Lung cancer in the emergency department

Identifying lung cancer in Emergency Department patients outside national lung cancer screening guidelines

Background

Lung cancer has become the second most common cancer and the leading cause of cancer death in the United States. We aim to determine factors associated with newly diagnosed lung cancer at the Emergency Department (ED) and identify specific patient populations eligible for lung cancer diagnostic screening.

Methods

This is a single-center retrospective observational study. We included all patients aged between 50 and 80 years old, who presented to the ED seeking healthcare between January 1, 2019, and December 31, 2023. Patients' socio-demographics, clinical information, and whether they were eligible for lung cancer screening determined by the United States Preventive Services Task Force (USPSTF) guideline were analyzed and compared between patients who had newly diagnosed lung cancer at ED and those without. Factors associated with newly diagnosed lung cancer patients were determined by multivariable logistic regressions with inverse probability weighting (IPW) to account for observed selection bias of lung cancer screening eligibility.

Results

Out of 75,516 patients in this study, 18,641 (25%) patients had documented smoking histories. Among these, only 8,051 (10.66%) were eligible for lung cancer screening, while 18,348 patients received lung computer tomography (CT). Among all patients whose CTs were performed, 123 individuals were identified as having been newly diagnosed with lung cancer. Multivariable logistic regressions showed that the adjusted odds ratio (AOR) for eligible lung cancer diagnostic screening was 3.07 [95% confidence interval (CI): 2.08-4.53, P<0.001] without IPW and 3.49 (95% CI: 2.24-5.42, P<0.001) with IPW. Other factors associated with newly diagnosed lung cancer in ED were older age, female, and patients who spoke neither English nor Spanish.

Conclusions

To optimize the identification of suitable patients for lung cancer diagnostic screening in the ED, it may be beneficial to modify the eligibility criteria beyond those currently outlined by the USPSTF guidelines. Integrating additional factors such as advanced age, female sex, and a preference for non-English languages could improve the screening's effectiveness by capturing at-risk populations that might otherwise be overlooked.

Navigating Emergency Management of Cancer Patients: A Retrospective Study on First-Time, End-Stage, and Other Established Diagnoses in a High Turnover Emergency County Hospital

Background and Objectives: The incidence and prevalence of cancers are increasing worldwide, with special emphasis placed on prevention, early detection, and the development of new therapeutic strategies that strongly impact patient outcomes. Limited data are available about emergency care's role in treating patients with cancer. This study aims to determine the burden of end-stage and first-time diagnosis of cancer on emergency care in a high-turnover emergency care center. Materials and Methods: A retrospective observational study was conducted to identify patients requesting emergent aid for cancer-related symptoms in the Emergency Department of "St. Spiridon" Hospital from Iasi (Romania) between 1 October 2022 and 30 September 2023. The proportion and demographic characteristics of end-stage patients and those who received a first-time diagnosis during the emergency visit were evaluated. Risk analysis was performed to understand these patients' care needs (such as medical care, surgical care, specialty consults, intensive care, ward admission, and other hospital transfers) and immediate care outcomes (such as in-hospital mortality and home discharge). Results: 2318 patients with cancer requested emergent care (patient presentation rate of 3.08%), of which 444 (19.15%) were diagnosed for the first time, and 616 (26.57%) were at the end-stage. First-time diagnosed patients had a significantly different distribution of cancer types (p < 0.001), were more likely to need any form of medical care, to require a specialty consultation, or to be admitted to a ward (OR 2.65, 95% CI: 2.12-3.32; p < 0.001; OR 3.28, 95% CI: 2.48-4.35, p < 0.001; OR 2.09, 95% CI: 1.70-2.59; p < 0.001, respectively) but were less severe, while end-stage patients were more likely to address repeatedly to the emergency room (OR 1.86, 95% CI: 1.32-2.59; p = 0.001) and had higher odds of needing intensive care, assisted ventilation and death (OR-4.63, 95% CI: 1.10-19.45, p = 0.04; OR 2.59, 95% CI: 1.57-4.28; p < 0.001, and OR 4.06, 95% CI: 1.73-9.54; p = 0.001, respectively). Conclusions: The emergency department often carries the weight of diagnosing patients with cancer and treating patients with end-stage disease. These data highlight the importance of prehospital care, particularly for cancer screening and palliative care, and the importance of fostering multidisciplinary collaboration in the emergency room with oncologists, geriatricians, and palliative care specialists to improve patient outcomes.

Investigating socioeconomic disparities in lung cancer diagnosis, treatment and mortality: an Italian cohort study

BACKGROUND

Lung cancer is one of the most lethal cancers worldwide and patient clinical outcomes seem influenced by their socioeconomic position (SEP). Since little has been investigated on this topic in the Italian context, our aim was to investigate the role of SEP in the care pathway of lung cancer patients in terms of diagnosis, treatment and mortality.

METHODS

This observational retrospective cohort study included patients discharged in the Lazio Region with a lung cancer diagnosis between 2014 and 2017. In the main analysis, educational level was used as SEP measure. Multivariate models, adjusted for demographic and clinical variables, were applied to evaluate the association between SEP and study outcomes, stratified for metastatic (M) and non-metastatic (NM) cancer. We defined a diagnosis as 'delayed' when patients received their initial cancer diagnosis after an emergency department admission. Access to advanced lung cancer treatments (high-cost, novel and innovative treatments) and mortality were investigated within the 24-month period post-diagnosis. Moreover, two additional indicators of SEP were examined in the sensitivity analysis: one focusing on area deprivation and the other on income-based exemption.

RESULTS

A total of 13,251 patients were identified (37.3% with metastasis). The majority were males (> 60%) and over half were older than 70 years. The distribution of SEP levels among patients was as follow: 31% low, 29% medium-low, 32% medium-high and 7% high. As SEP increased, the risks of receiving a delayed diagnosis ((high vs low: M: OR = 0.29 (0.23-0.38), NM: OR = 0.20 (0.16-0.25)) and of mortality ((high vs low M: OR = 0.77 (0.68-0.88) and NM: 0.61 (0.54-0.69)) decreased. Access to advanced lung cancer treatments increased in accordance with SEP only in the M cohort (high vs low: M: OR = 1.57 (1.18-2.09)). The primary findings were corroborated by sensitivity analysis.

CONCLUSIONS

Our study highlighted the need of public health preventive and educational programs in Italy, a country where the care pathway of lung cancer patients, especially in terms of diagnosis and mortality, appears to be negatively affected by SEP level.

Risk Prediction of Emergency Department Visits in Patients With Lung Cancer Using Machine Learning: Retrospective Observational Study

BACKGROUND

Patients with lung cancer are among the most frequent visitors to emergency departments due to cancer-related problems, and the prognosis for those who seek emergency care is dismal. Given that patients with lung cancer frequently visit health care facilities for treatment or follow-up, the ability to predict emergency department visits based on clinical information gleaned from their routine visits would enhance hospital resource utilization and patient outcomes.

OBJECTIVE

This study proposed a machine learning-based prediction model to identify risk factors for emergency department visits by patients with lung cancer.

METHODS

This was a retrospective observational study of patients with lung cancer diagnosed at Seoul National University Bundang Hospital, a tertiary general hospital in South Korea, between January 2010 and December 2017. The primary outcome was an emergency department visit within 30 days of an outpatient visit. This study developed a machine learning-based prediction model using a common data model. In addition, the importance of features that influenced the decision-making of the model output was analyzed to identify significant clinical factors.

RESULTS

The model with the best performance demonstrated an area under the receiver operating characteristic curve of 0.73 in its ability to predict the attendance of patients with lung cancer in emergency departments. The frequency of recent visits to the emergency department and several laboratory test results that are typically collected during cancer treatment follow-up visits were revealed as influencing factors for the model output.

CONCLUSIONS

This study developed a machine learning-based risk prediction model using a common data model and identified influencing factors for emergency department visits by patients with lung cancer. The predictive model contributes to the efficiency of resource utilization and health care service quality by facilitating the identification and early intervention of high-risk patients. This study demonstrated the possibility of collaborative research among different institutions using the common data model for precision medicine in lung cancer.

Time intervals and previous primary care consultations in the pathway to emergency cancer diagnosis

BACKGROUND

Time intervals and number of prior consultations in primary care (PC) are recognised metrics of diagnostic timeliness of cancer and are interrelated. However, whether and how the two measures correlate with each other in the emergency diagnostic pathway is unknown. We investigated the association between the number of prereferral consultations and the length of intervals from PC presentation to cancer diagnosis following emergency referral to hospital.

METHODS

Patients were eligible if they first consulted in PC and were diagnosed with cancer following emergency or nonemergency referral to hospital. We analysed for differences in PC and diagnostic intervals and number of consultations between emergency and nonemergency presenters and determined their associations by cancer type. Differences in presenting symptoms and stage at diagnosis between populations and according to number of consultations were also examined.

RESULTS

There were 796 emergency and 865 nonemergency presenters with comparable sociodemographic and comorbidity data. Correlation analysis in emergency presenters revealed a strong positive association between number of consultations and intervals for seven of 13 different cancers, including cancers characterised by high proportions of > 3 consultations and long intervals (pancreatic, lung, and colorectal cancer) and vice versa for others (e.g., endometrial, cervical, or oesophageal cancer). Additionally, emergency presenters with > 3 consultations were more likely than those with 1-2 to report nonspecific symptoms (60 vs. 40%, respectively) and to be diagnosed at a later stage.

CONCLUSION

System level interventions are needed to reduce unnecessary delays in the emergency diagnostic pathway, particularly in cancer patients with multiple prereferral consultations. The findings also suggest opportunities to reduce the proportion of emergency diagnoses by targeting symptomatic individuals pre-presentation.