BackgroundTo construct prognostic model of colorectal cancer (CRC) recurrence and metastasis (R&M) with traditional Chinese medicine (TCM) factors based on different machine learning (ML) methods. Aiming to offset the defects in the existing model lacking TCM factors.MethodsPatients with stage I-III CRC after radical resection were included as the model data set. The training set and the internal verification set were randomly divided at a ratio of 7: 3 by the “set aside method”. The average performance index and 95% confidence interval of the model were calculated by repeating 100 tests. Eight factors were used as predictors of Western medicine. Two types of models were constructed by taking “whether to accept TCM intervention” and “different TCM syndrome types” as TCM predictors. The model was constructed by four ML methods: logistic regression, random forest, Extreme Gradient Boosting (XGBoost) and support vector machine (SVM). The predicted target was whether R&M would occur within 3 years and 5 years after radical surgery. The area under curve (AUC) value and decision curve analysis (DCA) curve were used to evaluate accuracy and utility of the model.ResultsThe model data set consisted of 558 patients, of which 317 received TCM intervention after radical resection. The model based on the four ML methods with the TCM factor of “whether to accept TCM intervention” showed good ability in predicting R&M within 3 years and 5 years (AUC value > 0.75), and XGBoost was the best method. The DCA indicated that when the R&M probability in patients was at a certain threshold, the models provided additional clinical benefits. When predicting the R&M probability within 3 years and 5 years in the model with TCM factors of “different TCM syndrome types”, the four methods all showed certain predictive ability (AUC value > 0.70). With the exception of the model constructed by SVM, the other methods provided additional clinical benefits within a certain probability threshold.ConclusionThe prognostic model based on ML methods shows good accuracy and clinical utility. It can quantify the influence degree of TCM factors on R&M, and provide certain values for clinical decision-making.
Objective: To evaluate the effectiveness of Chinese Herbal Medicine (CHM) on leukopenia/neutropenia induced by chemotherapy in adults with colorectal cancer (CRC). Methods: Eight electronic databases were searched from their inception to June 2020. Randomized controlled trials with clarified sequence generation were qualified. Two reviewers independently conducted the screening and data extraction. Methodological quality was assessed using the Risk of Bias tool. RevMan 5.4 was applied to the meta-analysis. Results: Twenty-seven studies involving 1867 participants were qualified, of which 26 were included in the quantitative synthesis. Meta-analysis showed that CHM significantly reduced the incidence of leukopenia induced by chemotherapy (RR = 0.69; 95% CI 0.59-0.82), as well as the grade 3/4 leukopenia (RR = 0.71; 95% CI 0.55-0.90). Meanwhile,CHM decreased the occurrence of neutropenia (RR = 0.52, 95% CI 0.35-0.77), especially for the grades 3/4 neutropenia (RR = 0.42, 95% CI 0.27-0.64). Twenty-six of the included studies focused on the adverse events related to CHM. Conclusion: CHM may relieve neutropenia/leukopenia induced by chemotherapy in adults with colorectal cancer.
Objective: To access the comparative effectiveness and safety of different oral Chinese patent medicine (OCPM) versus oxaliplatin-based chemotherapy regimen (C) alone for colorectal cancer (CRC) through network meta-analysis (NMA). Methods: Several electronic databases were searched for randomized controlled trials (RCTs) concentrated on the use of OCPM to treat CRC with C from the inception of the databases to January 10, 2021. We performed frequentist NMA and indirect comparison to compare study outcomes from the included RCTs. The risk of bias of each study was assessed using the Cochrane risk of bias tool. Confidence in evidence was assessed using Confidence in Network Meta-Analysis (CINeMA). Results: A total of 31 RCTs with 1985 participants comparing 10 OCPM, namely, Antike (ATK), Shenyi (SY), Huachansu (HCS), Boerning (BEN), Xiaoaiping (XAP), Jinlong (JL), Compound matrine (CC), Pingxiao (PX), Xihuang pill (XHW), Kangaiping (KAP) were identified. The methodological quality of included RCTs was not very high. The results of the NMA showed that the comparisons were all indirect. Among diverse OCPM, ATK + C had the highest objective response rate (ORR) with a P-score of .63 with risk ratio (RR) of 1.37 (95% CI 1.12-1.66); with a RR of 1.96 (1.26-3.05), SY + C had the highest performance status with a P-score of .73; KAP + C had the lowest nausea and vomiting with a P-score of .91 and with a RR of 0.29 (0.10-0.79); and JL + C had lowest leukopenia with a P-score of .95 with a RR of 0.47 (0.31-0.72). The results of pairwise comparison suggested no difference in outcomes among 10 kinds of OCPM + C. The comparison-adjusted funnel plots suggested that there might not be small-study effects for outcomes. According to the CINeMa approach, the confidence rating of this NMA ranged from “very low” to “low” for various comparisons. Conclusion: Based on the NMA, ATK + C, SY + C, KAP + C and JL + C were associated with more preferable and options for CRC patients when referring to ORR, performance status, nausea and vomiting, and leukopenia, respectively. However, owing to the limitations of this research, the above conclusions require further verification by more high-quality RCTs. PROSPERO registration: CRD42020160658.
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