Nomogram Incorporating Preoperative Testing Markers for the prediction of Early Recurrence for Colorectal Liver Metastases with Neoadjuvant Chemotherapy followed by Hepatectomy

Chen, Qichen; Zhang, Yizhou; Li, Xingchen; Huang, Zhen; Zhao, Hong; Cai, Jianqiang

doi:10.7150/jca.65677

Cited by 7 publications

(8 citation statements)

References 48 publications

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“…In addition, it was reported that the same or different therapies with curative intent after initial treatment for CRLM patients who suffered from early recurrence, such as repeated local treatments ( 25 ), might improve survival outcomes, so the early recognition of these patients would help to guide personalized medical management. Also, the proportion of early recurrence among CRLM patients with recurrence in the current study was consistent with previous studies ( 26 - 28 ). TBS is a prognostic index that combines the impacts of tumour size and number, and many previous studies have explored its utility in discriminating the survival of CRLM patients.…”

Section: Discussionsupporting

confidence: 92%

Nomogram predicting early recurrence defined by the minimum P value approach for colorectal liver metastasis patients receiving colorectal cancer resection with simultaneous liver metastasis resection: development and validation

Deng¹,

Chen²,

Liu³

et al. 2023

J Gastrointest Oncol

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Background Simultaneous resections have been increasingly performed for colorectal liver metastasis patients. However, studies explored risk stratification for these patients are scarce. Among which, a clear definition of early recurrence remains controversial and models for predicting early recurrence in these patients are lacking. Methods Colorectal liver metastasis patients who developed recurrence followed by simultaneous resection were enrolled. Early recurrence was determined by the minimum P value method, and patients were divided into an early recurrence group and late recurrence group. Standard clinical data were collected from each patient including demographics features, preoperative laboratory tests and postoperative regular follow-up results. All the data were accessed by clinicians and recorded accordingly. The nomogram for early recurrence was constructed in the training cohort and validated externally in the test cohort. Results The optimal value of early recurrence by the minimum P value method was 13 months. A total of 323 patients were included in the training cohort, of which 241 (74.6%) experienced early recurrence. Seventy-one patients were included in the test cohort, of which 49 (69.0%) experienced early recurrence. Significantly worse post-recurrence survival (median 27.0 vs. 52.8 months, P=0.00083) and overall survival (median 33.8 vs. 70.9 months, P<0.0001) were observed in patients with early recurrence in the training cohort. Positive lymph node metastases (P=0.003), tumour burden scores ≥4.09 (P=0.001), preoperative neutrophil-to-lymphocyte ratios ≥1.44 (P=0.006), preoperative blood urea nitrogen levels ≥3.55 µmol/L (P=0.017) and postoperative complications (P=0.042) were independently associated with early recurrence, and all these predictors were included in the nomogram. The nomogram for predicting early recurrence had a receiver operating characteristic curve of 0.720 in the training cohort and a receiver operating characteristic curve of 0.740 in the test cohort. The Hosmer-Lemeshow test and calibration curves showed acceptable model calibration in the training set (P=0.7612) and in the test set (P=0.8671). The decision curve analysis results for the training cohort and test cohort also indicated that the nomogram showed good clinical applicability. Conclusions Our findings provide clinicians with new insights into accurate risk stratification for colorectal liver metastasis patients receiving simultaneous resection and contributing to the management of patients.

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Section: Discussionsupporting

confidence: 92%

Nomogram predicting early recurrence defined by the minimum P value approach for colorectal liver metastasis patients receiving colorectal cancer resection with simultaneous liver metastasis resection: development and validation

Deng¹,

Chen²,

Liu³

et al. 2023

J Gastrointest Oncol

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“…This review included 24 studies, comprising 12,705 patients who underwent LR for CRLM, with a comprehensive summary presented in Table 1 . Among these, twelve studies adopted a prospective cohort design [ 12 , 18 , 21 , 22 , 28 – 32 , 34 – 36 ], with the remaining adopting a retrospective cohort approach [ 14 – 16 , 19 , 20 , 23 – 27 , 33 , 37 ]. The publication years of the studies spanned from 2007 to 2023.…”

Section: Resultsmentioning

confidence: 99%

“…The publication years of the studies spanned from 2007 to 2023. In terms of geographical distribution, 15 studies originated from Asia [ 14 – 16 , 19 , 20 , 23 , 24 , 26 , 27 , 29 – 31 , 33 , 35 , 37 ], 7 from Europe [ 12 , 18 , 22 , 25 , 28 , 32 , 34 ], 1 from Australia [ 36 ], and the other one from the United States [ 21 ]. The recruitment period ranged from 1986 to 2020, with the median duration of follow-up ranging varying from 22 to 86.3 months.…”

Section: Resultsmentioning

confidence: 99%

“…Adjustment for other PF 6. Statistical analysis and reporting Overall Bhogal,2015, [ 18 ] Mod a Mod c Low Low Low Low Mod Chen,2022, [ 19 ] Low Low Low Low Low Low Low Dai,2021, [ 15 ] Low Low Low Low Low Low Low Deng,2023, [ 20 ] Low Mod c Low Low Low Low Low Finkelstein,2008, [ 21 ] Mod a Mod c Low Low Low Low Mod Imai,2016, [ 22 ] Low Mod c Low Low Low Low Low Inoue,2020 [ 23 ] Low Mod Low Low Low Lo...…”

Section: Resultsmentioning

confidence: 99%

“…In this study, class I evidence demonstrated that a CRS > 2 increase the risk of ER. Furthermore, several studies have utilized multiple prognostic factors to develop nomograms to better predict ER of CRLM [ 15 , 19 , 20 ]. However, the generalizability of these nomograms requires further research, and there is an urgent need to develop a universal ER risk prediction score.…”

Section: Discussionmentioning

confidence: 99%

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Prognostic factors associated with early recurrence following liver resection for colorectal liver metastases: a systematic review and meta-analysis

Tian,

Wang,

Wen

et al. 2024

BMC Cancer

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Background Colorectal cancer (CRC) is the 3rd most common malignancy with the liver being the most common site of metastases. The recurrence rate of colorectal liver metastases (CRLM) after liver resection (LR) is notably high, with an estimated 40% of patients experiencing recurrence within 6 months. In this context, we conducted a meta-analysis to synthesize and evaluate the reliability of evidence pertaining to prognostic factors associated with early recurrence (ER) in CRLM following LR. Methods Systematic searches were conducted from the inception of databases to July 14, 2023, to identify studies reporting prognostic factors associated with ER. The Quality in Prognostic Factor Studies (QUIPS) tool was employed to assess risk-of-bias for included studies. Meta-analysis was then performed on these prognostic factors, summarized by forest plots. The grading of evidence was based on sample size, heterogeneity, and Egger’s P value. Results The study included 24 investigations, comprising 12705 individuals, during an accrual period that extended from 2007 to 2023. In the evaluation of risk-of-bias, 22 studies were rated as low/moderate risk, while two studies were excluded because of high risk. Most of the studies used a postoperative interval of 6 months to define ER, with 30.2% (95% confidence interval [CI], 24.1–36.4%) of the patients experiencing ER following LR. 21 studies were pooled for meta-analysis. High-quality evidence showed that poor differentiation of CRC, larger and bilobar-distributed liver metastases, major hepatectomy, positive surgical margins, and postoperative complications were associated with an elevated risk of ER. Additionally, moderate-quality evidence suggested that elevated levels of carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA199), lymph node metastases (LNM) of CRC, and a higher number of liver metastases were risk factors for ER. Conclusion This review has the potential to enhance the efficacy of surveillance strategies, refine prognostic assessments, and guide judicious treatment decisions for CRLM patients with high risk of ER. Additionally, it is essential to undertake well-designed prospective investigations to examine additional prognostic factors and develop salvage therapeutic approaches for ER of CRLM.

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Preoperative identification of early extrahepatic recurrence after hepatectomy for colorectal liver metastases: A machine learning approach

Kawashima,

Endo,

Woldesenbet

et al. 2024

World j. surg.

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BackgroundMachine learning (ML) may provide novel insights into data patterns and improve model prediction accuracy. The current study sought to develop and validate an ML model to predict early extra‐hepatic recurrence (EEHR) among patients undergoing resection of colorectal liver metastasis (CRLM).MethodsPatients with CRLM who underwent curative‐intent resection between 2000 and 2020 were identified from an international multi‐institutional database. An eXtreme gradient boosting (XGBoost) model was developed to estimate the risk of EEHR, defined as extrahepatic recurrence within 12 months after hepatectomy, using clinicopathological factors. The relative importance of factors was determined using Shapley additive explanations (SHAP) values.ResultsAmong 1410 patients undergoing curative‐intent resection, 131 (9.3%) patients experienced EEHR. Median OS among patients with and without EEHR was 35.4 months (interquartile range [IQR] 29.9–46.7) versus 120.5 months (IQR 97.2–134.0), respectively (p < 0.001). The ML predictive model had c‐index values of 0.77 (95% CI, 0.72–0.81) and 0.77 (95% CI, 0.73–0.80) in the entire dataset and the validation data set with bootstrapping resamples, respectively. The SHAP algorithm demonstrated that T and N primary tumor categories, as well as tumor burden score were the three most important predictors of EEHR. An easy‐to‐use risk calculator for EEHR was developed and made available online at: https://junkawashima.shinyapps.io/EEHR/.ConclusionsAn easy‐to‐use online calculator was developed using ML to help clinicians predict the chance of EEHR after curative‐intent resection for CRLM. This tool may help clinicians in decision‐making related to treatment strategies for patients with CRLM.

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Nomogram Incorporating Preoperative Testing Markers for the prediction of Early Recurrence for Colorectal Liver Metastases with Neoadjuvant Chemotherapy followed by Hepatectomy

Cited by 7 publications

References 48 publications

Nomogram predicting early recurrence defined by the minimum P value approach for colorectal liver metastasis patients receiving colorectal cancer resection with simultaneous liver metastasis resection: development and validation

Nomogram predicting early recurrence defined by the minimum P value approach for colorectal liver metastasis patients receiving colorectal cancer resection with simultaneous liver metastasis resection: development and validation

Prognostic factors associated with early recurrence following liver resection for colorectal liver metastases: a systematic review and meta-analysis

Preoperative identification of early extrahepatic recurrence after hepatectomy for colorectal liver metastases: A machine learning approach

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