Node Ratio Research Articles

Predictive value of positive lymph node ratio in patients with locally advanced gastric remnant cancer.

e16119 Background: Traditional lymph node stage (N stage) has limitations in advanced gastric remnant cancer (GRC)patients; therefore, establishing a new predictive stage is necessary.To explore the predictive value of positive lymph node ratio (LNR) according to clinicopathological characteristics and prognosis of locally advanced GRC. Methods: Seventy-four patients who underwent radical gastrectomy and lymphadenectomy for locally advanced GRC were retrospectively reviewed. The relationship between LNR and clinicopathological characteristics was analyzed. The survival analysis was performed using Kaplan–Meier survival curves and Cox regression model. Results: Number of metastatic LNs, tumor diameter, depth of tumor invasion, Borrmann type, serum tumor biomarkers, and tumor–node–metastasis (TNM) stage were correlated with LNR stage and N stage. Univariate analysis revealed that the factors affecting survival included tumor diameter, anemia, serum tumor biomarkers, vascular or neural invasion, combined resection, LNR stage, N stage, and TNM stage (all P < 0.05). The median survival time for those with LNR0, LNR1, LNR2 and LNR3 stage were 61, 31, 23 and 17 mo, respectively, and the differences were significant ( P = 0.000). Anemia, tumor biomarkers and LNR stage were independent prognostic factors for survival in multivariable analysis (all P < 0.05). Conclusions: The new LNR stage is uniquely based on number of metastatic LNs, with significant prognostic value for locally advanced GRC, and could better differentiate overall survival, compared with N stage.

Bi-institutional spline curve analysis of lymph node mapping in gallbladder cancer operated over 12 years: Impact of location and number of lymph nodal stations.

e16274 Background: Current staging system for gallbladder cancers (GBC) takes into account only the number of metastatic lymph nodes without addressing their location. The current study evaluates the prognostic impact of lymph node mapping (number and location) in node positive GBCs. Methods: Prospectively maintained operative database of GBC patients with positive lymph nodes were analysed from two tertiary cancer care centers in a retrospective cohort study design between April 2010 till March 2022. Nodal burden was assessed including both, the number of metastatic nodes and the lymph node station. Impact of lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) was evaluated using regression and spline curve analysis. Results: Amongst 1312 operated GBC patients, 272 patients with node positive disease were included. The median nodal yield was 8. The median LNR and LODDS was 0.222 and -0.48 respectively. The 5-year DFS and OS for patients with only cystic node metastases was 52.3% and 50.8% respectively (median: not reached), as compared to 24.6% and 35.2% for involvement of regional nodal stations beyond cystic nodes. Higher LODDS was associated with inferior DFS and OS when compared to the LNR. On multivariate analysis, multi-station involvement was the only factor associated with inferior DFS (p < 0.001) and OS (p = 0.007). Conclusions: Station wise pathological assessment of lymph nodal involvement could potentially provide superior prognostic information, in addition to number of involved nodes. Involvement of cystic lymph node alone has relatively superior prognosis as compared to multi-station involvement.

Major pathologic response and long-term clinical benefit in hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer after neoadjuvant chemotherapy.

e12608 Background: Rates of pathological complete response (pCR) are much lower in patients with hormone receptor–positive (HR+) /HER2-negative (HER2-) breast cancer than in those with HER2-positive and triple-negative breast cancer (TNBC). The majority of HR+/HER2- breast cancer patients can also achieve long-term survival despite not attaining pCR, indicating limited prognostic value of pCR in this population. This study aimed to identify novel pathologic end points for predicting long-term outcomes in HR+/HER2- breast cancer after neoadjuvant chemotherapy. Methods: We analyzed HR+/HER2- breast cancer patients with stage II-III tumors who underwent curative surgery after neoadjuvant chemotherapy from three hospitals. Major pathologic response (MPR), defined as the presence of Miller-Payne grades 3-5 and positive lymph node ratio of ≤10%, was used as a pathological evaluation indicator. MPR evaluates the extent of residual invasive carcinoma in both the breast and axillary lymph nodes following neoadjuvant therapy. We assessed the association between MPR and event-free survival (EFS) and performed Multivariable Cox regression to identify independent factors associated with EFS. Results: From January 2010 to December 2020, 386 patients were included in the final analysis. The median age was 46 years. 244 patients (63.2%) were premenopausal, with 271 (70.2%) patients diagnosed with stage III disease. The predominant neoadjuvant chemotherapy regimen was anthracycline combined taxane (79.3%). 28 patients (7.3%) achieved pCR and 118 patients (30.6%) achieved MPR. The median duration of follow-up was 54.4 months. Multivariate analysis showed that PR expression, Clinical stage, Miller–Payne grades and Positive lymph node ratio were independent prognostic factors for EFS (all P values <0.05). The prognostic effect of MPR remained in multivariable models (hazard ratio (HR), 0.45; 95% confidence interval (CI), 0.26–0.76; P = 0.008), with 5-year EFS of 87% vs. 68% in the non-MPR group. In non-pCR patients, those who achieved MPR exhibited a similar EFS compared with pCR patients (HR, 2.25; 95% CI, 0.51–9.84; P = 0.28). Conclusions: MPR was a novel pathologic end point for prognostic evaluation in HR+/HER2- breast cancer after neoadjuvant chemotherapy. Compared to pCR, MPR may hold greater applicability in the prognosis evaluation.

Development and validation of nomograms for predicting the prognosis of early and late recurrence of advanced gastric cancer after radical surgery based on post-recurrence survival.

In this study, we aimed to explore the risk factors influencing post-recurrence survival (PRS) of early recurrence (ER) and late recurrence (LR) in stage advanced gastric cancer (AGC) patients after radical surgery, respectively, and to develop predictive models in turn. Medical records of 192 AGC patients who recurred after radical gastrectomy were retrospectively reviewed. They were randomly divided into the training and validation set at a ratio of 2:1. Nomograms were built based on risk factors influencing PRS of ER and LR explored by Cox regression analyses, respectively. Concordance index (C-index) values and calibration curves were used to evaluate predictive power of nomograms. Body mass index < 18.5 kg/m2, prealbumin level < 70.1 mg/L, positive lymph nodes ratio ≥ 0.486 and palliative treatment after recurrence were independent risk factors for the prognosis of ER. In contrast, prealbumin level < 170.1 mg/L, CEA ≥ 18.32 μg/L, tumor diameter ≥ 5.5 cm and palliative treatment after recurrence were independent risk factors for the prognosis of LR. The C-index values were 0.801 and 0.772 for ER and LR in the training set, respectively. The calibration curves of validation set showed a C-index value of 0.744 and 0.676 for ER and LR, respectively. Nomograms which were constructed to predict the prognosis of ER and LR of AGC after surgery showed great predictive power and could provide reference for clinicians' treatment strategies to some extent.

Revolutionizing T3-4N0-2M0 gastric cancer staging with an innovative pathologic N classification system

BackgroundThe current pathologic N (pN) classification exhibits limitations in the prognostic stratification of patients with pT3-4N0-2M0 gastric cancer (GC). Therefore, this study aimed to develop and validate a new lymph nodal staging method based on the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). MethodsData from 7883 patients with pT3-4N0-2M0 GC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and Zhejiang Cancer Provincial Hospital. Optimal cutoff values for ELNs and LNR were determined using X-tile software. Kaplan-Meier methods, Log-rank tests, and Cox regression analyses were employed in this study. Patients were categorized into 3 new pN stages: new pN0 (pN0 with ELNs of >16), new pN1 (pN0 with ELNs of ≤16 or pN1-2 with LNR of ≤0.15), and new pN2 (pN1-2 with LNR of >0.15). The prognostic predictive power of both current and new pN staging was evaluated using the Akaike information criterion (AIC), Bayesian information criterion, concordance index (C-index), and receiver operating characteristic curve. ResultsThe new pN classification exhibited excellent performance in Kaplan-Meier survival analysis. After adjusting for confounding factors, the new pN staging emerged as an independent prognostic indicator in patients with GC. In the SEER cohort, the new pN staging demonstrated enhanced prognostic prediction accuracy over the American Joint Committee on Cancer pN staging (AIC: 75578.85 vs 75755.06; C-index: 0.642 vs 0.630; P < .001). Similar findings were validated in the Chinese cohort. ConclusionThis study developed and validated an improved pN classification for patients with pT3-4N0-2M0 GC. Surgeons should consider ELNs and LNR when assessing postoperative prognosis in patients with GC.

Survival analysis in pT1-3 and paracolic lymph-node invasion colorectal cancer: the prognostic role of positive paracolic lymph-node ratio for adjuvant chemotherapy.

Several studies have observed that some stage III colorectal cancer (CRC) patients cannot benefit from standard adjuvant chemotherapy. However, there is no unified screening standard to date. Consecutive patients with pathologically confirmed colon adenocarcinoma treated in 3 centers between January 2016 and December 2018 were included. Patients were divided into four groups according to different stages and positive paracolic lymph-node ratio (P-LNR) [Cohort 1: pT1-3N0M0, Cohort 2: pT1-3N + (P-LNR ≤ 0.15)M0, Cohort 3: pT4N0M0, Cohort 4: stage III patients except for pT1-3N + (P-LNR ≤ 0.15)M0], and further overall survival was compared by Kaplan-Meier method. The univariate and multivariate analyses were employed for cox proportional hazards model. We retrospectively reviewed 5581 consecutive CRC patients with, and 2861 eligible patients were enrolled for further analysis. The optimal cut-off value of P-LNR in our study was 0.15. There was no significant difference in OS (91.36 vs. 93.74%) and DFS (87.65 vs. 90.96%) between stage III patients with pT1-3N + (P-LNR ≤ 0.15)M0 and those with pT1-3N0M0. Further analysis demonstrated that CRC patients with pT1-3N + (P-LNR ≤ 0.15)M0 were less likely to benefit from 8 cycles of CAPOX or FOLFOX chemotherapy and suffered fewer adverse events from declining chemotherapy. Comparing with 0-4 cycles versus 8 cycles, the overall survival rates were 91.35 versus 90.19% (P = 0.79), and with a DFS of 87.50 versus 88.24% (P = 0.49), the duration of adjuvant chemotherapy was not an independent risk factor for patients with pT1-3N + (P-LNR ≤ 0.15)M0 (HR: 0.70, 95% CI 0.90-1.30, P = 0.42). The concept of P-LNR we proposed might have a high clinical application value and accurately enable clinicians to screen out specific CRC patients who decline or prefer limited chemotherapy. The clinical trial registration number: ChiCTR2300076883.

Significance of metastatic lymph nodes ratio in overall survival for patients with resected nonsmall cell lung cancer: a retrospective cohort study.

The tumor, node and metastasis stage is widely applied to classify lung cancer and is the foundation of clinical decisions. However, increasing studies have pointed out that this staging system is not precise enough for the N status. In this study, we aim to build a convenient survival prediction model that incorporates the current items of lymph node status. We performed a retrospective cohort study and collected the data from resectable nonsmall cell lung cancer (NSCLC) (IA-IIIB) patients from the Surveillance, Epidemiology, and End Results database (2006-2015). The x-tile program was applied to calculate the optimal threshold of metastatic lymph node ratio (MLNR). Then, independent prognostic factors were determined by multivariable Cox regression analysis and enrolled to build a nomogram model. The calibration curve as well as the Concordance Index (C-index) were selected to evaluate the nomogram. Finally, patients were grouped based on their specified risk points and divided into three risk levels. The prognostic value of MLNR and examined lymph node numbers (ELNs) were presented in subgroups. 40853 NSCLC patients after surgery were finally enrolled and analyzed. Age, metastatic lymph node ratio, histology type, adjuvant treatment and American Joint Committee on Cancer 8th T stage were deemed as independent prognostic parameters after multivariable Cox regression analysis. A nomogram was built using those variables, and its efficiency in predicting patients' survival was better than the conventional American Joint Committee on Cancer stage system after evaluation. Our new model has a significantly higher concordance Index (C-index) (training set, 0.683 v 0.641, respectively; P < 0.01; testing set, 0.676 v 0.638, respectively; P < 0.05). Similarly, the calibration curve shows the nomogram was in better accordance with the actual observations in both cohorts. Then, after risk stratification, we found that MLNR is more reliable than ELNs in predicting overall survival. We developed a nomogram model for NSCLC patients after surgery. This novel and useful tool outperforms the widely used tumor, node and metastasis staging system and could benefit clinicians in treatment options and cancer control.

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

Colorectal neuroendocrine neoplasms (NENs) are a rare malignancy that primarily arises from the diffuse distribution of neuroendocrine cells in the colon and rectum. Previous studies have pointed out that the status of lymph node may be used to predict the prognosis. To investigate the predictive values of lymph node ratio (LNR), positive lymph node (PLN), and log odds of PLNs (LODDS) staging systems on the prognosis of colorectal NENs treated surgically, and compare their predictive values. This cohort study included 895 patients with colorectal NENs treated surgically from the Surveillance, Epidemiology, and End Results database. The endpoint was mortality of patients with colorectal NENs treated surgically. X-tile software was utilized to identify most suitable thresholds for categorizing the LNR, PLN, and LODDS. Participants were selected in a random manner to form training and testing sets. The prognosis of surgically treating colorectal NENs was examined using multivariate cox analysis to assess the associations of LNR, PLN, and LODDS with the prognosis of colorectal NENs. C-index was used for assessing the predictive effectiveness. We conducted a subgroup analysis to explore the different lymph node staging systems' predictive values. After adjusting all confounding factors, PLN, LNR and LODDS staging systems were linked with mortality in patients with colorectal NENs treated surgically (P < 0.05). We found that LODDS staging had a higher prognostic value for patients with colorectal NENs treated surgically than PLN and LNR staging systems. Similar results were obtained in the different G staging subgroup analyses. Furthermore, the area under the receiver operating characteristic curve values for LODDS staging system remained consistently higher than those of PLN or LNR, even at the 1-, 2-, 3-, 4-, 5- and 6-year follow-up periods. LNR, PLN, and LODDS were found to significantly predict the prognosis of patients with colorectal NENs treated surgically.

Synergy of nodal factors in predicting recurrence after treatment of N1b papillary thyroid carcinoma.

Nodal factors are important predictors of prognosis for papillary thyroid carcinoma (PTC), but their synergy effect is not well understood. We aimed to explore their synergy effect in predicting recurrence of clinical N1b PTC. Patients who underwent surgery for cN1b PTC from 2013 to 2017 were enrolled. The association between nodal factors and recurrence was assessed using Cox proportional hazards regression models. Interaction and stratified analyses were conducted according to significant nodal factors. Of 1067 cN1b PTC patients included, all nodal factors (bilateral metastasis, largest dimension>3cm, micro and gross extranodal extension (mENE, gENE), No. of metastatic lymph nodes (MLN), lymph node yield (LNY) and ratio (LNR)) were significantly associated with all site and nodal recurrence in the univariate analysis (all P<0.05). Multivariate analyses revealed largest dimension>3cm, gENE and LNR>0.21 were associated with elevated both all site (HR [95%CI], 2.58 [1.67-4.00], 1.87[1.26-3.01], 1.68[1.11-2.42], all P<0.01) and nodal recurrences (HR[95%CI], 2.63[1.67-4.13], 1.90[1.15-3.12], 1.76[1.17-2.66], all P<0.01). LNR and gENE had interactive effect (all site recurrence: P for interaction = 0.009; nodal recurrence: P for interaction = 0.02). LNR was significantly associated with recurrence in patients without gENE (HR[95% CI], all site recurrence: 2.41[1.50-3.87]; nodal recurrence: 2.51[1.52-4.14], all P< 0.001), while when gENE appeared, LNR was no longer associated with recurrence (HR [95% CI], all site recurrence: 0.81[0.43-1.54], P=0.53; nodal recurrence: 0.85[0.43-1.67], P=0.64). Nodal factors have synergy effect in predicting recurrence in cN1b PTC patients. Increasing lymph nodes harvest may only decrease recurrence in patients without gENE, while not in gENE patients.

A machine learning predictive model for recurrence of resected distal cholangiocarcinoma: Development and validation of predictive model using artificial intelligence

IntroductionDistal Cholangiocarcinoma (dCCA) represents a challenge in hepatobiliary oncology, that requires nuanced post-resection prognostic modeling. Conventional staging criteria may oversimplify dCCA complexities, prompting the exploration of novel prognostic factors and methodologies, including machine learning algorithms. This study aims to develop a machine learning predictive model for recurrence after resected dCCA. Material and methodsThis retrospective multicentric observational study included patients with dCCA from 13 international centers who underwent curative pancreaticoduodenectomy (PD).A LASSO-regularized Cox regression model was used to feature selection, examine the path of the coefficient and create a model to predict recurrence. Internal and external validation and model performance were assessed using the C-index score. Additionally, a web application was developed to enhance the clinical use of the algorithm. ResultsAmong 654 patients, LNR (Lymph Node Ratio) 15, neural invasion, N stage, surgical radicality, and differentiation grade emerged as significant predictors of disease-free survival (DFS). The model showed the best discrimination capacity with a C-index value of 0.8 (CI 95 %, 0.77%–0.86 %) and highlighted LNR15 as the most influential factor. Internal and external validations showed the model's robustness and discriminative ability with an Area Under the Curve of 92.4 % (95 % CI, 88.2%–94.4 %) and 91.5 % (95 % CI, 88.4%–93.5 %), respectively. The predictive model is available at https://imim.shinyapps.io/LassoCholangioca/. ConclusionsThis study pioneers the integration of machine learning into prognostic modeling for dCCA, yielding a robust predictive model for DFS following PD. The tool can provide information to both patients and healthcare providers, enhancing tailored treatments and follow-up.

A Prognostic Model Based on the Log Odds Ratio of Positive Lymph Nodes Predicts Prognosis of Patients with Rectal Cancer

ObjectiveThis study aimed to compare the prognostic value of rectal cancer by comparing different lymph node staging systems, and a nomogram was constructed based on superior lymph node staging.MethodsOverall, 8700 patients with rectal cancer was obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The area under the curve (AUC), the C index, and the Akaike informativeness criteria (AIC) were used to examine the predict ability of various lymph node staging methods. Prognostic indicators were assessed using univariate and multivariate COX regression, and further correlation nomograms were created after the data were randomly split into training and validation cohorts. To evaluate the effectiveness of the model, the C index, calibration curves, decision curves (DCA), and receiver operating characteristic curve (ROC) were used. We ran Kaplan-Meier survival analyses to look for variations in risk classification.ResultsWhile compared to the N-stage positive lymph node ratio (LNR), the log odds ratio of positive lymph nodes (LODDS) had the highest predictive effectiveness. Multifactorial COX regression analyses were used to create nomograms for overall survival (OS) and cancer-specific survival (CSS). The C indices of OS and CSS for this model were considerably higher than those for TNM staging in the training cohort. The created nomograms demonstrated good efficacy based on ROC, rectification, and decision curves. Kaplan-Meier survival analysis revealed notable variations in patient survival across various patient strata.ConclusionsCompared to AJCC staging, the LODDS-based nomograms have a more accurate predictive effectiveness in predicting OS and CSS in patients with rectal cancer.

Abstract PS01-01: Feasibility and oncological safety of targeted axillary dissection or sentinel lymph node biopsy in patients with clinically node-positive disease after neoadjuvant chemotherapy in the prospective MF-1803 NEOSENTITURK-study

Abstract PS01-01: Feasibility and oncological safety of targeted axillary dissection or sentinel lymph node biopsy in patients with clinically node-positive disease after neoadjuvant chemotherapy in the prospective MF-1803 NEOSENTITURK-study

Analysis of chemoresistance characteristics and prognostic relevance of postoperative gemcitabine adjuvant chemotherapy in pancreatic cancer.

To investigate the relationship between chemoresistance in pancreatic cancer patients receiving postoperative gemcitabine adjuvant therapy and specific clinical/pathological characteristics, as well as its impact on patient prognosis. From June 2018 to June 2021, clinical and pathological data of 148 pancreatic cancer patients were collected, and 101 patients were followed up for tumor recurrence/metastasis and survival status. The correlation between chemoresistance and specific clinical/pathological characteristics or patient prognosis was retrospectively analyzed. Of the 148 patients, 78 were in the chemoresistance group and 70 in the non-chemoresistance group. Univariate analysis showed that the development of chemoresistance may be related to patient age, combined diabetes, preoperative CA19-9 level, tumor size, AJCC stage, vascular invasion, and positive lymph node ratio. Furthermore, subsequent multivariate analysis incorporating these variables indicated that tumor size may be a key factor influencing chemoresistance (p < 0.001, OR = 1.584). Log-rank test showed patients in the chemoresistance group had worse overall survival (OS) (HR = 2.102, p = 0.018) and progression free survival (PFS) (HR = 3.208, p = 0.002) than patients in the non-chemoresistance group; and patients with smaller size tumors (diameter ≤3 cm) had significantly better OS (HR = 2.923, p < 0.001) and PFS (HR = 2.930, p = 0.003) than those with larger size tumors (diameter >3 cm). Patients with pancreatic cancer receiving postoperative gemcitabine adjuvant therapy are more likely to develop chemoresistance when their tumor sizes are larger (diameter >3 cm). Development of chemoresistance exacerbates the prognosis of patients with pancreatic cancer, and larger tumor size is also a risk factor for poor prognosis in these patients.

Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study

ObjectiveThe purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC).MethodsClinicopathologic data of 286 patients with RGC undergoing operation (radical resection and palliative resection) from a multi-institution database were enrolled and analyzed retrospectively. These individuals were split into training (80%) and test cohort (20%) by using random allocation. Nine commonly used ML methods were employed to construct survival prediction models. Algorithm performance was estimated by analyzing accuracy, precision, recall, F1-score, area under the receiver operating characteristic curve (AUC), confusion matrices, five-fold cross-validation, decision curve analysis (DCA), and calibration curve. The best model was selected through appropriate verification and validation and was suitably explained by the SHapley Additive exPlanations (SHAP) approach.ResultsCompared with the traditional methods, the RGC survival prediction models employing ML exhibited good performance. Except for the decision tree model, all other models performed well, with a mean ROC AUC above 0.7. The DCA findings suggest that the developed models have the potential to enhance clinical decision-making processes, thereby improving patient outcomes. The calibration curve reveals that all models except the decision tree model displayed commendable predictive performance. Through CatBoost-based modeling and SHAP analysis, the five-year survival probability is significantly influenced by several factors: the lymph node ratio (LNR), T stage, tumor size, resection margins, perineural invasion, and distant metastasis.ConclusionsThis study established predictive models for survival probability at five years in RGC patients based on ML algorithms which showed high accuracy and applicative value.

Twenty-five Years Overall Survival Prognostic Value of the Lymph Node Ratio in De Novo Metastatic Breast Cancer.

The lymph node ratio (LNR) indicates the number of involved lymph nodes divided by the number of lymph nodes found during axillary exploration. This study investigated the prognostic value of the LNR in de novo metastatic breast cancer (dnMBC). We hypothesized that LNR might predict long-term survival even in cases where the disease has already disseminated beyond the regional stage. Patients with dnMBC were selected from the Surveillance, Epidemiology, and End Results (SEER) 9-registries database 1988-2012. Positive lymph nodes (npos) were categorized as pN0 (npos=0), pN1 (npos=1 to 3), pN2 (npos=4 to 9), and pN3 (npos≥10). The LNR was categorized as Lnr0 (LNR=0), Lnr1 (LNR=0.01 to 0.20), Lnr2 (LNR=0.21 to 0.65), and Lnr3 (LNR≥0.65). The prognostic values were compared using Gini's mean difference Δ of the restricted mean overall survival time (RMST) according to npos versus LNR groups. A total of 12,085 patients with dnMBC had LNR data. At 25 years follow-up, the npos RMSTs were 10.4, 5.1, 5.8, and 5.0 years, for pN0 to pN3, respectively. The npos Gini's Δ was 2.8 years (standard error ±0.2). The LNR RMSTs were 10.4, 9.9, 7.6, and 4.0 years for Lnr0 to Lnr3, respectively. Δ for LNR was 3.6 (±0.2) years. Among node positive cases, the LNR low-risk group had an RMST of 9.9 years, approaching node-negative cases, while the high-risk group had an RMST of 4.0 years. LNR identified different prognostic groups, suggesting a possible role of lymph node involvement as a marker of lymphangiogenesis or lymphatic changes in the immune microenvironment, which warrants further investigation in dnMBC.

Development and validation of a preoperative radiomics-based nomogram to identify patients who can benefit from splenic hilar lymphadenectomy: a pooled analysis of three prospective trials.

The authors aimed to use preoperative computed tomography images to develop a radiomic nomogram to select patients who would benefit from spleen-preserving splenic hilar (No.10) lymphadenectomy (SPSHL). A pooled analysis of three distinct prospective studies was performed. The splenic hilar lymph node (SHLN) ratio (sLNR) was established as the quotient of the number of metastatic SHLN to the total number of SHLN. Radiomic features reflecting the phenotypes of the primary tumor (RS1) and SHLN region (RS2) were extracted and used as predictive factors for sLNR. This study included 733 patients: 301 in the D2 group and 432 in the D2+No.10 group. The optimal sLNR cutoff value was set at 0.4, and the D2+No.10 group was divided into three groups: sLNR=0, sLNR ≤0.4, and sLNR >0.4. Patients in the D2+No. 10 group were randomly divided into the training ( n =302) and validation ( n =130) cohorts. The AUCs value of the nomogram, including RS1 and RS2, were 0.952 in the training cohort and 0.888 in the validation cohort. The entire cohort was divided into three groups based on the nomogram scores: low, moderate, and high SHLN metastasis burden groups (LMB, MMB, and HMB, respectively). A similar 5-year OS rate was found between the D2 and D2+No. 10 groups in the LMB and HMB groups. In the MMB group, the 5-year OS of the D2+No. 10 group (73.4%) was significantly higher than that of the D2 group (37.6%) ( P <0.001). The nomogram showed good predictive ability for distinguishing patients with various SHLN metastasis burdens. It can accurately identify patients who would benefit from SPSHL.

Impact of pCR after neoadjuvant chemotherapy and radical D2 dissection in locally advanced gastric cancers: Analysis of 1001 cases

BackgroundAdvances in perioperative chemotherapy have improved outcomes in patients with gastric cancers (GC). This strategy leads to tumour downstaging and may result in a pathologic complete response (pCR). The study aimed to evaluate the predictors of pCR and determine the impact of pCR on long-term survival. MethodsAt the Department of Gastrointestinal and HPB Oncology at the Tata Memorial Centre, Mumbai, 1001 consecutive patients with locally advanced GCs undergoing radical resection following neoadjuvant chemotherapy from January 2005 to June 2022 were included. ResultsAt a median follow-up of 61 months, the median OS was 53 months with a 5-year OS of 46.8 %. Ninety-five patients (9.49 %) realized pCR. Non-signet and well-differentiated histology were associated with pCR. pCR was significantly associated with improved OS, 5-year OS 79.2 % vs 43.2 % (HR 0.30, p < 0.001). On multivariable analysis, the realization of pCR and completion of adjuvant chemotherapy had superior OS. Whereas, signet-ring histology, linitis-like tumours, and high lymph node ratio had adverse outcomes. ConclusionTumour grade and signet-ring histology predict achievement of pCR in locally advanced GCs after neoadjuvant chemotherapy. Patients with pCR have significantly improved survival. Future neoadjuvant strategies should focus on enhancing pCR rates to improve overall outcomes.

Surface Albedo Dominates Radiation Efficiency of Alpine Grasslands Along an Elevation Profile of Qilian Mountains

AbstractQuantifying the elevation dependency of radiation partitioning in high‐altitude mountains is crucial for projecting regional energy balance while remains highly uncertain. We compared the surface radiation partitioning parameters across a meadow (3,200 m), shrub (3,400 m), and forb (3,600 m) along a southern slope of the Qilian Mountains. At a daily scale, the downward shortwave radiation (Rs) fluctuated minimally among the grassland types probably induced by similar site orientations. The greatest downward and upward longwave radiation (Ld and Lu) happened at the lowest meadow while the largest net shortwave (Sn) and longwave (Ln) radiation occurred at the deciduous shrub. The net all‐wave radiation (Rn) of the meadow and shrub was similar and exceeded that of the forb by ∼20%. The differences in Rn between the sites were jointly explained by those of upward shortwave radiation (Ru) and Lu, more than by Rs and Ld, suggesting the importance of surface attributes. The monthly normalized effective terrestrial radiation (λ, the ratio of Ln to Rs) varied insignificantly among the sites and averaged 0.25 ± 0.05, which was comparable to the global mean value (0.26). The smallest surface albedo (α, the ratio of Ru to Rs) and largest radiation efficiency (η, the ratio of Rn to Rs) were 0.13 ± 0.02 and 0.64 ± 0.09, respectively, both at the shrub. Grassland type dominated the spatial variations of monthly α and η. These findings highlighted the importance of grassland types to explain the spatiotemporal variations of radiation partitioning parameters in high‐altitude alpine grasslands.

Radioactive iodine therapy improves overall survival outcome in oncocytic carcinoma of the thyroidby reducing death risks from noncancer causes: A competing risk analysis of 4641 patients.

Oncocytic carcinoma of the thyroid (OCA) is an independent type of thyroid cancer. Radioactive iodine (RAI) therapy was frequently administered to OCA patients, but its contribution to improving survival is indefinite. 4641 OCA patients from 2000 to 2018 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Cox proportional hazard regression and competing risk analysis were applied. Tumor size, SEER stage, primary surgery, and neck dissection were prognostic factors for cancer-specific survival. The results of competing risk analysis demonstrated that age over 55 years dramatically increased non-OCA death risks. Treatments that improve non-OCA survival (including total thyroidectomy, RAI therapy, and systemic therapy) should be recommended in OCA patients older than 55 years of age. Neck lymphadenectomy should not be recommended for OCA, since the metastatic lymph node ratio was low (about 3%). RAI therapy can improve survival in OCA by reducing noncancer death risks.

Prognostic Significance of Lymph Node Ratio in Predicting the Outcome of Oral Squamous Cell Carcinoma - A Retrospective Study.

The lymph node status is a very important prognostic factor in head-and-neck cancer. The presence of metastatic lymph nodes will reduce the overall survival by 50%. Lymph node ratio (LNR) is defined as the ratio of the number of positive lymph nodes to the total number of lymph nodes dissected. The aim of the study was to investigate the prognostic value of LNR in oral squamous cell carcinoma (OSCC). Medical records of pathologically confirmed OSCC patients who reported with loco-regional recurrence from January 2017 to January 2022 were analysed. LNR and disease-free survival (DFS) were calculated for each patient. The endpoint of the study was disease-free survival. Spearman's correlation was used to establish a correlation between DFS and LNR. A total of 33 patients were included in the study. DFS was calculated for all the patients. LNR was calculated in patients with pathological N+ neck. There was a negative significant moderate correlation between LNR and DFS (Spearman's rho = -0.593, P < 0.001). A higher LNR value of more than 0.01 was associated with a shorter DFS period. T4 tumour stage had significantly higher LNR. A positive significant moderate correlation was found between LNR and tumour stage (Spearman's rho = 0.703, P = 0.01). As the T stage increased, the LNR ratio also increased. In the present study, tumour subsite tongue was associated with significantly higher LNR (P = 0.001). LNR can be considered an independent prognostic parameter for DFS in OSCC patients with cervical lymph node metastasis.