Predictors for regional lymph node metastasis in T1 rectal cancer: a population-based SEER analysis

Differences in Factors Predicting Lymph Node Metastasis Between pT1 Rectal Cancer and pT1 Colon Cancer: A Retrospective Study

BACKGROUND

Studies have demonstrated conflicting results regarding factors that predict lymph node metastasis (LNM) in pT1 colorectal cancers. We hypothesized that these discrepancies could be related to different factors predicting LNM between rectal and colon cancer. This study aimed to compare predicting factors for LNM between pT1 rectal and colon cancer.

METHODS

This retrospective study evaluated a prospectively maintained database that included 380 patients with pT1 colorectal cancer from January 2010 to December 2020. Patients were grouped according to whether they had rectal or colon cancer, with or without LNM, and factors predicting LNM were analyzed.

RESULTS

In pT1 rectal cancer, LNM was associated with deeper submucosal (SM) invasion (P = .024) and a higher proportion of poorly differentiated tumors (P = .006). In pT1 colon cancer, LNM was associated with a higher proportion of moderately/poorly differentiated tumors (P = .002) and lymphatic invasion (P = .004). In the multivariate analysis for rectal cancer, depth of SM invasion (≥3000 μm) was an independent predictive factor for LNM (95% confidence interval [CI], 1.48-27.94; P = .013), whereas for colon cancer, moderately/poorly differentiated tumors (95% CI, 1.38-8.13; P = .008) and lymphatic invasion (95% CI, 1.44-11.78; P = .008) were independent predictive factors for LNM.

DISCUSSION

There were distinct differences in the factors predicting LNM between pT1 rectal cancer and colon cancer. These results suggest the necessity in differentiating between rectal and colon cancer when performing studies on LNM in pT1 colorectal cancer.

Development and validation of a competitive risk model in patients with rectal cancer: based on SEER database

BACKGROUND

Rectal cancer is one of the most common malignancies. To predict the specific mortality risk of rectal cancer patients, we constructed a predictive nomogram based on a competing risk model.

METHODS

The information on rectal cancer patients was extracted from the SEER database. Traditional survival analysis and specific death analysis were performed separately on the data.

RESULTS

The present study included 23,680 patients, with 16,580 in the training set and 7100 in the validation set. The specific mortality rate calculated by the competing risk model was lower than that of the traditional survival analysis. Age, Marriage, Race, Sex, ICD-O-3Hist/Behav, Grade, AJCC stage, T stage, N stage, Surgery, Examined LN, RX SUMM-SURG OTH, Chemotherapy, CEA, Deposits, Regional nodes positive, Brain, Bone, Liver, Lung, Tumor size, and Malignant were independent influencing factors of specific death. The overall C statistic of the model in the training set was 0.821 (Se = 0.001), and the areas under the ROC curve for cancer-specific survival (CSS) at 1, 3, and 5 years were 0.842, 0.830, and 0.812, respectively. The overall C statistic of the model in the validation set was 0.829 (Se = 0.002), and the areas under the ROC curve for CSS at 1, 3, and 5 years were 0.851, 0.836, and 0.813, respectively.

CONCLUSIONS

The predictive nomogram based on a competing risk model for time-specific mortality in patients with rectal cancer has very desirable accuracy. Thus, the application of the predictive nomogram in clinical practice can help physicians make clinical decisions and follow-up strategies.

Prediction of lymph node metastasis in stage T1-2 rectal cancers with MRI-based deep learning

OBJECTIVES

This study aimed to investigate whether a deep learning (DL) model based on preoperative MR images of primary tumors can predict lymph node metastasis (LNM) in patients with stage T1-2 rectal cancer.

METHODS

In this retrospective study, patients with stage T1-2 rectal cancer who underwent preoperative MRI between October 2013 and March 2021 were included and assigned to the training, validation, and test sets. Four two-dimensional and three-dimensional (3D) residual networks (ResNet18, ResNet50, ResNet101, and ResNet152) were trained and tested on T2-weighted images to identify patients with LNM. Three radiologists independently assessed LN status on MRI, and diagnostic outcomes were compared with the DL model. Predictive performance was assessed with AUC and compared using the Delong method.

RESULTS

In total, 611 patients were evaluated (444 training, 81 validation, and 86 test). The AUCs of the eight DL models ranged from 0.80 (95% confidence interval [CI]: 0.75, 0.85) to 0.89 (95% CI: 0.85, 0.92) in the training set and from 0.77 (95% CI: 0.62, 0.92) to 0.89 (95% CI: 0.76, 1.00) in the validation set. The ResNet101 model based on 3D network architecture achieved the best performance in predicting LNM in the test set, with an AUC of 0.79 (95% CI: 0.70, 0.89) that was significantly greater than that of the pooled readers (AUC, 0.54 [95% CI: 0.48, 0.60]; p < 0.001).

CONCLUSION

The DL model based on preoperative MR images of primary tumors outperformed radiologists in predicting LNM in patients with stage T1-2 rectal cancer.

KEY POINTS

• Deep learning (DL) models with different network frameworks showed different diagnostic performance for predicting lymph node metastasis (LNM) in patients with stage T1-2 rectal cancer. • The ResNet101 model based on 3D network architecture achieved the best performance in predicting LNM in the test set. • The DL model based on preoperative MR images outperformed radiologists in predicting LNM in patients with stage T1-2 rectal cancer.

Rectal cancer: Maximizing local control and minimizing toxicity

Adoption of multimodality treatment approach for rectal cancer has resulted in significant improvements in oncologic outcomes. The roles of chemotherapy, radiation, and surgery in rectal cancer treatment are continuously evolving with the goal of achieving the best possible oncologic and functional outcome while minimizing treatment toxicity. The aim of this review is to summarize the most recent trials focusing on organ-sparing treatment strategies and the optimal selection of patients for neoadjuvant radiation therapy.

AGA Clinical Practice Update on Surveillance After Pathologically Curative Endoscopic Submucosal Dissection of Early Gastrointestinal Neoplasia in the United States: Commentary

The purpose of this American Gastroenterological Association (AGA) Institute Clinical Practice Update was to review the available evidence and provide expert advice regarding surveillance using endoscopy and other relevant modalities after removal of dysplastic lesions and early gastrointestinal cancers with endoscopic submucosal dissection deemed to be pathologically curative. This Clinical Practice Update was commissioned and approved by the AGA Institute Clinical Practice Updates Committee and the AGA Governing Board to provide timely guidance on a topic of high clinical importance to the AGA membership, and underwent internal peer review by the Clinical Practice Updates Committee and external peer review through standard procedures of Gastroenterology. This expert commentary incorporates important as well as recently published studies in this field, and it reflects the experiences of the authors, who are advanced endoscopists with high-level expertise in performing endoscopic submucosal dissection to treat dysplasia and early cancers in the luminal gastrointestinal tract.

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.

Influence of Old Age on Risk of Lymph Node Metastasis and Survival in Patients With T1 Colorectal Cancer: A Population-Based Analysis

Background

We aimed at determining the influence of old age on lymph node metastasis (LNM) and prognosis in T1 colorectal cancer (CRC).

Methods

We collected data from eligible patients in Surveillance, Epidemiology, and End Results database between 2004 and 2015. Independent predictors of LNM were identified by logistic regression analysis. Cox regression analysis, propensity score-matched analysis, and competing risks analysis were used to analyze the associations between old age and lymph node (LN) status and to validate the prognostic value of old age on cancer-specific survival (CSS).

Results

In total, 10,092 patients were identified. Among them, 6,423 patients (63.6%) had greater than or equal to 12 examined lymph nodes (LNE ≥12), and 5,777 patients (57.7%) were 65 years or older. The observed rate of LNM was 4.6% (15 out of 325) in T1 CRC elderly patients, with tumor size <3 cm, well differentiated, with negative carcinoembryonic antigen (CEA) level, and adenocarcinoma. Logistic regression models demonstrated that tumor size ≥3 cm (odds ratio, OR = 1.316, P = 0.038), poorly differentiated (OR = 3.716, P < 0.001), older age (OR = 0.633 for ages 65–79 years, OR = 0.477 for age over 80 years, both P <0.001), and negative CEA level (OR = 0.71, P = 0.007) were independent prognostic factors. Cox regression analysis demonstrated that CSS was not significantly different between elderly patients undergoing radical resection with LNE ≥12 and those with LNE <12 (hazard ratio = 0.865, P = 0.153), which was firmly validated after a propensity score-matched analysis by a competing risks model.

Conclusions

The predictive value of tumor size, grading, primary site, histology, CEA level, and age for LNM should be considered in medical decision making about local resection. We found that tumor size was <3 cm, well differentiated, negative CEA level, and adenocarcinoma in elderly patients with T1 colorectal cancer which was suitable for local excision.

Classic and Novel Histopathologic Risk Factors for Lymph Node Metastasis in T1 Colorectal Cancer: A Systematic Review and Meta-analysis

BACKGROUND

Treatment of endoscopically resected T1 colorectal cancers is based on the risk of lymph node metastasis. Risk is based on histopathologic features, although there is lack of consensus as to what constitutes high-risk features.

OBJECTIVE

The purpose of this study was to conduct a systematic review and meta-analysis of histopathologic risk factors for lymph node metastasis.

DATA SOURCES

A search of MEDLINE, Embase, Scopus, and Cochrane controlled register of trials for risk factors for lymph node metastasis was performed from inception until August 2018.

STUDY SELECTION

Included patients must have had an oncologic resection to confirm lymph node status and reported at least 1 histopathologic risk factor.

INTERVENTION

Rates of lymph node positivity were compared between patients with and without risk factors.

MAIN OUTCOME MEASURES

We report the results of the meta-analysis as ORs.

RESULTS

Of 8592 citations, 60 met inclusion criteria. Pooled analyses found that lymphovascular invasion, vascular invasion, neural invasion, and poorly differentiated histology were significantly associated with lymph node metastasis, as were depths of 1000 µm (OR = 2.76), 1500 µm (OR = 4.37), 2000 µm (OR = 2.37), submucosal level 3 depth (OR = 3.08), and submucosal level 2/3 (OR = 3.08) depth. Depth of 3000 µm, Haggitt level 4, and widths of 3000 µm and 4000 µm were not significantly associated with lymph node metastasis. Tumor budding (OR = 4.99) and poorly differentiated clusters (OR = 14.61) were also significantly associated with lymph node metastasis.

LIMITATIONS

Included studies reported risk factors independently, making it impossible to examine the additive metastasis risk in patients with numerous risk factors.

CONCLUSIONS

We identified 1500 μm as the depth most significantly associated with lymph node metastasis. Novel factors tumor budding and poorly differentiated clusters were also significantly associated with lymph node metastasis. These findings should help inform guidelines regarding risk stratification of T1 tumors and prompt additional investigation into the exact contribution of poorly differentiated clusters to lymph node metastasis.

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.

Histopathological risk factors for lymph node metastases in T1 colorectal cancer: meta-analysis

BACKGROUND

National screening programmes increase the proportion of T1 colorectal cancers. Local excision may be possible, but the risk of lymph node metastases (LNMs) could jeopardize long-term outcomes. The aim of the present study was to review the association between histopathological findings and LNMs in T1 colorectal cancer.

METHODS

A systematic literature search was conducted using PubMed,Embase, and Cochrane online databases. Studies investigating the association between one or more histopathological factors and LNMs in patients who underwent resection for T1 colorectal cancer were included.

RESULTS

Sixteen observational studies were included in the meta-analysis, including a total of 10 181 patients, of whom 1 307 had LNMs. Lymphovascular invasion (odds ratio (OR) 7.42; P < 0.001), tumour budding (OR 4.00; P < 0.001), depth of submucosal invasion, whether measured as at least 1000 µm (OR 3.53; P < 0.001) or Sm2-3 (OR 2.12; P = 0.020), high tumour grade (OR 3.75; P < 0.001), polypoid growth pattern (OR 1.59; P = 0.040), and rectal location of tumour (OR 1.36; P = 0.003) were associated with LNMs.

CONCLUSION

Distinct histopathological factors associated with nodal metastases in T1 colorectal cancer can aid selection of patients for local excision or major excisional surgery.

A Liquid Biopsy Assay for Noninvasive Identification of Lymph Node Metastases in T1 Colorectal Cancer

BACKGROUND & AIMS

We recently reported use of tissue-based transcriptomic biomarkers (microRNA [miRNA] or messenger RNA [mRNA]) for identification of lymph node metastasis (LNM) in patients with invasive submucosal colorectal cancers (T1 CRC). In this study, we translated our tissue-based biomarkers into a blood-based liquid biopsy assay for noninvasive detection of LNM in patients with high-risk T1 CRC.

METHODS

We analyzed 330 specimens from patients with high-risk T1 CRC, which included 188 serum samples from 2 clinical cohorts-a training cohort (N = 46) and a validation cohort (N = 142)-and matched formalin-fixed paraffin-embedded samples (N = 142). We performed quantitative reverse-transcription polymerase chain reaction, followed by logistic regression analysis, to develop an integrated transcriptomic panel and establish a risk-stratification model combined with clinical risk factors.

RESULTS

We used comprehensive expression profiling of a training cohort of LNM-positive and LMN-negative serum specimens to identify an optimized transcriptomic panel of 4 miRNAs (miR-181b, miR-193b, miR-195, and miR-411) and 5 mRNAs (AMT, forkhead box A1 [FOXA1], polymeric immunoglobulin receptor [PIGR], matrix metalloproteinase 1 [MMP1], and matrix metalloproteinase 9 [MMP9]), which robustly identified patients with LNM (area under the curve [AUC], 0.86; 95% confidence interval [CI], 0.72-0.94). We validated panel performance in an independent validation cohort (AUC, 0.82; 95% CI, 0.74-0.88). Our risk-stratification model was more accurate than the panel and an independent predictor for identification of LNM (AUC, 0.90; univariate: odds ratio [OR], 37.17; 95% CI, 4.48-308.35; P < .001; multivariate: OR, 17.28; 95% CI, 1.82-164.07; P = .013). The model limited potential overtreatment to only 18% of all patients, which is dramatically superior to pathologic features that are currently used (92%).

CONCLUSIONS

A novel risk-stratification model for noninvasive identification of T1 CRC has the potential to avoid unnecessary operations for patients classified as high-risk by conventional risk-classification criteria.

Preoperative Predictors of Lymph Node Metastasis in Colon Cancer

Background

Lymph node metastasis (LNM) is a well-established prognostic factor for colon cancer. Preoperative LNM evaluation is relevant for planning colon cancer treatment. The aim of this study was to construct and evaluate a nomogram for predicting LNM in primary colon cancer according to pathological features.

Patients and Methods

Six-hundred patients with clinicopathologically confirmed colon cancer (481 cases in the training set and 119 cases in the validation set) were enrolled in the Affiliated Cancer Hospital of Guangxi Medical University from January 2010 to December 2019. The expression of molecular markers (p53 and β-catenin) was determined by immunohistochemistry. Multivariate logistic regression was used to screen out independent risk factors, and a nomogram was established. The accuracy and discriminability of the nomogram were evaluated by consistency index and calibration curve.

Results

Univariate logistic analysis revealed that LNM in colon cancer is significantly correlated (P <0.05) with tumor size, grading, stage, preoperative carcinoembryonic antigen (CEA) level, and peripheral nerve infiltration (PNI). Multivariate logistic regression analysis confirmed that CEA, grading, and PNI were independent prognostic factors of LNM (P <0.05). The nomogram for predicting LNM risk showed acceptable consistency and calibration capability in the training and validation sets.

Conclusions

Preoperative CEA level, grading, and PNI were independent risk factor for LNM. Based on the present parameters, the constructed prediction model of LNM has potential application value.

The correlation between tumor size, lymph node status, distant metastases and mortality in rectal cancer patients without neoadjuvant therapy

Tumor size has an effect on decision making for the treatment rectal cancer. Transanal local excision can be selected to remove rectal cancer with favorable histopathological features. It is generally recognized that the risk of lymph node involvement and distant metastases increases as the tumor enlarges. However, the majority of the studies classified patients into two groups using concrete value as a cutoff point. The coarse classification was not sufficient to reveal a correlation between the tumor size and lymph node status or distant metastases across the full range of sizes examined. Between 1988 and 2015, a total of 77,746 patients were diagnosed with first primary rectal cancer who had not received neoadjuvant therapy. These subjects were identified using the Surveillance, Epidemiology and End Results (SEER) database. The association between tumor size, lymph node status, distant metastases and cancer-specific mortality was investigated. Tumor size was examined as a continuous (1-30 mm) and categorical variable (11 size groups; 10-mm intervals). A non-linear correlation between increasing tumor size and the prevalence of lymph node involvement was observed, while a near-positive correlation between tumor size and distant metastases was presented. In addition, the 5-year and 10-year rates of rectal cancer-specific mortality were increased as the tumor enlarged. For small tumors (under 30 mm), a positive correlation was noted between tumor size and lymph node involvement. The clinical value of the tumor size should be reevaluated by exact classification.

Recursive Partitioning Analysis for Local Control Achieved With Stereotactic Body Radiation Therapy for the Liver, Spine, or Lymph Nodes

Purpose

This study aims to develop a local control risk stratification using recursive partitioning analysis (RPA) for patients receiving stereotactic body radiation therapy (SBRT) for metastatic cancer.

Methods and Materials

A single institutional database of 397 SBRT treatments to the liver, spine, and lymph nodes was constructed. All treatments required imaging follow-up to assess for local control. Cox proportional hazards analysis was implemented before the decision tree analysis. The data were split into training (70%), validation (10%), and testing (20%) sets for RPA to optimize the training set.

Results

In the study, 361 treatments were included in the local control analysis. Two-year local control was 71%. A decision tree analysis was used and the resulting model demonstrated 93.10% fidelity for the validation set and 87.67% for the test set. RPA class 3 was composed of patients with non-small cell lung cancer (NSCLC) primary tumors and treatment targets other than the cervical, thoracic, and lumbar spines. RPA class 2 included patients with primary cancers other than NSCLC or breast and treatments targets of the sacral spine or liver. RPA class 1 consisted of all other patients (including lymph node targets and patients with primary breast cancer). Classes 3, 2, and 1 demonstrated 3-year local controls rates of 29%, 50%, and 83%, respectively. On subgroup analysis using the Kaplan-Meier method, treatments for lymph nodes and primary ovarian disease demonstrated improved local control relative to other treatment targets (P < .005) and primary disease sites (P < .005), respectively.

Conclusions

A local control risk stratification model for SBRT to sites of metastatic disease was developed. Treatment target and primary tumor were identified as critical factors determining local control. NSCLC primary lesions have increased local failure for targets other than the cervical, thoracic, or lumbar spines, and improved local control was identified for lymph node sites and breast or ovarian primary tumors.

Histological grades of rectal cancer: whole-volume histogram analysis of apparent diffusion coefficient based on reduced field-of-view diffusion-weighted imaging

Background

To explore the role of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) technique in discriminating histological grades of rectal carcinoma.

Methods

Altogether, 49 patients with rectal cancer were enrolled in this retrospective study. All patients received preoperative 3.0 T MR scan. Histogram parameters from rFOV DWI were calculated and correlated with histological differentiation of rectal cancer. The parameters were compared between different histological grades of rectal cancer by independent Student's t-test or Man-Whitney U-test. The Spearman correlation test analyzed correlations between histological grade and histogram parameters. The diagnostic performance of individual parameters for distinguishing poorly from well-/moderately differentiated tumors was assessed by receiver operating characteristic curve (ROC) analysis.

Results

There were significant differences for ADCmean, 25^th, 50^th, 75^th, 90^th, 95^th percentiles, skewness, and kurtosis of rFOV DWI sequence between well-, moderately, and poorly differentiated rectal cancers (P<0.05). Significant correlations were noted between histological grades and the above histogram parameters (r=0.679, 0.540, 0.701, 0.730, 0.669, 0.574, -0.730, and -0.760 respectively, P<0.001). Among the individual histogram parameter, kurtosis achieved the highest AUC of 0.882 with an optimal cutoff value of 1.934 in distinguishing poorly from well-/moderately differentiated rectal cancers. The combination of ADCmean, 75^th percentile, and kurtosis yielded the highest AUC of 0.927 with a sensitivity of 88.00% and a sensitivity of 91.7% using logistic regression.

Conclusions

Quantitative whole-lesion ADC histogram analysis based on the rFOV DWI technique could help differentiate histological grades of rectal cancer. The combination of ADCmean, 75^th percentile, and kurtosis may be the best choice.

Executive Summary of the American Radium Society Appropriate Use Criteria for Local Excision in Rectal Cancer

The goal of treatment for early stage rectal cancer is to optimize oncologic outcome while minimizing effect of treatment on quality of life. The standard of care treatment for most early rectal cancers is radical surgery alone. Given the morbidity associated with radical surgery, local excision for early rectal cancers has been explored as an alternative approach associated with lower rates of morbidity. The American Radium Society Appropriate Use Criteria presented in this manuscript are evidence-based guidelines for the use of local excision in early stage rectal cancer that include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) used by a multidisciplinary expert panel to rate the appropriateness of imaging and treatment procedures. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment. These guidelines are intended for the use of all practitioners and patients who desire information regarding the use of local excision in rectal cancer.

Population-based analysis on predictors for lymph node metastasis in T1 colon cancer

Background

In this study, we aimed to identify independent predictive factors for lymph node metastasis (LNM) in T1 colon cancer.

Methods

Data of 8056 eligible patients were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database during 2004–2012. We performed logistic regression analysis to identify predictive factors for LNM. Both unadjusted and adjusted Cox regression analyses were used to determine the association between LNM and patient survival. Finally, we used competing risks analysis and the cumulative incidence function (CIF) to further confirm the prognostic role of LNM in cancer-specific survival (CSS).

Results

The overall risk of LNM in patients with T1 colon cancer was 12.0% (N = 967). Adjusted logistic regression models revealed that mucinous carcinoma [odds ratio (OR) = 2.26, P < 0.001], moderately differentiated (OR 1.74, P < 0.001), poorly differentiated (OR 5.16, P < 0.001), and undifferentiated carcinoma (OR 3.01, P = 0.003); older age (OR 0.66, P < 0.001 for age 65–79 years, OR 0.44, P < 0.001 for age over 80 years); and carcinoma located in the ascending colon (OR 0.77, P = 0.018) and sigmoid colon (OR 1.24, P = 0.014) were independent predictive factors for LNM. Adjusted Cox regression analysis showed that positive lymph node involvement was significantly associated with CSS [hazard ratio (HR) = 3.02, P < 0.001], which was further robustly confirmed using a competing risks model and the CIF.

Conclusions

This population-based study showed that mucinous carcinoma, tumor grade, age, and primary tumor location were independent predictive factors for LNM in T1 colon cancer. The risk of LNM should be carefully evaluated in patients with T1 colon cancer, before clinical management.

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

OBJECTIVE

This study aimed to assess the incidence, identify independent factors, and develop a lymph node metastasis (LNM) prediction model for patients with T1 colon cancer.

METHODS

Statistics were drawn from the Surveillance, Epidemiology, and End Results database between 2004 and 2014. A multivariate logistic regression analysis was performed to determine independent predictors of LNM. A nomogram for predicting the possibility of LNM was developed based on those factors.

RESULTS

A total of 5397 patients with T1 colon cancer were identified. The overall LNM rate was 15.0% (808/5397). A multivariate analysis showed that age (odds ratio [OR] 0.97, P < 0.001), tumor size (OR 1.01, P < 0.001), moderate (OR 1.77, P = 0.001) or poorly differentiated/undifferentiated tumor (OR 5.60, P < 0.001), right colon cancer (OR 1.39, P = 0.008), and a positive carcinoembryonic antigen level (OR 1.51, P = 0.004) were independent predictive factors for LNM. The area under the receiver operating characteristic curve was 0.68 (95% confidence interval [CI] 0.65-0.71) in the training set and 0.65 (95% CI 0.61-0.67) in the validation set. A calibration plot showed good consistency between the bias-corrected prediction and the ideal reference line with 1000 additional bootstraps (mean absolute error = 0.007).

CONCLUSIONS

The incidence of LNM was high in patients with T1 colon cancer. A nomogram for predicting the probability of LNM for T1 colon cancer may be used to help determine the optimal treatment for these patients.

Long-term oncological outcomes of local excision versus radical resection for early colorectal cancer in young patients without preoperative chemoradiotherapy: a population-based propensity matching study

The incidence and mortality of colorectal carcinoma are rising in young adults. This population-based propensity matching study aimed to compare long-term oncological outcomes of local excision with radical resection for early localized colorectal cancer (CRC) in young patients without preoperative chemoradiotherapy. Patients under 45 years old with T1 colon or rectal adenocarcinoma who underwent local excision or radical resection were included from the Surveillance, Epidemiology, and End Results (SEER) database between 1998 and 2014. Survival curves were plotted using the Kaplan-Meier method. Cancer-specific survival (CSS) was compared using adjusted hazard ratios (HRs) between local excision and radical resection. After propensity score matching procedure, total of 1719 patients were included in the analysis, among which 573 treated with local excision and 1146 treated with radical resection. The median follow-up was 80 months (interquartile range(IQR): 37-132), with 1074 patients followed for ≥5 years and 508 patients followed for ≥10 years. Five-year CSS of local excision versus radical resection was 93.4% versus 96.7% for colon cancer and 96.6% versus 98.4% for rectal cancer. Ten-year CSS of local excision versus radical resection was 91.4% versus 94.0% for colon cancer and 92.8% versus 96.7% for rectal cancer. On multivariable analysis, compared with radical resection, local excision was not associated with inferior CSS for colon (HR 1.74, 95% CI: 0.92-3.29, P = 0.090) and rectal cancer (HR 2.16, 95% CI: 0.99-4.71, P = 0.052). There is no evidence of differential long-term oncological outcomes between local excision and radical resection. These findings supported clinical application of local excision for early colon and rectal cancer in young adults.

A MicroRNA Signature Associated With Metastasis of T1 Colorectal Cancers to Lymph Nodes

Most T1 colorectal cancers treated by radical surgery can now be cured by endoscopic submucosal dissection. Although 70%-80% of T1 colorectal cancers are classified as high risk, <16% of these patients actually have lymph node metastases. Biomarkers are needed to identify patients with T1 cancers with the highest risk of metastasis, to prevent unnecessary radical surgery. We collected data from The Cancer Genome Atlas and identified 5 microRNAs (MIR32, MIR181B, MIR193B, MIR195, and MIR411) with significant changes in expression in T1 and T2 colorectal cancers with vs without lymph node metastases. Levels of the 5 microRNAs identified patients with lymph node invasion by T1 or T2 cancers with an area under the receiver operating characteristic curve (AUROC) value of 0.84. We validated these findings in 2 cohorts of patients with T1 cancers, using findings from histology as the reference. The 5-microRNA signature identified T1 cancers with lymph node invasion in cohort 1 with an AUROC value of 0.83, and in cohort 2 with an AUROC value of 0.74. When we analyzed biopsy samples from untreated patients, the 5-microRNA signature identified cancers with lymph node metastases with an AUROC value of 0.77. The 5-microRNA therefore identifies high-risk T1 colorectal cancers with a greater degree of accuracy than currently used pathologic features.

Management of complex polyps of the colon and rectum

PUPRPOSE

Benign polyps that are technically challenging and unsafe to remove via polypectomy are known as complex polyps. Concerns regarding safety and completeness of resection dictate they undergo advanced endoscopic techniques, such as endoscopic mucosal resection or surgery. We provide a comprehensive overview of complex polyps and current treatment options.

METHODS

A review of the English literature was conducted to identifyarticles describing the management of complex polyps of the colon and rectum.

RESULTS

Endoscopic mucosal resection is the standard of care for the majority of complex polyps. Only polyps that fail endoscopic mucosal resection or are highly suspicious of invasive cancer but which cannot be removed endoscopically warrant surgery.

CONCLUSION

Several factors influence the treatment of a complex polyp; therefore, there cannot be a "one-size-fitsall" approach. Treatment should be tailored to the lesion's characteristics, the risk of adverse events, and the resources available to the treating physician.

Prognostic factors of overall survival and cancer-specific survival in patients with resected early-stage rectal adenocarcinoma: a SEER-based study

The benefits of radiotherapy for colorectal cancer are well documented, but the impact of adjuvant radiotherapy on early-stage rectal adenocarcinoma remains unclear. This study aimed to identify predictors of overall survival (OS) and cancer-specific survival (CSS) in patients with stage II rectal adenocarcinoma treated with preoperative or postoperative radiation therapy. Patients with early-stage rectal adenocarcinoma in the postoperative state were identified using the Surveillance, Epidemiology, and End Results database. The primary endpoints were OS and overall CSS. Stage IIA patients without radiotherapy had significantly lower OS and CSS compared with those who received radiation before or after surgery. Stage IIB patients with radiotherapy before surgery had significantly higher OS and CSS compared with patients in the postoperative or no radiotherapy groups. Patients with signet ring cell carcinoma had the poorest OS among all the groups. Multivariable analysis showed that ethnicity (HR, 0.388, p=0.006) and radiation before surgery (HR, 0.614, p=0.006) were favorable prognostic factors for OS, while age (HR, 1.064, p<0.001), race (HR, 1.599, p=0.041), stage IIB (HR, 3.011, p=0.011), and more than one tumor deposit (TD) (HR, 2.300, p=0.001) were unfavorable prognostic factors for OS. Old age (HR, 1.047, p<0.00 L), stage IIB (HR, 8.619, p=0.005), circumferential resection margin between 0.1 mm and 10 mm (HR, 1.529, p=0.039), and more than one TD (HR, 2.688, p=0.001) were unfavorable prognostic factors for CSS. This population-based study identified predictors of OS and CSS in patients with early-stage resected rectal adenocarcinoma, which may help to guide future management of this patient population.

Local Excision of Rectal Cancer

Local excision (LE) of early-stage rectal cancer avoids the morbidity associated with radical surgery but has historically been associated with inferior oncologic outcomes. Newer techniques, including transanal endoscopic microsurgery (TEM) and transanal minimally invasive surgery (TAMIS), have been developed to improve the quality of LE and extend the benefits of LE to tumors in the more proximal rectum. This article provides an overview of conventional LE, TEM, and TAMIS techniques, including indications for their use and pertinent literature on their associated outcomes for rectal cancer.