Assessing the impact of socioeconomic status on incidental lung nodules at an urban safety net hospital

INTRODUCTION

Lower socioeconomic status has been identified as an emerging risk factor for health disparities, including lung cancer outcomes. Most research investigating these outcomes includes patients from formal lung cancer screening programs. There is a paucity of studies assessing the relationship between socioeconomic status and incidental lung nodules. This study aimed to investigate the association between socioeconomic status and the size of incidental lung nodules on initial presentation at an urban safety net hospital, which did not have a formal lung cancer screening program or incidental lung nodule program.

METHODS

A retrospective chart review was conducted on patients with incidental lung nodules on CT chest imaging who were referred from primary care to a pulmonology clinic at a safety net hospital. Patients with incomplete nodule characteristics information were excluded. Data on demographics, comorbidities, smoking history, insurance type, immigration status, and geographical factors were collected. Less commonly studied determinants such as crime index, cost of living, and air quality index were also assessed. Logistic regression analysis was performed to assess relationships between nodule size and socioeconomic determinants.

RESULTS

Out of 3,490 patients with chest CT scans, 268 patients with ILNs were included in the study. 84.7% of patients represented racial or ethnic minorities, and most patients (67.8%) had federal insurance. Patients with non-commercial insurance were more likely to have larger, inherently higher-risk nodules (> 8 mm) compared to those with commercial insurance (OR 2.18, p 0.01). Patients from areas with higher unemployment rates were also less likely (OR 0.75, p 0.04) to have smaller nodules (< 6 mm). Patients representing racial or ethnic minorities were also more likely to have nodules > 8 mm (OR 1.6, p 0.24), and less likely to have nodules < 6 mm (OR 0.6, p 0.32), however, these relationships were not statistically significant.

CONCLUSION

This study found that lower socioeconomic status, indicated by having non-commercial insurance, was associated with larger incidental lung nodule size on initial presentation. While it is established that socioeconomic status is associated with disparities in lung cancer screening, these findings suggest that inequalities may also be present in those with incidental lung nodules. Further research is needed to understand the underlying mechanisms and develop interventions to address these disparities in incidental lung nodule evaluation and improve outcomes.

The Role of Sphingolipids in Regulating Vascular Permeability in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a disease that causes scarring and fibrotic transformation of the lung parenchyma, resulting in the progressive loss of respiratory function and, often, death. Current treatments that target profibrotic factors can slow the rate of progression but are unable to ultimately stop it. In the past decade, many studies have shown that increased vascular permeability may be both a predictive and perpetuating factor in fibrogenesis. Consequently, there is a search for therapeutic targets to try and modulate vascular permeability in fibrotic lungs. One such class of targets that show great promise is sphingolipids. Sphingolipids are common in cell membranes and are increasingly recognized as critical to many cell signaling pathways, including those that affect the integrity of the vascular endothelial barrier. In this focused review we look at sphingolipids, particularly the sphingosine-1-phosphate (S1P) axis and its effects on vascular permeability, and how those effects may affect the pathogenesis of IPF. We further examine existing S1P modulators and their potential efficacy as therapeutics for IPF.

An organ systems-based review of outcomes associated with sleep apnea in hospitalized patients

The current global health crisis due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has prompted the medical community to investigate the effects of underlying medical conditions, including sleep-disordered breathing, on inpatient care. Obstructive sleep apnea (OSA) is a common form of sleep-disordered breathing that may complicate numerous acquired conditions, particularly in inpatient and critical care settings. Viral pneumonia is a major contributor to intensive care unit (ICU) admissions and often presents more severely in patients with underlying pulmonary disease, especially those with obesity and OSA. This review summarizes the most recent data regarding complications of both OSA and obesity and highlights their impact on clinical outcomes in hospitalized patients. Additionally, it will highlight pertinent evidence for the complications of OSA in an organ-systems approach. Finally, this review will also discuss impatient treatment approaches for OSA, particularly in relation to the SARS-CoV-2 pandemic.

Factors Affecting Patient Adherence to Lung Cancer Screening

OBJECTIVES

The National Lung Screening Trial (NLST) demonstrated a 20% reduction in mortality with low-dose computed tomography (CT) for lung cancer screening (LCS). The NLST found the greatest benefit to LCS for patients who underwent annual screening for a full 3-year follow-up period. The adherence to serial imaging in the NLST was 95%.

METHODS

We conducted a prospective study of 268 patients who presented for LCS and who were not enrolled in a research study to determine the adherence to recommended follow-up imaging and biopsy at a single center. We evaluated the correlations among sociodemographic characteristics, Lung Imaging and Reporting Data System, and adherence.

RESULTS

Only 48% of the patient population received recommended follow-up (either imaging or biopsy) after their referent LCS. Patients with abnormal LCS (Lung Imaging and Reporting Data System 3 or 4) were more likely to adhere to the recommended follow-up (additional imaging or biopsy) compared with those with negative screens. Sex, ethnicity, smoking status, and household income were not correlated with adherence to screening and biopsy.

CONCLUSIONS

The benefits from LCS observed in the NLST may be undermined by low adherence to follow-up screening. Studies targeting LCS patients to bolster adherence to follow-up are needed.

Will That Pulmonary Nodule Become Cancerous? A Risk Prediction Model for Incident Lung Cancer

This prospective investigation derived a prediction model for identifying risk of incident lung cancer among patients with visible lung nodules identified on computed tomography (CT). Among 2,924 eligible patients referred for evaluation of a pulmonary nodule to the Stony Brook Lung Cancer Evaluation Center between January 1, 2002 and December 31, 2015, 171 developed incident lung cancer during the observation period. Cox proportional hazard models were used to model time until disease onset. The sample was randomly divided into discovery (n = 1,469) and replication (n = 1,455) samples. In the replication sample, concordance was computed to indicate predictive accuracy and risk scores were calculated using the linear predictions. Youden index was used to identify high-risk versus low-risk patients and cumulative lung cancer incidence was examined for high-risk and low-risk groups. Multivariable analyses identified a combination of clinical and radiologic predictors for incident lung cancer including ln-age, ln-pack-years smoking, a history of cancer, chronic obstructive pulmonary disease, and several radiologic markers including spiculation, ground glass opacity, and nodule size. The final model reliably detected patients who developed lung cancer in the replication sample (C = 0.86, sensitivity/specificity = 0.73/0.81). Cumulative incidence of lung cancer was elevated in high-risk versus low-risk groups [HR = 14.34; 95% confidence interval (CI), 8.17-25.18]. Quantification of reliable risk scores has high clinical utility, enabling physicians to better stratify treatment protocols to manage patient care. The final model is among the first tools developed to predict incident lung cancer in patients presenting with a concerning pulmonary nodule.