Reply to Wilson: Risk-Stratifying Pulmonary Nodules.
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ABSTRACT:
SUBMITTER: Massion PP
PROVIDER: S-EPMC7781119 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Publications
Reply to Wilson: Risk-Stratifying Pulmonary Nodules.
American journal of respiratory and critical care medicine 20210101 1
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Project description: Not available
| S-EPMC7781134 | biostudies-literature
Project description:Multidrug-resistant tuberculosis (MDR-TB), resistance to at least isoniazid and rifampin, is a worldwide problem.To develop a clinical prediction rule to stratify risk for MDR-TB among patients with pulmonary tuberculosis.Derivation and internal validation of the rule among adult patients prospectively recruited from 37 health centers (Perú), either a) presenting with a positive acid-fast bacillus smear, or b) had failed therapy or had a relapse within the first 12 months.Among 964 patients, 82 had MDR-TB (prevalence, 8.5%). Variables included were MDR-TB contact within the family, previous tuberculosis, cavitary radiologic pattern, and abnormal lung exam. The area under the receiver-operating curve (AUROC) was 0.76. Selecting a cut-off score of one or greater resulted in a sensitivity of 72.6%, specificity of 62.8%, likelihood ratio (LR) positive of 1.95, and LR negative of 0.44. Similarly, selecting a cut-off score of two or greater resulted in a sensitivity of 60.8%, specificity of 87.5%, LR positive of 4.85, and LR negative of 0.45. Finally, selecting a cut-off score of three or greater resulted in a sensitivity of 45.1%, specificity of 95.3%, LR positive of 9.56, and LR negative of 0.58.A simple clinical prediction rule at presentation can stratify risk for MDR-TB. If further validated, the rule could be used for management decisions in resource-limited areas.
| S-EPMC2920322 | biostudies-other
Project description: Not available
| S-EPMC7560797 | biostudies-literature
Project description:It is estimated that over 1.5 million lung nodules are detected annually in the United States. Most of these are benign but frequently undergo invasive and costly procedures to rule out malignancy. A risk predictor that can accurately differentiate benign and malignant lung nodules could be used to more efficiently route benign lung nodules to non-invasive observation by CT surveillance and route malignant lung nodules to invasive procedures. The majority of risk predictors developed to date are based exclusively on clinical risk factors, imaging technology or molecular markers. Assessed here are the relative performances of previously reported clinical risk factors and proteomic molecular markers for assessing cancer risk in lung nodules. From this analysis an integrated model incorporating clinical risk factors and proteomic molecular markers is developed and its performance assessed on a subset of 222 lung nodules, between 8mm and 20mm in diameter, collected in a previously reported prospective study. In this analysis it is found that the molecular marker is most predictive. However, the integration of clinical and molecular markers is superior to both clinical and molecular markers separately.Clinical trial registrationRegistered at ClinicalTrials.gov (NCT01752101).
| S-EPMC5435179 | biostudies-literature
Project description:Rationale: NT-proBNP (N-terminal pro-brain natriuretic peptide), a biomarker of cardiac origin, is used to risk stratify patients with pulmonary arterial hypertension (PAH). Its limitations include poor sensitivity to early vascular pathology. Other biomarkers of vascular or systemic origin may also be useful in the management of PAH. Objectives: Identify prognostic proteins in PAH that complement NT-proBNP and clinical risk scores. Methods: An aptamer-based assay (SomaScan version 4) targeting 4,152 proteins was used to measure plasma proteins in patients with idiopathic, heritable, or drug-induced PAH from the UK National Cohort of PAH (n = 357) and the French EFORT (Evaluation of Prognostic Factors and Therapeutic Targets in PAH) study (n = 79). Prognostic proteins were identified in discovery-replication analyses of UK samples. Proteins independent of 6-minute-walk distance and NT-proBNP entered least absolute shrinkage and selection operator modeling, and the best combination in a single score was evaluated against clinical targets in EFORT. Measurements and Main Results: Thirty-one proteins robustly informed prognosis independent of NT-proBNP and 6-minute-walk distance in the UK cohort. A weighted combination score of six proteins was validated at baseline (5-yr mortality; area under the curve [AUC], 0.73; 95% confidence interval [CI], 0.63-0.85) and follow-up in EFORT (AUC, 0.84; 95% CI, 0.75-0.94; P = 9.96 × 10-6). The protein score risk stratified patients independent of established clinical targets and risk equations. The addition of the six-protein model score to NT-proBNP improved prediction of 5-year outcomes from AUC 0.762 (0.702-0.821) to 0.818 (0.767-0.869) by receiver operating characteristic analysis (P = 0.00426 for difference in AUC) in the UK replication and French samples combined. Conclusions: The plasma proteome informs prognosis beyond established factors in PAH and may provide a more sensitive measure of therapeutic response.
| S-EPMC9851485 | biostudies-literature
Project description:A serum miRNA combination could be a favourable classifier to differentiate malignant pulmonary nodules from benign pulmonary nodules.
2023-08-27 | GSE157074 | GEO
Project description:There are no large samples or exact prediction models for assessing the cancer risk factors of solitary pulmonary nodules (SPNs) in the Chinese population. We retrospectively analyzed the clinical and imaging data of patients with SPNs who underwent computer tomography guided needle biopsy in our hospital from Jan 1st of 2011 to March 30th of 2016. These patients were divided into a development data set and a validation data set. These groups included 1078 and 344 patients, respectively. A prediction model was developed from the development data set and was validated with the validation data set using logistic regression. The predictors of cancer in our model included female gender, age, pack-years of smoking, a previous history of malignancy, nodule size, lobulated and spiculated edges, lobulation alone and spiculation alone. The Area Under the Curves, sensitivity and specificity of our model in the development and validation data sets were significantly higher than those of the Mayo model and VA model (p < 0.001). We established the largest sampling risk prediction model of SPNs in a Chinese cohort. This model is particularly applicable to SPNs > 8 mm in size. SPNs in female patients, as well as SPNs featuring a combination of lobulated and spiculated edges or lobulated edges alone, should be evaluated carefully due to the probability that they are malignant.
| S-EPMC5438732 | biostudies-literature
Project description:BackgroundPrevious studies have indicated that clinical and imaging features may assist in distinguishing between benign and malignant solid lung nodules. Yet, the specific characteristics in question continue to be debated. This meta-analysis aims to identify risk factors for malignant solid lung nodules, thereby supporting informed clinical decision-making.MethodsA comprehensive search of databases including PubMed, Embase, Web of Science, Cochrane Library, Scopus, Wanfang, CNKI, VIP, and CBM was conducted up to October 6, 2024. Only publications in Chinese or English were considered. Data analysis was performed using Stata 16.0 software.ResultsThis analysis included 32 studies, comprising 7758 solid pulmonary nodules, of which 3359 were benign and 4399 were malignant. It was found that the incidence of spiculate signs in malignant solid pulmonary nodules (MSPN) was higher than in benign solid pulmonary nodules (BSPN) [OR = 3.06, 95% CI (2.35, 3.98), P < 0.05. Additionally, increases were observed in the incidences of vascular convergence[OR = 16.57, 95% CI (8.79, 31.24), P < 0.05], lobulated signs [OR = 5.17, 95% CI (3.83, 6.98)], air bronchogram sign[OR = 2.96, 95% CI (1.62, 5.41), P < 0.05], pleura traction sign [OR = 2.33, 95% CI (1.65, 3.29), P < 0.05], border blur [OR = 2.94, 95% CI (1.47, 5.85), P < 0.05], vacuole signs [OR = 5.25, 95% CI (2.66, 10.37), P < 0.05], and family history of cancer [OR = 3.85, 95% CI (2.43, 6.12), P < 0.05] compared to BSPN. Older age[OR = 1.06, 95% CI (1.04, 1.07), P < 0.05], higher prevalence in females [OR = 2.98, 95% CI (2.27, 3.92), P < 0.05], larger nodule diameters [OR = 1.25, 95% CI (1.13, 1.38), P < 0.05], and lower incidence of calcification [OR = 0.21, 95% CI (0.10, 0.48), P < 0.05] were also associated with MSPN. No significant differences were found between MSPN and BSPN regarding CEA and emphysema (all P > 0.05).ConclusionsThis meta-analysis highlights that spiculate sign, vascular convergence sign, lobulated sign, diameter, border blur, vacuole sign, age, gender, family history of cancer, pleura traction, air bronchogram sign, and calcification are significant markers for predicting malignancy in SPNs, potentially influencing clinical management. However, further well-designed, large-scale studies are needed to confirm these findings.
| S-EPMC11844030 | biostudies-literature
Project description:RationaleWilson disease is an autosomal recessive genetic disease found by Samuel Alexander Kinnier Wilson and prevalent in childhood and adolescents.Patient concernsAn 18-year-old female patient presented to our hospital with a continuous decrease of 3 blood cell lines for more than 10 days, and diagnosed as decompensated cirrhosis. Ultrasonography showed diffuse lesions in the hepatic parenchyma, with multiple hypoechoic light masses in the parenchyma, the outline was still clear, and the internal echo was uneven. Contrast-enhanced ultrasound showed that the nodules were enhanced rapidly and uniformly, with an initial enhancement time of 9 seconds and a peak time of 17.2 seconds. The washing time was slightly earlier than that of the hepatic parenchyma and showed slightly higher enhancement in the delayed phase. Finally, ultrasound-guided biopsies showed unexplained liver cirrhosis.DiagnosesCombined with clinical examination, it was inferred to be Wilson disease. It is difficult to diagnose hepatolenticular degeneration because of its concealed incidence, complex clinical manifestations, expensive detection of the ATP7B gene, and lack of other specific imaging signs.OutcomesAfter admission, the patient was given symptomatic support treatment such as liver protection.InterventionsThe patient was discharged after improvement of symptoms.LessonsHere, the results of contrast-enhanced ultrasound in our case may provide a new idea for the diagnosis of Wilson.
| S-EPMC11495761 | biostudies-literature
Project description:BackgroundScreening with low-dose computed tomography (LDCT) is an efficient way to detect lung cancer at an earlier stage, but has a high false-positive rate. Several pulmonary nodules risk prediction models were developed to solve the problem. This systematic review aimed to compare the quality and accuracy of these models.MethodsThe keywords "lung cancer," "lung neoplasms," "lung tumor," "risk," "lung carcinoma" "risk," "predict," "assessment," and "nodule" were used to identify relevant articles published before February 2021. All studies with multivariate risk models developed and validated on human LDCT data were included. Informal publications or studies with incomplete procedures were excluded. Information was extracted from each publication and assessed.ResultsA total of 41 articles and 43 models were included. External validation was performed for 23.2% (10/43) models. Deep learning algorithms were applied in 62.8% (27/43) models; 60.0% (15/25) deep learning based researches compared their algorithms with traditional methods, and received better discrimination. Models based on Asian and Chinese populations were usually built on single-center or small sample retrospective studies, and the majority of the Asian models (12/15, 80.0%) were not validated using external datasets.ConclusionThe existing models showed good discrimination for identifying high-risk pulmonary nodules, but lacked external validation. Deep learning algorithms are increasingly being used with good performance. More researches are required to improve the quality of deep learning models, particularly for the Asian population.
| S-EPMC8888150 | biostudies-literature