Clinician Trust in Artificial Intelligence: What is Known and How Trust Can Be Facilitated.

Predictive analytics based on artificial intelligence (AI) offer clinicians the opportunity to leverage big data available in electronic health records (EHR) to improve clinical decision-making, and thus patient outcomes. Despite this, many barriers exist to facilitating trust between clinicians and AI-based tools, limiting its current impact. Potential solutions are available at both the local and national level. It will take a broad and diverse coalition of stakeholders, from health-care systems, EHR vendors, and clinical educators to regulators, researchers and the patient community, to help facilitate this trust so that the promise of AI in health care can be realized.

Staging lymph node metastases from lung cancer in the mediastinum.

BACKGROUND: The presence of tumor metastases in the mediastinum is one of the most important elements in determining the optimal treatment strategy in patients with non-small cell lung cancer. This review is aimed at examining the current strategies for investigating lymph node metastases corresponding to an "N2" classification delineated by The International Staging Committee of the International Association for the Study of Lung Cancer (IASLC). METHODS: Extensive review of the existing scientific literature related to the investigation of mediastinal lymph node metastases was undertaken in order to summarize and report current best practices. CONCLUSIONS: N2 disease is very heterogeneous requiring multiple modalities for thorough investigation. New research is now focusing on better identifying, defining, and classifying lymph node metastases in the mediastinum. Molecular staging and sub-classifying mediastinal lymph node metastases are being actively researched in order to provide better prognostic value and to optimize treatment strategies. Non-invasive imaging, such as PET/CT and minimally invasive techniques such as endobronchial and endoscopic ultrasound guided biopsy, are now the lead investigative methods in evaluating the mediastinum for metastatic presence.

Prospective CT screening for lung cancer in a high-risk population: HIV-positive smokers.

BACKGROUND: Epidemiological evidence suggests that HIV-infected individuals are at increased risk of lung cancer, but no data exist because large computed tomography (CT) screening trials routinely exclude HIV-infected participants. METHODS: From 2006 to 2013, we conducted the world's first lung cancer screening trial of 224 HIV-infected current/former smokers to assess the CT detection rates of lung cancer. We also used 130 HIV-infected patients with known lung cancer to determine radiographic markers of lung cancer risk using multivariate analysis. RESULTS: Median age was 48 years with 34 pack-years smoked. During 678 person-years, one lung cancer was found on incident screening. Besides this lung cancer case, 18 deaths (8%) occurred, but none were cancer related. There were no interim diagnoses of lung or extrapulmonary cancers. None of the pulmonary nodules detected in 48 participants at baseline were diagnosed as cancer by study end. The heterogeneity of emphysema across the entire lung as measured by CT densitometry was significantly higher in HIV-infected subjects with lung cancer compared with the heterogeneity of emphysema in those without HIV (p ≤ 0.01). On multivariate regression analysis, increased age, higher smoking pack-years, low CD4 nadir, and increased heterogeneity of emphysema on quantitative CT imaging were all significantly associated with lung cancer. CONCLUSIONS: Despite a high rate of active smoking among HIV-infected participants, only one lung cancer was detected in 678 patient-years. This was probably because of the young age of participants suggesting that CT screening of high-risk populations should strongly consider advanced age as a critical inclusion criterion. Future screening trials in urban American must also incorporate robust measures to ensure HIV patient compliance, adherence, and smoking cessation.