Integrated Biomarkers for the Management of Indeterminate Pulmonary Nodules.

Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk prediction model that combined clinical, blood, and imaging biomarkers to improve the noninvasive management of IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability of cancer was calculated for 456 patient nodules using the Mayo Clinic model, and patients were categorized into low-, intermediate-, and high-risk groups. A combined biomarker model (CBM) including clinical variables, serum high sensitivity CYFRA 21-1 level, and a radiomic signature was trained in cohort 1 (n = 170) and validated in cohorts 2-4 (total n = 286). All patients were pooled to recalibrate the model for clinical implementation. The clinical utility of the CBM compared with current clinical care was evaluated in 2 cohorts. Measurements and Main Results: The CBM provided improved diagnostic accuracy over the Mayo Clinic model with an improvement in area under the curve of 0.124 (95% bootstrap confidence interval, 0.091-0.156; P < 2 × 10-16). Applying 10% and 70% risk thresholds resulted in a bias-corrected clinical reclassification index for cases and control subjects of 0.15 and 0.12, respectively. A clinical utility analysis of patient medical records estimated that a CBM-guided strategy would have reduced invasive procedures from 62.9% to 50.6% in the intermediate-risk benign population and shortened the median time to diagnosis of cancer from 60 to 21 days in intermediate-risk cancers. Conclusions: Integration of clinical, blood, and image biomarkers improves noninvasive diagnosis of patients with IPNs, potentially reducing the rate of unnecessary invasive procedures while shortening the time to diagnosis.

Measurement of provider fidelity to immunization guidelines: a mixed-methods study on the feasibility of documenting patient refusals of the human papillomavirus vaccine.

BACKGROUND: Assessment and feedback is a common implementation strategy to improve healthcare provider fidelity to clinical guidelines. For immunization guidelines, fidelity is often measured with doses administered during eligible visits. Adding a patient refusal measure captures provider fidelity more completely (i.e., all instances of a provider recommending a vaccine, resulting in vaccination or refusal) and enables providers to track patient vaccine hesitancy patterns. However, many electronic health record (EHR) systems have no structured field to document multiple instances of refusals for specific vaccines, and existing billing codes for refusal are not vaccine specific. This study assessed the feasibility of a novel method for refusal documentation used in a study focused on human papillomavirus (HPV) vaccine. METHODS: An observational, descriptive-comparative, mixed-methods study design was used to conduct secondary data analysis from an implementation-effectiveness trial. The parent trial compared coach-based versus web-based practice facilitation, including assessment and feedback, to increase HPV vaccination in 21 community-based private pediatric practices. Providers were instructed to document initial HPV vaccine refusals in the EHR's immunization forms and subsequent refusals using dummy procedure codes, for use in assessment and feedback reports. This analysis examined adoption and maintenance of the refusal documentation method during eligible well visits, identified barriers and facilitators to documentation and described demographic patterns in patient refusals. RESULTS: Seven practices adopted the refusal documentation method. Among adopter practices, documented refusals started at 2.4% of eligible well visits at baseline, increased to 14.2% at the start of implementation, peaked at 24.0%, then declined to 18.8%. Barriers to refusal documentation included low prioritization, workflow integration and complication of the billing process. Facilitators included high motivation, documentation instructions and coach support. Among adopter practices, odds of refusing HPV vaccine were 25% higher for patients aged 15-17 years versus 11-12 years, and 18% lower for males versus females. CONCLUSIONS: We demonstrated the value of patient refusal documentation for measuring HPV vaccination guideline fidelity and ways that it can be improved in future research. Creation of vaccine-specific refusal billing codes or EHR adaptations to enable documenting multiple instances of specific vaccine refusals would facilitate consistent refusal documentation. Trial Registration NCT03399396 Registered in ClinicalTrials.gov on 1/16/2018.

A retrospective approach to evaluating potential adverse outcomes associated with delay of procedures for cardiovascular and cancer-related diagnoses in the context of COVID-19.

OBJECTIVE: During the COVID-19 pandemic, health systems postponed non-essential medical procedures to accommodate surge of critically-ill patients. The long-term consequences of delaying procedures in response to COVID-19 remains unknown. We developed a high-throughput approach to understand the impact of delaying procedures on patient health outcomes using electronic health record (EHR) data. MATERIALS AND METHODS: We used EHR data from Vanderbilt University Medical Center's (VUMC) Research and Synthetic Derivatives. Elective procedures and non-urgent visits were suspended at VUMC between March 18, 2020 and April 24, 2020. Surgical procedure data from this period were compared to a similar timeframe in 2019. Potential adverse impact of delay in cardiovascular and cancer-related procedures was evaluated using EHR data collected from January 1, 1993 to March 17, 2020. For surgical procedure delay, outcomes included length of hospitalization (days), mortality during hospitalization, and readmission within six months. For screening procedure delay, outcomes included 5-year survival and cancer stage at diagnosis. RESULTS: We identified 416 surgical procedures that were negatively impacted during the COVID-19 pandemic compared to the same timeframe in 2019. Using retrospective data, we found 27 significant associations between procedure delay and adverse patient outcomes. Clinician review indicated that 88.9% of the significant associations were plausible and potentially clinically significant. Analytic pipelines for this study are available online. CONCLUSION: Our approach enables health systems to identify medical procedures affected by the COVID-19 pandemic and evaluate the effect of delay, enabling them to communicate effectively with patients and prioritize rescheduling to minimize adverse patient outcomes.

Modeling the impact of delaying surgery for early esophageal cancer in the era of COVID-19.

BACKGROUND: Surgical society guidelines have recommended changing the treatment strategy for early esophageal cancer during the novel coronavirus (COVID-19) pandemic. Delaying resection can allow for interim disease progression, but the impact of this delay on mortality is unknown. The COVID-19 infection rate at which immediate operative risk exceeds benefit is unknown. We sought to model immediate versus delayed surgical resection in a T1b esophageal adenocarcinoma. METHODS: A decision analysis model was developed, and sensitivity analyses performed. The base case was a 65-year-old male smoker presenting with cT1b esophageal adenocarcinoma scheduled for esophagectomy during the COVID-19 pandemic. We compared immediate surgical resection to delayed resection after 3 months. The likelihood of key outcomes was derived from the literature where available. The outcome was 5-year overall survival. RESULTS: Proceeding with immediate esophagectomy for the base case scenario resulted in slightly improved 5-year overall survival when compared to delaying surgery by 3 months (5-year overall survival 0.74 for immediate and 0.73 for delayed resection). In sensitivity analyses, a delayed approach became preferred when the probability of perioperative COVID-19 infection increased above 7%. CONCLUSIONS: Immediate resection of early esophageal cancer during the COVID-19 pandemic did not decrease 5-year survival when compared to resection after 3 months for the base case scenario. However, as the risk of perioperative COVID-19 infection increases above 7%, a delayed approach has improved 5-year survival. This balance should be frequently re-examined by surgeons as infection risk changes in each hospital and community throughout the COVID-19 pandemic.

Projecting Cancer Incidence for 2025 in the 2 Largest Populated Cities in Vietnam.

The population size and projected demographics of Vietnam's 2 largest cities, Ho Chi Minh City (HCMC) and Hanoi, will change dramatically over the next decade. Demographic changes in an aging population coupled with income growth and changes in lifestyle will result in a very different distribution of common cancers in the future. The study aimed to project the number of cancer incidence in the 2 largest populated cities in Vietnam for the year 2025. Cancer incidence data from 2004 to 2013 collected from population-based cancer registries in these 2 cities were provided by Vietnam National Cancer Institute. Incidence cases in 2013 and the previous decades average annual percent changes of age-standardized cancer incidence rates combined with expected population growth were modeled to project cancer incidence for each cancer site by gender to 2025. A substantial double in cancer incidence from 2013 to 2025 resulted from a growing and aging population in HCMC and Hanoi. Lung, colorectum, breast, thyroid, and liver cancers, which represent 67% of the overall cancer burden, are projected to become the leading cancer diagnoses by 2025 regardless of genders. For men, the leading cancer sites in 2025 are predicted to be lung, colorectum, esophagus, liver, and pharynx cancer, and among women, they are expected to be breast, thyroid, colorectum, lung, and cervical cancer. We projected an epidemiological transition from infectious-associated cancers to a high burden of cancers that have mainly been attributed to lifestyle in both cities. We predicted that with 16.9% growth in the overall population and dramatic aging with these 2 urban centers, the burdens of cancer incidence will increase sharply in both cities over the next decades. Data on projections of cancer incidence in both cities provide useful insights for directing appropriate policies and cancer control programs in Vietnam.

Impact of Culture-Independent Diagnostic Testing on Recovery of Enteric Bacterial Infections.

Background: Culture-independent diagnostic tests (CIDTs) are increasingly used to identify enteric pathogens. However, foodborne illness surveillance systems have relied upon culture confirmation to estimate disease burden and identify outbreaks through molecular subtyping. This study examined the impacts of CIDT and estimated costs for culture verification of Shigella, Salmonella, Shiga toxin-producing Escherichia coli (STEC), and Campylobacter at the Tennessee Department of Health Public Health Laboratory (PHL). Methods: This observational study included laboratory and epidemiological surveillance data collected between years 2013-2016 from patients with the reported enteric illness. We calculated pathogen recovery at PHL based on initial diagnostic test type reported at the clinical laboratory. Adjusted prevalence ratios (PRs) and 95% confidence intervals (CIs) were estimated with modified Poisson regression. Estimates of cost were calculated for pathogen recovery from CIDT-positive specimens compared to recovery from culture-derived isolates. Results: During the study period, PHL received 5553 specimens from clinical laboratories from patients with the enteric illness. Pathogen recovery was 57% (984/1713) from referred CIDT-positive stool specimens and 95% (3662/3840) from culture-derived isolates (PR, 0.61 [95% CI, .56-.66]). Pathogen recovery from CIDT-positive specimens varied based on pathogen type: Salmonella (72%), Shigella (64%), STEC (57%), and Campylobacter (26%). Compared to stool culture-derived isolates, the cost to recover pathogens from 100 CIDT-positive specimens was higher for Shigella (US $6192), Salmonella (US $18373), and STEC (US $27783). Conclusions: Pathogen recovery was low from CIDT-positive specimens for enteric bacteria. This has important implications for the current enteric disease surveillance system, outbreak detection, and costs for public health programs.

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.

Accuracy of FDG-PET to diagnose lung cancer in areas with infectious lung disease: a meta-analysis.

IMPORTANCE: Positron emission tomography (PET) combined with fludeoxyglucose F 18 (FDG) is recommended for the noninvasive diagnosis of pulmonary nodules suspicious for lung cancer. In populations with endemic infectious lung disease, FDG-PET may not accurately identify malignant lesions. OBJECTIVES: To estimate the diagnostic accuracy of FDG-PET for pulmonary nodules suspicious for lung cancer in regions where infectious lung disease is endemic and compare the test accuracy in regions where infectious lung disease is rare. DATA SOURCES AND STUDY SELECTION: Databases of MEDLINE, EMBASE, and the Web of Science were searched from October 1, 2000, through April 28, 2014. Articles reporting information sufficient to calculate sensitivity and specificity of FDG-PET to diagnose lung cancer were included. Only studies that enrolled more than 10 participants with benign and malignant lesions were included. Database searches yielded 1923 articles, of which 257 were assessed for eligibility. Seventy studies were included in the analysis. Studies reported on a total of 8511 nodules; 5105 (60%) were malignant. DATA EXTRACTION AND SYNTHESIS: Abstracts meeting eligibility criteria were collected by a research librarian and reviewed by 2 independent reviewers. Hierarchical summary receiver operating characteristic curves were constructed. A random-effects logistic regression model was used to summarize and assess the effect of endemic infectious lung disease on test performance. MAIN OUTCOME AND MEASURES: The sensitivity and specificity for FDG-PET test performance. RESULTS: Heterogeneity for sensitivity (I2 = 87%) and specificity (I2 = 82%) was observed across studies. The pooled (unadjusted) sensitivity was 89% (95% CI, 86%-91%) and specificity was 75% (95% CI, 71%-79%). There was a 16% lower average adjusted specificity in regions with endemic infectious lung disease (61% [95% CI, 49%-72%]) compared with nonendemic regions (77% [95% CI, 73%-80%]). Lower specificity was observed when the analysis was limited to rigorously conducted and well-controlled studies. In general, sensitivity did not change appreciably by endemic infection status, even after adjusting for relevant factors. CONCLUSIONS AND RELEVANCE: The accuracy of FDG-PET for diagnosing lung nodules was extremely heterogeneous. Use of FDG-PET combined with computed tomography was less specific in diagnosing malignancy in populations with endemic infectious lung disease compared with nonendemic regions. These data do not support the use of FDG-PET to diagnose lung cancer in endemic regions unless an institution achieves test performance accuracy similar to that found in nonendemic regions.

Assessing the transportability of radiomic models for lung cancer diagnosis: commercial vs. open-source feature extractors.

Background: Radiomics has shown promise in improving malignancy risk stratification of indeterminate pulmonary nodules (IPNs) with many platforms available, but with no head-to-head comparisons. This study aimed to evaluate transportability of radiomic models across platforms by comparing performances of a commercial radiomic feature extractor (HealthMyne) with an open-source extractor (PyRadiomics) on diagnosis of lung cancer in IPNs. Methods: A commercial radiomic feature extractor was used to segment IPNs from computed tomography (CT) scans, and a previously validated radiomic model based on commercial features was used as baseline (ComRad). Using same segmentation masks, PyRadiomics, an open-source feature extractor was used to build three open-source radiomic models (OpenRad) using different methods: de novo open-source model derived using least absolute shrinkage and selection operator (LASSO) for feature selection, selecting open-source features matched to ComRad features based upon Imaging Biomarker Standardization Initiative (IBSI) nomenclature, and selecting open-source features most highly correlated to ComRad features. Radiomic models were trained on an internal cohort (n=161) and externally validated on 3 cohorts (n=278). We added Mayo clinical risk score to OpenRad and ComRad models, creating integrated clinical radiomic (ClinRad) models. All models were compared using area under the curve (AUC) and evaluated for clinical improvement using bias-corrected clinical net reclassification indices (cNRIs). Results: ComRad AUC was 0.76 [95% confidence interval (CI): 0.71-0.82], and OpenRad AUC was 0.75 (95% CI: 0.69-0.81) for LASSO model, 0.74 (95% CI: 0.68-0.79) for Spearman's correlation, and 0.71 (95% CI: 0.65-0.77) for IBSI. Mayo scores were added to OpenRad LASSO model, which performed best, forming open-source ClinRad model with AUC of 0.80 (95% CI: 0.74-0.86), identical to commercial ClinRad's AUC. Both ClinRad models showed clinical improvement compared to Mayo alone, with commercial ClinRad achieving cNRI of 0.09 (95% CI: 0.02-0.15) for benign and 0.07 (95% CI: 0.00-0.13) for malignant, and open-source ClinRad achieving cNRI of 0.09 (95% CI: 0.02-0.15) for benign and 0.06 (95% CI: 0.00-0.12) for malignant. Conclusions: Transportability of radiomic models across platforms directly does not conserve performance, but radiomic platforms can provide equivalent results when building de novo models allowing for flexibility in feature selection to maximize prediction accuracy.

Principal Component Patterns of Pediatric Respiratory Viral Testing Across Health Care Settings.

BACKGROUND AND OBJECTIVES: Factors prompting clinicians to request viral testing in children are unclear. We assessed patterns prompting clinicians to perform viral testing in children discharged from an emergency department (ED) or hospitalized with an acute respiratory infection (ARI). METHODS: Using active ARI surveillance data collected from November 2017 through February 2020, children aged between 30 days and 17 years with fever or respiratory symptoms who had a research respiratory specimen tested were included. Children's presentation patterns from their initial evaluation at each health care setting were analyzed using principal components (PCs) analysis. PC-specific models using logistic regression with robust sandwich estimators were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) between PCs and provider-ordered viral testing. PCs were assigned respiratory virus/viruses names a priori based on the patterns represented. RESULTS: In total, 4107 children were enrolled and tested, with 2616 (64%) discharged from the ED and 1491 (36%) hospitalized. In the ED, children with a coviral presentation pattern had a 1.44-fold (95% CI, 1.24-1.68) increased odds of receiving a provider-ordered viral test than children showing clinical symptoms less representative of coviral-like infection. Whereas children in the ED and hospitalized with rhinovirus-like symptoms had 71% (OR, 0.29; 95% CI, 0.24-0.34) and 39% (OR, 0.61; 95% CI, 0.49-0.76) decreased odds, respectively, of receiving a provider-ordered viral test during their medical encounter. CONCLUSIONS: Viral tests are frequently ordered by clinicians, but presentation patterns vary by setting and influence the initiation of testing. Additional assessments of factors affecting provider decisions to use viral testing in pediatric ARI management are needed to maximize patient benefits of testing.

Provider-ordered viral testing and antibiotic administration practices among children with acute respiratory infections across healthcare settings in Nashville, Tennessee.

Objective: Evaluate the association between provider-ordered viral testing and antibiotic treatment practices among children discharged from an ED or hospitalized with an acute respiratory infection (ARI). Design: Active, prospective ARI surveillance study from November 2017 to February 2020. Setting: Pediatric hospital and emergency department in Nashville, Tennessee. Participants: Children 30 days to 17 years old seeking medical care for fever and/or respiratory symptoms. Methods: Antibiotics prescribed during the child's ED visit or administered during hospitalization were categorized into (1) None administered; (2) Narrow-spectrum; and (3) Broad-spectrum. Setting-specific models were built using unconditional polytomous logistic regression with robust sandwich estimators to estimate the adjusted odds ratios and 95% confidence intervals between provider-ordered viral testing (ie, tested versus not tested) and viral test result (ie, positive test versus not tested and negative test versus not tested) and three-level antibiotic administration. Results: 4,107 children were enrolled and tested, of which 2,616 (64%) were seen in the ED and 1,491 (36%) were hospitalized. In the ED, children who received a provider-ordered viral test had 25% decreased odds (aOR: 0.75; 95% CI: 0.54, 0.98) of receiving a narrow-spectrum antibiotic during their visit than those without testing. In the inpatient setting, children with a negative provider-ordered viral test had 57% increased odds (aOR: 1.57; 95% CI: 1.01, 2.44) of being administered a broad-spectrum antibiotic compared to children without testing. Conclusions: In our study, the impact of provider-ordered viral testing on antibiotic practices differed by setting. Additional studies evaluating the influence of viral testing on antibiotic stewardship and antibiotic prescribing practices are needed.

The Lung Cancer Prediction Model "Stress Test": Assessment of Models' Performance in a High-Risk Prospective Pulmonary Nodule Cohort.

BACKGROUND: Pulmonary nodules represent a growing health care burden because of delayed diagnosis of malignant lesions and overtesting for benign processes. Clinical prediction models were developed to inform physician assessment of pretest probability of nodule malignancy but have not been validated in a high-risk cohort of nodules for which biopsy was ultimately performed. RESEARCH QUESTION: Do guideline-recommended prediction models sufficiently discriminate between benign and malignant nodules when applied to cases referred for biopsy by navigational bronchoscopy? STUDY DESIGN AND METHODS: We assembled a prospective cohort of 322 indeterminate pulmonary nodules in 282 patients referred to a tertiary medical center for diagnostic navigational bronchoscopy between 2017 and 2019. We calculated the probability of malignancy for each nodule using the Brock model, Mayo Clinic model, and Veterans Affairs (VA) model. On a subset of 168 patients who also had PET-CT scans before biopsy, we also calculated the probability of malignancy using the Herder model. The performance of the models was evaluated by calculating the area under the receiver operating characteristic curves (AUCs) for each model. RESULTS: The study cohort contained 185 malignant and 137 benign nodules (57% prevalence of malignancy). The malignant and benign cohorts were similar in terms of size, with a median longest diameter for benign and malignant nodules of 15 and 16 mm, respectively. The Brock model, Mayo Clinic model, and VA model showed similar performance in the entire cohort (Brock AUC, 0.70; 95% CI, 0.64-0.76; Mayo Clinic AUC, 0.70; 95% CI, 0.64-0.76; VA AUC, 0.67; 95% CI, 0.62-0.74). For 168 nodules with available PET-CT scans, the Herder model had an AUC of 0.77 (95% CI, 0.68-0.85). INTERPRETATION: Currently available clinical models provide insufficient discrimination between benign and malignant nodules in the common clinical scenario in which a patient is being referred for biopsy, especially when PET-CT scan information is not available.

Biomarkers in Lung Cancer Screening: a Narrative Review.

Although when used as a lung cancer screening tool low-dose computed tomography (LDCT) has demonstrated a significant reduction in lung cancer related mortality, it is not without pitfalls. The associated high false positive rate, inability to distinguish between benign and malignant nodules, cumulative radiation exposure, and resulting patient anxiety have all demonstrated the need for adjunctive testing in lung cancer screening. Current research focuses on developing liquid biomarkers to complement imaging as non-invasive lung cancer diagnostics. Biomarkers can be useful for both the early detection and diagnosis of disease, thereby decreasing the number of unnecessary radiologic tests performed. Biomarkers can stratify cancer risk to further enrich the screening population and augment existing risk prediction. Finally, biomarkers can be used to distinguish benign from malignant nodules in lung cancer screening. While many biomarkers require further validation studies, several, including autoantibodies and blood protein profiling, are available for clinical use. This paper describes the need for biomarkers as a lung cancer screening tool, both in terms of diagnosis and risk assessment. Additionally, this paper will discuss the goals of biomarker use, describe properties of a good biomarker, and review several of the most promising biomarkers currently being studied including autoantibodies, complement fragments, microRNA, blood proteins, circulating tumor DNA, and DNA methylation. Finally, we will describe future directions in the field of biomarker development.

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.

A plasma miRNA-based classifier for small cell lung cancer diagnosis.

Introduction: Small 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. Methods: We 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. Results: We 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. Discussion: This study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis.

Assessing the clinical utility of biomarkers using the intervention probability curve (IPC).

BACKGROUND: Assessing the clinical utility of biomarkers is a critical step before clinical implementation. The reclassification of patients across clinically relevant subgroups is considered one of the best methods to estimate clinical utility. However, there are important limitations with this methodology. We recently proposed the intervention probability curve (IPC) which models the likelihood that a provider will choose an intervention as a continuous function of the probability, or risk, of disease. OBJECTIVE: To assess the potential impact of a new biomarker for lung cancer using the IPC. METHODS: The IPC derived from the National Lung Screening Trial was used to assess the potential clinical utility of a biomarker for suspected lung cancer. The summary statistics of the change in likelihood of intervention over the population can be interpreted as the expected clinical impact of the added biomarker. RESULTS: The IPC analysis of the novel biomarker estimated that 8% of the benign nodules could avoid an invasive procedure while the cancer nodules would largely remain unchanged (0.1%). We showed the benefits of this approach compared to traditional reclassification methods based on thresholds. CONCLUSIONS: The IPC methodology can be a valuable tool for assessing biomarkers prior to clinical implementation.

Improving Lung Cancer Diagnosis with CT Radiomics and Serum Histoplasmosis Testing.

BACKGROUND: Indeterminate pulmonary nodules (IPN) are a diagnostic challenge in regions where pulmonary fungal disease and smoking prevalence are high. We aimed to determine the impact of a combined fungal and imaging biomarker approach compared with a validated prediction model (Mayo) to rule out benign disease and diagnose lung cancer. METHODS: Adults ages 40 to 90 years with 6-30 mm IPNs were included from four sites. Serum samples were tested for histoplasmosis IgG and IgM antibodies by enzyme immunoassay and a CT-based risk score was estimated from a validated radiomic model. Multivariable logistic regression models including Mayo score, radiomics score, and IgG and IgM histoplasmosis antibody levels were estimated. The areas under the ROC curves (AUC) of the models were compared among themselves and to Mayo. Bias-corrected clinical net reclassification index (cNRI) was estimated to assess clinical reclassification using a combined biomarker model. RESULTS: We included 327 patients; 157 from histoplasmosis-endemic regions. The combined biomarker model including radiomics, histoplasmosis serology, and Mayo score demonstrated improved diagnostic accuracy when endemic histoplasmosis was accounted for [AUC, 0.84; 95% confidence interval (CI), 0.79-0.88; P < 0.0001 compared with 0.73; 95% CI, 0.67-0.78 for Mayo]. The combined model demonstrated improved reclassification with cNRI of 0.18 among malignant nodules. CONCLUSIONS: Fungal and imaging biomarkers may improve diagnostic accuracy and meaningfully reclassify IPNs. The endemic prevalence of histoplasmosis and cancer impact model performance when using disease related biomarkers. IMPACT: Integrating a combined biomarker approach into the diagnostic algorithm of IPNs could decrease time to diagnosis.

Short-term outcomes of robotic-assisted transthoracic diaphragmatic plication.

Background: Patients who are symptomatic from diaphragmatic dysfunction may benefit from diaphragmatic plication. We recently modified our plication approach from open thoracotomy to robotic transthoracic. We report our short-term outcomes. Methods: We conducted a single-institution retrospective review of all patients who underwent transthoracic plications from 2018, when we began using the robotic approach, to 2022. The primary outcome was short-term recurrence of diaphragm elevation with symptoms noted before or during the first planned postoperative visit. We also compared proportions of short-term recurrences in patients that underwent plication with extracorporeal knot-tying device alone versus those that used intracorporeal instrument tying (alone or supplemental). Secondary outcomes included subjective postoperative improvement of dyspnea at follow-up visit and by postoperative patient questionnaire, chest tube duration, length of stay (LOS), 30-day readmission, operative time, estimated blood loss (EBL), intraoperative complications, and perioperative complications. Results: Forty-one patients underwent robotic-assisted transthoracic plication. Four patients experienced recurrent diaphragm elevation with symptoms before or during their first routine postoperative visit, occurring on POD 6, 10, 37, and 38. All four recurrences occurred in patients whose plications were performed with the extracorporeal knot-tying device without supplemental intracorporeal instrument tying. Proportion of recurrences in the group that used extracorporeal knot-tying device alone was significantly greater than the recurrences in the group that used intracorporeal instrument tying (alone or supplemental) (P=0.016). The majority (36/41) reported clinical improvement postoperatively and 85% of questionnaire respondents also agreed they would recommend the surgery to others with similar condition. The median LOS and of chest tube duration were 3 days and 2 days, respectively. There were two patients with 30-day readmissions. Three patients developed postoperative pleural effusion necessitating thoracenteses and 8 patients (20%) had postoperative complications. No mortalities were observed. Conclusions: While our study shows the overall acceptable safety and favorable outcomes in patients undergoing robotic-assisted transthoracic diaphragmatic plications, the incidence of short-term recurrences and its association with the use of extracorporeally knot-tying device alone in diaphragm plication warrant further investigation.

Age-related Muscle Fat Infiltration in Lung Screening Participants: Impact of Smoking Cessation.

Rationale: Skeletal muscle fat infiltration progresses with aging and is worsened among individuals with a history of cigarette smoking. Many negative impacts of smoking on muscles are likely reversible with smoking cessation. Objectives: To determine if the progression of skeletal muscle fat infiltration with aging is altered by smoking cessation among lung cancer screening participants. Methods: This was a secondary analysis based on the National Lung Screening Trial. Skeletal muscle attenuation in Hounsfield unit (HU) was derived from the baseline and follow-up low-dose CT scans using a previously validated artificial intelligence algorithm. Lower attenuation indicates greater fatty infiltration. Linear mixed-effects models were constructed to evaluate the associations between smoking status and the muscle attenuation trajectory. Measurements and Main Results: Of 19,019 included participants (age: 61 years, 5 [SD]; 11,290 males), 8,971 (47.2%) were actively smoking cigarettes. Accounting for body mass index, pack-years, percent emphysema, and other confounding factors, actively smoking predicted a lower attenuation in both males (ß0 =-0.88 HU, P<.001) and females (ß0 =-0.69 HU, P<.001), and an accelerated muscle attenuation decline-rate in males (ß1=-0.08 HU/y, P<.05). Age-stratified analyses indicated that the accelerated muscle attenuation decline associated with smoking likely occurred at younger age, especially in females. Conclusions: Among lung cancer screening participants, active cigarette smoking was associated with greater skeletal muscle fat infiltration in both males and females, and accelerated muscle adipose accumulation rate in males. These findings support the important role of smoking cessation in preserving muscle health.