revealing GCRF (comprehensive deep learning classifier) as an independent prognostic factor associated with overall survival (OS) and disease-free survival (DFS). Locally advanced gastric cancer (LAGC) patients are categorized into the high-risk group (HRG) and low-risk group (LRG). In HRG, OS and DFS of the AC group are significantly higher than those of the non-AC group (all p˂0.05), whereas in LRG, OS and DFS of the AC group are comparable to those of the non-AC group (all p > 0.05). Furthermore, combined GCRF with 8th AJCC TNM staging system, only 650 (51.1%) patients can benefit most from AC among 1273 patients with pStage II-III. From the perspective of recurrence pattern, the recurrence rate of HRG is significantly higher than that of LRG in any recurrence type, including local recurrence, peritoneal recurrence, and distant recurrence (all p˂0.05). Furthermore, the mean time to peritoneal recurrence and lung metastasis in HRG is earlier than that in the LRG (p = 0.028 and 0.011, respectively). ConclusionIn summary, our novel classifier based on deep learning preoperative hematological indices can predict not only the AC benefit of LAGC patients, but also the recurrence hazard after surgery. This classifier is expected to be an effective supplement to the 8th AJCC TNM staging system for the prediction of AC benefits and is helpful for clinical decision in AC individual administration. Further large-scale western studies are warranted.

Indication to post-operative radiotherapy for oral cavity squamous cell carcinoma: what's new in the depth of infiltration (DOI) era?

The last edition of the American Joint Committee on Cancer (AJCC eighth) has introduced the depth of infiltration (DOI) as a new prognostic parameter in oral cavity squamous cell carcinomas (OCSCCs). The aim of this study is to analyze the impact of stage migration on the indication to post-operative radiotherapy (PORT). OCSCCs treated at two institutions between 2014 and 2019 were retrieved. As per the AJCC eighth, only pT3 primarily OCSCCs were considered; availability of the pathologic specimen was a further inclusion criterion. Risk factors considered for PORT were: pT3-pT4, nodal involvement, positive/close surgical margins, perineural and lymph vascular invasion. 149 patients staged as pT3 AJCC eighth were included. A four-fold increase in the number of patients staged as pT3 from the seventh to the eighth AJCC was found. Stage migration to pT3 was equally due to the downstaging from former pT4 (38%) and upstaging of former pT1-pT2 (35%). Considering the former pT1-pT2 53 patients, 13 (25%) had no risk factors for PORT other than DOI. Among 25 cases with former pT1-pT2 and negative lymph nodes, no additional risk factors were found in 11 (44%). 90% of patients had at least one risk factor besides DOI and would have received PORT also according to the AJCC seventh; notably, of former pT1-pT2N0, half of them have been upstaged to pT3 in the current TNM classification. The role of PORT in this cohort of patients has not been clarified yet. Other-than-DOI risk factors leading to PORT indication are highly prevalent in OCSSC patients classified as pT3 per the latest AJCC TNM staging system and should therefore be considered for a comprehensive oncological assessment.

Superior pancreatic lymphadenectomy with portal vein priority via posterior common hepatic artery approach in laparoscopic radical gastrectomy.

BACKGROUNDD2 lymph node dissection for advanced gastric cancer is advocated, and station 8p lymph node should be considered in selected patients, which is, however, technically difficult.AIMTo introduce a new and easy-to-perform procedure for dissection of the lymph nodes superior to the pancreas.METHODSA series of patients who underwent laparoscopic gastrectomy for gastric cancer were retrospectively included with utilization of a new procedure for superior pancreatic lymphadenectomy (LND) with portal vein priority via the posterior common hepatic artery approach (SPLD-PPPH) based on a newly defined portal triangle. The surgical outcome of the patients, as well as the efficacy and safety of SPLD-PPPH are reported.RESULTSA total of 51 patients were included with most of them being male (n = 34, 66.7%). According to the 8th edition of AJCC TNM staging, there were four (7.8%) patients in stage I, 13 (25.5%) in stage II, 33 (64.7%) in stage III and one (2.0%) in stage IV. The average duration for LND was about 1 h (67.7 ± 6.9 min). After surgery, four patients developed morbidities, but all were treated successfully with no perioperative mortality. Among the 51 patients included, the percentage of patients who had lymph node metastasis at station 8p was 9.8%. Of note, with a total of 14 lymph nodes harvested at station 8p, the incidence of nodal metastasis was 14.3%.CONCLUSIONAbout one in 10 patients with advanced gastric cancer had nodal metastasis at station 8p. The new approach of SPLD-PPPH is safe and effective for D2+ LND during laparoscopic radical gastrectomy.

A predictive model with a risk-classification system for cancer-specific survival in patients with primary osteosarcoma of long bone

BackgroundOsteosarcoma (OS), most commonly occurring in long bone, is a group of malignant tumors with high incidence in adolescents. No individualized model has been developed to predict the prognosis of primary long bone osteosarcoma (PLBOS) and the current AJCC TNM staging system lacks accuracy in prognosis prediction. We aimed to develop a nomogram based on the clinicopathological factors affecting the prognosis of PLBOS patients to help clinicians predict the cancer-specific survival (CSS) of PLBOS patients. MethodWe studied 1199 PLBOS patients from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 and randomly divided the dataset into training and validation cohorts at a proportion of 7:3. Independent prognostic factors determined by stepwise multivariate Cox analysis were included in the nomogram and risk-stratification system. C-index, calibration curve, and decision curve analysis (DCA) were used to verify the performance of the nomogram. ResultsAge, Histological type, Surgery of primary site, Tumor size, Local extension, Regional lymph node (LN) invasion, and Distant metastasis were identified as independent prognostic factors. C-indexes, calibration curves and DCAs of the nomogram indicating that the nomogram had good discrimination and validity. The risk-stratification system based on the nomogram showed significant differences (P < 0.05) in CSS among different risk groups. ConclusionWe established a nomogram with risk-stratification system to predict CSS in PLBOS patients and demonstrated that the nomogram had good performance. This model can help clinicians evaluate prognoses, identify high-risk individuals, and give individualized treatment recommendation of PLBOS patients.

Nomogram for the prediction of lymph node metastasis and survival outcomes in rectal neuroendocrine tumour patients undergoing resection.

The current study analysed rectal neuroendocrine tumour (RNET) patients undergoing resection to identify predictive factors and construct nomograms for lymph node metastasis, cancer-specific survival (CSS) and overall survival (OS). RNET patients registered in the Surveillance, Epidemiology, and End Results (SEER) database were included in this study. Multivariable logistic regression analysis was used to investigate the relationships between clinicopathological factors and lymph node metastasis. A multivariate competing risk model was applied to investigate factors independently associated with CSS. Through the Cox regression model, a multivariable analysis of OS was performed. Nomograms were established based on independent predictive factors. Calibration plots, receiver operating characteristic (ROC) curves and Brier scores were used to evaluate the predictive accuracy of the nomograms. In this study, 1,253 RNET patients were included for further analysis. Tumour size ≥12 mm (P<0.001), T3/T4 stage (P<0.001) and M1 stage (P=0.001) were independently associated with lymph node metastasis. The performance of the nomogram was acceptable for predicting lymph node metastasis, with an area under the ROC curve (AUC) of 0.937 [95% confidence interval (CI): 0.874-1.000]. Calibration curves and the Hosmer-Lemeshow test revealed desirable model calibration (P=0.99996). The multivariate competing risk model analysis showed that grade II (P=0.017), tumour size ≥12 mm (P=0.007), AJCC TNM stage II (P=0.002), stage III (P<0.001) and stage IV (P<0.001) were significantly associated with worse CSS. In the competing risk nomogram model, the time-dependent AUC revealed good discriminatory ability of the model (time from 1 to 107 months, AUC >0.900), and the Brier score showed good accuracy of the nomogram, which was greater than that of the AJCC TNM stage. Multivariate Cox analysis showed that age >60 years (P=0.002), median income ≥$65,000 (P=0.013), AJCC TNM stage III (P=0.038) and AJCC TNM stage IV (P<0.001) were independently associated with worse OS. In the nomogram for the prediction of OS, the C-statistic was 0.703 (95% CI: 0.615-0.792), which was significantly better than that of the AJCC TNM stage (0.703 vs. 0.607, P=0.009). A calibration plot for the probability of survival demonstrated good calibration. The present study is the first to establish nomograms with great discrimination and accuracy for the prediction of lymph node metastases, CSS and OS in RNET patients, which can be used to guide treatment decision-making and surveillance.

Predicting survival in colorectal carcinoma after curative resection: a new prognostic nomogram.

Several prognostic nomograms designed to predict survival after curative resection for colorectal cancer (CRC) have been proposed. Recently, routine pathological assessment has evolved with subtle changes to the AJCC staging system, and routine screening for mismatch repair deficiency (MMRd). Therefore we sought to develop and validate a new prognostic nomogram. All cause survival data from 4517 consecutive patients with primary CRC were used as independent training and validation cohorts to develop a final model including only: age, sex, tumour stage, nodal status, number of lymph nodes resected, apical node status, distant metastases, thin-walled vascular invasion, and MMR status. Patients were stratified into four risk groups to assess model discrimination and calibration. To assess discrimination, the area-under-the-curve (AUC) of a receiver-operator-curve (ROC), concordance-index (C-index), and D-index were calculated. The model was compared to the Memorial Sloan Kettering Cancer Center (MSKCC) CRC nomogram and the AJCC TNM staging. Based on the 5-year ROC analysis, the AUC for our model was 0.81 (0.79 and 0.74 for MSKCC and AJCC, respectively). Moreover, our model demonstrated a concordance index of 0.77 (95% CI 0.70-0.82) compared to 0.75 (95% CI 0.68-0.81) for MSKCC and 0.73 (95% CI 0.65-0.79) for AJCC. In conclusion, our new prognostic nomogram incorporates a larger number of clinically relevant prognostic markers, including MMR status, and therefore demonstrates improved predictive capability. As these factors are routinely assessed, it is hoped that this model will inform prognostication and difficult management decisions, such as patient selection for adjuvant therapy.

Clinicopathological features and prognosis of papillary thyroid cancer patients with type 2 diabetes mellitus.

The clinicopathological characteristics of patients with papillary thyroid carcinoma (PTC) combined with type 2 diabetes mellitus (T2DM) and patients with PTC alone were explored and compared in order to provide a more reasonable treatment plan for the clinical diagnosis and treatment of these patients. A total of 1,771 patients from January 2017 to December 2019 who underwent PTC surgery for the first time in the west branch of the Fourth Hospital of Hebei Medical University were analyzed retrospectively. Among them, 111 patients had PTC with T2DM (D-T group) and 1,660 patients had PTC alone (PTC group). The differences in general data and clinical characteristics between the D-T group and the PTC group were analyzed. There were statistically significant differences in age, gender, and body mass index (BMI) between the D-T group and PTC group (P<0.05). Multifocality and extra-glandular invasion in the D-T group were significantly higher than the PTC group (P<0.05). In women, the D-T group was older, had a higher BMI, and was more likely to have extra-glandular invasion (P<0.05) than the PTC group. The prognosis of the D-T group was worse than that of the PTC group as determined by 3 well-developed prognostic staging systems, 8th AJCC TNM staging, MAGIS SCORE, AMES staging, and the results were statistically significant (P=0.001, P<0.001, P=0.021). Our study showed that the overall prognosis of PTC patients with T2DM was worse than that of patients with PTC alone. At the same time, especially in patients younger than 55 years of age, multifocal carcinoma and extra-glandular invasion are likely to occur. In addition, female patients with T2DM are more likely to have extra-glandular invasion than male patients. Therefore, for such patients, preoperative evaluation should be fully conducted.

MiR-21/Sonic Hedgehog (SHH)/PI3K/AKT Pathway is Associated with NSCLC of Primary EGFR-TKI Resistance

Background: Non-small cell lung cancer (NSCLC), caused by abnormal gene drive, may have primary drug resistance after treatment with tyrosine kinase inhibitors (EGFR-TKIs). Therefore, we explore whether the primary drug-resistant NSCLC treated with EGFR-TKI is related to the miR-21/Sonic Hedgehog (SHH)/PI3K/AKT pathway. Methods: The patients from our hospital who meet the AJCC TNM staging (7th edition) stage IIIB and stage IV NSCLC were selected in this case study. Thereafter, the treatment response of EGFR-TKIs was evaluated according to the solid tumor efficacy evaluation standard (version 1.1). The patients were divided into the EGFR-TKIs primary drug resistance group (EGFR-TKIs-Primary-R) and the EGFR-TKIs sensitive group (EGFR-TKIs-Primary-S). Apoptosis level and degree of fibrosis in patients’ tumor tissues were detected by the TUNEL assay and Masson staining, respectively. The levels of miR-21 and GLI1 were measured by qRT-PCR technique. The contents of E-cadherin and Snail were detected by IF method, and the degree of PI3K/AKT phosphorylation was measured using IHC technique. Results: Compared with the EGFR-TKIs-Primary-S group, the EGFR-TKIs-Primary-R group showed lower levels of apoptosis and tumor tissue fibrosis. The levels of miR-21, GLI1, Snail, p-PI3K and p-AKT increased, while the level of E-cadherin decreased. However, the levels of total protein PI3K and AKT remained the same. Conclusion: NSCLC of primary EGFR-TKI resistance was found to be related to miR-21/SHH, the process of epithelial to mesenchymal transition (EMT), and PI3K/AKT phosphorylation. The present study provides a reference for future research in drug resistance, and paves the way to discover new therapeutic gene targets to alleviate lung cancer drug resistance.