A Prognostic Scoring System to Predict Survival Outcome of Resectable Colorectal Liver Metastases in this Modern Era

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of colorectal cancer, 2024 update

The 2024 updates of the Chinese Society of Clinical Oncology (CSCO) Clinical Guidelines for the diagnosis and treatment of colorectal cancer emphasize standardizing cancer treatment in China, highlighting the latest advancements in evidence-based medicine, healthcare resource access, and precision medicine in oncology. These updates address disparities in epidemiological trends, clinicopathological characteristics, tumor biology, treatment approaches, and drug selection for colorectal cancer patients across diverse regions and backgrounds. Key revisions include adjustments to evidence levels for intensive treatment strategies, updates to regimens for deficient mismatch repair (dMMR)/ microsatellite instability-high (MSI-H) patients, proficient mismatch repair (pMMR)/ microsatellite stability (MSS) patients who have failed standard therapies, and rectal cancer patients with low recurrence risk. Additionally, recommendations for digital rectal examination and DNA polymerase epsilon (POLE)/ DNA polymerase delta 1 (POLD1) gene mutation testing have been strengthened. The 2024 CSCO Guidelines are based on both Chinese and international clinical research, as well as expert consensus, ensuring their relevance and applicability in clinical practice, while maintaining a commitment to scientific rigor, impartiality, and timely updates.

The impact of neoadjuvant therapy on the prognostic value of preoperative neutrophil-to-lymphocyte ratio for colorectal liver metastases: a multi-center cohort study

BACKGROUND

Neutrophil-to-lymphocyte ratio (NLR) is a promising prognostic marker for patients undergoing hepatectomy for colorectal liver metastases (CRLM). However, its prognostic value in patients receiving neoadjuvant therapy (NAT) has not been sufficiently addressed.

METHODS

From 2013 to 2023, a cohort of 692 patients with CRLM receiving hepatectomy were enrolled in five centers. Clinicopathological characteristics were obtained from a prospectively maintained multi-center database. The effect of NLR (> 2 versus ≤ 2) on overall survival (OS) and recurrence-free survival was estimated by Kaplan-Meier analysis. Univariable and multivariable Cox regression analysis was applied to investigate the influence of individual clinicopathological parameters on OS.

RESULTS

In the entire cohort, the median NLR level was 2.11 (0.30-16.33). There were 307 (44.4%) patients receiving NAT followed by hepatectomy, while 385 (55.6%) patients undergoing upfront surgery. Notably, patients in the NAT group showed significantly lower NLR level than those in the upfront surgery group (1.83 versus 2.32, P < 0.001). In the upfront surgery group, high NLR was significantly associated with worse OS, independent of other factors (HR = 1.49, 95% CI 1.08-2.05, P = 0.02). In the NAT group, there was no significant difference in OS between the high NLR and low NLR group.

CONCLUSION

The prognostic value of NLR in surgically resected CRLM is potentially influenced by NAT in the modern era.

GAME-SCORE predicts pathological and radiological response to chemotherapy in patients with colorectal liver metastases

BACKGROUND

Genetic And Morphological Evaluation (GAME) score is the newest prognostic model for patient with colorectal liver metastases (CRLMs). Pathological and radiological responses to neoadjuvant chemotherapy (NAC) are key factors for prognostic stratification of these patients. The present study aims to evaluate the GAME-score's ability to predict pathological and radiologic responses to NAC.

METHODS

CRLM patients who underwent liver resection after NAC from January 2010 to December 2021 were categorized by GAME scores: low risk (LR, 0-1), moderate risk (MR, 2-3), and high risk (HR, ≥4). Correlations between groups and radiological/pathological features were analyzed. Poor pathological response was defined as Tumor Regression Grade 4-5.

RESULTS

Of 1054 liver resections for CRLMs, 448 were included. GAME scores were LR: 80 (18 %), MR: 228 (51 %), and HR: 140 (31 %). In this cohort, HR-GAME scores were associated with lower pathological response (LR: 67.1 %, MR: 74.9 %, HR: 82.6 %; p = 0.010). Radiologic progression occurred in 10 % of HR patients, significantly more than in LR (3.8 %) and MR (3.5 %) groups (p = 0.011). Multivariable analysis for independent predictors of pathological response confirmed HR-GAME (RR 1.843, p=0.025) along with age higher than 70 years (RR 2.111, p=0.022) and irinotecan-based NAC (RR 3.066, p < 0.001). For radiological progression disease after NAC, the HR-GAME score (RR 2.77, p=0.016) was the only independent predictor. HR-GAME scores were also associated with higher rates of mucinous differentiation (p = 0.021), satellitosis (p = 0.001), vascular invasion (p = 0.011), and perineural invasion (p = 0.010).

CONCLUSIONS

GAME score category should be considered into planning of therapeutic strategy of patients with CRLMs.

Radiomics analysis of baseline computed tomography to predict oncological outcomes in patients treated for resectable colorectal cancer liver metastasis

OBJECTIVE

The purpose of this study was to determine and compare the performance of pre-treatment clinical risk score (CRS), radiomics models based on computed (CT), and their combination for predicting time to recurrence (TTR) and disease-specific survival (DSS) in patients with colorectal cancer liver metastases.

METHODS

We retrospectively analyzed a prospectively maintained registry of 241 patients treated with systemic chemotherapy and surgery for colorectal cancer liver metastases. Radiomics features were extracted from baseline, pre-treatment, contrast-enhanced CT images. Multiple aggregation strategies were investigated for cases with multiple metastases. Radiomics signatures were derived using feature selection methods. Random survival forests (RSF) and neural network survival models (DeepSurv) based on radiomics features, alone or combined with CRS, were developed to predict TTR and DSS. Leveraging survival models predictions, classification models were trained to predict TTR within 18 months and DSS within 3 years. Classification performance was assessed with area under the receiver operating characteristic curve (AUC) on the test set.

RESULTS

For TTR prediction, the concordance index (95% confidence interval) was 0.57 (0.57-0.57) for CRS, 0.61 (0.60-0.61) for RSF in combination with CRS, and 0.70 (0.68-0.73) for DeepSurv in combination with CRS. For DSS prediction, the concordance index was 0.59 (0.59-0.59) for CRS, 0.57 (0.56-0.57) for RSF in combination with CRS, and 0.60 (0.58-0.61) for DeepSurv in combination with CRS. For TTR classification, the AUC was 0.33 (0.33-0.33) for CRS, 0.77 (0.75-0.78) for radiomics signature alone, and 0.58 (0.57-0.59) for DeepSurv score alone. For DSS classification, the AUC was 0.61 (0.61-0.61) for CRS, 0.57 (0.56-0.57) for radiomics signature, and 0.75 (0.74-0.76) for DeepSurv score alone.

CONCLUSION

Radiomics-based survival models outperformed CRS for TTR prediction. More accurate, noninvasive, and early prediction of patient outcome may help reduce exposure to ineffective yet toxic chemotherapy or high-risk major hepatectomies.

Personalized prediction of postoperative complication and survival among Colorectal Liver Metastases Patients Receiving Simultaneous Resection using machine learning approaches: A multi-center study

BACKGROUND

To predict clinical important outcomes for colorectal liver metastases (CRLM) patients receiving colorectal resection with simultaneous liver resection by integrating demographic, clinical, laboratory, and genetic data.

METHODS

Random forest (RF) models were developed to predict postoperative complications and major complications (binary outcomes), as well as progression-free survival (PFS) and overall survival (OS) (time-to-event outcomes) of the CRLM patients based on data from two hospitals. The models were validated on an external dataset from an independent hospital. The clinical utility of the models was assessed via decision curve analyses (DCA).

RESULTS

There were 1067 patients included in survival prediction analyses and 1070 patients included in postoperative complication prediction analyses. The RF models provided an assessment of the model contributions of features for outcomes and suggested KRAS, BRAF, and MMR status were salient for the PFS or OS predictions. RF model of PFS showed that the Brier scores at 1-, 3-, and 5-year PFS were 0.213, 0.202 and 0.188; and the AUCs of 1-, 3- and 5-year PFS were 0.702, 0.720 and 0.743. RF model of OS revealed that Brier scores of 1-,3-, and 5-year OS were 0.040, 0.183 and 0.211; and the AUCs of 1-, 3- and 5-year OS were 0.737, 0.706 and 0.719. RF model for postoperative complication resulted in an AUC of 0.716 and a Brier score of 0.196. DCA curves clearly demonstrated that the RF models for these outcomes exhibited a superior net benefit across a wide range of threshold probabilities, signifying their favorable clinical utility. The RF models consistently exhibited robust performance in both internal cross-validation and external validation. The individualized risk profile predicted by the models closely aligned with the actual survival outcomes observed for the patients. A web-based tool (https://kanli.shinyapps.io/CRLMRF/) was provided to demonstrate the practical use of the prediction models for new patients in the clinical setting.

CONCLUSION

The predictive models and a web-based tool for personalized prediction demonstrated a moderate predictive performance and favorable clinical utilities on several key clinical outcomes of CRLM patients receiving simultaneous resection, which could facilitate the clinical decision-making and inform future interventions for CRLM patients.

Clinical Prediction Models for Prognosis of Colorectal Liver Metastases: A Comprehensive Review of Regression-Based and Machine Learning Models

Colorectal liver metastasis (CRLM) is a disease entity that warrants special attention due to its high frequency and potential curability. Identification of "high-risk" patients is increasingly popular for risk stratification and personalization of the management pathway. Traditional regression-based methods have been used to derive prediction models for these patients, and lately, focus has shifted to artificial intelligence-based models, with employment of variable supervised and unsupervised techniques. Multiple endpoints, like overall survival (OS), disease-free survival (DFS) and development or recurrence of postoperative complications have all been used as outcomes in these studies. This review provides an extensive overview of available clinical prediction models focusing on the prognosis of CRLM and highlights the different predictor types incorporated in each model. An overview of the modelling strategies and the outcomes chosen is provided. Specific patient and treatment characteristics included in the models are discussed in detail. Model development and validation methods are presented and critically appraised, and model performance is assessed within a proposed framework.

A nomogram was developed using clinicopathological features to predict postoperative liver metastasis in patients with colorectal cancer

PURPOSE

The objective of this study is to examine the risk factors that contribute to the development of liver metastasis (LM) in patients who have suffered radical resection for colorectal cancer (CRC), and to establish a nomogram model that can be used to predict the occurrence of the LM.

METHODS

The present study enrolled 1377 patients diagnosed with CRC between January 2010 and July 2021. The datasets were allocated to training (n = 965) and validation (n = 412) sets in a randomly stratified manner. The study utilized univariate and multivariate logistic regression analyses to establish a nomogram for predicting LM in patients with CRC.

RESULTS

Multivariate analysis revealed that T stage, N stage, number of harvested lymph nodes (LNH), mismatch repair (MMR) status, neutrophil count, monocyte count, postoperative carcinoembryonic antigen (CEA) levels, postoperative cancer antigen 125 (CA125) levels, and postoperative carbohydrate antigen 19-9 (CA19-9) levels were independent predictive factors for LM after radical resection. These factors were then utilized to construct a comprehensive nomogram for predicting LM. The nomogram demonstrated great discrimination, with an area under the curve (AUC) of 0.782 for the training set and 0.768 for the validation set. Additionally, the nomogram exhibited excellent calibration and significant clinical benefit as confirmed by the calibration curves and the decision curve analysis, respectively.

CONCLUSION

This nomogram has the potential to support clinicians in identifying high-risk patients who may develop LM post-surgery. Clinicians can devise personalized treatment and follow-up plans, ultimately leading to an improved prognosis for patients.

Impact of Molecular Status on Metastasectomy of Colorectal Cancer Liver Metastases

Although surgical resection could provide better survival for patients with colorectal cancer liver metastases (CRLM), the recurrence rate after resection of CRLM remains high. The progress of genome sequencing technologies has greatly improved the molecular understanding of colorectal cancer. In the era of genomics and targeted therapy, genetic mutation analysis is of great significance to guide systemic treatment and identify patients who can benefit from resection of CRLM. RAS and BRAF mutations and microsatellite instability/deficient deoxyribonucleic acid (DNA) mismatch repair status have been incorporated into current clinical practice. Other promising molecular biomarkers such as coexisting gene mutations and circulating tumor DNA are under active investigation. This study aimed to review the prognostic significance of molecular biomarkers in patients with CRLM undergoing metastasectomy based on the current evidence.

Complete Blood Count Alterations Prior to the Diagnosis of Colorectal Cancer May Help in the Detection of Synchronous Liver Metastases

Background and Aims: Colorectal cancer (CRC) represents 10% of all cancers worldwide with the highest incidence in developed countries; its incidence is also increasing in middle- and low-income countries. Population screening programs facilitate early diagnosis of the disease. When the diagnosis is carried out in advanced stages, approximately 80% of patients with liver metastases (LM) are considered unresectable at the time of diagnosis. In our study, variations in blood counts prior to CRC diagnosis were analyzed to assess whether they could be useful in identifying smaller, more manageable metastases at earlier stages for more effective treatment. Methods: A study was carried out using complete blood counts (CBCs) from CRC patients, obtained from primary health centers and the La Ribera University Hospital within La Ribera Health Department, Valencian Community, Spain, between July 2012 and September 2020. Data from CRC patients who presented synchronous liver metastasis (CRLM) were compared with those with CRC without LM at diagnosis (CRC patients). Results: Our analysis shows that at least 15 months before CRC diagnosis, a progressive alteration was observed in CBC parameters in both groups. A higher incidence of anemia (p < 0.001) was observed among CRLM patients in the three months prior to CRC diagnosis than in CRC patients showing no LM. Conclusions: A statistically significant deterioration of CBC was observed in patients with advanced-stage CRC and synchronous or early LM (CRLM) in the three months prior to diagnosis. The primary goal of incorporating CBC variations into predictive models is to identify individuals who are at a greater risk of developing metastatic colon cancer, leading to early diagnosis. Our research improves these models by highlighting a more pronounced and rapid decline in hemoglobin levels among CRLM patients. Identification of metastases at an earlier stage when they are smaller, more manageable, and more amenable to treatment may be a valuable tool to prevent their further progression.

Validation study of the JSHBPS nomogram for patients with colorectal liver metastases who underwent hepatic resection in the recent era - a nationwide survey in Japan

BACKGROUND

The Japanese Society of Hepato-Biliary-Pancreatic Surgery (JSHBPS) nomogram was developed to predict disease-free survival in patients with colorectal liver metastases (CRLM) undergoing upfront hepatectomy. However, the utility of the nomogram in patients with resected CRLM remains unknown in the current situation in which treatment strategies are changing with advances in drugs.

METHODS

Patients in the initial nomogram cohort (n = 727) and validation cohort (n = 2225) were divided into the upfront hepatectomy and preoperative chemotherapy groups. The nomogram was validated by measuring calibration and discrimination in the two cohorts. Calibration curves were plotted, and survival probabilities were compared. Finally, to quantify the discrimination power, we estimated the concordance index (C-index).

RESULTS

In the upfront hepatectomy group, the C-index was 0.63, the suitable cutoff value of the Beppu score was 7, and adjuvant chemotherapy was significantly effective limited to high-risk patients (Beppu score ≥7). The C-index was 0.56 in the preoperative chemotherapy group.

CONCLUSIONS

The JSHBPS nomogram remains beneficial for patients undergoing upfront hepatectomy in the recent era but is less effective for patients undergoing hepatectomy after chemotherapy. Patients with a Beppu score ≥7 showed high-risk recurrence, and adjuvant chemotherapy should be recommended for these patients.

Extensive Phenotypic Characterization of T Cells Infiltrating Liver Metastasis from Colorectal Cancer: A Potential Role in Precision Medicine

Colorectal cancer (CRC) is one of the most common cancers worldwide, with liver metastasis being its main cause of death. This study harvested fresh biological material from non-tumor and tumor tissue from 47 patients with CRC liver metastasis after surgery, followed by mechanical cellular extraction and stain-lyse-wash direct immunofluorescence technique. Here, 60 different T-cell populations were characterized by flow cytometry. Tumor samples were also subdivided according to their growth pattern into desmoplastic and non-desmoplastic. When we compared tumor versus non-tumor samples, we observed a significantly lower percentage of T-lymphocyte infiltration in the tumor in which the CD4⁺ T-cell density increased compared to the CD8⁺ T cells. T regulatory cells also increased within the tumor, even with an activated phenotype (HLA-DR⁺). A higher percentage of IL-17-producing cells was present in tumor samples and correlated with the metastasis size. In contrast, we also observed a significant increase in CD8⁺ follicular-like T cells (CD185⁺), suggesting a cytotoxic response to cancer cells. Additionally, most infiltrated T cells exhibit an intermediate activation phenotype (CD25⁺). In conclusion, our results revealed potential new targets and prognostic biomarkers that could take part in an algorithm for personalized medicine approaches improving CRC patients' outcomes.

Construction of a co-expression network and prediction of metastasis markers in colorectal cancer patients with liver metastasis

BACKGROUND

Colorectal cancer (CRC) is a common global malignancy associated with high invasiveness, high metastasis, and poor prognosis. CRC commonly metastasizes to the liver, where the treatment of metastasis is both difficult and an important topic in current CRC management.

METHODS

Microarrays data of human CRC with liver metastasis (CRCLM) were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database to identify potential key genes. Differentially expressed (DE) genes (DEGs) and DEmiRNAs of primary CRC tumor tissues and metastatic liver tissues were identified. Microenvironment Cell Populations (MCP)-counter was used to estimate the abundance of immune cells in the tumor micro-environment (TME), and weighted gene correlation network analysis (WGCNA) was used to construct the co-expression network analysis. Gene Ontology and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were conducted, and the protein-protein interaction (PPI) network for the DEGs were constructed and gene modules were screened.

RESULTS

Thirty-five pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened, and 610 DEGs (265 up-regulated and 345 down-regulated) and 284 DEmiRNAs were identified. The DEGs were mainly enriched in the complement and coagulation cascade pathways and renin secretion. Immune infiltrating cells including neutrophils, monocytic lineage, and cancer-associated fibroblasts (CAFs) differed significantly between primary tumor tissues and metastatic liver tissues. WGCN analysis obtained 12 modules and identified 62 genes with significant interactions which were mainly related to complement and coagulation cascade and the focal adhesion pathway. The best subset regression analysis and backward stepwise regression analysis were performed, and eight genes were determined, including F10, FGG, KNG1, MBL2, PROC, SERPINA1, CAV1, and SPP1. Further analysis showed four genes, including FGG, KNG1, CAV1, and SPP1 were significantly associated with CRCLM.

CONCLUSIONS

Our study implies complement and coagulation cascade and the focal adhesion pathway play a significant role in the development and progression of CRCLM, and FGG, KNG1, CAV1, and SPP1 may be metastatic markers for its early diagnosis.

Irinotecan- vs oxaliplatin-based regimens for neoadjuvant chemotherapy in colorectal liver metastasis patients: A retrospective study

BACKGROUND

Neoadjuvant chemotherapy (NC) improves the survival outcomes of selected patients with colorectal liver metastasis (CRLM). The benefits of irinotecan-based regimens in these patients are still under debate.

AIM

To compare the benefits of irinotecan- and oxaliplatin-based regimens in patients with resectable CRLM.

METHODS

From September 2003 to August 2020, 554 patients received NC and underwent hepatectomy for CRLM. Based on a 1:1 propensity score matching (PSM) model, 175 patients who received irinotecan were matched to 175 patients who received oxaliplatin to obtain two balanced groups regarding demographic, therapeutic, and prognostic characteristics.

RESULTS

Chemotherapy was based on oxaliplatin in 353 (63.7%) patients and irinotecan in 201 (36.3%). After PSM, the 5-year progression-free survival (PFS) and overall survival (OS) rates with irinotecan were 18.0% and 49.7%, respectively, while the 5-year PFS and OS rates with oxaliplatin were 26.0% and 46.8%, respectively. Intraoperative blood loss, operating time, and postoperative complications differed significantly between the two groups. In the multivariable analysis, carbohydrate antigen 19-9, RAS mutation, response to NC, tumor size > 5 cm, and tumor number > 1 were independently associated with PFS.

CONCLUSION

In NC in patients with CRLM, irinotecan is similar to oxaliplatin in survival outcomes, but irinotecan is superior regarding operating time, intraoperative blood loss, and postoperative complications.

Characterization of Genomic Alterations in Colorectal Liver Metastasis and Their Prognostic Value

Colorectal liver metastases (CRLMs) are clinically heterogeneous lesions with poor prognosis. Genetic alterations play a crucial role in their progression. The traditional Fong clinical risk score (Fong-CRS) is commonly used for risk stratification and prognosis prediction. By identifying the genomic alterations of CRLMs, we aimed to develop a mutation-based gene-signature-based clinical score (mut-CS) system to improve clinical prognostication. Tumour tissues from 144 patients with CRLMs were analysed with next-generation sequencing (NGS). A mut-CS scoring system considering the unique mutation-based gene signature, primary site, and Fong-CRS was developed and could identify CRLM patients with poor prognosis. The mean time-dependent receiver operating characteristic curve AUC value of the mut-CS system was greater than that of previously established scoring measures (the Fong-CRS, the e-clinical score, the presence of concomitant RAS and TP53 mutations, and other clinical traits). Taking together, we identified a mutant signature that exhibits a strong prognostic effect for CRLMs. Traditional clinical scoring system characteristics were incorporated into the new mut-CS scoring system to help determine the appropriate treatment for CRLMs.

Prognostic Models Incorporating RAS Mutation to Predict Survival in Patients with Colorectal Liver Metastases: A Narrative Review

Recurrence and survival vary widely among patients who undergo curative-intent resection of colorectal liver metastases (CRLM). Prognostic models provide estimated probabilities of these outcomes and allow the effects of multiple potentially interacting variables to be adjusted and assessed simultaneously. Although many prognostic models based on clinicopathologic factors have been developed since the 1990s to predict survival after resection of CRLM, these models vary in their predictive performance when applied to contemporary cohorts. Rat sarcoma viral oncogene homolog (RAS) mutation status is routinely tested in patients with metastatic colorectal cancer to predict response to anti-epidermal growth factor therapy. In addition, mutations in RAS predict survival and recurrence in patients undergoing hepatectomy for CRLM. Several recent prognostic models have incorporated RAS mutation status as a surrogate of tumor biology and combined revised clinicopathologic variables to improve the prediction of recurrence and survival. This narrative review aims to evaluate the differences between contemporary prognostic models incorporating RAS mutation status and their clinical applicability in patients considered for curative-intent resection of CRLM.

Impact of Preoperative CEA Uptrend on Survival Outcomes in Patients with Colorectal Liver Metastasis After Hepatectomy

BACKGROUND

Preoperative carcinoembryonic antigen (CEA) has been reported as a prognostic factor in patients with colorectal liver metastasis (CRLM) after hepatectomy. However, the impact of a preoperative "CEA uptrend" on prognosis after hepatectomy in these patients remains unknown. This study assessed the impact of CEA uptrend on prognosis in patients undergoing hepatectomy for CRLM.

METHODS

Consecutive patients with CRLM who underwent hepatectomy between 2009 and 2018 were retrospectively analyzed. Patients with CRLM for whom CEA was measured both around 1 month before (CEA-1m) and within 3 days (CEA-3d) before hepatectomy were enrolled. A CEA-3d higher than both the upper limit of normal (5 ng/ml) and CEA-1m was defined as a CEA uptrend.

RESULTS

Study participants comprised 212 patients with CRLM. Of these, 88 patients (41.5%) showed a CEA uptrend. CEA uptrend indicated better discriminatory ability (corrected Akaike information criteria, 733.72) and homogeneity (likelihood ratio chi-square value, 18.80) than CEA-3d or CEA-1m. Patients with CEA uptrend showed poorer overall survival than those without CEA uptrend (p < 0.001). After adjusting for known prognostic factors, the prognostic significance of CEA uptrend retained (hazard ratio 2.63, 95% confidence interval 1.63-4.26, p < 0.001). In subgroup analyses, the prognostic significance of CEA uptrend was retained irrespective of the status of RAS mutation or response to preoperative chemotherapy.

CONCLUSIONS

CEA uptrend offers better prediction of survival outcomes than conventional CEA measurements in patients undergoing hepatectomy for CRLM.

High Neutrophil-To-Lymphocyte Ratio (NLR) and Systemic Immune-Inflammation Index (SII) Are Markers of Longer Survival After Metastasectomy of Patients With Liver-Only Metastasis of Rectal Cancer

Background: The literature data regarding colon cancer patients with liver-only metastases (CLM) show that NLR determined before metastasectomy is a prognostic marker of shorter relapse-free survival (RFS), but no results has been reported to date for rectal cancer patients with liver-only metastases (RLM). This study aimed to investigate the NLR and SII in CLM and RLM.

Methods: Relapse-free (RFS) and overall survival (OS) were evaluated in 67 CLM and 103 RLM patients with a median follow-up of 46.5 and 59.8 months, respectively. Pre- and/or postoperative chemotherapy ± targeted treatment was applied in 96% and 87% of CLM and RLM patients, respectively. The cut-off level for hematologic parameters were determined by receiver operating characteristic (ROC) analysis. Univariate analysis was performed by Kaplan-Meier method and log rank test. For multivariate analysis Cox regression was applied.

Results: In univariate analysis low NLR (cut-off 2) and SII (535) were predictors of longer RFS in case of CLM (p < 0.01). In contrast, for RLM high NLR (2.42) and SII (792) were predictors of longer RFS (p < 0.001). For RLM both NLR and SII proved to be independent markers of RFS (HR 0.66 (95% CI 0.52–0.84) and 0.73 (0.57–0.91), respectively) and OS (0.76 (0.58–0.99) and 0.66 (0.5–0.87), respectively). Only NLR (1.44 (1.04–1.99)) was independent marker of RFS for CLM. The preoperative treatment has not influenced the role of NLR or SII.

Conclusion: In contrast to CLM, in RLM the high NLR or SII determined before metastasectomy proved to be independent prognostic factors of longer RFS and OS.

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.