Development and validation of nomograms for prediction of overall survival and cancer-specific survival of patients with Stage IV colorectal cancer

Development and validation of comprehensive nomograms from the SEER database for predicting early mortality in metastatic rectal cancer patients

BACKGROUND

Metastatic rectal cancer is an incurable malignancy, which is prone to early mortality. We aimed to establish nomograms for predicting the risk of early mortality in patients with metastatic rectal cancer.

METHODS

In this study, clinical data were obtained from the Surveillance, Epidemiology, and End Results (SEER) database.We utilized X-tile software to determine the optimal cut-off points of age and tumor size in diagnosis. Significant independent risk factors for all-cause and cancer-specific early mortality were determined by the univariate and multivariate logistic regression analyses, then we construct two practical nomograms. In order to assess the predictive performance of nomograms, we performed calibration plots, time-dependent receiver-operating characteristic curve (ROC), decision curve analysis (DCA) and clinical impact curve (CIC).

RESULTS

A total of 2570 metastatic rectal cancer patients were included in the study. Multivariate logistic regression analyses revealed that age at diagnosis, CEA level, tumor size, surgical intervention, chemotherapy, radiotherapy, and metastases to bone, brain, liver, and lung were independently associated with early mortality of metastatic rectal cancer patients in the training cohort. The area under the curve (AUC) values of nomograms for all-cause and cancer-specific early mortality were all higher than 0.700. Calibration curves indicated that the nomograms accurately predicted early mortality and exhibited excellent discrimination. DCA and CIC showed moderately positive net benefits.

CONCLUSIONS

This study successfully generated applicable nomograms that predicted the high-risk early mortality of metastatic rectal cancer patients, which can assist clinicians in tailoring more effective treatment regimens.

Impact of colorectal cancer screening on survival after metachronous metastasis

BACKGROUND

An increasing proportion of colorectal cancer (CRC) cases in Europe are detected by screening with faecal immunochemical testing (FIT). Previous studies showed that population screening with FIT leads to a decrease in CRC incidence and to detection at an earlier stage. However, approximately twenty percent of patients with CRC without metastases at initial diagnosis still develop metachronous metastases. We investigated the association between detection mode of the primary tumor and overall survival (OS) after metachronous metastasis in patients with CRC.

METHODS

Nationwide registry-based data was obtained of 794 patients who developed metachronous metastases after being diagnosed with stage I-III CRC between January and June 2015. With multivariable Cox PH regression modelling, we analyzed the (causal) association between detection mode of the primary tumor (FIT screen-detected versus non-screen-detected) and OS after metachronous metastasis while adjusting for potential confounders.

RESULTS

Median OS and five-year OS after metachronous metastasis were significantly higher for patients with screen-detected (n = 152) vs. non-screen-detected primary tumors (n = 642): 38.3 vs. 19.2 months, and 35.4% vs. 18.8%, respectively, p < 0.0001). After adjustment for potential confounders, the association between detection mode and OS after metachronous metastasis remained significant (HR 0.70 [95% CI 0.56-0.89]).

CONCLUSIONS

Screen-detection of the primary tumor was independently associated with longer OS after metachronous metastasis. This may support the clinical utility of the population screening program and it shows the prognostic value of detection mode of the primary tumor once metachronous metastasis is diagnosed.

A predictive model for early death in elderly colorectal cancer patients: a population-based study

Purpose

The purpose of this study is to determine what variables contribute to the early death of elderly colorectal cancer patients (ECRC) and to generate predictive nomograms for this population.

Methods

This retrospective cohort analysis included elderly individuals (≥75 years old) diagnosed with colorectal cancer (CRC) from 2010-2015 in the Surveillance, Epidemiology, and End Result databases (SEER) databases. The external validation was conducted using a sample of the Chinese population obtained from the China-Japan Union Hospital of Jilin University. Logistic regression analyses were used to ascertain variables associated with early death and to develop nomograms. The nomograms were internally and externally validated with the help of the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

Results

The SEER cohort consisted of 28,111 individuals, while the Chinese cohort contained 315 cases. Logistic regression analyses shown that race, marital status, tumor size, Grade, T stage, N stage, M stage, brain metastasis, liver metastasis, bone metastasis, surgery, chemotherapy, and radiotherapy were independent prognostic factors for all-cause and cancer-specific early death in ECRC patients; The variable of sex was only related to an increased risk of all-cause early death, whereas the factor of insurance status was solely associated with an increased risk of cancer-specific early death. Subsequently, two nomograms were devised to estimate the likelihood of all-cause and cancer-specific early death among individuals with ECRC. The nomograms exhibited robust predictive accuracy for predicting early death of ECRC patients, as evidenced by both internal and external validation.

Conclusion

We developed two easy-to-use nomograms to predicting the likelihood of early death in ECRC patients, which would contribute significantly to the improvement of clinical decision-making and the formulation of personalized treatment approaches for this particular population.

Construction and validation of a nomogram model for predicting the overall survival of colorectal cancer patients

BACKGROUND

Colorectal cancer (CRC) is a frequent cancer worldwide with varied survival outcomes.

OBJECTIVE

We aimed to develop a nomogram model to predict the overall survival (OS) of CRC patients after surgery.

DESIGN

This is a retrospective study.

SETTING

This study was conducted from 2015 to 2016 in a single tertiary center for CRC.

PATIENTS

CRC patients who underwent surgery between 2015 and 2016 were enrolled and randomly assigned into the training (n = 480) and validation (n = 206) groups. The risk score of each subject was calculated based on the nomogram. All participants were categorized into two subgroups according to the median value of the score.

MAIN OUTCOME MEASURES

The clinical characteristics of all patients were collected, significant prognostic variables were determined by univariate analysis. Least absolute shrinkage and selection operator (LASSO) regression was applied for variable selection. The tuning parameter (λ) for LASSO regression was determined by cross-validation. Independent prognostic variables determined by multivariable analysis were used to establish the nomogram. The predictive capacity of the model was assessed by risk group stratification.

RESULTS

Infiltration depth, macroscopic classification, BRAF, carbohydrate antigen 19 - 9 (CA-199) levels, N stage, M stage, TNM stage, carcinoembryonic antigen levels, number of positive lymph nodes, vascular tumor thrombus, and lymph node metastasis were independent prognostic factors. The nomogram established based on these factors exhibited good discriminatory capacity. The concordance indices for the training and validation groups were 0.796 and 0.786, respectively. The calibration curve suggested favorable agreement between predictions and observations. Moreover, the OS of different risk subgroups was significantly different.

LIMITATIONS

The limitations of this work included small sample size and single-center design. Also, some prognostic factors could not be included due to the retrospective design.

CONCLUSIONS

A prognostic nomogram for predicting the OS of CRC patients after surgery was developed, which might be helpful for evaluating the prognosis of CRC patients.

A Nomogram for Predicting Survival in Patients With Colorectal Cancer Incorporating Cardiovascular Comorbidities

Background

Cardiovascular comorbidities (CVCs) affect the overall survival (OS) of patients with colorectal cancer (CRC). However, a prognostic evaluation system for these patients is currently lacking.

Objectives

This study aimed to develop and validate a nomogram, which takes CVCs into account, for predicting the survival of patients with CRC.

Methods

In total, 21,432 patients with CRC were recruited from four centers in China between January 2011 and December 2017. The nomogram was constructed, based on Cox regression, using a training cohort (19,102 patients), and validated using a validation cohort (2,330 patients). The discrimination and calibration of the model were assessed by the concordance index and calibration curve. The clinical utility of the model was measured by decision curve analysis (DCA). Based on the nomogram, we divided patients into three groups: low, middle, and high risk.

Results

Independent risk factors selected into our nomogram for OS included age, metastasis, malignant ascites, heart failure, and venous thromboembolism, whereas dyslipidemia was found to be a protective factor. The c-index of our nomogram was 0.714 (95% CI: 0.708–0.720) in the training cohort and 0.742 (95% CI: 0.725–0.759) in the validation cohort. The calibration curve and DCA showed the reliability of the model. The cutoff values of the three groups were 68.19 and 145.44, which were also significant in the validation cohort (p < 0.001).

Conclusion

Taking CVCs into account, an easy-to-use nomogram was provided to estimate OS for patients with CRC, improving the prognostic evaluation ability.

The number of cycles of adjuvant chemotherapy in stage III and high-risk stage II rectal cancer: a nomogram and recursive partitioning analysis

Objective

The prognostic role of the number of cycles of adjuvant chemotherapy (ACT) after total mesorectal excision in stage III and high-risk stage II rectal cancer is unknown. As a result of this, our study was designed to assess the effect of the number of cycles of ACT on the prediction of cancer-specific survival.

Methods

Four hundred patients that were diagnosed as stage III and high-risk stage II rectal cancer from January 2012 to January 2018 and who had received total mesorectal excision were enrolled in this study. A nomogram incorporating the number of cycles of ACT was also developed in this study. For internal validation, the bootstrap method was used and the consistency index was used to evaluate the accuracy of the model. The patients were stratified into risk groups according to their tumor characteristics by recursive partitioning analysis.

Results

We found that the risk of death was decreased by 26% (HR = 0.74, 95% CI: 0.61–0.89, P = 0.0016) with each increasing ACT cycle. The N stage, positive lymph node ratio (PLNR), carcinoembryonic antigen, neutrophil-to-lymphocyte ratio, and the number of cycles of ACT were chosen and entered into the nomogram model. Recursive partitioning analysis-based risk stratification revealed a significant difference in the prognosis in rectal cancer patients with high-risk, intermediate-risk, and low-risk (3-year cancer-specific survival: 0.246 vs. 0.795 vs. 0.968, P < 0.0001). Seven or more cycles of ACT yielded better survival in patients with PLNR ≥ 0.28 but not in patients with PLNR < 0.28.

Conclusion

In conclusion, the nomogram prognosis model based on the number of cycles of ACT predicted individual prognosis in rectal cancer patients who had undergone total mesorectal excision. These findings further showed that in patients with PLNR ≥ 0.28, no fewer than 7 cycles of ACT are needed to significantly reduce the patient’s risk of death.

Development and Internal Validation of a Nomogram-Based Model to Predict Three-Year and Five-Year Overall Survival in Patients with Stage II/III Colon Cancer

OBJECTIVE

The aim of this study was to develop a nomogram-based model to predict the three-year and five-year overall survival (OS) of patients with stage II/III colon cancer following radical resection.

METHODS

A total of 1156 patients with stage II/III colon cancer who underwent radical resection at the Affiliated Hospital of Guizhou Medical University between December 2012 and December 2018 were enrolled. Lasso regression was used to screen out 12 variables: age, prealbumin, albumin, degree of differentiation, total tumor-node-metastasis (TNM) stage, T stage, N stage, prognostic nutritional index (PNI), platelet/lymphocyte count, carcinoembryonic antigen, carbohydrate antigen 19-9 (CA19-9), and postoperative adjuvant chemotherapy. The data set was then randomly split into a modeling set and a validation set, and the bootstrap method was used to verify the internal validity of the final model. A nomogram was then used to present the model, and the risk groups were categorized according to the total score in the nomogram.

RESULTS

This study established and developed a simple, easy-to-use predictive model that included age, degree of differentiation, N stage, CA19-9, PNI, and postoperative chemotherapy as variables. In the multivariate Cox regression analysis, only postoperative chemotherapy was identified as an independent risk factor for death in patients with colon cancer. The receiver operating characteristic curve showed that the model demonstrated good resolution, with an area under the curve of 0.803. Decision curve analysis indicated that the model had a good positive net gain, and the bootstrap method was used to verify its stability. In the OS rate, the C-index was 0.78. According to the total score of the nomogram, the risk group was layered by drawing the Kaplan-Meier (K-M) curve. In the three-year OS K-M curve, the survival rates of the low-risk group, the medium-risk group, and the high-risk group were 96%, 93%, and 82%, respectively. In the five-year OS K-M curve, the survival rates of the low-risk group, the medium-risk group, and the high-risk group were 94%, 90%, and 73%, respectively.

CONCLUSION

The nomogram-based prediction model developed in this study is stable and has good resolution, reliability, and net gain. It will therefore be useful for clinicians performing risk stratification and postoperative monitoring and in the development of personalized treatment options for patients with stage II/III colon cancer.

Nomogram Based on Log Odds of Positive Lymph Nodes Predicting Cancer-Specific Survival in Patients With T3 and T4 Gallbladder Cancer After Radical Resection

Background: The aim of this study based on log odds of positive lymph nodes (LODDS) is to develop and validate an effective prognostic nomogram for patients with T3 and T4 gallbladder cancer (GBC) after resection.

Patients and Methods: A total of 728 T3 and T4 gallbladder cancer patients after resection from the Surveillance, Epidemiology, and End Results (SEER) database, randomly divided into training cohort and validation cohort according to 7:3. Another 128 patients from The Second Affiliated Hospital of Nanchang University for external validation. The nomograms were built by the Cox regression model and the Fine and Grey's model. Concordance index (C-index), calibration curve and the area under receiver operating characteristic (ROC) curve (AUC) were used to evaluate the nomogram and internal verification. The decision curve analysis (DCA) was used to measure clinical applicability.

Result: LODDS was independent prognostic predictor for overall survival (OS) and cancer-specific survival (CSS), and established the nomograms on this basis. The nomogram we have established has a good evaluation effect, with a C-index of 0.719 (95%CI, 0.707–0.731) for OS and 0.747 (95%CI, 0.733–0.760) for CSS. The calibration curves of OS and CSS both showed good calibration capability, and the AUC for predicting 1-, 2-, and 3-year 0.858, 0.848 were and 0.811 for OS, and 0.794, 0.793, and 0.750 for CSS. The DCA of nomograms both showed good clinical applicability.

Conclusion: The nomogram can provide effective OS and CSS prediction for patients with advanced gallbladder cancer after surgery.

Development and validation of a novel prognostic model for long-term overall survival in liposarcoma patients: a population-based study

Objective

To construct and validate a clinically accurate and histology-specific nomogram to predict overall survival (OS) among liposarcoma (LPS) patients.

Methods

We retrospectively screened eligible patients with LPS diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database. We screened independent predictors for the nomogram using univariate and multivariate analyses. We then evaluated the prognostic accuracy of the nomogram by receiver operating characteristic (ROC) curve analysis and Harrell’s concordance index. The prognostic performances of the nomogram and the American Joint Committee on Cancer (AJCC) seventh edition staging system were compared using integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analyses (DCA).

Results

A novel nomogram was developed using independent prognostic variables, which exhibited excellent predictive performances for 3- and 5-year OS according to ROC curves. The C-index proved that the proposed nomogram had better prognostic accuracy for LPS than the traditional AJCC system, while the NRI, IDI, and DCA of the nomogram indicated better clinical net benefit.

Conclusions

The proposed nomogram can predict 3- and 5-year OS of LPS patients with reliable accuracy and may thus help clinicians to develop appropriate clinical therapies and counseling strategies to prolong the life expectancy of these patients.

Nomogram for predicting overall survival in colorectal cancer with distant metastasis

Background

Colorectal cancer (CRC) is a major cancer burden, and prognosis is determined by many demographic and clinicopathologic factors. The present study aimed to construct a prognostic nomogram for colorectal cancer patients with distant metastasis.

Methods

Colorectal cancer patients with distant metastasis diagnosed between 2010 and 2016 were selected from the Surveillance, Epidemiology, and End Results database. Cox proportional hazards regression was used to identify independent prognostic factors. A nomogram was constructed to predict survival, and validation was performed.

Results

A total of 7099 stage IV colorectal cancer patients were enrolled in the construction cohort. The median overall survival was 20.0 (95% CI 19.3–20.7) months. Age at diagnosis, marital status, race, primary tumour site, tumour grade, CEA level, T stage, N stage, presence of bone, brain, liver and lung metastasis, surgery for primary site and performance of chemotherapy were independent prognostic factors. The nomogram was constructed and the calibration curve showed satisfactory agreement. The C-index was 0.742 (95% CI 0.726–0.758). In the validation cohort (7098 patients), the nomogram showed satisfactory discrimination and calibration with a C-index of 0.746 (95% CI 0.730–0.762).

Conclusion

A series of factors associated with the survival of CRC patients with distant metastasis were found. Based on the identified factors, a nomogram was generated to predict the survival of stage IV colorectal cancer patients. The predictive model showed satisfactory discrimination and calibration, which can provide a reference for survival estimation and individualized treatment decisions.

Oncological and prognostic impact of lymphovascular invasion in Colorectal Cancer patients

Objectives: Lymphovascular invasion (LVI) is correlated with unfavorable prognoses in several types of cancers. We aimed to identify the informative features associated with LVI and to determine its prognostic value in colorectal cancer (CRC) patients. Methods: We retrospectively analyzed 1,474 CRC patients admitted in Wuhan Union Hospital between 2013 and 2017 as the development cohort and 549 CRC patients from The Cancer Genome Atlas (TCGA) database as the validation cohort. Logistical and Cox regression analyses were conducted to determine the oncological and prognostic significance of LVI in CRC patients. A survival nomogram based on LVI status was established using the Wuhan Union cohort and validated using TCGA cohort. Results: The LVI detection rates were 21.64% in the Wuhan Union cohort and 35.15% in TCGA cohort. LVI was closely correlated with advanced T stage, N stage, and TNM stage. LVI positivity was an independent biomarker for unfavorable overall survival (hazard ratio [HR]=2.25, 95% confidence interval [CI]=1.70-2.96, P<0.0001) and worse disease-free survival (HR=2.34, 95% CI=1.76-3.12, P<0.0001) in CRC patients. The survival nomogram incorporating LVI exhibited good predictive performance and reliability in the Wuhan Union cohort and TCGA cohort. Conclusion: LVI is a significant indicator of advanced stage and is remarkably correlated with worse prognosis in CRC patients. The survival nomogram incorporating LVI may assist clinicians to better strategize the therapeutic options for patients with CRC.

Personalizing prognostic prediction in early-onset Colorectal Cancer

Accurately estimating prognosis based on clinicopathologic variables could improve risk stratification for patients with early-onset colorectal cancer (EOCRC). Our primary goal was to create and validate a survival nomogram with adequate performance for predicting overall survival (OS) in patients with EOCRC. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to identify clinical features statistically related to OS. Then we established and internally validated a survival nomogram based on surveillance, epidemiology and end results (SEER) database (N=23813). A cohort of 77 patients with EOCRC from Renmin Hospital of Wuhan University (RHWU) was employed to detect the external validity of the survival nomogram. Moreover, we compared the predictive accuracy of survival nomogram with TNM stage, and also compared the OS between endoscopy and surgery groups before and after propensity score matching (PSM) among EOCRC patients with early stage (Tis-T1N0M0). We selected seven informative indexes (N stage, M stage, perineural invasion, chemotherapy, surgery primary site, summary stage and tumor grade) for the construction of the survival nomogram. Then the survival nomogram exhibited good discrimination with C-index of 0.829, 0.841 and 0.796 in the SEER training, SEER validation and RHWU validation sets, respectively. Calibration curves showed good concordance between the survival nomogram predictions and actual outcomes for 1-year, 3-year and 5-year OS. Furthermore, the survival nomogram was superior to risk stratification by TNM stage in predicting OS among patients with EOCRC. Early-stage patients treated with endoscopy showed similar survival to those with surgery before and after PSM. We proposed a survival nomogram based on the extensively used parameters to precisely predict OS in EOCRC patients. This survival nomogram will contribute to aid oncologists better risk stratification and prognostication for patients with EOCRC.

Colorectal adenocarcinoma patients with M1a diseases gain more clinical benefits from palliative primary tumor resection than those with M1b diseases: A propensity score matching analysis

BACKGROUND

Surgical resection is regarded as the only potentially curative treatment option for patients with metastatic colorectal cancer (CRC). The National Comprehensive Cancer Network clinical practice guidelines do not recommend palliative surgery unless there is a risk of severe symptoms. However, accumulating evidence has shown that palliative surgery is associated with more favorable outcomes for patients with metastatic CRC.

AIM

To investigate the separate role of palliative primary tumor resection for patients with stage IVA (M1a diseases) and stage IVB (M1b diseases) colorectal adenocarcinoma (CRA).

METHODS

CRA patients diagnosed from 2010 to 2015 with definite M1a and M1b categories according to the 8^th edition of American Joint Committee on Cancer staging system were selected from the Surveillance Epidemiology and End Results (SEER) database. To minimize potential selection bias, the data were adjusted by propensity score matching (PSM). Baseline characteristics, including gender, year of diagnosis, age, marital status, primary site, surgical information, race, grade, chemotherapy, and radiotherapy, were recorded and analyzed. Univariate and multivariate analyses were performed to explore the separate role of palliative surgery for patients with M1a and M1b diseases.

RESULTS

A total of 19680 patients with metastatic CRA were collected from the SEER database, including 10399 cases of M1a diseases and 9281 cases of M1b diseases. Common independent prognostic factors for both M1a and M1b patients included year of diagnosis, age, race, marital status, primary site, grade, surgery, and chemotherapy. After PSM adjustment, 3732 and 3568 matched patients in the M1a and M1b groups were included, respectively. Patients receiving palliative primary tumor resection had longer survival time than those without surgery (P < 0.001). For patients with M1a diseases, palliative resection could increase the median survival time by 9 mo; for patients with M1b diseases, palliative resection could prolong the median survival time by 7 mo. For M1a diseases, patients with lung metastasis had more clinical benefit from palliative resection than those with liver metastasis (15 mo for lung metastasis vs 8 mo for liver metastasis, P < 0.001).

CONCLUSION

CRA patients with M1a diseases gain more clinical benefits from palliative primary tumor resection than those with M1b diseases. Those patients with M1a (lung metastasis) have superior long-term outcomes after palliative primary tumor resection.

Nomogram predicting cancer-specific mortality in early-onset rectal cancer: a competing risk analysis

BACKGROUND

The incidence of rectal cancer has meaningfully increased in young patients. However, quantitative evaluation for the competing data of early-onset rectal cancer is lacking. So, we performed a competing risk analysis to calculate the cumulative incidence of death for patients with early-onset rectal cancer and developed a nomogram to predict the probability of cancer-specific mortality for these patients.

METHODS

We abstracted data of patients with early-onset rectal cancer between 2004 and 2016 by using the Surveillance, Epidemiology, and End Results program database. The cumulative incidence function was used to calculate the crude cancer-specific mortality of early-onset rectal cancer. Fine and Gray's proportional sub-distribution hazard model was adopted to explore the risk factors of cancer-specific death. Then, we establish a nomogram to predict their 3-, 5-, and 10-year probabilities.

RESULTS

We identified 9917 patients with early-onset rectal cancer, and they were randomly divided into training (n = 6941) and validation (n = 2976) cohorts. In the training cohort, the 3-, 5-, and 10-year cumulative incidences of cancer-specific death after diagnosis for early-onset rectal cancer were 11.4%, 19.9%, and 28.8%, respectively. Fine and Gray's model showed that sex, race, marital status, histology, T stage, N stage, M stage, examined lymph nodes, and pretreatment carcinoembryonic antigen were independently associated with cancer-specific mortality. Such factors were selected to develop a prognostic nomogram.

CONCLUSION

The competing risk nomogram has an ideal performance for predictive cancer-specific mortality in early-onset rectal cancer.

Development and validation of nomograms for prediction of overall survival and cancer-specific survival of patients of colorectal cancer

PURPOSE

Nomograms are intuitive tools for individualized cancer prognosis. We sought to develop a clinical nomogram for prediction of overall survival and cancer-specific survival for patients with colorectal cancer.

METHODS

Patients with colorectal cancer diagnosed between 1988 and 2006 and those who underwent surgery were retrieved from the Surveillance, Epidemiology, and End Results database and randomly divided into the training (n = 119 797) and validation (n = 119 797) cohorts. Log-rank and multivariate Cox regression analyses were used in our analysis. To find out death from other cancer causes and non-cancer causes, a competing-risks model was used, based on which we integrated these significant prognostic factors into nomograms and subjected the nomograms to bootstrap internal validation and to external validation.

RESULTS

The 1-, 3-, 5- and 10-year probabilities of overall survival in patients of colorectal cancer after surgery intervention were 83.04, 65.54, 54.79 and 38.62%, respectively. The 1-, 3-, 5- and 10-year cancer-specific survival was 87.36, 73.44, 66.22 and 59.11%, respectively. Nine independent prognostic factors for overall survival and nine independent prognostic factors for cancer specific survival were included to build the nomograms. Internal and external validation CI indexes of overall survival were 0.722 and 0.721, and those of cancer-specific survival were 0.765 and 0.766, which was satisfactory.

CONCLUSIONS

Nomograms for prediction of overall survival and cancer-specific survival of patients with colorectal cancer. Performance of the model was excellent. This practical prognostic model may help clinicians in decision-making and design of clinical studies.

The Prognostic Value of Autophagy-Related Markers Bclin-1 and LC-3 in Colorectal Cancers: A Systematic Review and Meta-analysis

Objective

At present, the relationship between autophagosomes and the prognosis of various cancers has become a subject of active investigation. A series of studies have demonstrated the correlation between autophagy microtubule-associated protein light chain 3 (LC-3), Beclin-1, and colorectal cancer (CRC). Since autophagy has dual regulatory roles in tumors, the results of this correlation are also uncertain. Hence, we summarized the relationship between Beclin-1, LC-3, and CRC using systematic reviews and meta-analysis to clarify their prognostic significance in it.

Methods

PubMed, EMBASE, Cochrane Library, and Web of Science databases were searched online up to April 1, 2019. The quality of the involving studies was assessed against the Newcastle-Ottawa Scale (NOS). Pooled hazard ratio (HR) and 95% confidence interval (CI) in a fixed or random effects model were used to assess the strength of correlation between Beclin-1, LC-3, and CRC.

Results

A total of 9 articles were collected, involving 2,297 patients. Most literatures scored more than 6 points, suggesting that the quality of our including research was acceptable. Our finding suggested that the expression of Beclin-1 was not associated with overall survival (HR = 0.68, 95% CI (0.31–1.52), P=0.351). Nonetheless, LC-3 expression exerted significant impact on OS (HR = 0.51, 95% CI (0.35–0.74), P < 0.05). Subgroup analysis exhibited that Beclin-1 expression was associated with OS at TNM stage III (HR = 0.04, 95% CI = 0.02–0.08, P < 0.05), surgical treatment (HR = 1.53, 95% CI (1.15–2.02), P=0.003), and comprehensive treatment (HR = 0.27 95% CI (0.08–0.92), P=0.036), respectively. Similarly, the results showed the increased LC-3 expression in CRC was related to OS in multivariate analyses (HR = 0.44, 95% CI (0.34–0.57), P < 0.05), stages (HR = 0.51, 95% CI (0.35–0.74), P < 0.05), and comprehensive treatment (HR = 0.44, 95% CI (0.34–0.57), P < 0.05).

Conclusions

Autophagy-related proteins of LC-3 might be an important marker of CRC progression. However, since the number of the original studies was limited, more well-designed, large-scale, high-quality studies are warranted to provide more convincing and reliable information.

Nomogram for predicting overall survival in stage II-III colorectal cancer

PURPOSE

The overall survival (OS) of patients diagnosed with stage II-III colorectal cancer (CRC) can vary greatly, even between patients with the same tumor stage. We aimed to design a nomogram to predict OS in resected, stage II-III CRC and stratify patients with CRC into different risk groups.

PATIENTS AND METHODS

Based on data from 873 patients with CRC, we used univariate Cox regression analysis to select the significant prognostic features, which were subjected to the least absolute shrinkage and selection operator (LASSO) regression algorithm for feature selection. Cross-validation was used to confirm suitable tuning parameters (λ) for LASSO logistic regression. Then, the nomogram was used to estimate 3- and 5-year OS based on the multivariable Cox regression model. The survival curves of the two groups were produced using the Kaplan-Meier method. Risk group stratification was performed to assess the predictive capacity of the nomogram.

RESULTS

Preoperative mean platelet volume, preoperative platelet distribution width, monocytes, and postoperative adjuvant chemotherapy were identified as independent prognostic factors by LASSO regression and integrated for the construction of the nomogram. The nomogram provided good discrimination, with C-indices of 0.67 and 0.69 for the training and validation sets, respectively. Calibration plots illustrated excellent agreement between the nomogram predictions and actual observations for 3- and 5-year OS. Moreover, a significant difference in OS was shown between patients stratified into different risk groups (P < .001).

CONCLUSION

We constructed and validated an original predictive nomogram for OS in patients with CRC after surgery, facilitating physicians to appraise the individual survival of postoperative patients accurately and identify high-risk patients who need more aggressive treatment and follow-up strategies.