The prognostic significance of the treatment response of regional lymph nodes and the refinement of the current TNM staging system in locally advanced rectal cancer after neoadjuvant chemoradiotherapy

Lymph node regression after neoadjuvant chemoradiotherapy in rectal cancer

AIMS

Lymph node metastases (LNM) are one of the most important prognostic indicators in solid tumours and a major component of cancer staging. Neoadjuvant therapy might influence nodal status by induction of regression. Our aim is to determine the prevalence and role of regression of LNM on outcomes in patients with rectal cancer.

METHODS AND RESULTS

Four independent study populations of rectal cancer patients treated with similar regimens of chemoradiotherapy were pooled together to obtain a total cohort of 469 patients. Post-treatment nodal status (ypN) and signs of tumour regression (Reg) were incorporated to form three-tiered (ypN- Reg+, ypN- Reg- and ypN+) and four-tiered (ypN- Reg+, ypN- Reg-, ypN+ Reg+ and ypN+ Reg-) classifications. In our cohort, 31% of patients presented with ypN+ rectal cancer. As expected, we found significantly worse overall survival (OS) in ypN+ patients compared to ypN- patients (P = 0.002). The percentage of ypN- patients with lymph nodes with complete regression was 20% in our cohort. While node-negative patients with and without regression had similar OS (P = 0.09), disease-free survival (DFS) was significantly better in node-negative patients with regression (P = 0.009).

CONCLUSIONS

Regression in lymph nodes is frequent, and node-negative patients with evidence of lymph node regression have better DFS compared to node-negative patients without such evidence.

Development and Validation of a Radiomics Model Based on Lymph-Node Regression Grading After Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

PURPOSE

The response to neoadjuvant chemoradiotherapy (nCRT) varies among patients with locally advanced rectal cancer (LARC), and the treatment response of lymph nodes (LNs) to nCRT is critical in implementing a watch-and-wait strategy. A robust predictive model may help personalize treatment plans to increase the chance that patients achieve a complete response. This study investigated whether radiomics features based on prenCRT magnetic resonance imaging nodes could predict treatment response in preoperative LARC LNs.

METHODS AND MATERIALS

The study included 78 patients with clinical stage T3-T4, N1-2, and M0 rectal adenocarcinoma who received long-course neoadjuvant radiotherapy before surgery. Pathologists evaluated 243 LNs, of which 173 and 70 were assigned to training and validation cohorts, respectively. For each LN, 3641 radiomics features were extracted from the region of interest in high-resolution T2WI magnetic resonance imaging before nCRT. The least absolute shrinkage and selection operator regression model was used for feature selection and radiomics signature building. A prediction model based on multivariate logistic analysis, combining radiomics signature and selected LN morphologic characteristics, was developed and visualized by drawing a nomogram. The model's performance was assessed by receiver operating characteristic curve analysis and calibration curves.

RESULTS

The radiomics signature consists of 5 selected features that were effectively discriminated within the training cohort (area under the curve [AUC], 0.908; 95% CI, 0.857%-0.958%) and the validation cohort (AUC, 0.865; 95% CI, 0.757%-0.973%). The nomogram, which consisted of radiomics signature and LN morphologic characteristics (short-axis diameter and border contours), showed better calibration and discrimination in the training and validation cohorts (AUC, 0.925; 95% CI, 0.880%-0.969% and AUC, 0.918; 95% CI, 0.854%-0.983%, respectively). The decision curve analysis confirmed that the nomogram had the highest clinical utility.

CONCLUSIONS

The nodal-based radiomics model effectively predicts LNs treatment response in patients with LARC after nCRT, which could help personalize treatment plans and guide the implementation of the watch-and-wait approach in these patients.

Risk-factors for locally advanced rectal cancer relapse after neoadjuvant chemoradiotherapy: A single center experience

The overall prognosis of locally advanced rectal cancer (LARC) remains unsatisfactory due to a high incidence of disease relapse. The present understanding of the factors that determine the likelihood of recurrence is limited or ineffective. We aimed to identify the main risk factors influencing tumor relapse in LARC patients after neoadjuvant chemoradiotherapy (nCRT) and surgical treatment in a single center in Republika Srpska. Patients with stage II or stage III who received nCRT before surgery for primary rectal cancer at the Oncology Clinic, University Clinical Center of Republika Srpska from January 2017 and December 2022 were included in the study. We collected patient demographics, clinical stage and characteristics, neoadjuvant therapy, and surgical methods, along with the pathological response after treatment completion, and analyzed them to identify the risk factors for tumor relapse. Out of 109 patients diagnosed with LARC, 34 (31,2%) had tumor relapse. The median time to relapse was 54 months. Participants with clinical T4 stage had a significantly shorter relapse time compared to the patients with clinical T2/3 stage. Subjects with positive lymph nodes removed, perivascular and perineural invasion, intraoperative perforation and patients without ypN stage improvement had significantly shorter time to relapse. Subjects with T4 stage had more than 4 times higher risk of relapse than patients with clinical T2/3 stage. Higher clinical T stage was an essential risk factor for tumor relapse in LARC patients after nCRT and surgical treatment. Comprehensive understanding and identification of the risk factors for tumor relapse in LARC patients are crucial for improving their long-term outcomes.

Comparation between novel online models and the AJCC 8th TNM staging system in predicting cancer-specific and overall survival of small cell lung cancer

Background

Most of previous studies on predictive models for patients with small cell lung cancer (SCLC) were single institutional studies or showed relatively low Harrell concordance index (C-index) values. To build an optimal nomogram, we collected clinicopathological characteristics of SCLC patients from Surveillance, Epidemiology, and End Results (SEER) database.

Methods

24,055 samples with SCLC from 2010 to 2016 in the SEER database were analyzed. The samples were grouped into derivation cohort (n=20,075) and external validation cohort (n=3,980) based on America's different geographic regions. Cox regression analyses were used to construct nomograms predicting cancer-specific survival (CSS) and overall survival (OS) using derivation cohort. The nomograms were internally validated by bootstrapping technique and externally validated by calibration plots. C-index was computed to compare the accuracy and discrimination power of our nomograms with the 8th of version AJCC TNM staging system and nomograms built in previous studies. Decision curve analysis (DCA) was applied to explore whether the nomograms had better clinical efficiency than the 8th version of AJCC TNM staging system.

Results

Age, sex, race, marital status, primary site, differentiation, T classification, N classification, M classification, surgical type, lymph node ratio, radiotherapy, and chemotherapy were chosen as predictors of CSS and OS for SCLC by stepwise multivariable regression and were put into the nomograms. Internal and external validations confirmed the nomograms were accurate in prediction. C-indexes of the nomograms were relatively satisfactory in derivation cohort (CSS: 0.761, OS: 0.761) and external validation cohort (CSS: 0.764, OS: 0.764). The accuracy of the nomograms was superior to that of nomograms built in previous studies. DCA showed the nomograms conferred better clinical efficiency than 8th version of TNM staging system.

Conclusions

We developed practical nomograms for CSS (https://guowei2020.shinyapps.io/DynNom-CSS-SCLC/) and OS (https://drboidedwater.shinyapps.io/DynNom-OS-SCLC/) prediction of SCLC patients which may facilitate clinicians in individualized therapeutics.

Lymph node regression grading of locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy

Neoadjuvant chemoradiotherapy (nCRT) and total rectal mesenteric excision are the main standards of treatment for locally advanced rectal cancer (LARC). Lymph node regression grade (LRG) is an indicator of prognosis and response to preoperative nCRT based on postsurgical metastatic lymph node pathology. Common histopathological findings in metastatic lymph nodes after nCRT include necrosis, hemorrhage, nodular fibrosis, foamy histiocytes, cystic cell reactions, areas of hyalinosis, residual cancer cells, and pools of mucin. A number of LRG systems designed to classify the amount of lymph node regression after nCRT is mainly concerned with the relationship between residual cancer cells and regressive fibrosis and with estimating the number of lymph nodes existing with residual cancer cells. LRG offers significant prognostic information, and in most cases, LRG after nCRT correlates with patient outcomes. In this review, we describe the systematic classification of LRG after nCRT, patient prognosis, the correlation with tumor regression grade, and the typical histopathological findings of lymph nodes. This work may serve as a reference to help predict the clinical complete response and determine lymph node regression in patients based on preservation strategies, allowing for the formulation of more accurate treatment strategies for LARC patients, which has important clinical significance and scientific value.

Prognostic significance of metastatic lymph node ratio in patients with gastric cancer after curative gastrectomy: a single-center retrospective study

BACKGROUND

The objective of this study was to evaluate the prognostic value of Metastatic lymph node ratio (MLNR) after curative gastrectomy in patients with gastric cancer (GC) and the potential for new indicators to strengthen the current guidelines.

METHODS

We retrospectively researched 3864 GC patients with curative gastrectomy between February 2011 and February 2016. The following clinical data were collected from the included patients: gender, type of gastrectomy, tumor location, T stage, N stage, ELN, tumor size, age at surgery, perineural invasion, vascular invasion, TNM stage, survival time and survival status. Patients were divided into low-MLNR (L-MLNR), and high-MLNR (H-MLNR) groups based on adjusted the X-tile cutoff-value of 0.25 for MLNR, the survival rates and clinicopathological characteristics of each group were compared. For the assessment of significant associations between clinicopathological characteristics and patients' survival, univariate and multivariate analyses were performed using the Kaplan-Meier method and Cox proportional hazards analysis. The log-rank test was used to examine the statistical significance of differences among different survival curves. Clinicopathological features significantly associated with MLNR were assessed by the Chi-square test and multinomial logistic regression. The discriminative ability was measured by calculating the Bayesian Information Criterion (BIC) values for each category. Assessment of the effect of clinicopathological features on MLNR for predicting prognosis of GC patients used stratum analysis through Kaplan-Meier analysis and Cox proportional risk Analysis.

RESULTS

Survival analysis indicated that MLNR was negatively associated with overall survival (OS) (p < .001) and was an independent prognostic predictor in 3864 GC patients (p < .001). MLNR had significant prognostic significance in various subgroups with clinicopathological characteristics (gender, type of gastrectomy, tumor location, T stage, N stage, ELN, tumor size, age at surgery, perineural invasion, vascular invasion, and TNM stage) (p < .001).

CONCLUSIONS

The MLNR may become a new indicator to assess the prognosis of GC patients who underwent curative gastrectomy. The results may have potential clinical implications that should be considered when developing clinical practice guidelines or the design of the future investigation.

Risk factors for long-term survival in patients with ypN+ M0 rectal cancer after radical anterior resection

Background

Regional lymph node metastases are the main adverse prognostic factor in patients with rectal cancer without distant metastases. There are discrepancies, however, regarding additional risk factors in the group of ypN + M0 patients. The purpose of the study was to assess clinical and pathological factors affecting long-term oncological outcomes in the group of ypN + M0 patients after radical rectal anterior resection.

Methods

112 patients with ypN + M0 rectal cancer after neoadjuvant therapy and radical anterior resection were subject to a retrospective analysis. The effect of potential factors on survival was assessed with the use of Kaplan–Meier curves together with a log-rank test and multiple factor Cox proportional hazards model.

Results

In the multiple factor Cox analysis, adverse factors affecting disease-free survival (DFS) were: the use of angiotensin-converting enzyme inhibitors (ACEIs) (hazard ratio HR: 3.11, 95% CI 1.01–9.56, p = 0.047), presence of perineural invasion (HR: 7.27, 95% CI 2.74–19.3, p < 0.001) and occurrence of postoperative complications (HR: 6.79, 95% CI 2.09–22.11, p = 0.001), while a positive factor was the negative lymph node (NLN) count > 7 (HR: 0.33, 95% CI 0.12–0.88, p = 0.026). In the disease-specific survival (DSS) analysis, an adverse factor was the use of ACEIs (HR: 4.275, 95% CI 1.44–12.694, p = 0.009), while a positive effect was caused by NLN > 5 (HR: 0.22, 95% CI 0.082–0.586, p = 0.002).

Conclusions

The use of ACEIs may have a negative effect on long-term treatment outcomes in patients with ypN + M0 rectal cancer. In this group of patients, the NLN count seems to be an important prognostic factor, as well.

Metastatic lymph node ratio as a better prognostic tool than the TNM system in colorectal cancer

Background: The minimum number of lymph nodes that should be evaluated in colon cancer to adequately categorize lymph node status is still controversial. The lymph node ratio (LNR) may be a better prognostic indicator. Materials & methods: We studied 1065 patients treated from 1 January 2000 to 31 August 2012. Results: Significant differences in survival were detected according to regional lymph nodes (pN) (p < 0.001) and LNR (p < 0.001). LRN and pN are independent prognostic factors. Spearman correlation analysis showed a significant correlation between the total number of dissected lymph nodes and pN (rs = 0.167; p < 0.001), but the total number of dissected lymph nodes is not significantly correlated with LNR (rs = -0.019; p = 0.550). Interpretation: In this study, LNR seems to demonstrate a superior prognostic value compared with the pN categories, in part due to its greater independence regarding the extent of lymphadenectomy.