Incidence, risk factors, and a predictive model for lymph node metastasis of submucosal (T1) colon cancer: A population-based study

A clinical-radiomics nomogram based on spectral CT multi-parameter images for preoperative prediction of lymph node metastasis in colorectal cancer

To develop a clinical-radiomics nomogram based on spectral CT multi-parameter images for predicting lymph node metastasis in colorectal cancer. A total of 76 patients with colorectal cancer and 156 lymph nodes were included. The clinical data of the patients were collected, including gender, age, tumor location and size, preoperative tumor markers, etc. Three sets of conventional images in the arterial, venous, and delayed phases were obtained, and six sets of spectral images were reconstructed using the arterial phase spectral data, including virtual monoenergetic images (40 keV, 70 keV, 100 keV), iodine density maps, iodine no water maps, and virtual non-contrast images. Radiomics features of lymph nodes were extracted from the above images, respectively. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select features. A clinical model was constructed based on age and carcinoembryonic antigen (CEA) levels. The radiomics features selected were used to generate a composed radiomics signature (Com-RS). A nomogram was developed using age, CEA, and the Com-RS. The models' prediction efficiency, calibration, and clinical application value were evaluated by the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis, respectively. The nomogram outperforms the clinical model and the Com-RS (AUC = 0.879, 0.824). It is well calibrated and has great clinical application value. This study developed a clinical-radiomics nomogram based on spectral CT multi-parameter images, which can be used as an effective tool for preoperative personalized prediction of lymph node metastasis in colorectal cancer.

Determinants of survival and recurrence in patients with stage I colorectal cancer

Background

Due to the novel advanced screening methods, the number of patients diagnosed with stage I colorectal cancer (CRC) is increasing. This retrospective cohort study aimed to identify recurrence and survival risk factors of patients with stage I CRC after surgery.

Materials and methods

Patients with stage I CRC were evaluated, and their demographic and clinicopathologic variables were recorded. The log-rank test assessed the association of variables with overall survival (OS), recurrence-free survival (RFS), local recurrence, and distant metastasis.

Results

The median overall survival period was 51 months. The recurrence rate was 13.7%: 7.2% local and 9.3% distant recurrence. One-, two-, three-, and five-year RFS were 92%, 89%, 87%, and 83%, respectively, and OS were 96%, 93%, 90%, and 89%, respectively. Local and distant recurrence rates were higher in patients with higher tumor grades. Additionally, RFS and OS were worse in patients with higher tumor grades, and perforation was associated with worse OS.

Conclusions

The determinants of survival and recurrence identified in the present study can be used to improve patient outcomes by early diagnosis and appropriate management of high-risk patients.

Risk of recurrence in high-risk T1 colon cancer following endoscopic and surgical resection: registry-based cohort study

BACKGROUND

Endoscopic resection of T1 colon cancer (CC) is currently limited by guidelines related to risk of lymph node metastases. However, clinical outcome following endoscopic and surgical resection is poorly investigated.

METHOD

A retrospective multicentre national cohort study was conducted on prospectively collected data from the Swedish colorectal cancer registry on all non-pedunculated T1 CC patients undergoing surgical and endoscopic resection between 2009 and 2021. Patients were categorized on the basis of deep submucosal invasion (Sm2-3), lymphovascular invasion (LVI), poor tumour differentiation, and R1/Rx into low- and high-risk cases. The primary outcomes of interest were recurrence rates and disease-free interval (DFI, defined as time from treatment to date of recurrence) according to resection methods and risk factors (sex, age at diagnosis, histologic grade, LVI, perineural invasion, mucinous subtype, submucosal invasion, tumour location, resection margin and nodal positivity in the surgical group).

RESULTS

In total, 1805 patients undergoing endoscopic (488) and surgical (1317) resection with 60.0 months median follow-up were included. Recurrence occurred in 18 (3.7%) endoscopically and 48 (3.6%) surgically resected patients. Adjuvant treatment was administered in 7.4% and 0.2% of the cases respectively in the surgical and endoscopically treated patients. Five-year DFI was 95.6% after endoscopic and 96.2% after surgical resection, with no significant difference when adjusting for confounding factors (HR 1.03, 95% c.i. 0.56 to 1.91, P = 0.920). There were no statistically significant differences in recurrence comparing endoscopic (1.7%) versus surgical (3.6%) low-risk and endoscopic (5.4%) versus surgical (3.8%) high-risk cases. LVI was the only significant risk factor for recurrence in multivariate Cox regression (HR 3.73, 95% c.i. 1.76 to 7.92, P < 0.001).

CONCLUSIONS

This study shows no difference in recurrence after endoscopic and surgical resection in high-risk T1 CC. Although it was not possible to match groups according to treatment, the multivariate analysis showed that lymphovascular invasion was the only independent risk factor for recurrence.

A prediction nomogram for perineural invasion in colorectal cancer patients: a retrospective study

BACKGROUND

Perineural invasion (PNI), as the fifth recognized pathway for the spread and metastasis of colorectal cancer (CRC), has increasingly garnered widespread attention. The preoperative identification of whether colorectal cancer (CRC) patients exhibit PNI can assist clinical practitioners in enhancing preoperative decision-making, including determining the necessity of neoadjuvant therapy and the appropriateness of surgical resection. The primary objective of this study is to construct and validate a preoperative predictive model for assessing the risk of perineural invasion (PNI) in patients diagnosed with colorectal cancer (CRC).

MATERIALS AND METHODS

A total of 335 patients diagnosed with colorectal cancer (CRC) at a single medical center were subject to random allocation, with 221 individuals assigned to a training dataset and 114 to a validation dataset, maintaining a ratio of 2:1. Comprehensive preoperative clinical and pathological data were meticulously gathered for analysis. Initial exploration involved conducting univariate logistic regression analysis, with subsequent inclusion of variables demonstrating a significance level of p < 0.05 into the multivariate logistic regression analysis, aiming to ascertain independent predictive factors, all while maintaining a p-value threshold of less than 0.05. From the culmination of these factors, a nomogram was meticulously devised. Rigorous evaluation of this nomogram's precision and reliability encompassed Receiver Operating Characteristic (ROC) curve analysis, calibration curve assessment, and Decision Curve Analysis (DCA). The robustness and accuracy were further fortified through application of the bootstrap method, which entailed 1000 independent dataset samplings to perform discrimination and calibration procedures.

RESULTS

The results of multivariate logistic regression analysis unveiled independent risk factors for perineural invasion (PNI) in patients diagnosed with colorectal cancer (CRC). These factors included tumor histological differentiation (grade) (OR = 0.15, 95% CI = 0.03-0.74, p = 0.02), primary tumor location (OR = 2.49, 95% CI = 1.21-5.12, p = 0.013), gross tumor type (OR = 0.42, 95% CI = 0.22-0.81, p = 0.01), N staging in CT (OR = 3.44, 95% CI = 1.74-6.80, p < 0.001), carcinoembryonic antigen (CEA) level (OR = 3.13, 95% CI = 1.60-6.13, p = 0.001), and platelet-to-lymphocyte ratio (PLR) (OR = 2.07, 95% CI = 1.08-3.96, p = 0.028).These findings formed the basis for constructing a predictive nomogram, which exhibited an impressive area under the receiver operating characteristic (ROC) curve (AUC) of 0.772 (95% CI, 0.712-0.833). The Hosmer-Lemeshow test confirmed the model's excellent fit (p = 0.47), and the calibration curve demonstrated consistent performance. Furthermore, decision curve analysis (DCA) underscored a substantial net benefit across the risk range of 13% to 85%, reaffirming the nomogram's reliability through rigorous internal validation.

CONCLUSION

We have formulated a highly reliable nomogram that provides valuable assistance to clinical practitioners in preoperatively assessing the likelihood of perineural invasion (PNI) among colorectal cancer (CRC) patients. This tool holds significant potential in offering guidance for treatment strategy formulation.

Lymph node metastasis in T1-2 colorectal cancer: a population-based study

BACKGROUND

We performed this study to identify predictive factors for lymph node metastasis (LNM) and analyze the impact of LNM on the prognosis of patients with T1-2 colorectal cancer (CRC), with the intention of providing guidance for the treatment.

METHODS

The Surveillance Epidemiology and End Result database was used to identify 20,492 patients diagnosed with T1-2 stage CRC between 2010 and 2019, who underwent surgery and lymph node evaluation and had complete prognostic information. Clinicopathological data of patients with T1-2 stage colorectal cancer treated with surgery at Peking University People's Hospital from 2017 to 2021 with complete clinical information were retrieved. We identify and confirm the risk factors for positive lymph node involvement, and the results of follow-up were analyzed.

RESULTS

Age, preoperative carcinoembryonic antigen (CEA) level, perineural invasion, and primary tumor site were independent risk factors for LNM in T1-2 CRC based on the analysis of the SEER database, while tumor size and histology of mucinous carcinoma were also independent risk factors in T1 CRC. We then make the nomogram model for predicting LNM risk and showed an acceptable consistency and calibration capability. Survival analysis showed that LNM was an independent prognostic indicator of 5-year disease-specific survival (P = 0.013) and disease-free survival (P < 0.001) in patients with T1 and T2 CRC.

CONCLUSION

Age, CEA level and primary tumor site should be taken into consideration before making the surgical decision in T1-2 CRC patients. The tumor size and histology of mucinous carcinoma also need to be thought about in T1 CRC. Conventional imaging tests do not appear to provide a precise assessment for this issue.

CT is unreliable in locoregional staging of early colon cancer: A nationwide registry-based study

BACKGROUND AND OBJECTIVE

The option to treat early colon cancer (CC) with local resection, as well as trials investigating neoadjuvant treatment, has increased the importance of identifying early-stage disease in the workup. Most CC patients are T- and N-staged preoperatively with CT, although its reliability in staging early CC remains elusive. The aim of this study was to investigate CT-staging accuracy in early CC by evaluating pT and pN stages in patients staged as cT1-2, and cT and cN stages in patients with pT1 tumors.

METHODS

Retrospective population-based cohort study on data from the nationwide Swedish colorectal cancer registry on all CC patients staged as cT1-2 and all patients with pT1 undergoing surgical resection 2009-2018. CT-acquired T- and N-stages were compared with final histopathology. Factors potentially influencing accuracy were analyzed with uni- and multivariate logistic regression.

RESULTS

Computed tomography (CT) staged 4849 patients as cT1-2, whereas 2445 (50%) were pT3 and 453 (9%) pT4. Positive predictive value of the cT1-2 stage was 40%. Of 1401 pT1 patients, 624 (45%) were staged as cT1-2, 139 (10%) as cT3, 15 (1%) as cT4 and 623 (44%) as cTx. In all, 1474 (30%) of the cT1-2 patients were pN+, whereas CT staged 1062 (72%) as cN0. A total of 771 patients were staged as cN+, whereas 403 (52%) were pN0. Overall accuracy in determining N+ was 67%, with 26% sensitivity and 88% specificity. Positive and negative predictive values in determining N+ were 48% and 73%, respectively.

CONCLUSIONS

This nationwide population-based study shows that CT-staging carries a substantial risk of understaging locally advanced tumors as cT1-2 and pT1 tumors as cTx, in addition to poor N-staging. Thus, CT obtained T- and N-staging should not be used for deciding treatment strategies in early CC.

Clinicopathological features of small T1 colorectal cancers

BACKGROUND

Although small colorectal neoplasms (< 10 mm) are often easily resected endoscopically and are considered to have less malignant potential compared with large neoplasms (≥ 10 mm), some are invasive to the submucosa.

AIM

To clarify the clinicopathological features of small T1 colorectal cancers.

METHODS

Of 32025 colorectal lesions between April 2001 and March 2018, a total of 1152 T1 colorectal cancers resected endoscopically or surgically were included in this study and were divided into two groups by tumor size: a small group (< 10 mm) and a large group (≥ 10 mm). We compared clinicopathological factors including lymph node metastasis (LNM) between the two groups.

RESULTS

The incidence of small T1 cancers was 10.1% (116/1152). The percentage of initial endoscopic treatment in small group was significantly higher than in large group (< 10 mm 74.1% vs ≥ 10 mm 60.2%, P < 0.01). In the surgical resection cohort (n = 798), the rate of LNM did not significantly differ between the two groups (small 12.3% vs large 10.9%, P = 0.70). In addition, there were also no significant differences between the two groups in pathological factors such as histological grade, vascular invasion, or lymphatic invasion.

CONCLUSION

Because there was no significant difference in the rate of LNM between small and large T1 colorectal cancers, the requirement for additional surgical resection should be determined according to pathological findings, regardless of tumor size.

Association Between Chemotherapy and Survival in T1 Colon Cancer With Lymph Node Metastasis: A Propensity-Score Matched Analysis

This study aimed to comprehensively examine the efficacy of chemotherapy in T1 colon cancer patients with lymph node metastasis.

A predictive nomogram for lymph node metastasis of incidental gallbladder cancer: a SEER population-based study

BACKGROUND

Existing imaging techniques have a low ability to detect lymph node metastasis (LNM) of gallbladder cancer (GBC). Gallbladder removal by laparoscopic cholecystectomy can provide pathological information regarding the tumor itself for incidental gallbladder cancer (IGBC). The purpose of this study was to identify the risk factors associated with LNM of IGBC and to establish a nomogram to improve the ability to predict the risk of LNM for IGBC.

METHODS

A total of 796 patients diagnosed with stage T1/2 GBC between 2004 and 2015 who underwent surgery and lymph node evaluation were enrolled in this study. We randomly divided the dataset into a training set (70%) and a validation set (30%). A logistic regression model was used to construct the nomogram in the training set and then was verified in the validation set. Nomogram performance was quantified with respect to discrimination and calibration.

RESULTS

The rates of LNM in T1a, T1b and T2 patients were 7, 11.1 and 44.3%, respectively. Tumor diameter, T stage, and tumor differentiation were independent factors affecting LNM. The C-index and AUC of the training set were 0.718 (95% CI, 0.676-0.760) and 0.702 (95% CI, 0.659-0.702), respectively, demonstrating good prediction performance. The calibration curves showed perfect agreement between the nomogram predictions and actual observations. Decision curve analysis showed that the LNM nomogram was clinically useful when the risk was decided at a possibility threshold of 2-63%. The C-index and AUC of the validation set were 0.73 (95% CI: 0.665-0.795) and 0.692 (95% CI: 0.625-0.759), respectively.

CONCLUSION

The nomogram established in this study has good prediction ability. For patients with IGBC requiring re-resection, the model can effectively predict the risk of LNM and make up for the inaccuracy of imaging.

Risk factors and predictors of lymph nodes metastasis and distant metastasis in newly diagnosed T1 colorectal cancer

Background

Lymph nodes metastasis (LNM) and distant metastasis (DM) are important prognostic factors in colorectal cancer (CRC) and determine the following treatment approaches. We aimed to find clinicopathological factors associated with LNM and DM, and analyze the prognosis of CRC patients with T1 stage.

Methods

A total of 17 516 eligible patients with T1 CRC were retrospectively enrolled in the study based on the Surveillance, Epidemiology, and End Results (SEER) database during 2004‐2016. Logistic regression analysis was performed to identify risk factors for LNM and DM. Unadjusted and adjusted Cox proportional hazard models were used to identify prognostic factors for overall survival. We performed the cumulative incidence function (CIF) to further determine the prognostic role of LNM and DM in colorectal cancer‐specific death (CCSD). LNM, DM, and OS nomogram were constructed based on these models and evaluated by the C‐index and calibration plots for discrimination and accuracy, respectively. The clinical utility of the nomograms was measured by decision curve analyses (DCAs) and subgroups with different risk scores.

Results

Tumor grade, mucinous adenocarcinoma, and age accounted for the first three largest proportion among the LNM nomogram scores (all, P < .001), whereas N stage, carcinoembryonic antigen (CEA), and tumor size occupied the largest percentage in DM nomogram (all, P < .001). OS nomogram was formulated to visually to predict 3‐, 5‐, and 10‐ year overall survivals for patients with T1 CRC. The calibration curves showed an effectively predictive accuracy of prediction nomograms, of which the C‐index were 0.666, 0.874, and 0.760 for good discrimination, respectively. DCAs and risk subgroups revealed the clinical effectiveness of these nomograms.

Conclusions

Novel population‐based nomograms for T1 CRC patients could objectively and accurately predict the risk of LNM and DM, as well as OS for different stages. These predictive tools may help clinicians to make individual clinical decisions, before clinical management.