Meta-analysis of seven randomized control trials to assess the efficacy and toxicity of combining EGFR-TKI with chemotherapy for patients with advanced NSCLC who failed first-line treatment.

BACKGROUND: Some recent clinical trials have been conducted to evaluate a combination of EGFR- TKI with chemotherapy for advanced NSCLC patients as second-line therapy, but the results on the efficacy of such trials are inconsistent. The aim of this meta-analysis was to evaluate the efficacy and safety of combination of EGFR-TKI and chemotherapy for patients with advanced NSCLC who failed first-line treatment. MATERIALS AND METHODS: We searched relative trials from PubMed, EMBASE, ASCO Abstracts, ESMO Abstracts, Cochrane Library and Clinical Trials.gov. Outcomes analyzed were overall response rate (ORR), progression- free survival (PFS), overall survival (OS) and major toxicity. RESULTS: Seven trails eventually were included in this meta-analysis, covering 1,168 patients. The results showed that the combined regimen arm had a significant higher ORR (RR 1.76 [1.16, 2.66], p=0.007) and longer PFS (HR 0.75 [0.66-0.85], p<0.00001), but failed to show effects on OS (HR 0.88 [0.68- 1.15], p=0.36). In terms of subgroup results, continuation of EGFR-TKI in addition to chemotherapy after first-line EGFR-TKI resistance confered no improvement in ORR (RR 0.95 [0.68, 1.33], p=0.75) and PFS (HR 0.89[0.69, 1.15], p=0.38), and OS was even shorter (HR1.52 [1.05- 2.21], p=0.03). However, combination therapy with EGFR-TKI and chemotherapy after failure of first-line chemotherapy significantly improved the ORR (RR 2.06 [1.42, 2.99], p=0.0002), PFS (HR 0.71 [0.61, 0.82], p<0.00001) and OS (HR 0.74 [0.62- 0.88], p=0.0008), clinical benefit being restricted to combining EGFR-TKI with pemetrexed, but not docetaxel. Grade 3-4 toxicity was found at significantly higher incidence in the combined regimen arm. CONCLUSIONS: Continuation of EGFR-TKI in addition to chemotherapy after first-line EGFR-TKI resistance should be avoided. Combination therapy of EGFR-TKI and pemetrexed for advanced NSCLC should be further investigated for prognostic and predictive factors to find the group with the highest benefit of the combination strategy.

Efficacy and safety of sorafenib for advanced non-small cell lung cancer: a meta-analysis of randomized controlled trials.

BACKGROUND: Many clinical trials have been conducted to evaluate sorafenib for the treatment of advanced NSCLC, but the results for efficacy have been inconsistent. The aim of this study was to evaluate the efficacy and safety of sorafenib in patients with advanced NSCLC in more detail by meta-analysis. METHODS: This meta-analysis of randomized controlled trials (RCTs) was performed after searching PubMed, EMBASE, ASCO Abstracts, ESMO Abstracts, and the proceedings of major conferences for relevant clinical trials. Two reviewers independently assessed the quality of the trials. Outcomes analysis were disease control rate (DCR), progression- free survival (PFS), overall survival (OS) with 95% confidence intervals (CI) and major toxicity. Subgroup analysis was conducted according to sorafenib monotherapy, in combination with chemotherapy or EGFR-TKI to investigate the preferred therapy strategy. RESULTS: Results reported from 6 RCTs involving 2,748 patients were included in the analysis. Compared to sorafenib-free group, SBT was not associated with higher DCR (RR 1.31 (0.96-1.79), p=0.09), PFS (HR 0.82 (0.66-1.02), p=0.07) and OS (HR 1.01 (0.92-1.12), p=0.77). In terms of subgroup results, sorafenib monotherapy was associated with significant superior DCR and longer PFS, but failed to show advantage with regard to OS. Grade 3 or greater sorafenib-related adverse events included fatigue, hypertension, diarrhea, oral mucositis, rash and HFSR. CONCLUSIONS: SBT was revealed to yield no improvement in DCR, PFS and OS. However, sorafenib as monotherapy showed some activity in NSCLC. Further evaluation may be considered in subsets of patients who may benefit from this treatment. Sorafenib combined inhibition therapy should be limited unless the choice of platinum-doublet regimen, administration sequence or identification of predictive biomarkers are considered to receive better anti-tumor activity and prevention of resistance mechanisms.

Serum peptide pattern that differentially diagnoses hepatitis B virus-related hepatocellular carcinoma from liver cirrhosis.

BACKGROUND: Although alpha-fetoprotein (AFP) is a useful serologic marker of hepatocellular carcinoma (HCC), it is not sufficiently sensitive to differentiate HCC and liver cirrhosis (LC) caused by hepatitis B virus (HBV) infection. AIMS: The aim is to discover novel noninvasive specific serum biomarkers for the differential diagnosis of HBV-related HCC and LC. METHODS: With a highly optimized peptide extraction and matrix-assisted laser desorption/ionization time of flight/time of flight mass spectrometric approach, we investigated serum peptide profiles of 80 HCC and 67 LC patients. Three supervised machine learning methods were employed to construct classifiers. Receiver operator curves were plotted to evaluate the performance of classifiers. RESULTS: With a support vector machine-based strategy, we picked nine peaks with m/z ratios of 819.49, 1076.14, 1341.72, 2551.44, 3156.44, 3812.88, 4184.26, 4465.92, and 4776.41 to construct the classifier. We proposed a novel method for distinguishing HCC from cirrhosis, based on a multilayer perceptron (MLP) method. We obtained a sensitivity of 90.0%, specificity of 79.4%, and overall accuracy of 85.1% on an independent test set. The combination of the MLP model and serum AFP level outperformed serum AFP marker alone in distinguishing HCC patients from LC patients. In this experience, sensitivity increased from 62.5% to 87.5%, and specificity increased from 79.4% to 88.2%. CONCLUSIONS: Our results indicate that the MLP model is a novel and useful serum peptide pattern for distinguishing HCC and LC. The peptidome signature alone or together with serum AFP determination may be a more effective method for early diagnosis of HCC in patients with HBV-related LC.

Two classifiers based on serum peptide pattern for prediction of HBV-induced liver cirrhosis using MALDI-TOF MS.

Chronic infection with hepatitis B virus (HBV) is associated with the majority of cases of liver cirrhosis (LC) in China. Although liver biopsy is the reference method for evaluation of cirrhosis, it is an invasive procedure with inherent risk. The aim of this study is to discover novel noninvasive specific serum biomarkers for the diagnosis of HBV-induced LC. We performed bead fractionation/MALDI-TOF MS analysis on sera from patients with LC. Thirteen feature peaks which had optimal discriminatory performance were obtained by using support-vector-machine-(SVM-) based strategy. Based on the previous results, five supervised machine learning methods were employed to construct classifiers that discriminated proteomic spectra of patients with HBV-induced LC from those of controls. Here, we describe two novel methods for prediction of HBV-induced LC, termed LC-NB and LC-MLP, respectively. We obtained a sensitivity of 90.9%, a specificity of 94.9%, and overall accuracy of 93.8% on an independent test set. Comparisons with the existing methods showed that LC-NB and LC-MLP held better accuracy. Our study suggests that potential serum biomarkers can be determined for discriminating LC and non-LC cohorts by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. These two classifiers could be used for clinical practice in HBV-induced LC assessment.