Risk and prognostic nomograms for colorectal neuroendocrine neoplasm with liver metastasis: a population-based study

Clinical and pathological characteristics of and predictive model for colorectal neuroendocrine tumors

Background

The incidence of colorectal neuroendocrine tumors (NETs) is increasing, causing a social burden. At present, there is no specific prognostic model for colorectal NETs. Thus, an accurate model is needed to predict the prognosis of patients with colorectal NETs.

Aim

We aimed to create a new nomogram to predict the prognosis of patients with colorectal NETs. Furthermore, we compared nomogram we established and the 8th edition of the AJCC TNM staging system in terms of prediction ability and accuracy.

Methods

A total of 3353 patients with colorectal NETs were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier analyses were used to assess overall survival (OS) and cancer-specific survival (CSS). Additionally, LASSO regression was used to select variables for constructing the nomogram. Furthermore, the C-index and time-dependent receiver operating characteristic (tdROC) curve were used to evaluate the nomogram. Decision curve analysis (DCA) was performed to compare the clinical utility of the nomogram with that of the TNM system. An external validation cohort (N = 61) was established to evaluate the nomogram's prediction accuracy.

Results

A total of 9 factors (age, sex, marital status, tumor size, T stage, M stage, N stage, grade, and surgery) were selected based on the results of LASSO analysis. The C-indexes of the nomogram in the training and validation sets were 0.807 and 0.775, respectively, which indicated that the nomogram had better prediction accuracy than TNM staging (C-index = 0.700 in the training set and 0.652 in the validation set). The C-index of the nomogram in the external validation cohort was 0.954, indicating that the nomogram had satisfactory prediction accuracy. The results of DCA revealed that the survival nomogram possessed greater utility in clinical practice.

Conclusion

We determined the OS and CSS of patients with colorectal NETs and developed a robust and clinically useful survival nomogram.

Multifactorial risk prediction analysis of liver metastasis in colorectal cancer: incorporating programmed cell death ligand 1 combined positive score and other factors

BACKGROUND

The occurrence of liver metastasis significantly affects the prognosis of colorectal cancer (CRC). Existing research indicates that primary tumor location, vascular invasion, lymph node metastasis, and abnormal preoperative tumor markers are risk factors for CRC liver metastasis. Positive expression of programmed cell death ligand 1 (PD-L1) may serve as a favorable prognostic marker for nasopharyngeal and gastric cancers, in which combined positive score (CPS) quantifies the level of PD-L1 expression. This study aimed to explore CPS as a potential risk factor for CRC liver metastasis and integrate other independent risk factors to establish a novel predictive model for CRC liver metastasis.

METHODS

A retrospective analysis was conducted on 437 patients with CRC pathologically diagnosed at The Second Xiangya Hospital of Central South University from January 1, 2019, to December 31, 2021. Data were collected, including CPS, age, gender (male and female), primary tumor location, Ki-67 expression, pathologic differentiation, neural invasion, vascular invasion, lymph node metastasis, and preoperative tumor markers. The optimal cutoff point for the continuous variable CPS was determined using the Youden index, and all CPSs were dichotomized into high- and low-risk groups based on this threshold (scores below the threshold were considered high risk, and score above the threshold were considered low risk). Univariate logistic regression analysis was employed to identify risk factors for CRC liver metastasis, followed by multivariate logistic regression analysis to integrate the selected risk factors. The predictive model was validated through the construction of receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). A nomogram was constructed for visualization.

RESULTS

The determined cutoff point for PD-L1 CPS was 4.5, with scores below this threshold indicating a high risk of CRC liver metastasis. In addition, primary tumor origin other than the rectum, presence of pericolonic lymph node metastasis, and abnormal levels of tumor markers carcinoembryonic antigen and cancer antigen 19-9 were identified as independent risk factors for CRC liver metastasis. The constructed clinical prediction model demonstrated good predictive ability and accuracy, with an area under the ROC curve of 0.871 (95% CI, 0.838-0.904).

CONCLUSION

The exploration and validation of CPS as a novel predictor of CRC liver metastasis were performed. Based on these findings, a new clinical prediction model for CRC liver metastasis was developed by integrating other independent risk factors. The DCA, clinical impact curve, and nomogram graph constructed on the basis of this model have significant clinical implications and guide clinical practice.

Palliative primary tumor resection may not offer survival benefits for patients with unresectable metastatic colorectal neuroendocrine neoplasms, one multicenter retrospective cohort study

BACKGROUND

The efficacy of palliative primary tumor resection (PTR) in improving prognosis for patients with unresectable metastatic colorectal neuroendocrine neoplasms (NENs) has not been fully explored.

METHODS

We performed one retrospective cohort study and recruited 68 patients with unresectable metastatic colorectal NENs from two Chinese medical centers between 2000 and 2022. All patients were assigned to PTR group and no PTR group. The clinicopathological manifestation data were carefully collected, and the survival outcomes were compared between the two groups using Kaplan-Meier methods. Propensity score matching (PSM) was conducted to minimize confounding bias. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify prognostic factors.

RESULTS

A total of 32 patients received PTR, and the other 36 patients did not. The median progression-free survival (PFS) and overall survival (OS) times were 4 and 22 months in the whole cohort, respectively. For patients who received no PTR, the median OS was 16 months, and the 1-year OS rate and 3-year OS rate were 56.4% and 39.6%, respectively. For patients who received PTR, the median OS was 24 months, and the 1-year OS rate and 3-year OS rate were 67.9% and 34.1%, respectively. However, the Kaplan-Meier survival curves and log-rank test demonstrated no significant survival difference between the two groups (P = 0.963). Moreover, palliative PTR was also not confirmed as a prognostic factor in subsequent univariable and multivariable Cox proportional hazards regression analyses in both the original and matched cohorts. Only histological differentiation was identified as an independent prognostic factor affecting PFS [hazard ratio (HR) = 1.86, 95% confidence interval (CI): 1.02-3.41, P = 0.043] and OS [HR = 3.70, 95% CI: 1.09-12.48, P = 0.035] in the original cohort.

CONCLUSIONS

Palliative PTR may not offer survival benefits for patients with unresectable metastatic colorectal NENs.

Analysis of the Genetic Characteristics and Metastatic Pathways of G1 and G2 Colorectal Neuroendocrine Neoplasms

Objective

G1 and G2 colorectal neuroendocrine neoplasms (NENs) are a group of rare and indolent diseases. We aimed to delineate their genetic characteristics and explore their metastatic mechanisms.

Methods

We used next-generation sequencing technology for targeted sequencing for 54 patients with G1 and G2 colorectal NENs. We delineated their genetic features and compared the genetic characteristics between metastatic NENs and nonmetastatic NENs. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was utilized to explore their abnormal pathways and study their potential metastatic mechanisms.

Results

We collected 23 metastatic NENs and 31 nonmetastatic NENs. In the whole cohort, the common mutated genes were NCOR2, BRD4, MDC1, ARID1A, AXIN2, etc. The common copy number variations (CNVs) included amplification of HIST1H3D, amplification of HIST1H3E, and loss of PTEN. The KEGG enrichment analysis revealed that PI3K-Akt, MAPK, and Rap1 were the major abnormal pathways. There were significantly different genetic features between metastatic NENs and nonmetastatic NENs. The metastatic NENs shared only 47 (22.5%) mutated genes and 6 (13.3%) CNVs with nonmetastatic NENs. NCOR2, BRD4, CDKN1B, CYP3A5, and EIF1AX were the commonly mutated genes in metastatic NENs, while NCOR2, MDC1, AXIN2, PIK3C2G, and PTPRT were the commonly mutated genes in nonmetastatic NENs. Metastatic NENs presented a significantly higher proportion of abnormal pathways of cell senescence (56.5% vs 25.8%, P = .022) and lysine degradation (43.5% vs 16.1%, P = .027) than nonmetastatic NENs.

Conclusion

G1 and G2 colorectal NENs are a group of heterogeneous diseases that might obtain an increased invasive ability through aberrant cell senescence and lysine degradation pathways.

Second primary colorectal cancer in adults: a SEER analysis of incidence and outcomes

BACKGROUND

At present, there was no large epidemiological study exploring the actual incidence and survival of second primary colorectal cancer (spCRC). The different characteristics and survival of patients with spCRC and initial primary colorectal cancer (ipCRC) still need to be elucidated. In addition, the factors leading to different survival status of spCRC and ipCRC were still unclear. Our study plan to explore the annual incidence trend of spCRC as well as the factors influencing the occurrence and survival outcome of spCRC.

METHODS

This cohort study analyzed the data of 4680 spCRC patients and 330,937 initial primary colorectal cancer (ipCRC) patients. Whether patients had spCRC and whether spCRC patients survived or died were regarded as outcomes. The annual incidence of spCRC from 2004 to 2016 was analyzed by Jointpoint regression analysis. The truncation points were found, and the annual percentage change (APC) of each segment was calculated to explore the trend of spCRC change in the United States. Univariate and multivariable cox regression analyses were conducted to identify factors associated with the occurrence and prognosis of spCRC patients.

RESULTS

The total incidence of spCRC was decreased during 2000-2016 on the whole. The overall incidence of spCRC was lowered in both males and females despite 2013-2014, in the left colon, right colon, rectum and others. The incidence of spCRC was decreased in both 18-49 years' people and ≥ 50 years' people during 2000-2016, and the incidence of spCRC in the ≥ 50 years' people group was higher than those of 18-49 years. Insured (OR = 0.867 (0.778-0.966), initial primary site of other digestive (OR = 0.46, 95%CI: 0.42-0.50), rectum (OR = 0.74, 95%CI: 0.66-0.82), or right colon (OR = 0.73, 95%CI: 0.68-0.79), N 1 stage (OR = 0.87, 95%CI: 0.76-0.99), M 1 stage (OR = 0.49, 95%CI: 0.30-0.80), AJCC II stage (OR = 0.70, 95%CI: 0.60-0.82), AJCC III stage (OR = 0.69, 95%CI: 0.56-0.84), and radiation (OR = 0.69, 95%CI: 0.57-0.83) were associated with the risk of spCRC. At the end of follow-up, 2,246 spCRC patients were survived and 2,434 spCRC patients were dead. Patients with spCRC had poor survival probability than patients with ipCRC. Older age (HR = 1.02, 95%CI: 1.02-1.03), male (HR = 1.13, 95%CI: 1.04-1.23), Black (HR = 1.20, 95%CI: 1.06-1.35), uninsured (HR = 1.36, 95%CI: 1.16-1.59), Signet ring cell carcinoma (HR = 1.64, 95%CI: 1.19-2.25), T4 stage (HR = 1.63, 95%CI: 1.32-2.01), N2 stage (HR = 1.36, 95%CI: 1.08-1.72), M1 stage (HR = 4.51, 95%CI: 2.00-10.18), AJCC III (HR = 1.47, 95%CI: 1.08-1.98), and radiation (HR = 1.82, 95%CI: 1.43-2.33) were associated with increased risk of mortality in spCRC patients.

CONCLUSION

The incidence of spCRC was decreased except in people with initial primary tumor grade IV and those aged 15-39 years. The overall survival of spCRC patients was lower than ipCRC patients. Cancer patients with older age, high tumor grade, TNM stage, and AJCC stage should be caution to the occurrence of spCRC and timely interventions should be provided for spCRC patients to improve their outcomes.

Risk prediction of second primary malignancies in primary colorectal neuroendocrine neoplasms patients: a population-based study

PURPOSE

In this study, we aimed to identify risk factors for developing second primary malignancies (SPMs) in colorectal neuroendocrine neoplasms (NENs) patients and develop a competing-risk nomogram to predict SPMs' probabilities quantitatively.

METHODS

Patients with colorectal NENs were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database during 2000-2013. Potential risk factors for SPMs' occurrence in colorectal NENs' patients were identified by the Fine and Gray's proportional sub-distribution hazards model. Then, a competing-risk nomogram was constructed to quantify SPMs' probabilities. The discriminative abilities and calibrations of this competing-risk nomogram were assessed by the area under the receiver-operating characteristic (ROC) curves (AUC) and calibration curves.

RESULTS

We identified 11,017 colorectal NENs' patients, and randomly divided them into training (n = 7711 patients) and validation (n = 3306 patients) cohorts. In the whole cohort, 12.4% patients (n = 1369) had developed SPMs during the maximum follow-up of approximately 19 years (median 8.9 years). Sex, age, race, primary tumor location, and chemotherapy were identified as risk factors for SPMs' occurrence in colorectal NENs' patients. Such factors were selected to develop a competing-risk nomogram and showed excellent predictive ability for SPMs' occurrence (the 3-, 5-, and 10-year AUC values were 0.631, 0.632, and 0.629 in the training cohort and 0.665, 0.639, 0.624 in the validation cohort, respectively).

CONCLUSIONS

This research identified risk factors for SPMs' occurrence in colorectal NENs' patients. Competing-risk nomogram was constructed and proved to have good performance.

Development of novel prediction models for nodal and distant metastasis in G1 and G2 colorectal neuroendocrine tumors

PURPOSE

We aimed to construct novel nomograms for nodal and distant metastasis for patients with G1 and G2 colorectal neuroendocrine tumors (NETs).

METHODS

A training set and validation set were obtained by including G1 and G2 colorectal NET patients from the Surveillance, Epidemiology, and End Results database and the Cancer Hospital Chinese Academy of Medical Science, respectively. The area under curve (AUC) values under receiver operating characteristic (ROC) curves, calibration plots, and the Hosmer‒Lemeshow tests were used to evaluate the discriminability and calibration of nomograms.

RESULTS

In total, 3690 and 172 patients were included in the training set and validation set, respectively. Tumor size, location, and T stage were included in the nomogram predicting nodal metastasis. The AUC values of the nomogram were 0.972 (95% confidence interval (CI): 0.964-0.980) and 0.897 (95% CI: 0.846-0.948) in the training set and validation set, respectively. The calibration plots and Hosmer‒Lemeshow test for the training set (P = 0.999) and validation set (P = 0.537) showed good model calibration. Tumor size, T stage, and N stage were incorporated into the nomogram predicting distant metastasis. The ROC curves demonstrated desirable discrimination both in the training set (AUC = 0.938 (95% CI: 0.921-0.954)) and validation set (AUC = 0.938 (95% CI: 0.890-0.988)). The calibration curves and Hosmer‒Lemeshow test indicated acceptable model calibration both in the training set (P = 0.908) and validation set (P = 0.722).

CONCLUSION

The proposed nomograms may be used as a reliable tool to predict the nodal and distant metastasis in G1 and G2 colorectal NETs.

Risk Factors, Prognostic Factors, and Nomograms for Bone Metastasis in Patients with Newly Diagnosed Clear Cell Renal Cell Carcinoma: A Large Population-Based Study

Background

This study aimed to investigate risk factors and prognostic factors in patients with clear cell renal cell carcinoma (ccRCC) with bone metastasis (BM) and establish nomograms to provide a quantitative prediction of the risk of BM and survival probability.

Methods

The clinicopathological characteristics of patients with ccRCC between January 2010 and December 2015 were obtained from the Surveillance, Epidemiology and End Results (SEER) database. Independent factors for BM in ccRCC patients were identified using univariate and multivariate logistic regression analyses. Prognostic factors for predicting cancer-specific death were evaluated using univariate and multivariate analyses based on a competing risk regression model. We then constructed a diagnostic nomogram and a prognostic nomogram. The two nomograms were evaluated using calibration curves, receiver operating characteristic curves, and decision curve analysis.

Results

Our study included 34,659 patients diagnosed with ccRCC in the SEER database, with 1,415 patients who presented with bone metastasis. Risk factors for BM in patients with ccRCC included age, stage T, stage N, brain metastasis, liver metastasis, lung metastasis, tumor size, and laterality. Independent prognostic factors for patients with ccRCC patients with BM were Fuhrman grade, tumor size, T stage, N stage, brain metastases, lung metastasis, and surgery. For the diagnostic nomogram, the area under the curve values in the training and testing cohorts were 0.863 (95% CI, 0.851–0.875) and 0.859 (95% CI, 0.839–0.878), respectively. In the prognostic cohort, the area under the curve values for 1-, 2-, and 3-year cancer-specific survival rates in the training cohort were 0.747, 0.774, and 0.780, respectively, and 0.671, 0.706, and 0.696, respectively, in the testing cohort. Through calibration curves and decision curve analyses, the nomograms displayed excellent performance.

Conclusions

Several factors related to the development and prognosis of BM in patients with ccRCC were identified. The nomograms constructed in this study are expected to become effective and precise tools for clinicians to improve cancer management.

Predicting metachronous liver metastasis in patients with colorectal cancer: development and assessment of a new nomogram

Background

We aimed to develop and validate a nomogram model, which could predict metachronous liver metastasis in colorectal cancer within two years after diagnosis.

Methods

A retrospective study was performed on colorectal cancer patients who were admitted to Beijing Shijitan Hospital from January 1, 2016 to June 30, 2019. The least absolute shrinkage and selection operator (LASSO) regression model was used to optimize feature selection for susceptibility to metachronous liver metastasis in colorectal cancer. Multivariable logistic regression analysis was applied to establish a predictive model through incorporating features selected in the LASSO regression model. C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were employed to assess discrimination, distinctiveness, consistency with actual occurrence risk, and clinical utility of candidate predictive model. Internal validation was assessed with bootstrapping method.

Results

Predictors contained in candidate prediction nomogram included age, CEA, vascular invasion, T stage, N stage, family history of cancer, and KRAS mutation. This model displayed good discrimination with a C-index of 0.787 (95% confidence interval: 0.728–0.846) and good calibration, whereas area under the ROC curve (AUC) of 0.786. Internal validation obtained C-index of 0.786, and AUC of validation cohort is 0.784. Based on DCA, with threshold probability range from 1 to 60%; this predictive model might identify colorectal cancer metachronous liver metastasis to achieve a net clinical benefit.

Conclusion

We have developed and validated a prognostic nomogram with good discriminative and high accuracy to predict metachronous liver metastasis in CRC patients.

Tumor Differentiation is the Dominant Prognostic Factor for Patients with Colorectal Neuroendocrine Neoplasms with Distant Metastasis

PURPOSE

Colorectal neuroendocrine neoplasms (NENs) are rare tumors. The prognosis and prognostic factors of metastatic colorectal NENs have not been fully elucidated.

METHODS

We retrospectively enrolled 77 consecutive patients diagnosed with colorectal NENs with synchronous distant metastases between 2000 and 2021. All patients were assigned to the neuroendocrine tumor (NET) group or the neuroendocrine carcinoma (NEC) group based on histological differentiation. Propensity score matching (PSM) was performed to minimize confounding bias. The Kaplan-Meier method was used to calculate the survival rates. Univariate and multivariate logistic regression analyses were performed to identify prognostic factors.

RESULTS

In total, 35 (45.5%) and 42 (54.5%) patients had well-differentiated NETs and poorly differentiated NECs, respectively. The median overall survival (OS) was 26 months for the entire cohort, and the 1-year, 3-year, and 5-year OS rates were 69.4%, 41.4%, and 27.8%, respectively. In the subgroup analysis, the median OS was 62 and 10 months for NETs and NECs, respectively. Univariate analysis demonstrated that patients with a primary tumor located in the colon, ulcerative tumors and poorly differentiated tumors were at higher risk for poorer progression-free survival (PFS) and OS. However, only histological differentiation was identified as an independent factor affecting OS (hazard ratio (HR) = 8.28, 95% confidence interval (CI): 2.98-23.01, P < 0.001) in multivariate analysis. After PSM, histological differentiation was further confirmed as the dominant factor affecting OS (HR = 6.09, 95% CI: 1.96-18.95, P=0.002)).

CONCLUSION

Histological differentiation was the most dominant prognostic factor in patients with metastatic colorectal NENs. Patients with well-differentiated NETs had a good chance of long-term survival.