scholarly journals Accumulate evidence for IP-10 in diagnosing pulmonary tuberculosis

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Xia Qiu ◽  
Tao Xiong ◽  
Xiaojuan Su ◽  
Yi Qu ◽  
Long Ge ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Likelihood Ratio ◽  
Random Effect ◽  
Random Effect Model ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Assay Method ◽  
Cochrane Library ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Abstract Backgrounds Pulmonary tuberculosis (PTB) is a major health and economic burden. Accurate PTB detection is an important step to eliminating TB globally. Interferon gamma-induced protein 10 (IP-10) has been reported as a potential diagnostic marker for PTB since 2007. In this study, a meta-analysis approach was used to assess diagnostic value of IP-10 for PTB. Methods Web of Science, PubMed, the Cochrane Library, and Embase databases were searched for studies published in English up to February 2019. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), the area under the curve (AUC) and hierarchical summary receiver operating characteristic (HSROC) curve were estimated by the HSROC model and random effect model. Results Eighteen studies including 2836 total participants met our inclusion criteria. The pooled sensitivity, specificity, PLR, and NLR of IP-10 for PTB detection were 86, 88%, 7.00, and 0.16, respectively. The pooled DOR was 43.01, indicating a very powerful discriminatory ability of IP-10. The AUC was 0.93 (95% CI: 0.91–0.95), showed the accuracy of IP-10 was good. Meta-regression showed that there was no heterogeneity with respect to TB burden, study design type, age, IP-10 assay method, IP-10 condition and HIV-infection status. Conclusions Our results showed that IP-10 is a promising marker for differentiating PTB from non-TB.

scholarly journals Accumulate evidence for IP-10 in diagnosing pulmonary tuberculosis

2019 ◽  
Author(s):  
Xia Qiu ◽  
Tao Xiong ◽  
Xiaojuan Su ◽  
Yi Qu ◽  
Long Ge ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Likelihood Ratio ◽  
Random Effect ◽  
Random Effect Model ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Assay Method ◽  
Cochrane Library ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Abstract Backgrounds: Pulmonary tuberculosis (PTB) is a major health and economic burden. Accurate PTB detection is an important step to eliminating TB globally. I nterferon gamma-induced protein 10 (IP-10) has been reported as a potential diagnostic marker for PTB since 2007. In this study, a meta-analysis approach was used to assess diagnostic value of IP-10 for PTB. Methods: Web of Science, PubMed, the Cochrane Library, and Embase databases were searched for studies published in English up to February 2019. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), the area under the curve (AUC) and hierarchical summary receiver operating characteristic (HSROC) curve were estimated by the HSROC model and random effect model. Results: Eighteen studies including 2836 total participants met our inclusion criteria. The pooled sensitivity, specificity, PLR, and NLR of IP-10 for PTB detection were 86%, 88%, 7.00, and 0.16, respectively. The pooled DOR was 43.01, indicating a very powerful discriminatory ability of IP-10. The AUC was 0.93 (95% CI: 0.91–0.95), showed the accuracy of IP-10 was good. Meta-regression showed that there was no heterogeneity with respect to TB burden, study design type, age, IP-10 assay method, IP-10 condition and HIV-infection status. Conclusions: Our results showed that IP-10 is a promising marker for differentiating PTB from non-TB.

scholarly journals Accumulate evidence for IP-10 in diagnosing pulmonary tuberculosis

2019 ◽  
Author(s):  
Xia Qiu ◽  
Tao Xiong ◽  
Xiaojuan Su ◽  
Yi Qu ◽  
Long Ge ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Likelihood Ratio ◽  
Random Effect ◽  
Random Effect Model ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Assay Method ◽  
Cochrane Library ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Abstract Backgrounds: Pulmonary tuberculosis (PTB) is a major health and economic burden. Accurate PTB detection is an important step to eliminating TB globally. I nterferon gamma-induced protein 10 (IP-10) has been reported as a potential diagnostic marker for PTB since 2007. In this study, a meta-analysis approach was used to assess diagnostic value of IP-10 for PTB. Methods: Web of Science, PubMed, the Cochrane Library, and Embase databases were searched for studies published in English up to February 2019. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), the area under the curve (AUC) and hierarchical summary receiver operating characteristic (HSROC) curve were estimated by the HSROC model and random effect model. Results: Eighteen studies including 2836 total participants met our inclusion criteria. The pooled sensitivity, specificity, PLR, and NLR of IP-10 for PTB detection were 86%, 88%, 7.00, and 0.16, respectively. The pooled DOR was 43.01, indicating a very powerful discriminatory ability of IP-10. The AUC was 0.93 (95% CI: 0.91–0.95), showed the accuracy of IP-10 was good. Meta-regression showed that there was no heterogeneity with respect to TB burden, study design type, age, IP-10 assay method, IP-10 condition and HIV-infection status. Conclusions: Our results showed that IP-10 is a promising marker for differentiating PTB from non-TB.

scholarly journals Accumulate evidence for IP-10 in diagnosing pulmonary tuberculosis

2019 ◽  
Author(s):  
Xia Qiu ◽  
Tao Xiong ◽  
Xiaojuan Su ◽  
Yi Qu ◽  
Long Ge ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Assay Method ◽  
Cochrane Library ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Abstract Backgrounds Pulmonary tuberculosis (PTB) is a major health and economic burden. Accurate PTB detection is an important step to eliminating TB globally. Interferon gamma-induced protein 10 (IP-10) has been reported as a potential diagnostic marker for PTB since 2007. In this study, a meta-analysis approach was used to assess diagnostic value of IP-10 for PTB. Methods Web of Science, PubMed, the Cochrane Library, and Embase databases were searched for studies published in English up to February 2019. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and hierarchical summary receiver operating characteristic (HSROC) curve were estimated by a HSROC model. Results Eighteen studies including 2836 total participants met our inclusion criteria. The pooled sensitivity, specificity, PLR, and NLR of IP-10 for PTB detection were 86%, 88%, 7.00, and 0.16, respectively. The pooled DOR was 43.01, indicating a very powerful discriminatory ability of IP-10. Meta-regression showed that there was no heterogeneity with respect to TB burden, study design type, age, IP-10 assay method, IP-10 condition and HIV-infection status. Conclusions Our results showed that IP-10 is a promising marker for differentiating PTB from non-TB.

scholarly journals Clinical utility of microRNA-451 as diagnostic biomarker for human cancers

2019 ◽  
Vol 39 (1) ◽  
Author(s):  
Zhanzhan Li ◽  
Yanyan Li ◽  
Jun Fu ◽  
Na Li ◽  
Liangfang Shen
Keyword(s):  
Likelihood Ratio ◽  
Sensitivity And Specificity ◽  
Odds Ratio ◽  
Random Effect ◽  
Random Effect Model ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Diagnostic Ability ◽  
Sensitivity Specificity

AbstractWe conducted comprehensive analyses to assess the diagnostic ability of miRNA-451 in cancers. A systematic online search was conducted in PubMed, Web of Science, China’s national knowledge infrastructure, and VIP databases from inception to July 31, 2017. The bivariate random effect model was used for calculating sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under cure (AUC). The whole pooled sensitivity and specificity were 0.85 (0.77–0.90) and 0.85 (0.78–0.90) with their 95% confidence interval (95%CI), respectively. The pooled AUC was 0.91 (95%CI: 0.89–0.94). Positive likelihood ratio was 5.57 (95%CI: 3.74–8.31), negative likelihood ratio was 0.18 (95%CI: 0.11–0.28), and diagnostic odds ratio was 31.33 (95%CI: 15.19–64.61). Among Asian population, the sensitivity and specificity were 0.85 (95%CI: 0.77–0.91) and 0.86 (95%CI: 0.78–0.91), respectively. The positive likelihood ratio and negative likelihood ratio were 5.87 (95%CI: 3.78–9.12) and 0.17 (95%CI: 0.11–0.28). The diagnostic odds ratio and AUC were 34.31 (15.51–75.91) and 0.92 (0.89–0.94). The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and AUC for digestive system cancer were 0.83, 0.88, 6.87, 0.20, 35.13, and 0.92, respectively. The other cancers were 0.87, 0.81, 4.55, 0.16, 28.51, and 0.90, respectively. For sample source, the results still remain consistent. Our results indicated miRNA-451 has a moderate diagnostic ability for cancers, and could be a potential early screening biomarker, and considered as an adjuvant diagnostic index when being combined with other clinical examinations.

scholarly journals Systematic Review and Meta-Analysis of the Utility of Circular RNAs as Biomarkers of Hepatocellular Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Qingqin Hao ◽  
Yadi Han ◽  
Wei Xia ◽  
Qinghui Wang ◽  
Huizhong Qian
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Clinicopathological Characteristics ◽  
Cochrane Library ◽  
Circular Rnas ◽  
Clinical Value ◽  
Sensitivity Specificity

Emerging studies have reported circRNAs were dysregulated in HCC. However, the clinical value of these circRNAs remains to be clarified. Herein, we aimed to comprehensively explore their association with the diagnosis, prognosis, and clinicopathological characteristics of HCC. PubMed, EMBASE, Web of Science, and Cochrane Library databases were comprehensively searched for eligible studies up to October 30, 2018. The diagnostic effect was evaluated by the pooled sensitivity, specificity, and other indexes. The pooled hazard ratio (HR) for overall survival (OS) and recurrence free survival (RFS) was calculated to assess the prognostic value. Ten studies on diagnosis, 12 on prognosis, and 23 on clinicopathology were identified from the databases. A total of 11 upregulated and 11 downregulated circRNAs showed an association with clinicopathological features of HCC. For the diagnosis analyses, the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) of circRNAs for HCC were 0.74 (95%CI: 0.65-0.82) and 0.76 (95%CI: 0.70-0.81), 3.1 (95%CI: 2.5-3.8), 0.34 (95%CI: 0.25-0.47), and 9 (95%CI: 6-14), respectively. The area under SROC curve (AUC) was 0.81 (95% CI: 0.78–0.84), indicating moderate diagnostic accuracy. In stratified analyses, the diagnostic performance of circRNAs varied based on the source of control and specimen type. For the prognosis analyses, increased expression of upregulated circRNAs was associated with worse OS (HR: 3.67, 95%: 2.07-6.48), while high expression of downregulated circRNAs was associated with better OS (HR: 0.38, 95%: 0.30-0.48). In conclusion, this study reveals that circRNAs may serve as promising diagnostic and prognostic biomarkers for HCC. However, further investigations are still required to explore the clinical value of circRNAs.

scholarly journals Diagnostic Value of T-SPOT.TB Assay for Tuberculous Peritonitis: A Meta-Analysis

2020 ◽  
Vol 7 ◽  
Author(s):  
Ying Luo ◽  
Ying Xue ◽  
Liyan Mao ◽  
Qun Lin ◽  
Guoxing Tang ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Abdominal Tuberculosis ◽  
Tuberculous Peritonitis ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Background: Tuberculous peritonitis (TP) is a common form of abdominal tuberculosis (TB). Diagnosing TP remains challenging in clinical practice. The aim of the present meta-analysis was to evaluate the diagnostic accuracy of peripheral blood (PB) T-SPOT and peritoneal fluid (PF) T-SPOT for diagnosing TP.Methods: PubMed, EmBase, Cochrane, Scopus, Google scholar, China national knowledge internet, and Wan-Fang databases were searched for relevant articles from August 1, 2005 to July 5, 2020. Statistical analysis was performed using Stata, Revman, and Meta-Disc software. Diagnostic parameters including pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were determined. Summary receiver operating characteristic curve was used to determine the area under the curve (AUC).Results: Twelve studies were eligible and included in the meta-analysis. The analysis showed that the pooled sensitivity and specificity of PB T-SPOT in diagnosing TP were 0.91 (95% CI, 0.88–0.94) and 0.78 (95% CI, 0.73–0.81), respectively, while the pooled PLR, NLR, and DOR were 4.05 (95% CI, 2.73–6.01), 0.13 (95% CI, 0.07–0.23), and 37.8 (95% CI, 15.04–94.98), respectively. On the other hand, the summary estimates of sensitivity, specificity, PLR, NLR, and DOR of PF T-SPOT for TP diagnosis were 0.90 (95% CI, 0.85–0.94), 0.78 (95% CI, 0.72–0.83), 6.35 (95% CI, 2.67–15.07), 0.14 (95% CI, 0.09–0.21), and 58.22 (95% CI, 28.76–117.83), respectively. Furthermore, the AUC of PB T-SPOT and PF T-SPOT for TP diagnosis were 0.91 and 0.94, respectively.Conclusions: Our results indicate that both PB T-SPOT and PF T-SPOT can be served as sensitive approaches for the diagnosis of TP. However, the unsatisfactory specificities of these two methods limit their application as rule-in tests for TP diagnosis. Furthermore, the standardization of the operating procedure of PF T-SPOT is further needed.

scholarly journals Artificial Intelligence in Gastric Cancer: Identifying Gastric Cancer Using Endoscopic Images with Convolutional Neural Network

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5253
Author(s):  
Md. Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
Bruno Andreas Walther ◽  
Ming-Chin Lin ◽  
Yu-Chuan (Jack) Li
Keyword(s):  
Gastric Cancer ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Work Load ◽  
Diagnostic Odds Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Gastric cancer (GC) is one of the most newly diagnosed cancers and the fifth leading cause of death globally. Identification of early gastric cancer (EGC) can ensure quick treatment and reduce significant mortality. Therefore, we aimed to conduct a systematic review with a meta-analysis of current literature to evaluate the performance of the CNN model in detecting EGC. We conducted a systematic search in the online databases (e.g., PubMed, Embase, and Web of Science) for all relevant original studies on the subject of CNN in EGC published between January 1, 2010, and March 26, 2021. The Quality Assessment of Diagnostic Accuracy Studies-2 was used to assess the risk of bias. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated. Moreover, a summary receiver operating characteristic curve (SROC) was plotted. Of the 171 studies retrieved, 15 studies met inclusion criteria. The application of the CNN model in the diagnosis of EGC achieved a SROC of 0.95, with corresponding sensitivity of 0.89 (0.88–0.89), and specificity of 0.89 (0.89–0.90). Pooled sensitivity and specificity for experts endoscopists were 0.77 (0.76–0.78), and 0.92 (0.91–0.93), respectively. However, the overall SROC for the CNN model and expert endoscopists was 0.95 and 0.90. The findings of this comprehensive study show that CNN model exhibited comparable performance to endoscopists in the diagnosis of EGC using digital endoscopy images. Given its scalability, the CNN model could enhance the performance of endoscopists to correctly stratify EGC patients and reduce work load.

scholarly journals Reliability of circulating fibrinogen in the diagnosis of prosthesis-related infections: a systematic review and meta-analysis

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Xingyang Zhu ◽  
Haitao Zhang ◽  
Xiaobo Sun ◽  
Yijin Li ◽  
Jiahao Li ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Joint Infection ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Small Sample ◽  
Cochrane Library ◽  
Sensitivity Specificity

Abstract Background Fibrinogen (FIB) has recently been used as a biomarker to diagnose periprosthetic joint infection (PJI), but its reliability is still questionable. The aim of this study was to investigate the accuracy of FIB in the diagnosis of PJI after joint replacement. Methods We searched for literatures published in PubMed, EMBASE, and the Cochrane Library from the time of database inception to September 2020 and screened the studies according to the inclusion criteria. Then, we calculated the diagnostic parameters of FIB, including the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), area under the curve (AUC), and diagnostic odds ratio (DOR). In addition, we implemented subgroup analyses to identify the sources of heterogeneity. Results Seven studies including 1341 patients were selected in our meta-analysis. The pooled sensitivity, specificity, PLR, NLR, and DOR of FIB for PJI diagnosis were 0.78 (95% confidence interval [CI], 0.73–0.82), 0.83 (95% CI, 0.81–0.86), 4.60 (95% CI, 3.30–6.42), 0.24 (95% CI, 0.18–0.34), and 20.13 (95% CI, 14.80–27.36), respectively, while the AUC was 0.896. Conclusion The present study indicated that FIB was a reliable detection method and might be introduced into the diagnostic criteria for PJI. However, more robust studies are still needed to confirm the current findings, because most of the included studies were retrospective and had small sample sizes.

scholarly journals Diagnostic value of neutrophil CD64, procalcitonin, and interleukin-6 in sepsis: A meta-analysis

2020 ◽  
Author(s):  
Ke Wang ◽  
Shan Cong ◽  
Tiangang Ma ◽  
Xin Di ◽  
Chang Tian ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Interleukin 6 ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Value ◽  
Summary Receiver Operating Characteristic ◽  
Neutrophil Cd64 ◽  
Sensitivity Specificity

Abstract The aim of the study was to conduct a meta-analysis to evaluate the accuracy of neutrophil CD64, procalcitonin (PCT), and interleukin-6 (IL-6) for the diagnosis of sepsis. The sample articles were searched in various databases to collect published studies on the diagnosis of sepsis by neutrophil CD64, PCT, and IL-6. By using the Stata SE 15.0 software, forest plots and the area under the summary receiver operating characteristic curves were drawn. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve (AUC) were calculated. 54 articles were included in the study. The number of studies that evaluated the diagnostic value of neutrophil CD64, PCT, and interleukin-6 were 20, 39, and 15, respectively. The pooled sensitivity, specificity, and AUC of neutrophil CD64 for the diagnosis of sepsis were 0.88 [95% confidence interval (CI), 0.81–0.92], 0.88 (95% CI, 0.83–0.91), and 0.94 (95% CI, 0.91–0.96), respectively. The pooled sensitivity, specificity, and AUC of PCT for the diagnosis of sepsis were 0.82 (95% CI, 0.78–0.85), 0.78 (95% CI, 0.74–0.82), and 0.87 (95% CI, 0.83–0.89), respectively. Subgroup analysis showed that the AUC for PCT diagnosis of intensive care unit (ICU) sepsis was 0.86 (95% CI, 0.83–0.89) and the AUC for PCT diagnosis of non-ICU sepsis was 0.82 (95% CI, 0.78–0.85). The pooled sensitivity, specificity, and AUC of IL-6 for the diagnosis of sepsis were 0.72 (95% CI, 0.65–0.78), 0.70 (95% CI, 0.62–0.76), and 0.77 (95% CI, 0.73–0.80), respectively. Of the three biomarkers studied, neutrophil CD64 showed the highest diagnostic value for sepsis, followed by PCT, and IL-6. On the other hand, PCT showed a better diagnostic value for the diagnosis of sepsis in patients with severe conditions compared with that in patients with non-severe conditions.

Neutrophil-to-lymphocyte ratio predicts diagnosis and prognosis of patients with hepatocellular: A systematic review and meta-analysis

2020 ◽  
Author(s):  
Shan Lin ◽  
Shiping Hu ◽  
Yun Ran ◽  
Fenfang Wu
Keyword(s):  
Likelihood Ratio ◽  
Odds Ratio ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Neutrophil To Lymphocyte Ratio ◽  
Cochrane Library ◽  
Summary Receiver Operating Characteristic ◽  
Lymphocyte Ratio ◽  
Meta Analyses

Abstract Background: Neutrophil-to-lymphocyte ratio (NLR) is one of the poor prognostic factors of Hepatocellular carcinoma (HCC) in patients. As contradictory data are seen concerning the predictive ability of NLR, a meta-analysis is performed for the determination of its prognostic value in patients with HCC in this study.Methods: We systematically searched several databases including PubMed, EMBASE, and Cochrane Library with the updated date of January 21, 2020. Pooled estimates of odds ratio (OR) and diagnostic odds ratio (DOR) were used to assess the prognostic performance of NLR in HCC patients.Results: Nine studies containing a total of 3,862 HCC patients were included. High baseline NLR was correlated with poor prognosis or recurrence significantly. The patient-based analysis of pooled estimates was as follows: sensitivity 0.68 [95% confidence interval (CI), 0.58-0.77], specificity 0.73 (95% CI, 0.61-0.82), and DOR 6.347 (95% CI, 5.450-7.391), respectively. The pooled positive likelihood ratio (PLR) and negative likelihood ratio (NLHR) were 2.5 (95% CI, 1.8-3.6) and 0.43 (95% CI, 0.33-0.57). Furthermore, the area under the curve (AUC) of summary receiver operating characteristic (SROC) reflecting the diagnostic accuracy was 0.76 (95% CI, 0.72-0.80). Results obtained from subgroup meta-analyses and overall meta-analyses were accordingly consistent with each other.Conclusions: Our findings suggested that NLR is an efficient prognostic factor for patients with HCC, especially for those from East Asian with high incidence. In the future, trails with larger sample sizes and more high-quality evidence are needed to further enhance the patient outcomes.

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