47 research outputs found
Thoracic Operations for Pulmonary Nodules Are Frequently Not Futile in Patients with Benign Disease
IntroductionPulmonary nodules often require operative resection to obtain a diagnosis. However, 10 to 30% of operations result in a benign diagnosis. Our purpose was to determine whether negative thoracic operations are futile by describing the pathological diagnoses; determining new diagnoses and treatment changes initiated based on operative findings; and assessing morbidity, mortality, and cost of the procedure.MethodsAt our academic medical center, 278 thoracic operations were performed for known or suspected cancer between January 1, 2005, and April 1, 2009. We collected and summarized data pertaining to preoperative patient and nodule characteristics, pathologic diagnosis, postoperative treatment changes resulting from surgical resection, perioperative morbidity and mortality, and hospital charges for patients with benign pathology.ResultsTwenty-three percent (65/278) of patients who underwent surgical resection for a suspicious nodule had benign pathology. We report granulomatous disease in 57%, benign tumors in 15%, fibrosis in 12%, and autoimmune and vascular diseases in 9%. Definitive diagnosis or treatment changes occurred in 85% of cases. Surgical intervention led to a new diagnosis in 69%, treatment course changes in 68% of benign cases, medication changes in 38%, new consultation in 31%, definitive treatment in 9%, and underlying disease management in 34%. There was no intraoperative, in-hospital, or 30-day mortality. Postoperative in-hospital events occurred in seven patients. The mean total cost was 7618.ConclusionsPatients with a benign diagnosis after surgical resection for a pulmonary nodule received a new diagnosis or had a treatment course change in 85% of the cases
A plasma miRNA-based classifier for small cell lung cancer diagnosis
IntroductionSmall cell lung cancer (SCLC) is characterized by poor prognosis and challenging diagnosis. Screening in high-risk smokers results in a reduction in lung cancer mortality, however, screening efforts are primarily focused on non-small cell lung cancer (NSCLC). SCLC diagnosis and surveillance remain significant challenges. The aberrant expression of circulating microRNAs (miRNAs/miRs) is reported in many tumors and can provide insights into the pathogenesis of tumor development and progression. Here, we conducted a comprehensive assessment of circulating miRNAs in SCLC with a goal of developing a miRNA-based classifier to assist in SCLC diagnoses.MethodsWe profiled deregulated circulating cell-free miRNAs in the plasma of SCLC patients. We tested selected miRNAs on a training cohort and created a classifier by integrating miRNA expression and patients’ clinical data. Finally, we applied the classifier on a validation dataset.ResultsWe determined that miR-375-3p can discriminate between SCLC and NSCLC patients, and between SCLC and Squamous Cell Carcinoma patients. Moreover, we found that a model comprising miR-375-3p, miR-320b, and miR-144-3p can be integrated with race and age to distinguish metastatic SCLC from a control group.DiscussionThis study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis
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Mapping Histoplasma capsulatum Exposure, United States.
Maps of Histoplasma capsulatum infection prevalence were created 50 years ago; since then, the environment, climate, and anthropogenic land use have changed drastically. Recent outbreaks of acute disease in Montana and Nebraska, USA, suggest shifts in geographic distribution, necessitating updated prevalence maps. To create a weighted overlay geographic suitability model for Histoplasma, we used a geographic information system to combine satellite imagery integrating land cover use (70%), distance to water (20%), and soil pH (10%). We used logistic regression modeling to compare our map with state-level histoplasmosis incidence data from a 5% sample from the Centers for Medicare and Medicaid Services. When compared with the state-based Centers data, the predictive accuracy of the suitability score-predicted states with high and mid-to-high histoplasmosis incidence was moderate. Preferred soil environments for Histoplasma have migrated into the upper Missouri River basin. Suitability score mapping may be applicable to other geographically specific infectious vectors
Diagnostic models predicting paediatric viral acute respiratory infections: a systematic review
Objectives To systematically review and evaluate diagnostic models used to predict viral acute respiratory infections (ARIs) in children.Design Systematic review.Data sources PubMed and Embase were searched from 1 January 1975 to 3 February 2022.Eligibility criteria We included diagnostic models predicting viral ARIs in children (<18 years) who sought medical attention from a healthcare setting and were written in English. Prediction model studies specific to SARS-CoV-2, COVID-19 or multisystem inflammatory syndrome in children were excluded.Data extraction and synthesis Study screening, data extraction and quality assessment were performed by two independent reviewers. Study characteristics, including population, methods and results, were extracted and evaluated for bias and applicability using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and PROBAST (Prediction model Risk Of Bias Assessment Tool).Results Of 7049 unique studies screened, 196 underwent full text review and 18 were included. The most common outcome was viral-specific influenza (n=7; 58%). Internal validation was performed in 8 studies (44%), 10 studies (56%) reported discrimination measures, 4 studies (22%) reported calibration measures and none performed external validation. According to PROBAST, a high risk of bias was identified in the analytic aspects in all studies. However, the existing studies had minimal bias concerns related to the study populations, inclusion and modelling of predictors, and outcome ascertainment.Conclusions Diagnostic prediction can aid clinicians in aetiological diagnoses of viral ARIs. External validation should be performed on rigorously internally validated models with populations intended for model application.PROSPERO registration number CRD42022308917
Mapping Histoplasma capsulatum Exposure, United States
Maps of Histoplasma capsulatum infection prevalence were created 50 years ago; since then, the environment, climate, and anthropogenic land use have changed drastically. Recent outbreaks of acute disease in Montana and Nebraska, USA, suggest shifts in geographic distribution, necessitating updated prevalence maps. To create a weighted overlay geographic suitability model for Histoplasma, we used a geographic information system to combine satellite imagery integrating land cover use (70%), distance to water (20%), and soil pH (10%). We used logistic regression modeling to compare our map with state-level histoplasmosis incidence data from a 5% sample from the Centers for Medicare and Medicaid Services. When compared with the state-based Centers data, the predictive accuracy of the suitability score–predicted states with high and mid-to-high histoplasmosis incidence was moderate. Preferred soil environments for Histoplasma have migrated into the upper Missouri River basin. Suitability score mapping may be applicable to other geographically specific infectious vectors
Cancer screening: the journey from epidemiology to policy.
PurposeCancer screening procedures have brought great benefit to the public's health. However, the science of cancer screening and the evidence arising from research in this field as it is applied to policy is complex and has been difficult to communicate, especially on the national stage. We explore how epidemiologists have contributed to this evidence base and to its translation into policy.MethodsOur essay focuses on breast and lung cancer screening to identify commonalities of experience by epidemiologists across two different cancer sites and describe how epidemiologists interact with evolving scientific and policy environments.ResultsWe describe the roles and challenges that epidemiologists encounter according to the maturity of the data, stakeholders, and the related political context. We also explore the unique position of cancer screening as influenced by the legislative landscape where, due to recent healthcare reform, cancer screening research plays directly into national policy.ConclusionsIn the complex landscape for cancer screening policy, epidemiologists can increase their impact by learning from past experiences, being well prepared and communicating effectively