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Wang Y, Duan Y, Guo D, Lv H, Li Q, Liu X, Qiao N, Meng H, Zhang X, Lan L, Liu X, Liu X. Value of circulating tumor cell assisting low-dose computed tomography in screening pulmonary nodules based on existing liquid biopsy techniques: a systematic review with meta-analysis and trial sequential analysis. Clin Transl Oncol 2024:10.1007/s12094-024-03556-8. [PMID: 38869739 DOI: 10.1007/s12094-024-03556-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 06/04/2024] [Indexed: 06/14/2024]
Abstract
OBJECTIVE This study aims to assess the diagnostic utility of circulating tumor cells (CTCs) in conjunction with low-dose computed tomography (LDCT) for differentiating between benign and malignant pulmonary nodules and to substantiate the foundation for their integration into clinical practice. METHODS A systematic literature review was performed independently by two researchers utilizing databases including PubMed, Web of Science, The Cochrane Library, Embase, and Medline, to collate studies up to September 15, 2023, that investigated the application of CTCs in diagnosing pulmonary nodules. A meta-analysis was executed employing Stata 15.0 and Revman 5.4 to calculate the pooled sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and the area under the receiver operating characteristic curve (AUC). Additionally, trial sequential analysis was conducted using dedicated TSA software. RESULTS The selection criteria identified 16 studies, encompassing a total of 3409 patients. The meta-analysis revealed that CTCs achieved a pooled sensitivity of 0.84 (95% CI 0.80 to 0.87), specificity of 0.80 (95% CI 0.73 to 0.86), PLR of 4.23 (95% CI 3.12 to 5.72), NLR of 0.20 (95% CI 0.16 to 0.25), DOR of 20.92 (95% CI 13.52 to 32.36), and AUC of 0.89 (95% CI 0.86 to 0.93). CONCLUSIONS Circulating tumor cells demonstrate substantial diagnostic accuracy in distinguishing benign from malignant pulmonary nodules. The incorporation of CTCs into the diagnostic protocol can significantly augment the diagnostic efficacy of LDCT in screening for malignant lung diseases.
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Affiliation(s)
- Yixian Wang
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Yuqing Duan
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Dingjie Guo
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Hongbo Lv
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Qiong Li
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Xuan Liu
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Na Qiao
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Hengyu Meng
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Xin Zhang
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Linwei Lan
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Xiumin Liu
- Department of Clinical Laboratory, The Second Hospital of Jilin University, Changchun, Jilin, 130041, China.
| | - Xin Liu
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China.
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Tian S, Li X, Liu J, Wang X, Chen H, Dai Z, Chen Q, Shi H, Li Y, Huang H, Bai C. Radial endobronchial ultrasound - guided bronchoscopy for the diagnosis of peripheral pulmonary lesions: A systematic review and meta-analysis of prospective trials. Heliyon 2024; 10:e29446. [PMID: 38660275 PMCID: PMC11040069 DOI: 10.1016/j.heliyon.2024.e29446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 04/05/2024] [Accepted: 04/08/2024] [Indexed: 04/26/2024] Open
Abstract
Background The diagnostic yield of radial endobronchial ultrasound (r-EBUS) for the diagnosis of peripheral pulmonary lesions (PPLs) varies between studies and is affected by multiple factors. We aimed to evaluate the efficacy and safety of r-EBUS, and to explore the factors influencing the diagnostic yield of r-EBUS in patients with PPLs. Methods The PubMed, Web of Science, and EMBASE databases were searched to identify relevant studies that used r-EBUS for diagnosing PPLs from the date of inception to Dec 2022. Meta-analysis was conducted using Review Manager 5.4 and Stata 15.1. Results An analysis of 46 studies with a total of 7252 PPLs was performed. The pooled diagnostic yield of r-EBUS was 73.4 % (95 % CI: 69.9%-76.7 %), with significant heterogeneity detected among studies (I2 = 90 %, P < 0.001). Further analysis demonstrated PPLs located in the middle or lower lobe, >2 cm in size, malignant in type, solid in appearance on computerized tomography (CT), present in bronchus sign, the within probe location, and the addition of rapid on-site evaluation (ROSE) were associated with increased diagnostic yield, whereas use of a guide sheath (GS), bronchoscopy type, and a multimodality approach failed to influence the outcome. The pooled incidence rates of overall complications, pneumothorax and moderate and severe bleeding were 3.1 % (95 % CI: 2.1%-4.3 %), 0.4 % (95 % CI: 0.1%-0.7 %) and 1.1 % (95 % CI: 0.5%-2.0 %), respectively. Conclusions r-EBUS has an appreciable diagnostic yield and an excellent safety manifestation when used to deal with PPLs.
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Affiliation(s)
- Sen Tian
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China
- Department of Respiratory and Critical Care Medicine, No. 906 Hospital of the Chinese People's Liberation Army Joint Logistic Support Force, Ningbo, China
| | - Xiang Li
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China
- Department of Respiratory and Critical Care Medicine, General Hospital of Central Theater Command of Chinese People's Liberation Army, Wuhan, China
| | - Jian Liu
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Xinyu Wang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Hui Chen
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Zeyu Dai
- Department of Orthopaedic Oncology, The Second Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Qian Chen
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Naval Medical University, Shanghai, China
- Department of Cardiothoracic Surgery, No. 904 Hospital of the Chinese People's Liberation Army Joint Logistic Support Force, Wuxi, China
| | - Hui Shi
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Yonghua Li
- Department of Respiratory and Critical Care Medicine, No. 906 Hospital of the Chinese People's Liberation Army Joint Logistic Support Force, Ningbo, China
| | - Haidong Huang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Chong Bai
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China
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Kang J, Wang M, Hua P, Wang B. A rare case report: co-occurrence of two types of lung cancer with hamartoma and pulmonary tuberculosis. Front Oncol 2023; 13:1264871. [PMID: 37869098 PMCID: PMC10585360 DOI: 10.3389/fonc.2023.1264871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 09/18/2023] [Indexed: 10/24/2023] Open
Abstract
With the widespread use of low-dose chest Computed Tomography (CT), lung nodules are being increasingly detected. Common pulmonary conditions such as lung adenocarcinoma, lung squamous cell carcinoma, and tuberculosis are typically diagnosable through imaging examinations. Nevertheless, when multiple types of lung cancer are combined with other benign tumors, how can an accurate diagnosis be made? In this report, we present a rare case of a patient with the simultaneous occurrence of lung adenocarcinoma, lung squamous cell carcinoma, pulmonary tuberculosis, and pulmonary hamartoma, which has not been previously reported. This patient underwent surgical intervention in the Department of Thoracic Surgery at the Second Hospital of Jilin University and has now fully recovered and been discharged. The patient's preoperative positron emission tomography-CT(PET-CT)results did not align with the postoperative pathological diagnosis. The imaging findings were atypical, and the pathological diagnosis was exceptionally rare. We share this case report to contribute to the accumulation of clinical experience.
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Affiliation(s)
| | | | - Peiyan Hua
- Department of Thoracic of the Second Hospital of Jilin University, Changchun, Jilin, China
| | - Bin Wang
- Department of Thoracic of the Second Hospital of Jilin University, Changchun, Jilin, China
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Xue M, Li R, Wang K, Liu W, Liu J, Li Z, Ma Z, Zhang H, Tian H, Tian Y. Nomogram combining clinical and radiological characteristics for predicting the malignant probability of solitary pulmonary nodules measuring ≤ 2 cm. Front Oncol 2023; 13:1196778. [PMID: 37795448 PMCID: PMC10545867 DOI: 10.3389/fonc.2023.1196778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 09/04/2023] [Indexed: 10/06/2023] Open
Abstract
Background At present, how to identify the benign or malignant nature of small (≤ 2 cm) solitary pulmonary nodules (SPN) are an urgent clinical challenge. This retrospective study aimed to develop a clinical prediction model combining clinical and radiological characteristics for assessing the probability of malignancy in SPNs measuring ≤ 2 cm. Method In this study, we included patients with SPNs measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to December 2021. Clinical features, preoperative biomarker results, and computed tomography characteristics were collected. The enrolled patients were randomized at a ratio of 7:3 into a training cohort of 775 and a validation cohort of 331. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. The receiver operating characteristic (ROC) curve was used to evaluate the identification ability of the model. The calibration power was evaluated using the Hosmer-Lemeshow test and calibration curve. The clinical utility of the nomogram was also assessed by decision curve analysis (DCA). Result A total of 1,106 patients were included in this study. Among them, the malignancy rate of SPNs was 85.08% (941/1,106). We finally identified the following six independent risk factors by logistic regression: age, carcinoembryonic antigen, nodule shape, calcification, maximum diameter, and consolidation-to-tumor ratio. The area under the ROC curve (AUC) for the training cohort was 0.764 (95% confidence interval [CI]: 0.714-0.814), and the AUC for the validation cohort was 0.729 (95% CI: 0.647-0.811), indicating that the prediction accuracy of nomogram was relatively good. The calibration curve of the predictive model also demonstrated a good calibration in both cohorts. DCA proved that the clinical prediction model was useful in clinical practice. Conclusion We developed and validated a predictive model and nomogram for estimating the probability of malignancy in SPNs measuring ≤ 2 cm. With the application of predictive models, thoracic surgeons can make more rational clinical decisions while avoiding overtreatment and wasting medical resources.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Hui Tian
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Yu Tian
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, China
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Khodayari Moez E, Warkentin MT, Brhane Y, Lam S, Field JK, Liu G, Zulueta JJ, Valencia K, Mesa-Guzman M, Nialet AP, Atkar-Khattra S, Davies MPA, Grant B, Murison K, Montuenga LM, Amos CI, Robbins HA, Johansson M, Hung RJ. Circulating proteome for pulmonary nodule malignancy. J Natl Cancer Inst 2023; 115:1060-1070. [PMID: 37369027 PMCID: PMC10483334 DOI: 10.1093/jnci/djad122] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 05/29/2023] [Accepted: 06/22/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules. METHODS Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated. RESULTS We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001). CONCLUSIONS Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.
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Affiliation(s)
- Elham Khodayari Moez
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Matthew T Warkentin
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Yonathan Brhane
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Stephen Lam
- Integrative Oncology, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - John K Field
- Molecular & Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
| | - Geoffrey Liu
- Computational Biology and Medicine Program, Princess Margaret Cancer Center, Toronto, ON, Canada
| | - Javier J Zulueta
- Division of Pulmonary, Critical Care and Sleep Medicine, Mount Sinai Morningside Hospital, Icahn School of Medicine, New York, NY, USA
| | - Karmele Valencia
- Center of Applied Medical Research (CIMA) and Schools of Sciences and Medicine, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Centro de Investigacion Biomedica en Red de Cancer (CIBERONC), Madrid, Spain
| | - Miguel Mesa-Guzman
- Thoracic Surgery Department, Clínica Universidad de Navarra, Pamplona, Spain
| | - Andrea Pasquier Nialet
- Center of Applied Medical Research (CIMA) and Schools of Sciences and Medicine, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Centro de Investigacion Biomedica en Red de Cancer (CIBERONC), Madrid, Spain
| | | | - Michael P A Davies
- Molecular & Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
| | - Benjamin Grant
- Computational Biology and Medicine Program, Princess Margaret Cancer Center, Toronto, ON, Canada
| | - Kiera Murison
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Luis M Montuenga
- Center of Applied Medical Research (CIMA) and Schools of Sciences and Medicine, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Centro de Investigacion Biomedica en Red de Cancer (CIBERONC), Madrid, Spain
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Hilary A Robbins
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
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Song F, Fu B, Liu M, Liu X, Liu S, Lv F. Proposal of Modified Lung-RADS in Assessing Pulmonary Nodules of Patients with Previous Malignancies: A Primary Study. Diagnostics (Basel) 2023; 13:2210. [PMID: 37443604 DOI: 10.3390/diagnostics13132210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 06/12/2023] [Accepted: 06/16/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND In addition to the diameters of pulmonary nodules, the number and morphology of blood vessels in pure ground-glass nodules (pGGNs) were closely related to the occurrence of lung cancer. Moreover, the benign and malignant signs of nodules were also valuable for the identification of nodules. Based on these two points, we tried to revise Lung-RADS 2022 and proposed our Modified Lung-RADS. The aim of the study was to verify the diagnostic performance of Modified Lung-RADS for pulmonary solid nodules (SNs) and pure ground-glass nodules (pGGNs) in patients with previous malignancies. METHODS The chest CT and clinical data of patients with prior cancer who underwent pulmonary nodulectomies from 1 January 2018 to 30 November 2021 were enrolled according to inclusion and exclusion criteria. A total of 240 patients with 293 pulmonary nodules were included in this study. In contrast with the original version, the risk classification of pGGNs based on the GGN-vascular relationships (GVRs), and the SNs without burrs and with benign signs, could be downgraded to category 2. The sensitivity, specificity, and agreement rate of the original Lung-RADS 2022 and Modified Lung-RADS for pGGNs and SNs were calculated and compared. RESULTS Compared with the original version, the sensitivity and agreement rate of the Modified version for pGGNs increased from 0 and 23.33% to 97.10% and 92.22%, respectively, while the specificity decreased from 100% to 76.19%. As regards SNs, the specificity and agreement rate of the Modified version increased from 44.44% to 75.00% (p < 0.05) and 88.67% to 94.09% (p = 0.052), respectively, while the sensitivity was unchanged (98.20%). CONCLUSIONS In general, the diagnostic efficiency of Modified Lung-RADS was superior to that of the original version, and Modified Lung-RADS could be a preliminary attempt to improve Lung-RADS 2022.
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Affiliation(s)
- Feipeng Song
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1 YouYi Road, Chongqing 400010, China
| | - Binjie Fu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1 YouYi Road, Chongqing 400010, China
| | - Mengxi Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1 YouYi Road, Chongqing 400010, China
| | - Xiangling Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1 YouYi Road, Chongqing 400010, China
| | - Sizhu Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1 YouYi Road, Chongqing 400010, China
| | - Fajin Lv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1 YouYi Road, Chongqing 400010, China
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Guerra M. Predicting lung nodules malignancy. Pulmonology 2023:S2531-0437(22)00263-X. [PMID: 36639330 DOI: 10.1016/j.pulmoe.2022.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 11/18/2022] [Accepted: 11/21/2022] [Indexed: 01/13/2023] Open
Affiliation(s)
- M Guerra
- Thoracic Surgery, Centro Hospitalar de Vila Nova de Gaia, Portugal; Faculty of Medicine of Oporto, Portugal.
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Georgiev A, Chervenkov L, Anastasova V, Kitova T. Comment on "Evaluation of pulmonary nodules by magnetic resonance imaging sequences: which sequence will replace computed tomography?". REVISTA DA ASSOCIACAO MEDICA BRASILEIRA (1992) 2023; 69:e20221624. [PMID: 37075370 PMCID: PMC10176654 DOI: 10.1590/1806-9282.20221624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 01/10/2023] [Indexed: 04/21/2023]
Affiliation(s)
- Aleksandar Georgiev
- Medical University Plovdiv, Department of Diagnostic Imaging - Plovdiv, Bulgaria
- Complex Oncology Center Plovdiv, Department of Diagnostic Imaging - Plovdiv, Bulgaria
| | - Lyubomir Chervenkov
- Medical University Plovdiv, Department of Diagnostic Imaging - Plovdiv, Bulgaria
| | - Vania Anastasova
- Medical University Plovdiv, Faculty of Medicine, Department of Propaedeutics of Surgical Diseases, Section of Plastic, Reconstructive and Aesthetic Surgery and Thermal Trauma - Plovdiv, Bulgaria
| | - Tanya Kitova
- Medical University Plovdiv, Department of Human Anatomy, Histology and Embryology - Plovdiv, Bulgaria
- Trakia University, Medical College - Stara Zagora, Bulgaria
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Senent-Valero M, Librero J, Pastor-Valero M. Solitary pulmonary nodule malignancy predictive models applicable to routine clinical practice: a systematic review. Syst Rev 2021; 10:308. [PMID: 34872592 PMCID: PMC8650360 DOI: 10.1186/s13643-021-01856-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 11/18/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Solitary pulmonary nodule (SPN) is a common finding in routine clinical practice when performing chest imaging tests. The vast majority of these nodules are benign, and only a small proportion are malignant. The application of predictive models of nodule malignancy in routine clinical practice would help to achieve better diagnostic management of SPN. The present systematic review was carried out with the purpose of critically assessing studies aimed at developing predictive models of solitary pulmonary nodule (SPN) malignancy from SPN incidentally detected in routine clinical practice. METHODS We performed a search of available scientific literature until October 2020 in Pubmed, SCOPUS and Cochrane Central databases. The inclusion criteria were observational studies carried out in low-risk population from 35 years old onwards aimed at constructing predictive models of malignancy of pulmonary solitary nodule detected incidentally in routine clinical practice. Studies had to be published in peer-reviewed journals, either in Spanish, Portuguese or English. Exclusion criteria were non-human studies, or predictive models based in high-risk populations, or models based on computational approaches. Exclusion criteria were non-human studies, or predictive models based in high-risk populations, or models based on computational approaches (such as radiomics). We used The Transparent Reporting of a multivariable Prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement, to describe the type of predictive model included in each study, and The Prediction model Risk Of Bias ASsessment Tool (PROBAST) to evaluate the quality of the selected articles. RESULTS A total of 186 references were retrieved, and after applying the exclusion/inclusion criteria, 15 articles remained for the final review. All studies analysed clinical and radiological variables. The most frequent independent predictors of SPN malignancy were, in order of frequency, age, diameter, spiculated edge, calcification and smoking history. Variables such as race, SPN growth rate, emphysema, fibrosis, apical scarring and exposure to asbestos, uranium and radon were not analysed by the majority of the studies. All studies were classified as high risk of bias due to inadequate study designs, selection bias, insufficient population follow-up and lack of external validation, compromising their applicability for clinical practice. CONCLUSIONS The studies included have been shown to have methodological weaknesses compromising the clinical applicability of the evaluated SPN malignancy predictive models and their potential influence on clinical decision-making for the SPN diagnostic management. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42020161559.
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Affiliation(s)
- Marina Senent-Valero
- Department of Public Health, History of Science and Gynaecology, Faculty of Medicine, Miguel Hernández University, Sant Joan d'Alacant, Alicante, Spain.
| | - Julián Librero
- Navarrabiomed, Complejo Hospitalario de Navarra, UPNA, Pamplona, Spain
- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Valencia, Spain
| | - María Pastor-Valero
- Department of Public Health, History of Science and Gynaecology, Faculty of Medicine, Miguel Hernández University, Sant Joan d'Alacant, Alicante, Spain
- CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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