Prognostic significance of adjuvant radiation therapy in adenocarcinoma of the cecum

Optimal treatment strategy and prognostic analysis for patients with non-metastatic pT4 colon adenocarcinoma

Objective

This study endeavored to explore the optimal treatment strategy and conduct a prognostic analysis for patients diagnosed with pT4M0 (pathologic stage T4) colon adenocarcinoma (COAD).

Methods and materials

A total of 8,843 patients diagnosed with pT4M0 COAD between January 2010 and December 2015 were included in this study from the Surveillance, Epidemiology, and End Results (SEER) database. These patients were randomly divided into a training set and an internal validation set using a 7:3 ratio. Variables that demonstrated statistical significance (P<0.05) in univariate COX regression analysis or held clinical significance were incorporated into the multivariate COX regression model. Subsequently, this model was utilized to formulate a nomogram. The predictive accuracy and discriminability of the nomogram were assessed using the C-index, area under the curve (AUC), and calibration curves. Decision curve analysis (DCA) was conducted to confirm the clinical validity of the model.

Results

In the entire SEER cohort, the 3-year overall survival (OS) rate (74.22% vs. 63.20%, P<0.001) and the 3-year cancer-specific survival (CSS) rate (76.25% vs. 66.98%, P<0.001) in the surgery combined with postoperative adjuvant therapy (S+ADT) group surpassed those in the surgery (S) group. Multivariate COX regression analysis of the training set unveiled correlations between age, race, N stage, serum CEA (carcinoembryonic antigen), differentiation, number of resected lymph nodes, and treatment modalities with OS and CSS. Nomograms for OS and CSS were meticulously crafted based on these variables, achieving C-indexes of 0.692 and 0.690 in the training set, respectively. The robust predictive ability of the nomogram was further affirmed through receiver operating characteristic (ROC) and calibration curves in both the training and validation sets.

Conclusion

In individuals diagnosed with pT4M0 COAD, the integration of surgery with adjuvant chemoradiotherapy demonstrated a substantial extension of long-term survival. The nomogram, which incorporated key factors such as age, race, differentiation, N stage, serum CEA level, tumor size, and the number of resected lymph nodes, stood as a dependable tool for predicting OS and CSS rates. This predictive model held promise in aiding clinicians by identifying high-risk patients and facilitating the development of personalized treatment plans.

A nomogram for predicting cause-specific mortality among patients with cecal carcinoma: a study based on SEER database

OBJECTIVE

Classical Cox proportional hazard models tend to overestimate the event probability in a competing risk setup. Due to the lack of quantitative evaluation of competitive risk data for colon cancer (CC), the present study aims to evaluate the probability of CC-specific death and construct a nomogram to quantify survival differences among CC patients.

METHODS

Data on patients diagnosed with CC between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database. Patients were divided into a training dataset for the establishment of the model and a validation dataset to evaluate the performance the model at a ratio of 7:3. To evaluate the ability of multiple variables to predict cause-specific death in CC patients, univariate and multivariate analyses with Fine-Gray models were performed to screen the predictors of cause-specific death, and a nomogram for predicting cause-specific mortality was constructed. Then, the receiver operating characteristic (ROC) curve and the calibration curve were plotted to evaluate the prognostic performance of the nomogram.

RESULTS

The dataset was randomly divided into a training (n = 16,655) dataset and a validation (n = 7,139) dataset at a ratio of 7:3. In the training dataset, variables including pathological subtypes of tumors, pathological grading (degree of differentiation), AJCC staging, T-staging, surgical type, lymph node surgery, chemotherapy, tumor deposits, lymph node metastasis, liver metastasis, and lung metastasis were identified as independent risk factors for cause-specific death of CC patients. Among these factors, the AJCC stage had the strongest predictive ability, and these features were used to construct the final model. In the training dataset, the consistency index (C-index) of the model was 0.848, and the areas under the receiver operating characteristic curve (AUC) at 1, 3, and 5 years was 0.852, 0.861, and 0.856, respectively. In the validation dataset, the C-index of the model was 0.847, and the AUC at 1 year, 3 years, and 5 years was 0.841, 0.862, and 0.852, respectively, indicating that this nomogram had an excellent and robust predictive performance.

CONCLUSION

This study can help clinical doctors make better clinical decisions and provide better support for patients with CC.

Postoperative locoregional recurrence pattern and treatment management of stage pT4 sigmoid colon cancer: a retrospective cohort study

BACKGROUND

This study aimed to explore the pattern of locoregional recurrence after surgery in patients with non-metastatic stage pT4 sigmoid colon cancer and the role of adjuvant radiotherapy on survival.

METHODS

We retrospectively analyzed data from 208 patients who underwent surgery in our hospital. The patients were randomly divided into training and validation groups at a 1:1 ratio. Patients at high risk for locoregional recurrence were screened using Cox regression analysis. Based on the data of 2,886 patients in the Surveillance, Epidemiology, and End Results (SEER) database, the effect of adjuvant radiotherapy on overall survival (OS) and cancer-specific survival (CSS) was evaluated by Kaplan-Meier curves.

RESULTS

Of the 208 patients, 57 (27.4%) presented with locoregional recurrences (14 anastomotic and 43 abdominal or pelvic lymph node recurrences). Multivariate analysis showed that serum CEA, differentiation, lymph node dissection number, and N stage were independent predictors of locoregional recurrence-free survival (all p < 0.05). A risk-stratification model was constructed, and a total score of ≥ 6.5 points was considered the high-risk group for locoregional recurrence. Both the training and validation sets presented that the model had a good predictive ability (area under the curve = 0.828 and 0.724, respectively). Analysis of SEER data revealed that adjuvant radiotherapy significantly prolonged OS and CSS in the high-risk population (all p < 0.05, vs. no radiotherapy).

CONCLUSIONS

Patients with a total risk score of 6.5 or more had a high likelihood of locoregional recurrence, and perhaps adjuvant radiotherapy could improve their survival.

Prognostic analysis and beneficiary identification of adjuvant external beam radiotherapy for stage pT4b sigmoid colon cancer

The clinical efficacy of adjuvant radiotherapy in sigmoid colon cancer remains questioned. To evaluate the clinical efficacy of adjuvant external beam radiotherapy (EBRT) for patients with pathologic stage T4b sigmoid colon cancer. Patients with stage pT4b sigmoid colon cancer receiving adjuvant EBRT or not followed by surgery between 2004 and 2016 were extracted from the Surveillance, Epidemiology, and End Results database. Analysis of overall survival (OS) was performed using Kaplan-Meier curves and prognostic factors were identified using Cox proportional hazards regression models with 95% confidence intervals within the entire cohort. A risk-stratification system was then developed based on the β regression coefficient. Among 2073 patients, 284 (13.7%) underwent adjuvant EBRT. The median OS in the group receiving adjuvant EBRT was significantly longer than that in the non-radiotherapy group (p < 0.001). Age, serum carcinoembryonic antigen (CEA) level, perineural invasion, lymph node dissection (LND) number, and adjuvant EBRT were independent factors associated with OS. A risk-stratification system was generated, which showed that low-risk patients had a higher 5-year survival rate than high-risk patients (75.6% vs. 42.3%, p < 0.001). Adjuvant EBRT significantly prolonged the 5-year survival rate of high-risk patients (62.6% vs. 38.3%, p = 0.009) but showed no survival benefit among low-risk patients (87.7% vs. 73.2%, p = 0.100). Our risk-stratification model comprising age, serum CEA, perineural invasion, and LND number predicted the outcomes of patients with stage pT4b sigmoid colon cancer based on which subgroup of high-risk patients should receive adjuvant EBRT.

Assessing the Effect of Radiotherapy in Addition to Surgery in Colon Adenocarcinomas: a Systematic Review and Meta-analysis of Contemporary Evidence

PURPOSE

This study aims to review the contemporary evidence investigating radiotherapy (RT) in addition to surgery for colon adenocarcinomas.

METHODS

We searched the following databases: PubMed, Science Direct, Scopus, ASCOpubs, the Cochrane Library, and Google Scholar. Studies (since January 2005) comparing outcomes of high-risk colon adenocarcinomas who underwent RT in addition to surgery versus no RT were eligible. Pooling of outcomes from published results or from analysis of survival curves was done. Subgroup analysis was conducted to determine if the efficacy of RT varies with RT timing.

RESULTS

Eight studies were included (five retrospective cohorts, three population-based studies). Pooled analysis from retrospective cohorts showed a reduction in 5-year LR (OR 0.41; 95% CI 0.21-0.79; p = 0.007) in the RT group. A benefit in 3-year (OR 1.81; 95% CI 1.15-2.87; p = 0.01) and 5-year (OR 2.10; 95% CI 1.21-3.63; p = 0.008) DFS and in 3-year (OR 2.55; 95% CI 1.43-4.54; p = 0.001) and 5-year (OR 2.00; 95% CI 1.17-3.41; p = 0.01) OS was seen in the RT group. The OS benefit was demonstrated in the subgroup analysis of neoadjuvant RT, but not with adjuvant RT. The improvement in OS with neoadjuvant RT was supported by a population-based study from NCDB, while results from two population-based studies investigating adjuvant RT were conflicting.

CONCLUSION

Taking into account the limitations of the studies, our review of evidence suggests a possible role of RT in improving oncologic outcomes of select colon adenocarcinomas. Prospective studies are needed to definitively assess the value of RT for colon cancer.

Competitive Risk Analysis of Prognosis in Patients With Cecum Cancer: A Population-Based Study

Background:

The presence of competing risks means that the results obtained using the classic Cox proportional-hazards model for the factors affecting the prognosis of patients diagnosed with cecum cancer (CC) may be biased.

Objective:

The purpose of this study was to establish a competitive risk model for patients diagnosed with CC to evaluate the relevant factors affecting the prognosis of patients, and to compare the results with the classical COX proportional risk model.

Methods:

We extracted data on patients diagnosed with CC registered between 2004 and 2016 in the Surveillance, Epidemiology, and End Results (SEER) database. The univariate analysis utilized the cumulative incidence function and Gray’s test, while a multivariate analysis was performed using the Fine-Gray, cause-specific (CS), and Cox proportional-hazards models.

Results:

The 54463 eligible patients diagnosed with CC included 24387 who died: 12087 from CC and 12300 from other causes. The multivariate Fine-Gray analysis indicated that significant factors affecting the prognosis of patients diagnosed with CC include: age, race, AJCC stage, differentiation grade, tumor size, surgery, radiotherapy, chemotherapy and regional lymph nodes metastasis. Due to the presence of competitive risk events, COX model results could not provide accurate estimates of effects and false-negative results occurred. In addition, COX model misestimated the direction of association between regional lymph node metastasis and cumulative risk of death in patients diagnosed with CC. Competitive risk models tend to be more advantageous when analyzing clinical survival data with multiple endpoints.

Conclusions:

The present study can help clinicians to make better clinical decisions and provide patients diagnosed with CC with better support.

Nonmucinous adenocarcinoma of the cecum presenting as appendicitis complicated by hepatic abscess

A 59-year-old man presenting with right upper quadrant pain was found to have hepatic abscesses on CT imaging. After draining the abscess, a repeat CT 3 weeks later indicated that the cause of the hepatic abscesses was appendicitis. Upon surgical resection of the base of the cecum and appendix, an adenocarcinoma was demonstrated along the cecal wall both invading and occluding the appendix. The patient was initially treated for complications of appendicitis, but this case indicates the importance of considering additional etiologies for complex appendicitis. This case report provides a pathology-proven case of well-differentiated, nonmucinous adenocarcinoma of the cecum presenting as a complication of appendicitis and discusses standard treatment options. This case report also reviews the pathophysiological aspects of hepatic abscess as a complication of appendicitis as well as the importance of considering malignancy in a patient presenting with complications of appendicitis.