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Background: Little is understood about the association between psychosomatic symptoms and advanced cancer among older Chinese patients. Methods: This secondary analysis was part of a multicenter cross-sectional study based on an electronic patient-reported outcome platform. Patients with advanced cancer were included between August 2019 and December 2020 in China. Participants (over 60 years) completed the MD Anderson Symptom Inventory (MDASI) and Hospital Anxiety and Depression Scale (HADS) to measure symptom burden. Network analysis was also conducted to investigate the network structure, centrality indices (strength, closeness, and betweenness) and network stability. Results: A total of 1022 patients with a mean age of 66 (60–88) years were included; 727 (71.1%) were males, and 295 (28.9%) were females. A total of 64.9% of older patients with advanced cancer had one or more symptoms, and up to 80% had anxiety and depression. The generated network indicated that the physical symptoms, anxiety and depression symptom communities were well connected with each other. Based on an evaluation of the centrality indices, 'distress/feeling upset' (MDASI 5) appears to be a structurally important node in all three networks, and 'I lost interest in my own appearance' (HADS-D4) had the lowest centrality indices. The network stability was relatively high (> 0.7). Conclusion: The symptom burden remains high in older patients with advanced cancer in China. Psychosomatic symptoms are highly interactive and often present as comorbidities. This network can be used to provide targeted interventions to optimize symptom management in older patients with advanced cancer in China. Trial registration: Chinese Clinical Trial Registry (ChiCTR1900024957), registered on 06/12/2020. [ABSTRACT FROM AUTHOR] more...

Purpose: The present study aimed to develop prognostic prediction models based on machine learning (ML) for non-metastatic colon cancer (CRC), which can provide a precise quantitative risk assessment and serve as an assistive method for treatment strategy development. The possibility of improving prediction accuracy using nonlinear methods compared to linear methods was investigated. Patients and Methods: A cancer-specific survival (CSS) model constructed using logistic regression, extreme gradient boosting (XGBoost), and random forest algorithms was trained on the Surveillance, Epidemiology, and End Results datasets for 15,254 patients with non-metastatic CRC (split into training [70%] and internal validation [30%] datasets) and externally validated with an outpatient cohort of 311 cases from Xiyuan Hospital in China. A Chinese cohort was also used to develop recurrence and metastasis (R&M) models for CRC patients. The experiments for each model were performed 100 times to obtain average scores and 95% confidence intervals. The model performance was evaluated using the area under the receiver operating characteristic curve (AUC) values. Results: The XGBoost approach showed the highest AUC values of 0.86 (0.84– 0.88), 0.82 (0.81– 0.83), and 0.81 (0.79– 0.82) for one-, three-, and five-year CSS cohorts, respectively, along with a relatively high generalization ability. The XGBoost approach also performed best for the R&M model, with the AUC values of 0.71 (0.64– 0.79), 0.79 (0.74– 0.86), and 0.89 (0.82– 0.95) for one-, three-, and five-year R&M cohorts, respectively. The rankings of predictor importance for the CSS and R&M models were different, and the higher model accuracy was associated with more prognostic predictors. Conclusion: Three different ML algorithms for developing prognostic prediction models for non-metastatic CRC were compared. The predictive performance results showed that the nonlinear XGBoost approach performed best, suggesting that it can be used for quantifying the prognostic risk. It was also demonstrated that the model performance can be improved when more prognostic predictors are considered. [ABSTRACT FROM AUTHOR] more...

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. more...

BACKGROUND Lung cancer is the most common cause of cancer-associated deaths worldwide. This study aimed to investigate the efficacy and safety of Traditional Chinese Medicine combining EGFR-TKIs in treatment of NSCLC patients harboring EGFR mutations. MATERIAL AND METHODS This study involved 153 advanced-stage NSCLC patients harboring EGFR mutations. Patients were divided into a Control group (administered EGFR-TKI, n=61) and an Experimental group (administered Traditional Chinese Medicine combining EGFR and TKI, n=92). Progression-free survival (PFS) was evaluated for exon 19 deletion and/or 21 deletion patients. Disease control rate (DCR) was assessed to observe therapeutic effects. Adverse effects, including rashes, diarrhea, ALT/AST increase, dental ulcers, and onychia lateralis, were also evaluated. RESULTS TCM combining EGFR-TKI (90.11%) demonstrated no DCR improvement compared to single EGFR-TKI (83.33%) (p>0.05). Median PFS (mPFS) of TCM combining EGFR-TKI (13 months) was significantly longer compared to that in the single EGFR-TKI group (8.8 months) (p=0.001). For 19DEL mutant NSCLC, the mPFS (11 months) in TCM combining EGFR-TKI was significantly longer compared to single EGFR-TKI (8.5 months) (p=0.007). The mPFS of L858 mutant NSCLC patients in EGFR-TKI combining CTM (14 months) was significantly longer compared to single EGFR-TKI (9.5 months) (p=0.015). TCM combining EGFR-TKI was more inclined to prolong mPFS of NSCLC with exon 21 deletion. TCM combining EGFR-TKI illustrated no additional adverse effects in NSCLC patients (p=0.956). CONCLUSIONS Application of Traditional Chinese Medicine prolonged progression-free survival and enhanced therapeutic effect in NSCLC patients harboring EGFR mutations receiving EGFR-TKI treatment. Meanwhile, adjunctive Chinese medicine combining EGFR-TKI in NSCLC with EGFR mutations caused no adverse effects. more...

To control mosquito-borne diseases such as dengue, malaria, and Zika, {\it Wolbachia}-infected male mosquitoes have been released in open areas to suppress wild mosquito population driven by cytoplasmic incompatibility (CI). In this work, we initiate a preliminary assessment on how the CI intensity $\xi$, and the mating competitiveness $\mu$ of released males relative to wild males, impact the suppression efficacy by a delay differential equation model. Our analysis identifies a threshold CI intensity $\xi_0\in (0, 1)$ as an increasing function of the natural reproduction rate of the wild mosquitoes, and a threshold value $r^*$ for the ratio $r(t)$ between the numbers of released males and wild males. The population suppression fails when $\xi\le \xi_0$, and succeeds when $\xi>\xi_0$ and $r(t)\ge r^*$. Our analyses indicate that $\xi$ plays a more important role than $\mu$ in the population suppression. For instance, a slight decrease of $\xi$ from 1 to 0.92 is more devastating than halving $\mu$ from 1 to 0.5. In our estimation of the optimal starting date for infected male release to target a more than $95\%$ wild population reduction during the peak season of dengue in Guangzhou, we find that the optimal date is almost independent of $\mu$ but is sensitive to $\xi$. If CI is complete, then starting about two months ahead can be an optimal option for less financial and labor costs. A slight reduction in the CI intensity requires a considerably earlier starting date. more...