Association of Lymph Nodes Positive Rate With the Risk of Recurrence in Patients With Stage T1 Papillary Thyroid Cancer.

The incidence of lymph node metastasis in papillary thyroid carcinoma (PTC) is common and a significant risk factor for local recurrence; however, its impact on recurrence patterns among low-risk patients remains uncertain. We aimed to elucidate the effect of metastatic lymph node on recurrence type. The medical records of 1209 patients with stage T1 PTC who underwent unilateral thyroidectomy with ipsilateral central lymph node dissection were retrospectively analyzed. The study first identified risk factors for different types of recurrence and then categorized patients as high or low risk based on their lymph node positive ratio (LNPR). The diagnostic accuracy of LNPR in predicting recurrence was compared using receiver operating characteristic (ROC) curve analysis, while differences in recurrence-free survival were assessed using the Kaplan-Meier method. During follow-up, a total of 502 (41.5%) patients had central lymph node metastasis and 52 (4.3%) patients experienced recurrence. Notably, LNPR was significantly higher in relapsed patients compared to nonrelapsed patients, with mean values of 0.45 and 0.23, respectively (P < .001). The recurrence rate of residual thyroid did not differ significantly across different T stages (P = .679), N stages (P = .415), or LNPR risk groups (P = .175). However, the recurrence rate of lymph nodes showed a significant correlation with LNPR (P < .001). The area under the ROC curves for LNPR risk stratification at 5 and 10 years were approximately 0.691 and 0.634, respectively, both of which outperformed N stage. The findings underscore the significance of LNPR's reliability as a prognostic indicator for local lymph node recurrence in patients diagnosed with T1 stage PTC.

Separating lymph node stations by the surgeon from the gastric cancer specimen improves the quality of nodal status evaluation.

BACKGROUND: In gastric cancer (GC), the pN-stage is an important prognostic factor influencing treatment. Along with the depth of invasion of the tumor, the presence of nodal metastases is one of the most important prognostic factors guiding treatment strategies in gastric cancer. Examining a small number of lymph nodes may lead to understaging of the disease; hence, it is essential for the nodal status to be precisely assessed. In this study, we explored whether dissecting lymph node stations into separate samples by the surgeon from the gastric cancer surgical specimen affects the quality of nodal status evaluation and patient outcome. METHODS: The clinical data of 130 GC patients treated at the Helsinki University Hospital between 2016 and 2019 was reviewed. The performed operations included 59 total and 71 subtotal gastrectomies. The processing of the surgical specimen before the pathological examination was assessed from the operation records and pathology reports. The association of the number of examined lymph nodes with other variables was assessed, and multivariate survival analysis was performed to explore the independent prognostic factors in disease-specific survival. RESULTS: Dissecting lymph node stations into separate specimens before pathological evaluation yielded a significantly greater number of examined lymph nodes compared with a specimen without intervention (median 34.5 vs 21.0, p < 0.001). The pT-stage, the pN-stage, and the extent of lymphadenectomy were identified as independent prognostic factors, whereas dissecting the specimen's lymph node stations did not associate with survival. CONCLUSIONS: Dissecting lymph node stations into separate specimens results in a greater number of examined lymph nodes, which has the potential to lead to a more reliable pN-stage assessment.

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

BACKGROUND: Two 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. METHODS: This 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. RESULTS: The 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). CONCLUSIONS: The 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.

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

BACKGROUND: There is increasing evidence in the literature that alternative N-classification systems offer a simpler and more precise risk stratification than the current N- classification in patients with oral squamous cell carcinoma. The purpose of this study is to compare three broadly proposed models incorporating lymph node ratio, log odds of positive lymph nodes and number of positive lymph nodes regarding disease-free and overall survival. METHODS: This is a retrospective study of patients treated in a single center between 2013 and 2019. Cox proportional hazard models, Kaplan Meier curves, the long rank test and the area under the curve were implemented to compare the risk-stratification ability of the three models. Moreover, a hazard ratio plot was calculated to investigate the association between nodal yield and disease-free survival. RESULTS: 231 patients were included. All three proposed N-models were significantly correlated to the patient's prognosis in the multivariate analysis. Pairwise comparisons between the groups showed that the current pN classification offers the worst stratification and that the model incorporating the number of positive lymph nodes had a better performance for predicting both endpoints. Finally, a decrease in hazard ratio was observed with each additional lymph node removed up to the number of 39 lymph nodes. CONCLUSIONS: The model incorporating the nodal burden offered a better predictive ability. The current N-classification cannot adequately identify patients with different prognosis. A non-linear relationship was found between nodal yield and survival, which could be the disadvantage of the lymph node ratio and log odds models.

Association between multiple coagulation-related factors and lymph node metastasis in patients with gastric cancer: A retrospective cohort study.

Background: Patients with tumors generally present with accompanying activation of the coagulation system, which may be related to tumor stage. To our knowledge, few studies have examined the activation of the coagulation system in reference to lymph node metastasis within gastric cancer. This study aimed to investigate the correlation between multiple coagulation-related factors and lymph node metastasis in patients with gastric cancer after excluding the influence of tumor T stage. Materials and methods: We retrospectively evaluated the relationship between lymph node metastasis and coagulation-related factors in 516 patients with T4a stage gastric cancer. We further analyzed influencing factors for lymph node metastasis and verified the predictive value of maximum amplitude (MA, a parameter of thromboelastography which is widely used to assess the strength of platelet-fibrinogen interaction in forming clots) in reference to lymph node metastasis. Results: Platelet counts (P=0.011), fibrinogen levels (P=0.002) and MA values (P=0.006) were statistically significantly higher in patients with T4a stage gastric cancer presenting with lymph node metastasis than in those without lymph node metastasis. Moreover, tumor N stage was statistically significantly and positively correlated with platelet count (P<0.001), fibrinogen level (P=0.003), MA value (P<0.001), and D-dimer level (P=0.010). The MA value was an independent factor for lymph node metastasis (ß=0.098, 95% CI: 1.020-1.193, P=0.014) and tumor N stage (ß=0.059, 95% CI: 0.015-0.104, P=0.009), and could be used to predict the presence of lymph node metastasis in patients with gastric cancer (sensitivity 0.477, specificity 0.783, P=0.006). The independent influencing factors for MA value mainly included platelet levels, fibrinogen levels, D-dimer and hemoglobin levels; we found no statistically significant correlations with tumor diameter, tumor area, and other evaluated factors. Conclusion: We conclude that MA value is an independent influencing factor for lymph node metastasis and tumor N stage in patients with T4a stage gastric cancer. The MA value has important value in predicting the presence or absence of lymph node metastasis in patients with gastric cancer. Clinical trial registration: http://www.chictr.org.cn, identifier ChiCTR2200064936.

Artificial intelligence-based computer-aided diagnosis system supports diagnosis of lymph node metastasis in esophageal squamous cell carcinoma: A multicenter study.

Background: This study aimed to develop an artificial intelligence-based computer-aided diagnosis system (AI-CAD) emulating the diagnostic logic of radiologists for lymph node metastasis (LNM) in esophageal squamous cell carcinoma (ESCC) patients, which contributed to clinical treatment decision-making. Methods: A total of 689 ESCC patients with PET/CT images were enrolled from three hospitals and divided into a training cohort and two external validation cohorts. 452 CT images from three publicly available datasets were also included for pretraining the model. Anatomic information from CT images was first obtained automatically using a U-Net-based multi-organ segmentation model, and metabolic information from PET images was subsequently extracted using a gradient-based approach. AI-CAD was developed in the training cohort and externally validated in two validation cohorts. Results: The AI-CAD achieved an accuracy of 0.744 for predicting pathological LNM in the external cohort and a good agreement with a human expert in two external validation cohorts (kappa = 0.674 and 0.587, p < 0.001). With the aid of AI-CAD, the human expert's diagnostic performance for LNM was significantly improved (accuracy [95% confidence interval]: 0.712 [0.669-0.758] vs. 0.833 [0.797-0.865], specificity [95% confidence interval]: 0.697 [0.636-0.753] vs. 0.891 [0.851-0.928]; p < 0.001) among patients underwent lymphadenectomy in the external validation cohorts. Conclusions: The AI-CAD could aid in preoperative diagnosis of LNM in ESCC patients and thereby support clinical treatment decision-making.

A prospective study of diagnostic accuracy of multidisciplinary team and radiology reporting of preoperative colorectal cancer local staging.

INTRODUCTION: The aim of this study was to correlate and assess diagnostic accuracy of preoperative staging at multidisciplinary team meeting (MDT) against the original radiology reports and pathological staging in colorectal cancer patients. METHODS: A prospective observational study was conducted at two institutions. Patients with histologically proven colorectal cancer and available preoperative imaging were included. Preoperative tumor and nodal staging (cT and cN) as determined by the MDT and the radiology report (computed tomography [CT] and/or magnetic resonance imaging [MRI]) were recorded. Kappa statistics were used to assess agreement between MDT and the radiology report for cN staging in colon cancer, cT and cN in rectal cancer, and tumor regression grade (TRG) in patients with rectal cancer who received neoadjuvant therapy. Pathological report after surgery served as the reference standard for local staging, and AUROC curves were constructed to compare diagnostic accuracy of the MDT and radiology report. RESULTS: A total of 481 patients were included. Agreement between MDT and radiology report for cN stage was good in colon cancer (k = .756, Confidence Interval (CI) 95% .686-.826). Agreement for cT and cN and in rectal cancer was very good (kw = .825, CI 95% .758-.892) and good (kw = .792, CI 95% .709-.875), respectively. In the rectal cancer group that received neoadjuvant therapy, agreement on TRG was very good (kw = .919, CI 95% .846-.993). AUROC curves using pathological staging indicated no difference in diagnostic accuracy between MDT and radiology reports for either colon or rectal cancer. CONCLUSION: Preoperative colorectal cancer local staging was consistent between specialist MDT review and original radiology reports, with no significant differences in diagnostic accuracy identified.

Concordance between clinical and pathologic assessment of T and N stages of rectal adenocarcinoma patients who underwent surgery without neoadjuvant therapy: A National Cancer Database analysis.

BACKGROUND: Clinical assessment of T and N stages in rectal cancer is important to guide decision-making. The present study aimed to assess the accuracy of the clinical T and N staging of rectal cancer compared to the pathological staging and their overall agreement in a large cohort of patients. METHODS: This retrospective study used data from the National Cancer Database (NCDB) between 2004 and 2017. Patients with non-metastatic rectal adenocarcinoma who did not receive neoadjuvant therapy were reviewed and the clinical T and N stages were compared to their pathologic counterparts. The overall concordance between clinical and pathologic assessments was calculated using Kappa coefficient. RESULTS: The study included 8929 patients (57.3% male) with a mean age of 64 years. Clinical T stage and N stage were identical to pathologic stages in 70.3% and 77.6% of patients, respectively. Sensitivity and specificity of the clinical assessment of N stage was 35.2% and 95.5%, respectively. Concordance between the clinical and pathologic stages was moderate for the T stage (kappa = 0.575) and fair for the N stage (kappa = 0.346). Pathologic T4 stage (OR: 2.12, p < 0.0001), poorly differentiated adenocarcinoma (OR: 1.45, p = 0.026), lymphovascular invasion (OR: 4.5, p < 0.001), and longer time from diagnosis to first treatment (OR = 0.996, p = 0.046) were the independent predictors of N stage discrepancy. CONCLUSIONS: There was a moderate agreement between the clinical and pathologic T stages and a fair agreement between the clinical and pathologic N stages. The clinical assessment of the N stage was highly specific yet had low sensitivity.

Risk Factors and Establishment of Prediction Model for Preoperative Lymph Node Staging Deficiency in Gastric Cancer / 肿瘤防治研究

Objective To analyze the risk factors of preoperative lymph node staging (N-stage) deficiency in gastric cancer and establish a preoperative assessment model to assist in predicting preoperative N-stage. Methods A retrospective method was used to analyze the clinicopathological data of 268 patients with gastric cancer. The patients routinely underwent preoperative thin-section enhanced CT to assess preoperative N-stage. Results The risk factors for preoperative N-stage deficiency were analyzed in combination with postoperative pathological findings. Multifactorial logistic regression analysis was performed to determine influencing factors, and Kaplan-Meier analysis was used to plot the survival curves of preoperative N-stage accurate group and deficiency group. The nomogram plot and ROC curves of the prediction model were drawn using the R package. AUC, 95%CI, sensitivity, and specificity were calculated. Results Age, BMI, poor differentiation, and Lauren's classification as diffuse were independent risk factors for preoperative N-stage deficiency in gastric cancer (P < 0.05). Prognostic survival was significantly worse in the preoperative N stage-inadequate group than that in the accurate group (P=0.041). The AUC area was 0.935, with a sensitivity of 85.9% and specificity of 96.9%. Conclusion Young age, high BMI, poor differentiation, and Lauren's classification as diffuse are independent risk factors for preoperative N-stage deficiency. The established preoperative assessment model based on age, BMI, differentiation degree, and Lauren's classification in this study has relatively high credibility.

Development and validation of models for predicting the overall survival and cancer-specific survival of patients with primary vaginal cancer: A population-based retrospective cohort study.

Background: No models have been developed to predict the survival probability for women with primary vaginal cancer (VC) due to VC's extreme rareness. We aimed to develop and validate models to predict the overall survival (OS) and cancer-specific survival (CSS) of VC patients. Methods: A population-based multicenter retrospective cohort study was carried out using the 2004-2018 Surveillance, Epidemiology, and End Results Program database in the United States. The final multivariate Cox model was identified using the Brier score and Harrell's C concordance statistic (C-statistic). The decision curve, calibration plot, and area under the time-dependent receiver operating characteristic curve (AUC) were used to evaluate model prediction performance. Multiple imputation followed by bootstrap was performed. Bootstrap validation covered the entire statistic procedure from model selection to baseline survival and coefficient calculation. Nomograms predicting OS and CSS were generated. Results: Of the 2,417 eligible patients, 1,692 and 725 were randomly allocated to the training and validation cohorts. The median age (Interquartile range) was 66 (56-78) and 65 (55-76) for the two cohorts, respectively. Our models had larger net benefits in predicting the survival of VC patients than the American Joint Committee on Cancer stage, presenting great discrimination ability and excellent agreement between the expected and observed events. The performance metrics of our models were calculated in three cohorts: the training cohort, complete cases of the validation cohort, and the imputed validation cohort. For the OS model in the three cohorts, the C-statistics were 0.761, 0.752, and 0.743. The slopes of the calibration plots were 1.017, 1.005, and 0.959. The 3- and 5-year AUCs were 0.795 and 0.810, 0.768 and 0.771, and 0.770 and 0.767, respectively. For the CSS model in the three cohorts, the C-statistics were 0.775, 0.758, and 0.755. The slopes were 1.021, 0.939, and 0.977. And the 3- and 5-year AUCs were 0.797 and 0.793, 0.786 and 0.788, and 0.757 and 0.757, respectively. Conclusion: We were the first to develop and validate exemplary survival prediction models for VC patients and generate corresponding nomograms that allow for individualized survival prediction and could assist clinicians in performing risk-adapted follow-up and treatment.

Worst pattern of invasion in oral squamous cell carcinoma is an independent prognostic factor.

Introduction: Biologic aggressiveness of OSCC (Oral Cavity Squamous Cell Carcinoma), has intrigued research in various prognosticating histopathological markers over past few decades. DOI (Depth of Invasion) is one such histopathological factor which affects outcomes and was included in the AJCC 8th edition TNM staging. Pattern of Invasion (POI) has been widely reported as an adverse prognostic factor associated with higher locoregional failure and poor prognosis. However, these factors are not utilized for treatment decision making and for outcome assessment. Materials and methods: This is a retrospective analysis of 320 patients with OSCC who underwent treatment, from October 2018-February 2020. Clinic demographic details were extracted from electronic medical records. Univariate and multivariate analysis was done for the parameters. WPOI (Worst Pattern of Invasion) was correlated with all histopathological prognostic factors. Survival analysis was done using Kaplan Meier for WPOI type's I-V. DFS (Disease free Survival) was evaluated for different grades of WPOI. Results: We analyzed the results comparing, early and advanced T (Tumor) stages, cohesive WPOI I-III, non-cohesive WPOI IV-V. Univariate analysis showed a significant association of T-stage (p = 0.001), N (Nodal) -stage (p = 0.002), DOI (p = 0.008), PNI (Peri-neural invasion) (0.001) and Tumor differentiation Grade (p = 0.001). On multivariate analysis, non-cohesive WPOI (IV & V) showed significant association with grade, PNI, DOI (0.002, 0.033 & 0.033 respectively). Non-cohesive WPOI had significantly higher locoregional failures and short DFS. Conclusion: Presence of invasive WPOI is associated with advanced T stage, poor differentiation, PNI, greater depth of invasion, and higher chances of nodal metastasis. WPOI is associated with poor DFS, treatment intensification in early stage disease with WPOI type IV & V may improve survival.

A Nomogram to Identify the Optimal Candidates for Induction Chemotherapy in Advanced N-Stage Nasopharyngeal Carcinoma.

Purpose: We aimed to select optimal candidates benefiting from the addition of induction chemotherapy (IC) to concurrent chemoradiotherapy (CCRT) in advanced N-stage nasopharyngeal carcinoma (NPC). Patients and Methods: A total of 624 NPC patients with N2-3 stage received CCRT with or without IC were retrospectively reviewed. We constructed a nomogram for predicting overall survival (OS) based on the result of the multivariate analysis in the training cohort (n = 468) and then tested it on the validation cohort (n = 156). Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (tdROC) analysis were applied to evaluate the discriminatory ability of the nomogram and compare it with TNM staging. IC plus CCRT was compared with CCRT in the whole cohort and two risk groups based on the nomogram with balanced baseline characteristics. In addition, acute toxicities were compared between different treatment groups. Results: The nomogram showed good prognostic accuracy with a C-index of 0.716 (95% CI 0.669-0.763) in the validation cohort. The 5-year OS of low and high-risk groups stratified by the nomogram were significantly different. IC+CCRT was significantly associated with superior OS as compared with CCRT (75.4 vs 52.6%, p = 0.009) in the high-risk group. However, no significant difference between IC plus CCRT and CCRT was observed (p = 0.843) in the low-risk group. IC plus CCRT was associated with more grade 1-4 acute toxicities. Conclusion: Our study can help clinicians select NPC patients with advanced N stage who benefit from IC.

Beyond N Staging in Breast Cancer: Importance of MRI and Ultrasound-based Imaging.

The correct N-staging in breast cancer is crucial to tailor treatment and stratify the prognosis. N-staging is based on the number and the localization of suspicious regional nodes on physical examination and/or imaging. Since clinical examination of the axillary cavity is associated with a high false negative rate, imaging modalities play a central role. In the presence of a T1 or T2 tumor and 0-2 suspicious nodes, on imaging at the axillary level I or II, a patient should undergo sentinel lymph node biopsy (SLNB), whereas in the presence of three or more suspicious nodes at the axillary level I or II confirmed by biopsy, they should undergo axillary lymph node dissection (ALND) or neoadjuvant chemotherapy according to a multidisciplinary approach, as well as in the case of internal mammary, supraclavicular, or level III axillary involved lymph nodes. In this scenario, radiological assessment of lymph nodes at the time of diagnosis must be accurate. False positives may preclude a sentinel lymph node in an otherwise eligible woman; in contrast, false negatives may lead to an unnecessary SLNB and the need for a second surgical procedure. In this review, we aim to describe the anatomy of the axilla and breast regional lymph node, and their diagnostic features to discriminate between normal and pathological nodes at Ultrasound (US) and Magnetic Resonance Imaging (MRI). Moreover, the technical aspects, the advantage and limitations of MRI versus US, and the possible future perspectives are also analyzed, through the analysis of the recent literature.

Can Cervical Lymph Node Metastasis Increase the Risk of Distant Metastasis in Papillary Thyroid Carcinoma?

Background: Distant metastasis (DM) is a rare event and has a negative effect on the prognosis for papillary thyroid carcinoma (PTC). The relationship between cervical lymph node metastasis and DM is complicated and unclear. This study aimed to evaluate the impact of N stage subclassification on different distant metastasis sites based on age stratification, especially for patients with papillary thyroid microcarcinoma. Methods: A total of 28,712 patient with PTC cases between 2010 and 2018 were extracted from the Surveillance, Epidemiology, and End Results database. Multivariable logistic regression analysis was utilized to adjust for confounding variables. Risk stratification, including positive lymph node number and lymph node ratio, was established by receiver operating characteristic curves to help predict DM. Results: Lung was the most common metastatic site regardless of N0, N1a disease, or N1b disease. As the N stage increased, the higher the rate of DM identified. After age stratification, only N1b disease significantly increased the risk of lung metastasis (LM; odds ratio, OR = 20.45, P < 0.001) rather than bone metastasis (BM; OR = 3.46, P > 0.05) in younger patients. However, in older patients, N1b disease significantly increased the risk of both LM (OR = 4.10, P < 0.001) and BM (OR = 2.65, P = 0.007). In patients with papillary thyroid microcarcinoma (PTMC), N1a disease did not increase the risk of DM, LM, and BM compared with N0 disease (P > 0.05). Furthermore, combined N stage with risk stratification has well performance in predicting DM (area under the curve, AUC = 0.761). Similar results were shown in PTC patients with LM (AUC = 0.770) and BM (AUC = 0.729). Conclusion: Overall, the incidence of DM significantly increased with the progress of N disease after age stratification. N1a disease did not increase the risk of DM in PTMC patients, regardless of LM or BM. Combined N stage with risk stratification may be beneficial for DM prediction.

How Best to Play the Role of Tumor Deposits in Stage III Colon Cancer?

Background: The purpose of this study is to comprehensively evaluate the prognostic role of tumor deposits (TD) in stage III colon cancer. Methods: 24,600 CC patients with III stage colon cancer were collected from the Surveillance, Epidemiology, and End Result (SEER) database and 618 CC patients from the Second Affiliated Hospital of Harbin Medical University. All patients were divided into development, internal, and external validation cohorts. The combination of positive lymph nodes (PLN) and the status or number of TD was defined as modified pN (mpN) and novel pN (npN). The Cox proportional hazard regression model was used to analyze the relationship between cancer-specific survival (CSS) and mpN or npN. CSS stratified by pN, mpN, and npN was analyzed by the Kaplan-Meier curves. The area under the receiver operating characteristic curve (AUC) was used to demonstrate the predictive abilities of the pN, mpN, and npN stages. The validation cohorts were used to validate the results. Results: The Cox proportional hazard regression model showed that mpN and npN were an independent prognostic factor for CSS. AUC showed that the predictive accuracy of mpN was better than that of the pN stage for 5-year CSS in the development (0.621 vs. 0.609, p < 0.001) and internal validation cohorts (0.618 vs. 0.612, p = 0.016) and the npN was also better than the pN stage for 5-year CSS in the development (0.623 vs. 0.609, p < 0.001) and internal validation cohorts (0.620 vs. 0.612, p = 0.001). However, there was no significant difference between the AUCs of mpN and npN. Moreover, the pN stage for 5-year CSS in the external validation cohort is 0.606 vs. 0.563, p = 0.045. Conclusions: In stage III CC, mpN and npN may be superior to the pN stage in assessing prognosis, suggesting that the TD information should be included in the pN stage.

Identifying distinct risks of treatment failure in nasopharyngeal carcinoma: Study based on the dynamic changes in peripheral blood lymphocytes, monocytes, N classification, and plasma Epstein-Barr virus DNA.

BACKGROUND: To evaluate the prognostic value of the dynamic change in absolute lymphocyte counts (ALCs) and absolute monocyte counts (AMCs) and identify patients with N stage and plasma Epstein-Barr virus (EBV) DNA levels in nasopharyngeal carcinoma (NPC) who are at risk of treatment failure. METHODS: A total of 1124 eligible patients with Stage II-IVb NPC treated with concurrent chemoradiotherapy (CCRT) were enrolled. Percentage changes in the ALC (ΔALC%) and AMC (ΔAMC%) were calculated. RESULTS: Patients with high ΔALC% were correlated with poorer 5-year overall survival (OS), progression-free survival (PFS), and distant metastasis-free survival (DMFS) rates than those with low ΔALC%. Likewise, high ΔAMC% was significantly associated with worse outcome than low ΔAMC% (OS, p = 0.001; PFS, p = 0.001; DMFS, p = 0.034). Multivariate analyses revealed that ΔALC% (p = 0.046), ΔAMC% (p = 0.019), and EBV DNA level (p < 0.001) were independent prognostic factors for OS. With respect to PFS, ΔALC% (p = 0.036), ΔAMC% (p = 0.011), N classification (p = 0.016), and EBV DNA level (p < 0.001) were also independent prognosticators. Based on the aforementioned independent risk factors (ΔALC% ≥ 83.33%, ΔAMC% ≥ 40.00%, Stage N2-3, EBV DNA ≥ 4000 copies/ml), patients were divided into three different risk groups (low-risk group [with <1 risk factor], intermediate risk group [with 1-3 risk factors], and high-risk group [with 4 risk factors]) that correlated with disparate risks of death (p < 0.001), disease progression (p < 0.001), and distant metastasis (p < 0.001). CONCLUSIONS: High ΔALC% and ΔAMC% were correlated with poor prognosis in patients with NPC. Risk stratification based on ΔALC%, ΔAMC%, N classification, and plasma EBV DNA levels could provide potential utility for risk-adapted therapeutic strategies for NPC.

Quantitative Spatial Characterization of Lymph Node Tumor for N Stage Improvement of Nasopharyngeal Carcinoma Patients.

This study aims to investigate the feasibility of improving the prognosis stratification of the N staging system of Nasopharyngeal Carcinoma (NPC) from quantitative spatial characterizations of metastatic lymph node (LN) for NPC in a multi-institutional setting. A total of 194 and 284 NPC patients were included from two local hospitals as the discovery and validation cohort. Spatial relationships between LN and the surrounding organs were quantified by both distance and angle histograms, followed by principal component analysis. Independent prognostic factors were identified and combined with the N stage into a new prognostic index by univariate and multivariate Cox regressions on disease-free survival (DFS). The new three-class risk stratification based on the constructed prognostic index demonstrated superior cross-institutional performance in DFS. The hazard ratios of the high-risk to low-risk group were 9.07 (p < 0.001) and 4.02 (p < 0.001) on training and validation, respectively, compared with 5.19 (p < 0.001) and 1.82 (p = 0.171) of N3 to N1. Our spatial characterizations of lymph node tumor anatomy improved the existing N-stage in NPC prognosis. Our quantitative approach may facilitate the discovery of new anatomical characteristics to improve patient staging in other diseases.

Analysis of lymph node metastasis and prognosis of stage N1 thoracic esophageal squamous cell carcinoma / 中国胸心血管外科临床杂志

@#Objective    To investigate the rule of lymph node metastasis and its relationship with prognosis in stage N1 thoracic esophageal squamous cell carcinoma. Methods    The clinical and follow-up data of 121 stage N1 (1 to 2 lymph node metastases) thoracic esophageal squamous cell carcinoma patients, who underwent radical resection of esophageal carcinoma in our hospital from 2015 to 2017, were retrospectively analyzed. There were 104 (86.0%) males and 17 (14.0%) females with an average age of 64.9±8.3 years. Results    The early metastasis rates of the left upper paratracheal, right upper paratracheal, lower thoracic paraesophageal, paracardial, lesser curvature and greater curvature lymph nodes were 22.6%, 28.0%, 21.2%, 41.7%, 25.0% and 25.0%, respectively. The three-year survival rates in the group with and without left upper paratracheal lymph node metastasis were 8.3% and 34.9%, respectively (P=0.000). The three-year survival rates of the subcarinal lymph node metastasis group and the non-metastasis group were 10.5% and 36.3%, respectively (P=0.032). Multivariate Cox regression analysis showed that, left upper paratracheal lymph node metastasis (P=0.000) and subcarinal lymph node metastasis (P=0.010) were independent prognostic factors for early stage lymph node metastasis of esophageal squamous cell carcinoma. The three-year survival rates of patients with simple abdominal lymph node metastasis and those with simple thoracic lymph node metastasis were 51.1% and 25.0%, respectively (P=0.016). Conclusion    The lymph nodes of N1 stage thoracic esophageal squamous cell carcinoma are more likely to metastasize to left upper paratracheal lymph nodes, right upper paratracheal lymph nodes, lower thoracic paraesophageal lymph nodes, paracardial lymph nodes, lesser curvature of stomach and greater curvature of stomach lymph nodes. Lymph node metastases of left upper paratracheal and subcarinal are independent factors for the prognosis of patients with stage N1 thoracic esophageal squamous cell carcinoma. The prognosis of patients with simple abdominal lymph node metastasis is better than that of patients with simple thoracic lymph node metastasis.

Effect of Lymph Node Metastasis on Prognosis of Small Cell Lung Cancer with M1a Disease: A Study Based on SEER database / 肿瘤防治研究

Objective To investigate the impact of lymph node metastasis on the survival of SCLC patients with M1a disease. Methods We retrospectively analyzed the medical records of 7027 SCLC patients with M1a disease from 2004 to 2015 in SEER database. The Kaplan-Meier method and log-rank test were used to estimate the OS in all N stage subgroups. Cox proportional hazard model was used to assess whether N stage was an independent risk factor for prognosis. Results The median OS of all patients was 7 months. Among all M1a patients, the patients without lymph node involvement (N0) had the best OS, followed by N1 stage patients; N2 and N3 stage patients had the worst OS (P < 0.001). Similarly, this trend was observed when M1a disease was subdivided into contralateral pulmonary nodules, malignant pleural effusion and malignant pericardial effusion. Multivariate analysis showed that lymph node metastasis was an independent prognostic factor for SCLC patients with M1a disease, and this result was also noticed in all subgroups of M1a disease. Conclusion Lymph node metastasis may affect the survival of SCLC patients with M1a disease, adding prognostic information. And it is recommended to further improve the N descriptor in the next version of TNM staging system.

Developing and Validating Novel Nomograms for Predicting the Overall Survival and Cancer-Specific Survival of Patients With Primary Vulvar Squamous Cell Cancer.

Background: To develop and validate novel nomograms for better predicting the overall survival (OS) and cancer-specific survival (CSS) of patients with vulvar squamous cell cancer (VSCC). Methods: A retrospective analysis using a population-based database between 2004 and 2016 was carried. A 10-fold cross-validation with 200 repetitions was used to choose the best fit multivariate Cox model based on the net-benefit of decision curve analysis. Net-benefit, Harrell's C concordance statistic (C-statistic) of calibration plot, and area under the receiver operating characteristic curve (AUC) were used to evaluate the model prediction accuracy. Nomograms of the OS and CSS were generated based on the best fit model. Results: Of the 6,792 patients with VSCC, 5,094 (75%) and 1,698 (25%) were allocated to the training and validation cohort, respectively. All the variables were balanced between the training and validation cohorts. Age, insurance, tumor size, pathological grade, radiotherapy, chemotherapy, invasion depth, lymphadenectomy, sentinel lymph nodes biopsy, surgery, N stage, and M stage were in the best fit model for generating nomograms. The decision curve analysis, calibration plot, and receiver operating characteristic (ROC) curve show the better prediction performance of the model compared to previous studies. The C-statistics of our model for OS prediction are 0.80, 0.83, and 0.81 in the training, validation, and overall cohorts, respectively, while for CSS prediction are 0.83, 0.85, and 0.84. The AUCs for 3- and 5-year OS are the same and are 0.81, 0.83, and 0.81 in the training, validation, and overall cohorts, respectively. The AUCs for 3- and 5-year CSS are 0.78 and 0.80, 0.79 and 0.80, and 0.79 and 0.80 in those three cohorts. Conclusions: Our model shows the best prediction accuracy of the OS and CSS for patients with vulvar cancer (VC), which is of significant clinical practice value.