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BACKGROUND: With a high incidence globally, deaths form gastric cancer (GC) are not rare. Early diagnosis is crucial to ameliorate its prognosis. Confocal laser endomicroscopy (CLE) and narrow band imaging (NBI) have been extensively applied in gastroscopy, particularly when it comes to the detection and management of premalignant gastric lesion. Our meta-analysis intends to appraise the diagnostic capability and compare the efficacy of NBI and CLE for focal precancerous state of gastric cancer. METHODS: We performed a literature search up to November 5, 2020 in online databases and major conferences. Two investigators assessed the methodological bias by QUADAS-2, followed by sophisticated study selection and data exaction to make a comparison between sensitivity, specificity, positive and negative likelihood values, and diagnostic odds ratio. A symmetric summary receiver-operating curve (sROC) and its area under the curve (AUC) were used to estimate threshold effect. Additionally, we evaluated the publication bias by Deeks' asymmetry test. RESULTS AND CONCLUSIONS: Four studies involved 248 patients and 526 lesions. In analysis drawn from every lesion, the NBI's pooled sensitivity and specificity were 87% (95% CI: 0.80-0.92) and 85% (95% CI: 0.75-0.91), and those of CLE were 90% (95% CI: 0.85-0.91) and 87% (95% CI: 0.83-0.91). CLE illustrated that the pooled two were slightly higher than NBI when compared at the level of every lesion. The AUC for NBI and CLE was 0.92 (0.90-0.94) and 0.95 (0.92-0.96), and there might be a threshold effect, according to the shoulder-like distribution of scatter points in the sROC. We did not find obvious publication bias in our meta-analysis.
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Background and Aims: This research aimed to construct a novel model for predicting overall survival (OS) and surgical benefit in triple-negative breast cancer (TNBC) patients with de novo distant metastasis. Methods: We collected data from the Surveillance, Epidemiology, and End Results (SEER) database for TNBC patients with distant metastasis between 2010 and 2016. Patients were excluded if the data regarding metastatic status, follow-up time, or clinicopathological information were incomplete. Univariate and multivariate analyses were applied to identify significant prognostic parameters. By integrating these variables, a predictive nomogram and risk stratification model were constructed and assessed with C-indexes and calibration curves. Results: A total of 1,737 patients were finally identified. Patients enrolled from 2010 to 2014 were randomly assigned to two cohorts, 918 patients in the training cohort and 306 patients in the validation cohort I, and 513 patients enrolled from 2015 to 2016 were assigned to validation cohort II. Seven clinicopathological factors were included as prognostic variables in the nomogram: age, marital status, T stage, bone metastasis, brain metastasis, liver metastasis, and lung metastasis. The C-indexes were 0.72 [95% confidence interval [CI] 0.68-0.76] in the training cohort, 0.71 (95% CI 0.68-0.74) in validation cohort I and 0.71 (95% CI 0.67-0.75) in validation cohort II. Calibration plots indicated that the nomogram-based predictive outcome had good consistency with the recoded prognosis. A risk stratification model was further generated to accurately differentiate patients into three prognostic groups. In all cohorts, the median overall survival time in the low-, intermediate- and high-risk groups was 17.0 months (95% CI 15.6-18.4), 11.0 months (95% CI 10.0-12.0), and 6.0 months (95% CI 4.7-7.3), respectively. Locoregional surgery improved prognosis in both the low-risk [hazard ratio [HR] 0.49, 95% CI 0.41-0.60, P < 0.0001] and intermediate-risk groups (HR 0.55, 95% CI 0.46-0.67, P < 0.0001), but not in high-risk group (HR 0.73, 95% CI 0.52-1.03, P = 0.068). All stratified groups could prognostically benefit from chemotherapy (low-risk group: HR 0.50, 95% CI 0.35-0.69, P < 0.0001; intermediate-risk group: HR 0.34, 95% CI 0.26-0.44, P < 0.0001; and high-risk group: HR 0.16, 95% CI 0.10-0.25, P < 0.0001). Conclusion: A predictive nomogram and risk stratification model were constructed to assess prognosis in TNBC patients with de novo distant metastasis; these methods may provide additional introspection, integration and improvement for therapeutic decisions and further studies.
