Pulmonary metastasis in newly diagnosed colon-rectal cancer: a population-based nomogram study

Assessing the Therapeutic Value of Primary Tumor Resection in Colorectal Cancer Lung Metastases: A Dynamic Visualization Clinical Tool Constructed Based on the SEER Database

BACKGROUND

The efficacy of primary tumor resection (PTR) for colorectal cancer lung metastases (CRLM) is unclear. This study used the SEER database to investigate if PTR improves prognosis in CRLM patients and developed a nomogram to predict the likelihood of benefiting from PTR.

METHODS

Patients with CRLM from the SEER database (2010-2019) were included. Propensity score matching (PSM) balanced PTR and non-PTR groups. Kaplan-Meier analysis compared overall and cancer-specific survival. Cox regression identified survival factors. The PTR group was divided into training and validation sets (7:3 ratio) for nomogram development using logistic regression. Nomogram performance was validated using ROC curves, calibration curves, and decision curve analysis.

RESULTS

A total of 3264 CRLM patients were included (2459 with PTR, 805 without). After 1:1 PSM, each group had 484 patients. PTR significantly improved survival (p < 0.001). Logistic regression identified age, race, T-stage, chemotherapy, and metastases to the liver, brain, and bone as risk factors. The nomogram showed excellent predictive performance and clinical utility.

CONCLUSION

PTR improves survival in CRLM patients, and the nomogram effectively predicts the benefit of PTR.

Explainable machine learning for predicting lung metastasis of colorectal cancer

Patients with lung metastasis of colorectal cancer typically have a poor prognosis. Therefore, establishing an effective screening and diagnosis model is paramount. Our study seeks to construct and verify a predictive model utilizing machine learning (ML) that can evaluate the risk of lung metastasis with newly diagnosed colorectal cancer (CRC) using Shapley Additive exPlanations (SHAP). Using the Surveillance, Epidemiology, and End Results database, 39,674 were extracted for model development, all of whom had been pathologically diagnosed with CRC. The data spans from 2010 to 2015. Our study has constructed seven ML algorithms based on the data mentioned above, including Random Forest (RF), Decision Tree, Support Vector Machine, Naive Bayes, K-Nearest Neighbor, eXtreme Gradient Boosting, and Gradient Boosting Machine. We selected the best algorithm and visualized it using SHAP. We conducted a validation of the model utilizing data from a Chinese hospital to assess its practicality. Based on this, we have constructed an open web calculator. 39,674 patient data were included in our study, among whom 1369 (3.5%) presented with distant lung metastasis. The Random Forest (RF) algorithm demonstrated the highest predictive capability within the internal test set (AUC of 0.980, AUPR of 0.941). Furthermore, the random forest algorithm also exhibited excellent performance in external validation sets. Meanwhile, we have also established a web calculator ( http://121.43.117.60:8003/ ). The RF algorithm has demonstrated excellent predictive performance. It can assist clinicians in devising more personalized treatment plans.

TIPE Inhibits Ferroptosis in Colorectal Cancer Cells by Regulating MGST1/ALOX5

TIPE is a protein highly expressed in various cancers that promotes ferroptosis in colorectal cancer cells. Ferroptosis is a nonapoptotic cell death caused by lipid peroxidation, and microsomal glutathione transferase 1 (MGST1) is a critical enzyme that resists lipid peroxidation. This study explored how TIPE regulates MGST1 expression to inhibit ferroptosis and promote colorectal cancer proliferation. TIPE was highly expressed in colorectal cancer tissues and positively correlated with the proliferation of human colorectal cancer cells. We measured levels of reactive oxygen species and lipid reactive oxygen species in colorectal cancer cells with differential expression of TIPE and detected ferroptosis using transmission electron microscopy. Bioinformatics analysis revealed a positive correlation of expression patterns between TIPE and MGST1 in colorectal cancer. TIPE regulated the expression of MGST1 by activating the phosphorylation of ERK1/2. Coimmunoprecipitation revealed binding between MGST1 and ALOX5. This binding inhibited the phosphorylation of ALOX5, inhibiting ferroptosis and promoting the proliferation of colorectal cancer cells. A tumor formation experiment in nude mice supported our findings that TIPE regulates the proliferation of colorectal cancer by regulating ferroptosis. Implications: TIPE inhibits colorectal cancer ferroptosis via an MGST1-ALOX5 interaction to promote colorectal cancer proliferation. These findings suggest future colorectal cancer treatment strategies.

Complete blood counts as potential risk factors of early dissemination to liver and lungs in resected colorectal cancer: a retrospective cohort study

PURPOSE

Liver and lung metastases demonstrate distinct biological, particularly immunological, characteristics. We investigated whether preoperative complete blood count (CBC) parameters, which may reflect the immune system condition, predict early dissemination to the liver and lungs in colorectal cancer (CRC).

METHODS

In this retrospective single-centre study, we included 268 resected CRC cases with complete 2-year follow-up and analysed preoperative CBC for association with early liver or lung metastasis development. Next, selected CBC and clinicopathological parameters were analysed with uni- and multivariable Cox regression. Independent factors affecting liver or lung metastasis-free survival were incorporated into composite scores, which were further evaluated with receiver operating characteristic (ROC) curves and dichotomised using a modified, specificity-focused, Youden approach to identify particularly high-risk patients.

RESULTS

Compared to metastasis-free patients, early liver metastases were related to decreases in red blood cells, haematocrit, lymphocytes and elevated monocyte-to-lymphocyte ratio, while lung metastases to lower eosinophil counts. A composite score of independent factors (erythrocytopenia, lower lymphocyte count and pN) yielded HR of 8.01 (95% CI 3.45-18.57, p < 0.001) for liver-specific metastasis-free survival (MFS). For lung-specific MFS, the combination of eosinopenia, pN and primary tumour location showed HR of 13.69 (95% CI 4.34-43.20, p < 0.001).

CONCLUSION

Early CRC metastases to the liver and lungs are associated with partially divergent clinicopathological and peripheral blood features. We propose simple, clinically implementable scores, based on routinely assessed parameters, to identify patients with an increased risk of early dissemination to the liver or lungs. After validation in independent cohorts, these scores may provide easily available prognostic information.

Gangrene Secondary to Perineal Invasion by Rectal Cancer: A Case Report and Literature Review

Colorectal cancer usually metastasizes through lymphatic, blood, and intraperitoneal implantation. However, rectal cancer combined with perineal invasion after treated with chemotherapy is very rare. The present case study is of a 53-year-old male patient with a history of rectal cancer who developed a recto-perineal fistula with redness, swelling, and pain in the scrotum after repeated chemotherapy. After a CT examination and investigative observation, the patient was diagnosed with a recto-perineal fistula. After surgical debridement and postoperative implant treatment, the patient's infection resolved, and the skin-grafting treatment worked well. The present case called attention to rectal cancer after being treated with chemotherapy.

A prediction model for lung metastases in patients with indeterminate pulmonary nodules in newly diagnosed colorectal cancer

INTRODUCTION

Multidisciplinary teams treating patients with newly diagnosed Colorectal Cancer (CRC) often encounter the appearance of Indeterminate Pulmonary Nodules (IPNs) that warrants follow-up with repetitive medical imaging and anxiety for patients. We determined the incidence of IPNs in patients with newly diagnosed CRC and developed and validated a model for individualized risk prediction of IPNs being lung metastases.

MATERIAL AND METHODS

Newly diagnosed CRC who underwent surgery between November 2011 to June 2014 were included to create the risk model, developed using both clinical experience and statistical selection. Discrimination and calibration slopes of the risk score were evaluated in an independent temporal validation sample. A nomogram is presented to assist clinicians in estimating an individual risk score.

RESULTS

Out of 2111 CRC patients staged with chest CT, 204 (9.6%) had IPNs and 54/204 (26%) had lung metastases. We identified 4 predictors: "location of primary tumour", "pathological nodal stage", "size of the largest nodule" and "extrapulmonary synchronous metastases at diagnosis". Discrimination of the final model in the validation sample was demonstrated by the difference in mean predicted risk between progressed cases en non-progressed cases (49% versus 21%, p = <0.001).

CONCLUSION

A prediction model with 4 clinical risk factors can be used to assist multidisciplinary teams in the prediction of individualized risk of lung metastases and imaging strategy in patients with IPNs and newly diagnosed colorectal cancer. The model performed well in new patients not included in the model development.

Pulmonary Metastasis as the First Site of Metastasis After Curative Surgery for Colon Cancer: Incidence and Risk Factors According to the TNM Stage

BACKGROUND

The lungs are one of the most common sites for colon cancer metastasis. A few studies reported that approximately 2% to 10% of patients with colon cancer developed pulmonary metastasis. However, among these studies, patient characteristics were heterogeneous, and information on pulmonary metastasis incidence by the TNM stage was scarce.

OBJECTIVE

This study evaluated the incidence of pulmonary metastasis in colon cancer without synchronous metastasis treated with radical surgery and identified risk factors for pulmonary metastasis according to the TNM stage.

DESIGN AND SETTINGS

This retrospective study included all patients with colon cancer without metastasis who underwent radical surgery for primary tumor at Samsung Medical Center between January 2007 and December 2016.

PATIENTS

A total of 4889 patients who underwent radical surgery for stage I and III colon cancer were included.

MAIN OUTCOME MEASURES

The main outcome measures were the incidence of pulmonary metastasis and overall survival.

RESULTS

A total of 156 patients (3.2%) were diagnosed with pulmonary metastasis after a median of 16 months from the time of radical surgery for colon cancer to detection of pulmonary metastasis. The pulmonary metastasis incidence rate by the TNM stage was 0.5% in stage I, 1.6% in stage II, and 6% in stage III. Risk factors for pulmonary metastasis were preoperative CEA >5 ng/mL, cancer obstruction, N stage, vascular invasion, perineural invasion, and adjuvant chemotherapy for primary colon cancer in multivariable analysis.

LIMITATION

This was a retrospective single-center study.

CONCLUSIONS

Preoperative CEA >5 ng/mL, cancer obstruction, pN stage, vascular invasion, perineural invasion, and receiving adjuvant chemotherapy for primary colon cancer were risk factors for pulmonary metastasis in colon cancer. Therefore, patients with risk factors for pulmonary metastasis should be recommended for intensive follow-up to detect lung metastases. See Video Abstract .

METSTASIS PULMONAR EN EL PRIMER SITIO TRAS CIRUGA CURATIVA DEL CNCER DE COLON INCIDENCIA Y FACTORES DE RIESGO SEGN ESTADIO TNM

ANTECEDENTES:Los pulmones son uno de los sitios más comunes de metástasis del cáncer de colon. Algunos estudios informaron que aproximadamente entre el 2% y el 10% de los pacientes con cáncer de colon desarrollaron metástasis pulmonar. Sin embargo, entre estos estudios, las características de los pacientes fueron heterogéneas y la información sobre la incidencia de metástasis pulmonares según el estadio TNM fue escasa.OBJETIVO:Este estudio evaluó la incidencia de metástasis pulmonar en cáncer de colon sin metástasis sincrónica tratada con cirugía radical e identificó factores de riesgo para metástasis pulmonar según el estadio TNM.DISEÑO Y AJUSTES:Este estudio retrospectivo incluyó a todos los pacientes con cáncer de colon sin metástasis que se sometieron a cirugía radical por tumor primario en el Samsung Medical Center entre enero de 2007 y diciembre de 2016.PACIENTES:Se incluyó un total de 4.889 pacientes sometidos a cirugía radical por cáncer de colon en estadio I-III.PRINCIPALES MEDIDAS DE RESULTADO:Las principales medidas de resultado fueron la incidencia de metástasis pulmonar y la supervivencia general.RESULTADOS:Un total de 156 pacientes (3,2%) fueron diagnosticados con metástasis pulmonar con una duración media de 16 meses desde el momento de la cirugía radical por cáncer de colon hasta la detección de la metástasis pulmonar. La tasa de incidencia de metástasis pulmonares por estadio TNM fue del 0,5% en el estadio I, del 1,6% en el estadio II y del 6% en el estadio III. Los factores de riesgo de metástasis pulmonar fueron CEA preoperatorio superior a 5 ng/ml, obstrucción por cáncer, estadio N, invasión vascular, invasión perineural y quimioterapia adyuvante para el cáncer de colon primario en un análisis multivariable.LIMITACIÓN:Este fue un estudio retrospectivo de un solo centro.CONCLUSIÓN:CEA preoperatorio superior a 5 ng/ml, obstrucción por cáncer, estadio pN, invasión vascular, invasión perineural y recibir quimioterapia adyuvante para el cáncer de colon primario fueron factores de riesgo de metástasis pulmonar en el cáncer de colon. Por lo tanto, se debe recomendar un seguimiento intensivo a los pacientes con factores de riesgo de metástasis pulmonares para detectar metástasis pulmonares. (Traducción-Dr Yolanda Colorado ).

Development and validation of an artificial intelligence prediction model and a survival risk stratification for lung metastasis in colorectal cancer from highly imbalanced data: A multicenter retrospective study

BACKGROUND

To assist clinicians with diagnosis and optimal treatment decision-making, we attempted to develop and validate an artificial intelligence prediction model for lung metastasis (LM) in colorectal cancer (CRC) patients.

METHODS

The clinicopathological characteristics of 46037 CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database and 2779 CRC patients from a multi-center external validation set were collected retrospectively. After feature selection by univariate and multivariate analyses, six machine learning (ML) models, including logistic regression, K-nearest neighbor, support vector machine, decision tree, random forest, and balanced random forest (BRF), were developed and validated for the LM prediction. In addition, stratified LM patients by risk score were utilized for survival analysis.

RESULTS

Extremely low rates of LM with 2.59% and 4.50% were present in the development and validation set. As the imbalanced learning strategy, the BRF model with an Area under the receiver operating characteristic curve (AUC) of 0.874 and an average precision (AP) of 0.184 performed best compares with other models and clinical predictor. Patients with LM in the high-risk group had significantly poorer survival (P＜0.001) and failed to benefit from resection (P = 0.125).

CONCLUSIONS

In summary, we have utilized the BRF algorithm to develop an effective, non-invasive, and practical model for predicting LM in CRC patients based on highly imbalanced datasets. In addition, we have implemented a novel approach to stratify the survival risk of CRC patients with LM based the output of the model.

Nomograms for predicting overall survival in colorectal cancer patients with metastasis to the liver, lung, bone, and brain

BACKGROUND

The aim of this study was to identify the heterogeneous and homogeneous prognostic factors associated with distant metastasis to the liver, lung, bone, and brain in colorectal cancer (CRC) patients and then construct nomograms to predict the prognosis.

METHODS

CRC patients registered in the surveillance, epidemiology, and end results database between 2010 and 2017 were included. A Cox regression model was used to analyse homogeneous and heterogeneous prognostic factors, and Kaplan‒Meier analysis was performed to estimate overall survival (OS). Predictive nomograms were constructed, and their performance was evaluated with C-indexes, calibration curves and the area under the receiver operating characteristic (ROC) curve (AUC).

RESULTS

A total of 37,641 patients with distant metastasis to the liver, lung, bone, and brain were included. The median survival times of patients with liver metastasis, lung metastasis, bone metastasis, and brain metastasis were 12.00 months (95% CI 11.73-12.27 months), 10.00 months (95% CI 9.60-10.41 months), 5.00 months (95% CI 4.52-5.48 months), and 3.00 months (95% CI 2.28-3.72 months), respectively. An older age, higher N stage, elevated carcinoembryonic antigen level, no surgery at the primary site and no/unknown treatment with chemotherapy were identified as homogeneous prognostic factors for the four types of metastases. The calibration curves, C-indexes and AUCs exhibited good performance for predicting the OS of patients with distant metastases to the liver, lung, bone, and brain.

CONCLUSIONS

CRC patients with distant metastasis to the liver, lung, bone, and brain exhibited homogeneous and heterogeneous prognostic factors, all of which were associated with shorter survival. The nomograms showed good accuracy and may be used as tools for clinicians to predict the prognosis of CRC patients with distant metastasis.

Development and validation of prediction models for the prognosis of colon cancer with lung metastases: a population-based cohort study

Background

Current studies on the establishment of prognostic models for colon cancer with lung metastasis (CCLM) were lacking. This study aimed to construct and validate prediction models of overall survival (OS) and cancer-specific survival (CSS) probability in CCLM patients.

Method

Data on 1,284 patients with CCLM were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly assigned with 7:3 (stratified by survival time) to a development set and a validation set on the basis of computer-calculated random numbers. After screening the predictors by the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, the suitable predictors were entered into Cox proportional hazard models to build prediction models. Calibration curves, concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were used to perform the validation of models. Based on model-predicted risk scores, patients were divided into low-risk and high-risk groups. The Kaplan-Meier (K-M) plots and log-rank test were applied to perform survival analysis between the two groups.

Results

Building upon the LASSO and multivariate Cox regression, six variables were significantly associated with OS and CSS (i.e., tumor grade, AJCC T stage, AJCC N stage, chemotherapy, CEA, liver metastasis). In development, validation, and expanded testing sets, AUCs and C-indexes of the OS and CSS prediction models were all greater than or near 0.7, which indicated excellent predictability of models. On the whole, the calibration curves coincided with the diagonal in two models. DCA indicated that the models had higher clinical benefit than any single risk factor. Survival analysis results showed that the prognosis was worse in the high-risk group than in the low-risk group, which suggested that the models had significant discrimination for patients with different prognoses.

Conclusion

After verification, our prediction models of CCLM are reliable and can predict the OS and CSS of CCLM patients in the next 1, 3, and 5 years, providing valuable guidance for clinical prognosis estimation and individualized administration of patients with CCLM.

Crosstalk between PI3K/Akt and Wnt/β-catenin pathways promote colorectal cancer progression regardless of mutational status

The PI3K/Akt and Wnt/β-catenin pathways play an important role in the acquisition of the malignant phenotype in cancer. However, there are few data regarding the role of the interplay between both pathways in colorectal cancer (CRC) progression. The mutational status and the clinicopathological characteristics of PI3K/Akt and Wnt/β-catenin pathways were accessed by bioinformatic analysis whereas that the impact of the interplay between the activity of both pathways to explain tumorigenic potential was performed in vitro using IGF-1 and Wnt3a treatments in CRC cell models. The mutational status of these pathways did not influence the survival of CRC patients, but an association between clinicopathological characteristics in patients with mutations in one, but not in both pathways was observed. A potentiating effect on the activation of both pathways and enhanced cellular migration and proliferation was observed when both pathways were activated simultaneously with IGF-1 and Wnt3a. In addition, these effects were hindered after pretreatment with LY294002, a specific PI3K inhibitor, suggesting some dependence between these two signaling cascades. Our findings show that, regardless of mutational status, there is an interplay between the activity of PI3K/Akt and Wnt/β-catenin pathways that contributes to events related to CRC progression and that the reversal of such events using a PI3K inhibitor highlights the value of targeting these pathways for potential directed therapies in CRC patients.

Development and validation of a prognostic scoring system for patients with colorectal cancer hepato-pulmonary metastasis: a retrospective study

BACKGROUND

Hepato-pulmonary metastasis of colorectal cancer (CRC) is a rare disease with poor prognosis. This study aims to establish a highly efficient nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer hepato-pulmonary metastasis (CRCHPM).

METHODS

We retrospectively analyzed the data of patients with CRCHPM from SEER database and Wuhan Union Hospital Cancer Center (WUHCC). A total of 1250 CRCHPM patients were randomly assigned to the training, internal validation, and external validation cohorts from 2010 to 2016.Univariate and multivariate cox analysis were performed to identify independent clinicopathological predictors of OS and CSS, and a nomogram was constructed to predict OS and CSS in CRCHPM patients.

RESULTS

A nomogram of OS was constructed based on seven independent predictors of age, degree of differentiation, T stage, chemotherapy, number of lsampled lymph nodes, number of positive lymph nodes, and tumor size. Nomogram showed favorable sensitivity in predicting OS at 1, 3 and 5 years, with area under the receiver operating characteristic curve (AUROC) values of 0.802, 0.759 and 0.752 in the training cohort;0.814, 0.769 and 0.716 in the internal validation cohort;0.778, 0.756 and 0.753 in the external validation cohort, respectively. A nomogram of CSS was constructed based on three independent predictors of T stage, chemotherapy, and tumor size. The AUROC values of 1, 3 and 5 years were 0.709,0.588,0.686 in the training cohort; 0.751, 0.648,0.666 in the internal validation cohort;0.781,0.588,0.645 in the external validation cohort, respectively. Calibration curves, Concordance index (C-index), and decision curve analysis (DCA) results revealed that using our model to predict OS and CSS is more efficient than other single clinicopathological characteristics.

CONCLUSION

A nomogram of OS and CSS based on clinicopathological characteristics can be conveniently used to predict the prognosis of CRCHPM patients.

Survival and prognostic factors of isolated pulmonary metastases originating from colorectal cancer: An 8-year single-center experience

Background

Isolated pulmonary metastasis (IPM) is a rare entity that accounts for 10% of pulmonary metastases seen in colorectal cancer (CRC). This study aims to evaluate the overall 5-year survival of IPM originating from CRC and identify potential prognostic factors affecting the overall survival (OS).

Methods

A retrospective cohort study conducted in a tertiary care center. The study included all patients diagnosed with CRC aged 18–75 years who underwent primary tumor resection with curative intent between 2008 and 2015, and developed IPM. Patients with no follow-up and those with extra-pulmonary metastases were excluded.

Results

The prevalence of IPM in the overall CRC cases was 4.18% (20/478 patients). The mean age of patients with IPM was 52.7 ± 12.9 years. Ten patients had synchronous IPM (50%), thirteen had unilateral (65%), and eleven underwent metastasectomy (55%). The 5-year OS was 40%, and the mean OS was 3.12 ± 1.85 years. Several factors were found to be associated with a favorable outcome, which include unilateral IPM (3.69 vs. 2.07 years; P = 0.024), metachronous (4.25 vs. 2.14 years; P = 0.017), metastasectomy (4.81 vs. 1.83 years; P = 0.005). In addition, mortality was likely to be decreased by more than 90% after metastasectomy (unadjusted odds ratio = 0.071; 95% confidence interval [CI] = 0.01–0.8; P = 0.032).

Conclusions

Forty percent of the included patients survived the 5-year follow-up. Better survival was associated with the metastases being unilateral, metachronous, and metastasectomy. Mortality was lower in patients with pulmonary recurrence after metastasectomy.

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IPM showed an incidence of 4% among resectable CRC patients.

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IPM demonstrated 40% 5-year overall survival.

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Survival was not influenced by age, comorbidities, KRAS mutation, nor the number of pulmonary lesions.

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Unilateral lesions, metachronous metastases, and metastasectomy were associated with a favorable outcome.

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The mortality was likely to be decreased by >90% after metastasectomy.

Homogeneous and heterogeneous risk and prognostic factors for lung metastasis in colorectal cancer patients

Background

The lung is one of the most frequent distant metastasis sites in colorectal cancer (CRC) patients; however, lung metastasis risk and prognostic factors have not been comprehensively elucidated. This study aimed to identify the homogeneous and heterogeneous lung metastasis risk and prognostic factors in CRC patients using the Surveillance, Epidemiology, and End Results (SEER) database.

Methods

CRC patients registered in the SEER database between 2010 and 2016 were included to analyse risk factors for developing lung metastasis by using univariable and multivariable logistic regression. Patients diagnosed between 2010 and 2015 were selected to investigate prognostic factors for lung metastasis by conducting Cox regression. Kaplan–Meier analysis was used to estimate overall survival outcomes.

Results

A total of 10,598 (5.2%) patients with synchronous lung metastasis were diagnosed among 203,138 patients with CRC. The median survival time of patients with lung metastasis was 10.0 months (95% CI 9.6–10.5 months). Older age, unmarried status, uninsured status, poor histological differentiation, more lymphatic metastasis, CEA positivity, liver metastasis, bone metastasis and brain metastasis were lung metastasis risk and prognostic factors. Black patients and those with left colon, rectum, and stage T4 disease were more likely to develop lung metastasis, while patients with right colon cancer and no surgical treatment of the primary tumour had poor survival outcomes.

Conclusion

The incidence of lung metastasis in CRC patients was 5.2%. CRC patients with lung metastasis exhibited homogeneous and heterogeneous risk and prognostic factors. These results are helpful for clinical evaluation and individual treatment decision making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02270-5.

Prognostic Nomogram for Liver Metastatic Colon Cancer Based on Histological Type, Tumor Differentiation, and Tumor Deposit: A TRIPOD Compliant Large-Scale Survival Study

Objective

A proportional hazard model was applied to develop a large-scale prognostic model and nomogram incorporating clinicopathological characteristics, histological type, tumor differentiation grade, and tumor deposit count to provide clinicians and patients diagnosed with colon cancer liver metastases (CLM) a more comprehensive and practical outcome measure.

Methods

Using the Transparent Reporting of multivariable prediction models for individual Prognosis or Diagnosis (TRIPOD) guidelines, this study identified 14,697 patients diagnosed with CLM from 1975 to 2017 in the Surveillance, Epidemiology, and End Results (SEER) 21 registry database. Patients were divided into a modeling group (n=9800), an internal validation group (n=4897) using computerized randomization. An independent external validation cohort (n=60) was obtained. Univariable and multivariate Cox analyses were performed to identify prognostic predictors for overall survival (OS). Subsequently, the nomogram was constructed, and the verification was undertaken by receiver operating curves (AUC) and calibration curves.

Results

Histological type, tumor differentiation grade, and tumor deposit count were independent prognostic predictors for CLM. The nomogram consisted of age, sex, primary site, T category, N category, metastasis of bone, brain or lung, surgery, and chemotherapy. The model achieved excellent prediction power on both internal (mean AUC=0.811) and external validation (mean AUC=0.727), respectively, which were significantly higher than the American Joint Committee on Cancer (AJCC) TNM system.

Conclusion

This study proposes a prognostic nomogram for predicting 1- and 2-year survival based on histopathological and population-based data of CLM patients developed using TRIPOD guidelines. Compared with the TNM stage, our nomogram has better consistency and calibration for predicting the OS of CLM patients.

Robotic and robotic-assisted vs laparoscopic rectal cancer surgery: A meta-analysis of short-term and long-term results

The usage of robotic surgery in rectal cancer (RC) is increasing, but there is an ongoing debate as to whether it provides any benefit. This study conducted a meta-analysis of rectal cancer surgery for short-term and long-term outcome by Robotic and robotic-assisted surgery (RS) vs laparoscopic surgery (LS).Pubmed, Embase, Ovid, CNKI, Cochrane Library and Web of Science databases were searched. Studies clearly documenting a comparison of short-term and long-term effect between RS and LS for RC were selected. Lymph node harvested, operation time, hospital stay, circumferential resection margins（CRM), complications, 3-year disease-free survival (DFS) and 5-year DFS parameters were evaluated. All data were performed by Review Manager 5.3 software. Nine studies were collected that included 1436 cases in total, 716 (49.86%) in the RS group, 720(50.14%) in the LS group. Compared with LS, RS was associated with longer operation time (MD 35.19, 95%CI [7.57, 62.81]; P = 0.01), but similar hospital stay (MD -0.43, 95%CI [-0.87,0.01]; P = 0.05).Lymph node harvested, CRM, complications, 3-year DFS, 5-year DFS had no significance difference between RS and LS groups（MD -0.67，95%CI[-1.53，0.19]；P = 0.13；MD 0.86，95%CI[0.54,1.37]；P = 0.52；MD 0.97，95%CI [0.73,1.29]；P = 0.86；MD 0.94，95%CI[0.60,1.48]；P = 0.79；MD 0.88，95%CI[0.52,1.47]；P = 0.61 respectively）.RS is feasible and safe for RC. It has an advantage in short -term outcome and a similar effect in long-term outcome compared with LS.

Systematic Pan-Cancer Population-Based Analysis Reveals the Incidence and Prognosis of Lung Metastases at Diagnosis

Background

Metastasis is one of the most prevalent causes of death in cancer patients and the lungs are among the organs most commonly affected by metastasis. However, analysis of the incidence and prognosis of lung metastasis (LM) based on primary cancer sites is lacking.

Methods

We enrolled cancer patients with LM from the Surveillance, Epidemiology, and End Results (SEER) database. The risk factors for LM were determined using multivariate logistics regression. Forest plots were used to compare the impact of with LM versus without LM alone among different primary caner site subgroups.

Results

Among 1,525,441 cases, 47,537 presented with LM at initial diagnosis. Multivariate logistics regression revealed that male sex, older age, later T/N stage, unmarried status, and lack of insurance were risk factors for LM. The incidence of LM was 11.91% in bone cancer and 11.19% in pancreatic cancer. In terms of the distribution of primary cancers, 19.22% of LMs originated from the colon and rectum, with 11.63% from the kidneys. The median survival for LM cases was 6 months, with the best survival in testicular cancer (19 months) and bone cancer (12 months). Patients with LM had higher hazard ratio (HR) for mortality compared to those without LM, except for those with primary cancer in the brain (P=0.09). We stratified patients by primary cancer site, and subgroup analyses showed that LM had a significant negative impact on survival. The most significant was in thyroid cancer (HR = 44.79), followed by melanoma (HR = 24.26), prostate (HR = 16.0), breast (HR = 13.46), endometrial (HR = 12.64), testicular (HR = 12.31), and kidney (HR = 11.33) cancer (all P < 0.001).

Conclusion

Patients presenting with LM had higher HR for mortality compared to those without LM, except for those with brain tumor. Clinicians should pay more attention to the occurrence of LM, especially in patients with a significantly increased HR for mortality, such as those with thyroid cancer, melanoma, and prostate cancer.

Nomogram for predicting occurrence and prognosis of liver metastasis in colorectal cancer: a population-based study

PURPOSE

This study aimed to investigate the prevalence, risk, and prognostic factors for synchronous liver metastasis (LM) in colorectal cancer (CRC) and to construct nomogram for predicting occurrence and prognosis of synchronous LM.

METHODS

A total of 203,998 CRC patients who were registered in the SEER database between 2010 and 2016 were included. Logistic regression was used to analyze risk factors and Kaplan-Meier was used to estimate the overall survival of CRC patients with LM. Potential prognostic factors were identified by multivariable Cox regression. For predicting the risk for development and prognosis in CRC patients with LM, we constructed nomogram and the predictive performance was estimated by the receiver operating characteristics cure, the concordance index, and calibration curve.

RESULTS

In total, 15.3% of the CRC patients (N = 31,288) had synchronous LM. Male gender, black, uninsured status, left colon, T4/T1, and bone and lung metastases were positively associated with synchronous LM risk. The 1-year, 3-year, and 5-year overall survival rate was 49.1%, 18.4%, and 9.2%, respectively. Older age, male gender, black, uninsured status, poor histological differentiation, lymphatic metastasis, T4/T1, positive carcinoembryonic antigen, and lung, bone, and brain metastases were associated with the overall survival. Nomogram was constructed to predict the development and prognosis of synchronous LM and both of them were proved to have good calibration and discrimination.

CONCLUSION

LM is highly prevalent in CRC patients. Nomogram basing on the risk and prognostic factors for synchronous LM was proved to have good performance for predicting the probability of LM occurrence and prognosis.

Nomogram based on homogeneous and heterogeneous associated factors for predicting distant metastases in patients with colorectal cancer

BACKGROUND

The identification of the homogeneous and heterogeneous risk factors for different types of metastases in colorectal cancer (CRC) may shed light on the aetiology and help individualize prophylactic treatment. The present study characterized the incidence differences and identified the homogeneous and heterogeneous risk factors associated with distant metastases in CRC.

METHODS

CRC patients registered in the SEER database between 2010 and 2016 were included in this study. Logistic regression was used to analyse homogeneous and heterogeneous risk factors for the occurrence of different types of metastases. Nomograms were constructed to predict the risk for developing metastases, and the performance was quantitatively assessed using the receiver operating characteristics (ROC) curve and calibration curve.

RESULTS

A total of 204,595 eligible CRC patients were included in our study, and 17.07% of them had distant metastases. The overall incidences of liver metastases, lung metastases, bone metastases, and brain metastases were 15.34%, 5.22%, 1.26%, and 0.29%, respectively. The incidence of distant metastases differed by age, gender, and the original CRC sites. Poorly differentiated grade, more lymphatic metastasis, higher carcinoembryonic antigen (CEA), and different metastatic organs were all positively associated with four patterns of metastases. In contrast, age, sex, race, insurance status, position, and T stage were heterogeneously associated with metastases. The calibration and ROC curves exhibited good performance for predicting distant metastases.

CONCLUSIONS

The incidence of distant metastases in CRC exhibited distinct differences, and the patients had homogeneous and heterogeneous associated risk factors. Although limited risk factors were included in the present study, the established nomogram showed good prediction performance.

Predictive Risk Factors and Online Nomograms for Synchronous Colon Cancer With Liver Metastasis

OBJECTIVES

To develop and validate predictive nomograms of cancer specific survival (CSS) and overall survival (OS) for synchronous colon cancer with liver metastasis (SCLM) patients.

METHODS

Patients with pathologically diagnosed colon cancer with liver metastasis were retrieved from the SEER database between 2010 and 2015. Only SCLM patients were included. Univariate and multivariate cox regression analyses were conducted to identify the potential predictors of patients' survival outcomes. The selected variables were integrated to create predictive nomograms via R tools. Furthermore, the concordance index Harrell's C statistic (C-index) was calculated to describe the discrimination of nomograms. Calibration (1000 bootstrap resamples) curves were plotted to compare the predictions of nomograms with the observed outcomes. Decision curve analysis (DCA) and clinical impact curves were performed to evaluate the clinical effects of nomograms.

RESULTS

A total of 22,378 SCLM patients were included. The median time of OS and CSS was 13 and 17 months, respectively. The 1-, 2-, and 3-year rate of OS was 50.6, 28.1, and 14.8%, respectively. While the 1-, 2-, and 3-year rate of CSS was 58.7, 36.8, and 22.5%, respectively. SCLM patients with increased age, left primary tumor location, AJCC IVb stage, and no chemotherapy were associated with an obviously reduced OS and CSS. Variables including age, histological grade, T/N/M stage, tumor size, bone/lung metastasis, CEA, surgery of primary site, and chemotherapy were closely related to the prognoses of SCLM patients. Nomograms of OS and CSS were built and displayed online for convenient utilization. The C-index of OS and CSS monograms were 0.74 and 0.73, respectively, indicating relatively good discrimination of the nomograms. The calibration curves suggested a good agreement between the actual observation and the nomogram prediction. DCAs and clinical impact curves reflected favorable potential clinical effects of predictive nomograms.

CONCLUSION

Chemotherapy, surgery of primary site, and age were important independent risk factors for the CSS and OS of SCLM patients. We built and validated two reliable nomograms of OS and CSS to predict the prognoses of SCLM patients, which can be accessed online at (https://predictive-tool.shinyapps.io/CSS-DynNomapp/; https://predictive-tool.shinyapps.io/OS-DynNomapp/).

Establishment and validation of a novel nomogram incorporating clinicopathological parameters into the TNM staging system to predict prognosis for stage II colorectal cancer

Background

Survival outcomes are significantly different in stage II colorectal cancer (CRC) patients with diverse clinicopathological features. The objective of this study is to establish a credible prognostic nomogram incorporating easily obtained parameters for stage II CRC patients.

Methods

A total of 1708 stage II CRC patients seen at Fudan University Shanghai Cancer Center (FUSCC) from 2008 to 2013 were retrospectively analyzed in this study. Cases were randomly separated into a training set (n = 1084) and a validation set (n = 624). Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors that were subsequently incorporated into a nomogram. The performance of the nomogram was evaluated by the predicted concordance index (C-index) and ROC curve to calculate the area under the curve (AUC). The clinical utility of the nomogram was evaluated using decision curve analysis (DCA).

Results

In univariate and multivariate analyses, eight parameters were correlated with disease-free survival (DFS), which were subsequently selected to generate a prognostic nomogram based on DFS. For DFS predictions, the C-index values of the nomogram were 0.842 (95% confidence interval (CI) 0.710–0.980), and 0.701 (95% CI 0.610–0.770) for the training and validation sets, respectively. The AUC values of the ROC curves for the nomogram to predicted 1, 3 and 5-year survival were 0.869, 0.858, and 0.777 (training group) and 0.673, 0.714, and 0.706 (validation group), respectively. The recurrence probability calibration curve showed good consistency between actual observations and nomogram-based predictions. DCA showed better clinical application value for the nomogram than the TNM staging system.

Conclusion

A novel nomogram was established and validated in a large population, and the nomogram is a simple-to-use tool for physicians to facilitate postoperative personalized prognostic evaluation and determine therapeutic strategies for stage II CRC patients.

Colorectal cancer (CRC) as a multifactorial disease and its causal correlations with multiple signaling pathways

Colorectal cancer (CRC) is the third most common malignancy and one of the leading causes of cancer-related death among men worldwide. CRC is a multifactor digestive pathology, which is a huge problem faced not only by clinicians but also by researchers. Importantly, a unique feature of CRC is the dysregulation of molecular signaling pathways. To date, a series of reviews have indicated that different signaling pathways are disordered and have potential as therapeutic targets in CRC. Nevertheless, an overview of the function and interaction of multiple signaling pathways in CRC is needed. Therefore, we summarized the pathways, biological functions and important interactions involved in CRC. First, we investigated the involvement of signaling pathways, including Wnt, PI3K/Akt, Hedgehog, ErbB, RHOA, Notch, BMP, Hippo, AMPK, NF-κB, MAPK and JNK. Subsequently, we discussed the biological function of these pathways in pathophysiological aspects of CRC, such as proliferation, apoptosis and metastasis. Finally, we summarized important interactions among these pathways in CRC. We believe that the interaction of these pathways could provide new strategies for the treatment of CRC.