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BackgroundProstate cancer (PCa) is one of the most threatening health problems for the elderly males. However, our understanding of the disease has been limited by the research technology for a long time. Recently, the maturity of sequencing technology and omics studies has been accelerating the studies of PCa, establishing themselves as an essential impetus in this field.MethodsWe assessed Web of Science (WoS) database for publications of sequencing and omics studies in PCa on July 3rd, 2023. Bibliometrix was used to conduct ulterior bibliometric analysis of countries/affiliations, authors, sources, publications, and keywords. Subsequently, purposeful large amounts of literature reading were proceeded to analyze research hotspots in this field.Results3325 publications were included in the study. Research associated with sequencing and omics studies in PCa had shown an obvious increase recently. The USA and China were the most productive countries, and harbored close collaboration. CHINNAIYAN AM was identified as the most influential author, and CANCER RESEARCH exhibited huge impact in this field. Highly cited publications and their co-citation relationships were used to filtrate literatures for subsequent literature reading. Based on keyword analysis and large amounts of literature reading, ‘the molecular pathogenesis of PCa’ and ‘the clinical application of sequencing and omics studies in PCa’ were summarized as two research hotspots in the field.ConclusionSequencing technology had a deep impact on the studies of PCa. Sequencing and omics studies in PCa helped researchers reveal the molecular pathogenesis, and provided new possibilities for the clinical practice of PCa.

ObjectiveTo compare the diagnostic performance of automated breast ultrasound (ABUS) and contrast-enhanced ultrasound (CEUS) in breast cancer.MethodsPublished studies were collected by systematically searching the databases PubMed, Embase, Cochrane Library and Web of Science. The sensitivities, specificities, likelihood ratios and diagnostic odds ratio (DOR) were confirmed. The symmetric receiver operator characteristic curve (SROC) was used to assess the threshold of ABUS and CEUS. Fagan’s nomogram was drawn. Meta-regression and subgroup analyses were applied to search for sources of heterogeneity among the included studies.ResultsA total of 16 studies were included, comprising 4115 participants. The combined sensitivity of ABUS was 0.88 [95% CI (0.73–0.95)], specificity was 0.93 [95% CI (0.82–0.97)], area under the SROC curve (AUC) was 0.96 [95% CI (0.94–0.96)] and DOR was 89. The combined sensitivity of CEUS was 0.88 [95% CI (0.84–0.91)], specificity was 0.76 [95% CI (0.66–0.84)], AUC was 0.89 [95% CI (0.86–0.92)] and DOR was 24. The Deeks’ funnel plot showed no existing publication bias. The prospective design, partial verification bias and blinding contributed to the heterogeneity in specificity, while no sources contributed to the heterogeneity in sensitivity. The post-test probability of ABUS in BC was 75%, and the post-test probability of CEUS in breast cancer was 48%.ConclusionCompared with CEUS, ABUS showed higher specificity and DOR for detecting breast cancer. ABUS is expected to further improve the accuracy of BC diagnosis.

AimTo analyze locally advanced rectal cancer (LARC) patients and tumor characteristics during the period of total neoadjuvant therapy (TNT) and explore the risk factors that may predict poor tumor regression in response to TNT.Materials and methodsThe data of 120 LARC patients who received TNT from December 2016 and September 2019 in our hospital were retrospectively analyzed. The clinicopathological characteristics of patients with different tumor regression responses were compared. Then we divided patients into two groups according to the carcinoembryonic antigen (CEA) clearance pattern after chemoradiation to explore risk factors that might predict the tumor regression response.ResultsOf 120 LARC patients, 34 (28.3%) exhibited poor regression. Stratified analysis by tumor response showed that patients with poor response to TNT were more likely to obtain elevated CEA during the course of TNT (all P < 0.05). For those with elevated pretreatment CEA, fewer patients with poor response obtained normal CEA after chemoradiation (13.6% vs. 72.7%, P < 0.001). Besides, less patients’ CEA levels in the poor response group decreased by greater than 50% after chemoradiation when compared with that in the good response group (18.2% vs. 60.6%, P = 0.002). Stratified analysis by CEA clearance pattern after chemoradiation showed patients who obtained an elevated pretreatment CEA and decreased by less than 50% after chemoradiation were more likely to have poor response to TNT compared to others (76.2% vs. 18.2%, P < 0.001). Logistic multivariate analysis revealed that cN2 (95% CI 1.553-16.448), larger tumors (95% CI 2.250-21.428) and CEA clearance pattern after chemoradiation (95% CI 1.062-66.992) were independent risk factors for poor tumor regression response.ConclusionApproximately one-fourth of LARC patients with TNT achieved a poor regression response. Here, cN2, larger tumor size before treatment and elevated CEA levels were considered predictive features of a poor response. Active surveillance of CEA levels during the TNT course are potentially important, and CEA levels after chemoradiation might have important implications for the tumor response to TNT.

Objective: To compare the diagnostic performance of automated breast ultrasound (ABUS) and contrast-enhanced ultrasound (CEUS) in breast cancer. Methods: Published studies were collected by systematically searching the databases PubMed, Embase, Cochrane Library and Web of Science. The sensitivities, specificities, likelihood ratios and diagnostic odds ratio (DOR) were confirmed. The symmetric receiver operator characteristic curve (SROC) was used to assess the threshold of ABUS and CEUS. Fagan's nomogram was drawn. Meta-regression and subgroup analyses were applied to search for sources of heterogeneity among the included studies. Results: A total of 16 studies were included, comprising 4115 participants. The combined sensitivity of ABUS was 0.88 [95% CI (0.73-0.95)], specificity was 0.93 [95% CI (0.82-0.97)], area under the SROC curve (AUC) was 0.96 [95% CI (0.94-0.96)] and DOR was 89. The combined sensitivity of CEUS was 0.88 [95% CI (0.84-0.91)], specificity was 0.76 [95% CI (0.66-0.84)], AUC was 0.89 [95% CI (0.86-0.92)] and DOR was 24. The Deeks' funnel plot showed no existing publication bias. The prospective design, partial verification bias and blinding contributed to the heterogeneity in specificity, while no sources contributed to the heterogeneity in sensitivity. The post-test probability of ABUS in BC was 75%, and the post-test probability of CEUS in breast cancer was 48%. Conclusion: Compared with CEUS, ABUS showed higher specificity and DOR for detecting breast cancer. ABUS is expected to further improve the accuracy of BC diagnosis. [ABSTRACT FROM AUTHOR]