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New idea for treatment strategies for Barcelona Clinic Liver Cancer stages based on a network meta-analysis.

ABSTRACT: Currently, the Barcelona Clinic Liver Cancer staging (BCLC) system still remains controversies in the management of hepatocellular carcinoma. We are trying to determine the best therapeutic strategy for each BCLC stage through a network meta-analysis and provide a new treatment idea.We conducted a systematic literature search of the PubMed, EMBASE, and Cochrane Library databases and extracted data from randomized controlled trials (RCTs) that compared various strategies. Network meta-analyses were conducted in ADDIS by evaluating different overall survival of each stage. Cumulative probability was used to rank the included strategies. A node-splitting model assessed whether direct and indirect evidence on a specific node was in agreement.Of the 24 included RCTs, 3667 patients were included. Based on the probability P values, the results showed that TACE plus surgical resection (SR) was the first choice for BCLC Stage A (P?=?.38 and P?=?.52 for 3- and 5-year OS, respectively). The application of SR was the best strategy for BCLC Stage B (P?=?.51 and P?=?.95 for 1- and 3-year OS, respectively). For Stage C, whole net connections could not be established in this research, but combined therapy seemed to produce better results based on 3 separated net connections (P?=?.92, P?=?.80, and P?=?.69 for 1-year OS).The updated therapy strategies discussed in this study are recommended. More importantly, we deemed that the recommended strategy for each patient may be subject to adjustment due to individual clinical factors. The applicable scope of each strategy should also be evaluated before application.

SUBMITTER: Li K

PROVIDER: S-EPMC5440153 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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New idea for treatment strategies for Barcelona Clinic Liver Cancer stages based on a network meta-analysis.

Li Kun K Wang Hai-Tao HT He Yu-Kun YK Guo Tao T

Medicine 20170501 20

<h4>Background</h4>Currently, the Barcelona Clinic Liver Cancer staging (BCLC) system still remains controversies in the management of hepatocellular carcinoma. We are trying to determine the best therapeutic strategy for each BCLC stage through a network meta-analysis and provide a new treatment idea.<h4>Methods</h4>We conducted a systematic literature search of the PubMed, EMBASE, and Cochrane Library databases and extracted data from randomized controlled trials (RCTs) that compared various s ...[more]

PMID: 28514316

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Project description:BackgroundPostoperative adjuvant transcatheter arterial chemoembolization (PA-TACE) is effective in preventing the recurrence of hepatocellular carcinoma (HCC) in patients treated with surgery. However, there is a lack of reports studying the risk factors associated with recurrence in HCC patients who received PA-TACE. In this study, we identified the independent risk factors for recurrence of HCC patients who received PA-TACE. We also developed a novel, effective, and valid nomogram to predict the individual probability of recurrence, 1, 3, and 5 years after PA-TACE.MethodsA retrospective study was performed to identify the independent risk factors for recurrence of HCC in a group of 502 patients diagnosed in stage B based on the Barcelona Clinic Liver Cancer (BCLC) evaluation system for HCC that underwent curative resections. Then, subgroup analysis was performed for 184 patients who received PA-TACE, who were included in the training cohort. The other 147 HCC patients were included in a validation cohort. A recurrence-free survival (RFS)-predicting nomogram was constructed, and results were assessed using calibration and decision curves and a time-dependent AUC diagram.ResultsPA-TACE was shown to be a significant independent prognostic value for patients with BCLC stage B [p < 0.001, hazard ratio (HR) = 0.508, 95% CI = 0.375-0.689 for OS, p = 0.002; HR = 0.670, 95%CI = 0.517-0.868 for RFS]. Alpha fetoprotein (AFP), tumor number, tumor size, microvascular invasion (MVI), and differentiation were considered as independent risk factors for RFS in the training cohort, and these were further confirmed in the validation cohort. Next, a nomogram was constructed to predict RFS. The C-index for RFS in the nomogram was 0.721 (95% CI = 0.718-0.724), which was higher than SNACOR, HAP, and CHIP scores (0.587, 0.573, and 0.607, respectively). Calibration and decision curve analyses and a time-dependent AUC diagram were used. Our nomogram showed stronger performance than these other nomograms in both the training and validation cohorts.ConclusionsHCC patients diagnosed as stage B according to BCLC may benefit from PA-TACE after surgery. The RFS nomogram presented here provides an accurate and reliable prognostic model to monitor recurrence. Patients with a high recurrence score based on the nomogram should receive additional high-end imaging exams and shorter timeframes in between follow-up visits.

Project description:Resistance to therapy remains a major cause of the failure of cancer treatment. A major challenge in cancer therapy is to design treatment strategies that circumvent the higher-level homeostatic functions of the robust cellular network that occurs in resistant cells. There is a lack of understanding of mechanisms responsible for the development of cancer and the basis of therapy-resistance mechanisms. Cellular signaling networks have an underlying architecture guided by universal principles. A robust system, such as cancer, has the fundamental ability to survive toxic anticancer drug treatments or a stressful environment mainly due to its mechanisms of redundancy. Consequently, inhibition of a single component/pathway would probably not constitute a successful cancer therapy.We developed a computational method to study the mechanisms of redundancy and to predict communications among the various pathways based on network theory, using data from gene expression profiles of hepatocellular carcinoma (HCC) of patients with poor and better prognosis cancers. Our results clearly indicate that immune system pathways tightly regulate most cancer pathways, and when those pathways are targeted by drugs, the network connectivity is dramatically changed. We examined the main HCC targeted treatments that are currently being evaluated in clinical trials. One prediction of our study is that Sorafenib combined with immune system treatments will be a more effective combination strategy than Sorafenib combined with any other targeted drugs.We developed a computational framework to analyze gene expression data from HCC tumors with varying degrees of responsiveness and non-tumor samples, based on both Gene and Pathway Co-expression Networks. Our hypothesis is that redundancy is one of the major causes of drug resistance, and can be described as a function of the network structure and its properties. From this perspective, we believe that integration of the redundant variables could lead to the development of promising new methodologies to selectively identify and target the most significant resistance mechanisms of HCC. We describe three mechanisms of redundancy based on their levels of generalization and study the possible impact of those redundancy mechanisms on HCC treatments.

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New idea for treatment strategies for Barcelona Clinic Liver Cancer stages based on a network meta-analysis.

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New idea for treatment strategies for Barcelona Clinic Liver Cancer stages based on a network meta-analysis.

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