Is there a relationship between length of resection and lymph-node ratio in colorectal cancer?

Zanghì, Antonio; Cavallaro, Andrea; Menzo, Emanuele Lo; Botta, Serena Curella; Bianco, Salvatore Lo; Vita, Maria Di; Cardì, F; Cappellani, Alessandro

doi:10.1093/gastro/goz066

Cited by 6 publications

(5 citation statements)

References 29 publications

(25 reference statements)

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“…Some studies state that LNR is a significant risk factor that should be incorporated into the TNM staging system of the American Joint Committee on Cancer due to its high predictive value for survival [ 39 , 40 ]. However, some studies disagree with this because the lymph node assessment in CRC specimens can be influenced by both surgical and pathological factors, including the extent of the lymph node dissection, the length of the surgical specimen, the surgeon’s technique, and the thoroughness of the pathologists [ 41 , 42 , 43 ]. In our study, the mean number of total harvested lymph nodes was over 20, which is a proxy for high-quality surgical resection [ 44 ].…”

Section: Discussionmentioning

confidence: 99%

A Prediction Model for Tumor Recurrence in Stage II–III Colorectal Cancer Patients: From a Machine Learning Model to Genomic Profiling

et al. 2022

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Background: Colorectal cancer (CRC) is one of the most prevalent malignant diseases worldwide. Risk prediction for tumor recurrence is important for making effective treatment decisions and for the survival outcomes of patients with CRC after surgery. Herein, we aimed to explore a prediction algorithm and the risk factors for postoperative tumor recurrence using a machine learning (ML) approach with standardized pathology reports for patients with stage II and III CRC. Methods: Pertinent clinicopathological features were compiled from medical records and standardized pathology reports of patients with stage II and III CRC. Four ML models based on logistic regression (LR), random forest (RF), classification and regression decision trees (CARTs), and support vector machine (SVM) were applied for the development of the prediction algorithm. The area under the curve (AUC) of the ML models was determined in order to compare the prediction accuracy. Genomic studies were performed using a panel-targeted next-generation sequencing approach. Results: A total of 1073 patients who received curative intent surgery at the National Cheng Kung University Hospital between January 2004 and January 2019 were included. Based on conventional statistical methods, chemotherapy (p = 0.003), endophytic tumor configuration (p = 0.008), TNM stage III disease (p < 0.001), pT4 (p < 0.001), pN2 (p < 0.001), increased numbers of lymph node metastases (p < 0.001), higher lymph node ratios (LNR) (p < 0.001), lymphovascular invasion (p < 0.001), perineural invasion (p < 0.001), tumor budding (p = 0.004), and neoadjuvant chemoradiotherapy (p = 0.025) were found to be correlated with the tumor recurrence of patients with stage II–III CRC. While comparing the performance of different ML models for predicting cancer recurrence, the AUCs for LR, RF, CART, and SVM were found to be 0.678, 0.639, 0.593, and 0.581, respectively. The LR model had a better accuracy value of 0.87 and a specificity value of 1 in the testing set. Two prognostic factors, age and LNR, were selected by multivariable analysis and the four ML models. In terms of age, older patients received fewer cycles of chemotherapy and radiotherapy (p < 0.001). Right-sided colon tumors (p = 0.002), larger tumor sizes (p = 0.008) and tumor volumes (p = 0.049), TNM stage II disease (p < 0.001), and advanced pT3–4 stage diseases (p = 0.04) were found to be correlated with the older age of patients. However, pN2 diseases (p = 0.005), lymph node metastasis number (p = 0.001), LNR (p = 0.004), perineural invasion (p = 0.018), and overall survival rate (p < 0.001) were found to be decreased in older patients. Furthermore, PIK3CA and DNMT3A mutations (p = 0.032 and 0.039, respectively) were more frequently found in older patients with stage II–III CRC compared to their younger counterparts. Conclusions: This study demonstrated that ML models have a comparable predictive power for determining cancer recurrence in patients with stage II–III CRC after surgery. Advanced age and high LNR were significant risk factors for cancer recurrence, as determined by ML algorithms and multivariable analyses. Distinctive genomic profiles may contribute to discrete clinical behaviors and survival outcomes between patients of different age groups. Studies incorporating complete molecular and genomic profiles in cancer prediction models are beneficial for patients with stage II–III CRC.

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Section: Discussionmentioning

confidence: 99%

A Prediction Model for Tumor Recurrence in Stage II–III Colorectal Cancer Patients: From a Machine Learning Model to Genomic Profiling

et al. 2022

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“…LNM is an important factor affecting the prognosis of CRC and affects therapeutic decisions ( 5 ). AJCC pN stage and LNR are both reported as prognostic factors in CRC ( 6 , 8 ), but AJCC pN stage is limited by TLNs and LNR did not consider the effect of NLNs ( 7 , 11 ). LODDS has been reported to be less influenced by TLNs and takes into account the number of NLNs ( 9 ).…”

Section: Discussionmentioning

confidence: 99%

“…This may lead to underestimated stages and improper treatment. To address the limitations of the pN stage system, lymph node ratio (LNR) is proposed, which is defined as the ratio of the number of PLNs to the total number of retrieved lymph nodes (TLNs) ( 8 ). LNR is less influenced by TLNs and has been reported as a prognostic factor in CRC ( 8 , 9 ).…”

Section: Introductionmentioning

confidence: 99%

“…To address the limitations of the pN stage system, lymph node ratio (LNR) is proposed, which is defined as the ratio of the number of PLNs to the total number of retrieved lymph nodes (TLNs) ( 8 ). LNR is less influenced by TLNs and has been reported as a prognostic factor in CRC ( 8 , 9 ). However, for patients without LNM (pN0 patients), LNR cannot predict the prognosis better than pN stage system.…”

Section: Introductionmentioning

confidence: 99%

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Prognostic value of log odds of positive lymph nodes, lymph node ratio, and N stage in patients with colorectal signet ring cell carcinoma: A retrospective cohort study

Hu¹,

Jiang²,

Wu³

et al. 2023

Front. Surg.

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AimLittle attention has been paid in the prognosis of colorectal signet ring cell carcinoma (SRCC). This study aims to explore the predictive capacity of log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and pN stage in the prognosis of patients with colorectal SRCC.MethodsA retrospective cohort study was designed, and data were extracted from the Surveillance, Epidemiology and End Results (SEER) database. Data on demographic characteristics, clinicopathological features, and treatment were extracted. Outcomes were overall survival (OS) and cancer-specific survival (CSS). Association of LODDS, LNR, and pN stage with OS and CSS were explored using Cox proportional hazard model and Cox competing risk model, respectively, with results showing as hazard ratio and 95% confidence interval (CI). Predictive performance of LODDS, LNR, and pN stage in OS and CSS was assessed by calculating C-index.ResultsA total of 2,198 patients were included in this study. LODDS, LNR, and pN stage were associated with the OS and CSS of colorectal SRCC patients (all P < 0.05). LODDS showed a good performance in the OS (C-index: 0.704, 95% CI: 0.690–0.718), which was superior to LNR (C-index: 0.657, 95% CI: 0.643–0.671) and pN stage (C-index: 0.643, 95% CI: 0.629–0.657). The C-index of LODDS, LNR, and pN stage for CSS was 0.733 (95% CI: 0.719–0.747), 0.713 (95% CI: 0.697–0.729), and 0.667 (95% CI: 0.651–0.683), respectively.ConclusionsLODDS displayed a better predictive capacity in the OS and CSS than LNR and pN stage, indicating that LODDS may be effective to predict the prognosis of colorectal SRCC in the clinic.

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“…The American Joint Committee on Cancer recommends the resection of at least 12 LNR in the surgical specimen, however, this number depends on an adequate surgical resection and a good pathologist, in addition to these variables, this number is significantly reduced in patients with colon rectal cancer, with less than 12 LNR usually being found in the surgical specimen (3,4,(13)(14)(15)(16) . In studies on the size of the resection and the proportion of LNR influencing colorectal cancer, it was observed that the increase in the size of the resection causes an increase in the proportion of LNR, however, without affecting the number of positive LNR, thus constituting a factor that alters the conclusion of the prognostic value of the proportion of LNR (17)(18)(19) . Added to this, the prognostic importance of the number of LNR, in patients with few resected LNR, compared with patients with many resected LNR, after QRT, is not completely elucidated (20) .…”

Section: Introductionmentioning

confidence: 99%

Influence of Neoadjuvant Therapy on the Ratio of Lymph Nodes

CREDIDIO,

MARTINEZ,

MAGRO

et al. 2024

Arq. Gastroenterol.

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Background: To evaluate the relationship between the ratio of affected lymph nodes (LNR) and clinical and anatomopathological variables in patients with rectal adenocarcinoma submitted or not to neoadjuvant chemoradiotherapy. Methods: The LNR was determined by dividing the number of compromised LNR by the total number of LNR dissected in the surgical specimen. Patients were divided into two groups: with QRT and without QRT. In each group, the relationship between LNR and the following variables was evaluated: degree of cell differentiation, depth of invasion in the rectal wall, angiolymphatic /perineural invasion, degree of tumor regression and occurrence of metastases. The LNR was evaluated in patients with more than 1, LNR (LNR >12) or less (LNR<12) in the surgical specimen with overall survival (OS) and disease-free survival (DFS). The results were expressed as the mean with the respective standard deviation. Qualitative variables were analyzed using Fisher’s exact test, while quantitative variables were analyzed using the Kruskal -Wallis and Mann-Whitney tests. The significance level was 5%. Results: We evaluated 282 patients with QRT and 114 without QRT, between 1995-2011. In the QRT Group, LNR showed a significant association with mucinous tumors (P=0.007) and degree of tumor regression (P=0.003). In both groups, LNR was associated with poorly differentiated tumors (P=0.001, P=0.02), presence of angiolymphatic invasion (P<0.0001 and P=0.01), perineural (P=0.0007, P=0.02), degree of rectal wall invasion (T3>T2; P<0.0001, P=0.02); Compromised LNR (P<0.0001, P<0.01), metastases (P<0.0001, P<0.01). In patients with QRT, LNR<12 was associated with DFS (5.889; 95%CI1.935-19.687; P=0.018) and LNR>12 with DFS and OS (17.984; 95%CI5.931-54.351; P<0.001 and 10.286; 95%CI 2.654-39.854; P=0.007, respectively). Conclusion: LNR was associated with histological aspects of poor prognosis, regardless of the use of QRT. In the occurrence of less than 12 evaluated LNR, the LNR was associated only with the DFS.

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Is there a relationship between length of resection and lymph-node ratio in colorectal cancer?

Cited by 6 publications

References 29 publications

A Prediction Model for Tumor Recurrence in Stage II–III Colorectal Cancer Patients: From a Machine Learning Model to Genomic Profiling

A Prediction Model for Tumor Recurrence in Stage II–III Colorectal Cancer Patients: From a Machine Learning Model to Genomic Profiling

Prognostic value of log odds of positive lymph nodes, lymph node ratio, and N stage in patients with colorectal signet ring cell carcinoma: A retrospective cohort study

Influence of Neoadjuvant Therapy on the Ratio of Lymph Nodes

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