Ophthalmology Optical Coherence Tomography Databases for Artificial Intelligence Algorithm: A Review.

BACKGROUND: Imaging plays a pivotal role in eye assessment. With the introduction of advanced machine learning and artificial intelligence (AI), the focus has shifted to imaging datasets in ophthalmology. While disparities and health inequalities hidden within data are well-documented, the ophthalmology field faces specific challenges to the creation and maintenance of datasets. Optical Coherence Tomography (OCT) is useful for the diagnosis and monitoring of retinal pathologies, making it valuable for AI applications. This review aims to identify and compare the landscape of publicly available optical coherence tomography databases for AI applications. METHODS: We conducted a literature review on OCT and AI articles with publicly accessible datasets, using PubMed, Scopus, and Web of Science databases. The review retrieved 183 articles, and after full-text analysis, 50 articles were included. From the included articles were identified 8 publicly available OCT datasets, focusing on patient demographics and clinical details for thorough assessment and comparison. RESULTS: The resulting datasets encompass 154,313 images collected from Spectralis, Cirrus HD, Topcon 3D, and Bioptigen devices. These datasets included normal exams, age-related macular degeneration, and diabetic maculopathy, among others. Comprehensive demographic information is available in one dataset and the USA is the most represented population. DISCUSSION: Current publicly available OCT databases for AI applications exhibit limitations, stemming from their non-representative nature and the lack of comprehensive demographic information. Limited datasets hamper research and equitable AI development. To promote equitable AI algorithmic development in ophthalmology, there is a need for the creation and dissemination of more representative datasets.

A scoping review of the landscape of health-related open datasets in Latin America.

Artificial intelligence (AI) algorithms have the potential to revolutionize healthcare, but their successful translation into clinical practice has been limited. One crucial factor is the data used to train these algorithms, which must be representative of the population. However, most healthcare databases are derived from high-income countries, leading to non-representative models and potentially exacerbating health inequities. This review focuses on the landscape of health-related open datasets in Latin America, aiming to identify existing datasets, examine data-sharing frameworks, techniques, platforms, and formats, and identify best practices in Latin America. The review found 61 datasets from 23 countries, with the DATASUS dataset from Brazil contributing to the majority of articles. The analysis revealed a dearth of datasets created by the authors themselves, indicating a reliance on existing open datasets. The findings underscore the importance of promoting open data in Latin America. We provide recommendations for enhancing data sharing in the region.

Disparities in Access to Autologous Breast Reconstruction.

Background and objectives: This study aimed to determine if age, race, region, insurance, and comorbidities affect the type of breast reconstruction that patients receive. Materials and methods: This analysis used the Florida Inpatient Discharge Dataset from 1 January 2013 to 30 September 2017, which contains deidentified patient-level administrative data from all acute care hospitals in the state of Florida. We included female patients, diagnosed with breast cancer, who underwent mastectomy and a subsequent breast reconstruction. We performed an χ2 test and logistic regression in this analysis. Results: On the multivariable analysis, we found that age, race, patient region, insurance payer, and Elixhauser score were all variables that significantly affected the type of reconstruction that patients received. Our results show that African American (odds ratio (OR): 0.68, 95%CI: 0.58-0.78, p < 0.001) and Hispanic or Latino (OR: 0.82, 95%CI: 0.72-0.93, p = 0.003) patients have significantly lower odds of receiving implant reconstruction when compared to white patients. Patients with Medicare (OR: 1.57, 95%CI: 1.33-1.86, p < 0.001) had significantly higher odds and patients with Medicaid (OR: 0.61, 95%CI: 0.51-0.74, p < 0.001) had significantly lower odds of getting autologous reconstruction when compared to patients with commercial insurance. Conclusions: Our study demonstrated that, in the state of Florida over the past years, variables, such as race, region, insurance, and comorbidities, play an important role in choosing the reconstruction modality. More efforts are needed to eradicate disparities and give all patients, despite their race, insurance payer, or region, equal access to health care.

Biopsy Type Disparities in Patients With Melanoma: Who Receives the Standard of Care?

BACKGROUND/AIM: To analyze whether demographic and facility type characteristics cause inequality in the type of biopsy performed in patients with cutaneous melanoma. PATIENTS AND METHODS: The skin cancer National Cancer Database was assessed. Men and women of all ages with cutaneous melanoma in situ and malignant melanoma at any stage of the disease were included. Patients were selected who underwent one of the following biopsy types: excisional, punch, shave, or incisional. Bivariate and multivariate analyses were performed. RESULTS: We found that the likelihood of undergoing an excisional biopsy decreased in patients who were: Hispanic [odds ratio (OR)=0.63, confidence interval (CI)=0.55-0.71], non-White (OR=0.66, CI=0.58-0.76), older than 80 years (OR=0.77, CI=0.72-0.87), or in Comprehensive Community Cancer Programs (OR=0.33, CI=0.31-0.36), Community Cancer Programs (OR=0.52, CI=0.50-0.54) and Integrated Network Cancer Programs (OR=0.58, CI=0.55-0.61). CONCLUSION: Our study results demonstrate disparities in biopsy type in the treatment of melanoma.

Survival Disparities in Male Patients With Breast Cancer.

BACKGROUND/AIM: We evaluated factors associated with mortality among men with breast cancer. MATERIALS AND METHODS: We used the National Cancer Database to identify men with breast cancer and evaluated factors associated with mortality, using a Cox regression model. RESULTS: Black patients experienced an increased risk of death from any cause compared to white patients [hazard ratio (HR)=1.19, 95%CI=1.05-1.37]. Patients with government insurance had a greater risk of death compared to privately insured patients (HR=1.57, 95%CI=1.41-1.75). When compared to patients with an income of >$46,000, those with an income <$30,000 presented an increased risk of death (HR=1.35, 95%CI=1.14-1.60). Finally, patients treated at a comprehensive community cancer program (HR=1.129, 95%CI=1.021-1.248), community cancer program (HR=1.164, 95%CI=1.010-1.343), or integrated network cancer program (HR=1.216; 95%CI=1.056-1.401) experienced elevated risk of death compared to those treated at academic/research-programs. CONCLUSION: Race, insurance, income, education, and facility type are associated with the risk of mortality in male patients with breast cancer.

National Analysis of Patients With External Ear Melanoma in the United States.

BACKGROUND: External ear melanoma (EEM) is a rare condition with controversies in the literature. We analyzed patients with EEM in the United States compared to other head and neck melanomas (OHNMs). METHODS: The National Cancer Database (NCDB) was used to select patients with head and neck melanoma from January 1, 2004 to December 31, 2015. Mann-Whitney and χ tests were used to estimate statistical significance, and multivariate logistic regression to identify independent associations adjusted for confounders. RESULTS: A total of 137,233 patients met the study criteria. Among them, 16,991 (12.4%) had EEM and 120,242 (87.6%) had OHNM. For patients with EEM, the mean (standard deviation) age was 66.26 (15.798) years. Most of the patients with EEM were men (85.5%), insured by Medicare (52.4%), and treated in Academic/Research Programs (47.7%) or Comprehensive Community Cancer Programs (32.3%). Most of the EEM tumors had invasive behavior (68.0%) were Stages 0 (30.3%) or I (40.3%), and were without ulceration (76.9%). Mean time to receive any treatment was 14.1 days for EEM compared with 14.6 days for OHNM (P < 0.001). We noticed a greater proportion of EEM in men (14.8%; adjusted odds ratio [aOR] 2.72 [2.605-2.852]; P < 0.001) compared to women (6.22%; reference). EEM was an independent factor for tumor Stage I (14.47%; aOR 1.61 [1.101-1.224], P < 0.001) and invasive behavior (13.86%; aOR 1.268 [1.15-1.389]; P < 0.001) compared to OHNM. CONCLUSION: EEM was associated with higher odds of invasive behavior compared to OHNM. Furthermore, men were found to have a higher likelihood to develop EEM compared to women.

Eyelid Melanoma in the United States: A National Cancer Database Analysis.

BACKGROUND: Eyelid melanoma (EM) is a rare condition that accounts for <1% of all cutaneous melanomas. In this analysis, patients diagnosed with EM in the United States were compared to those with other melanomas in the head and neck. METHODS: The National Cancer Database was used to select patients with head and neck melanoma from 2004 to 2015. RESULTS: A total of 137,233 patients met the criteria of the study. Among them, 2694 were diagnosed with EM (2%) and 134,539 in other head and neck locations (98%). Regarding the patients with EM, the mean age was 68.56 years (standard deviation 14.04). A greater number of them were treated in Academic/Research Programs (53.6%), insured by Medicare (55.7%), tumor in situ (52.2%), stage 0 (49%), and without ulceration (75.9%). The mean time to treatment commencement was 18.96 days for EM compared to 14.4 days for other melanoma in the head and neck regions (P < 0.001). There was a greater proportion of EM in female patients (odds ratio [OR] 2.371 [2.191-2.566], P < 0.001), compared to male; age greater than 80 years (OR 1.622 [1.360-1.934], P < 0.001) compared to 0 to 49 years. Moreover, EM was an independent predictor for treatment in Academic/Research Programs (OR 1.258 [1.160-1.365], P < 0.001) and diagnosis at autopsy (OR 1.414 [1.083-1.847], P = 0.011) compared to other melanoma in the head and neck region. CONCLUSION: These novel findings have the potential to guide clinical decision making in head and neck melanoma management.