Geographic Access Disparities of Clinical Trials in Neovascular Age-Related Macular Degeneration in the United States

Soares, Rebecca R.; Gopal, Anand; Parikh, Devayu; Shields, Charlotte N; Patel, Samir N.; Hinkle, John W.; Sharpe, James; Ho, Allen C.; Regillo, Carl D.; Haller, Julia A.; Yonekawa, Yoshihiro

doi:10.1016/j.ajo.2021.04.001

Cited by 9 publications

(6 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As others have expressed, efforts to increase the concordance between the participants in clinical trials and the population with the disease under investigation are important. [3][4][5][6][7][15][16][17][18][19][20] Our study supports that these efforts must continue through the duration of the clinical trial and has identified populations that are especially at high risk of being LTFU to focus these efforts. It suggests that special attention should be considered to ensure retention of those highrisk populations through the end of trial periods.…”

Section: Discussionsupporting

confidence: 70%

“…Across numerous subspecialties of medicine, including within ophthalmology, disparities in access to and participation in clinical trials have been demonstrated. [3][4][5][6][7] Clinical trials often do not enroll a cohort which is representative of the population that is affected by the disease being investigated, which leads to concerns about the generalizability of their conclusions. Once enrolled in clinical trials, there is a known risk of losing participants before the first data reporting.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Characteristics of Participants in Diabetic Retinopathy Clinical Research Clinical Trials Who Were Lost to Follow up

Bowe,

Mahmoudzadeh,

Soares

et al. 2023

Retina

Self Cite

View full text Add to dashboard Cite

Purpose: Our study describes the racial/ethnic composition and the broad health status/severity of disease of the cohorts of Diabetic Retinopathy Clinical Research (DRCR) clinical trials and compares the rates of non-completion of the trial to the first data report (lost to follow up (LTFU)). Methods: This study is a retrospective cohort study of participants in Diabetic Retinopathy Clinical Research (DRCR) Retina Network clinical trials that met our inclusion criteria. The primary outcome was the lost to follow up rates and their associated risk factors. Results: Eight clinical trials with 3492 participants met our inclusion criteria. Participants who were LTFU were more likely younger, Hispanic or Black, Type 1 DM, worse baseline BCVA, higher HbA1c, higher BP, and had PDR (Diabetic Retinopathy Severity Score >66). Conclusions: Participants who were LTFU during DRCR clinical trials tended to be younger, Hispanic or Black, and have worse diabetes and hypertension. This study highlights the importance of ensuring a representative population is maintained through the end of the study period.

show abstract

Section: Discussionsupporting

confidence: 70%

mentioning

confidence: 99%

Characteristics of Participants in Diabetic Retinopathy Clinical Research Clinical Trials Who Were Lost to Follow up

Bowe,

Mahmoudzadeh,

Soares

et al. 2023

Retina

Self Cite

View full text Add to dashboard Cite

show abstract

“…A few studies in recent years have used this geographic analysis of ophthalmic accessibility. In several studies of accessibility to clinical trials in ophthalmology, Soares et al [45] looked at the travel time and distance between the centroid of each of the roughly 72000 census tracts in the United States to the nearest clinical trial site in diabetic eye disease, age-related macular degeneration [46], and retinopathy of prematurity [47]. The studies used GIS software (ArcGIS, Esri, Redlands, California, USA) [48] to construct origin-destination cost-matrices.…”

Section: The Role Of Geographic Information Systems Analysis In Ophth...mentioning

confidence: 99%

The evolving field of Big Data: understanding geographic information systems analysis and its transformative potential in ophthalmic research

Soares¹

2022

Current Opinion in Ophthalmology

View full text Add to dashboard Cite

Purpose of reviewThe purpose of this review to is to highlight alternative uses of Big Data in the pursuit of ophthalmologic public health. In particular, we highlight geographic information systems (GIS) analysis as a type of Big Data, summarize various GIS methods, and enumerate sources of geographic data. Recent findingsThe recent implementation of the IRIS Registry Data, has expanded our real-world knowledge of ophthalmology in the United States. Such innovations in Big Data allow us to better define ophthalmic diseases, treatments, and outcomes for underserved individuals and subpopulations. One underutilized source of Big Data entails use of geographic information to evaluate geographic heterogeneity and access across the United States. SummaryGIS and Big Data allow for refined epidemiologic estimates of eye disease for specific communities. In particular, how GIS can enable researchers to examine disparities in access to ophthalmic care is reviewed. GIS best practices and some data sources for GIS in ophthalmology are also summarized.

show abstract

“…10,11 Previous research on OCTs characterized publication rates, geographic disparities, and design characteristics. [12][13][14] The effects of the COVID-19 pandemic on OCT discontinuation are unclear. A greater understanding of trials discontinued due to the pandemic may aid the design and management of future trials, leading to reduced resource waste.…”

Section: Introductionmentioning

confidence: 99%

The impact of the COVID-19 pandemic on early termination of ophthalmology clinical trials: A cross-sectional analysis of ClinicalTrials.gov

Kakkilaya,

Hooda,

Kalva

et al. 2023

SAGE Open Medicine

View full text Add to dashboard Cite

Objective: To study the effect of the COVID-19 pandemic on the early termination of ophthalmology clinical trials. Methods: On June 10, 2022, we searched ClinicalTrials.gov and identified clinical trials pertaining to eye diseases. We included trials last updated between January 1, 2020 and June 8, 2022, as ones possibly impacted by the pandemic. We selected all interventional trials in any stage and country that were “recruiting,” “active, not recruiting,” “enrolling by invitation,” “suspended,” “terminated,” “completed,” or “withdrawn” and excluded trials that had been completed or discontinued before 2020, had incomplete data, trials in which the eye was not the primary focus of the trial (e.g., Chediak-Higashi syndrome, myasthenia gravis). The following trial-level characteristics were collected: location, trial status, enrollment count, ocular condition, sponsors, intervention purpose, trial phase (I–IV), randomization, number of arms, and reasons for discontinuation. In addition to calculating descriptive statistics, we assessed whether trial characteristics differed between ophthalmology clinical trials canceled due to COVID-19 and those canceled for other reasons. Results: Following the screening, 2280/12,679 (18%) ophthalmology clinical trials were retained. Of these, 142 (6.2%) were discontinued between January 1, 2020 and June 8, 2022. Moreover, 34 out of 142 (23.9%) ophthalmology clinical trials were discontinued due to COVID-19. These trials were more likely to be sponsored by academic medical centers (26/34, 76.5% vs 57/108, 52.8%, p = 0.03) and were not assigned to a specific study phase, indicating they were not investigational new drugs (22/34, 64.7% vs 46/108 42.6%, p = 0.003). Conclusions: COVID-19-related trial discontinuations were more likely to be reported by academic medical centers and associated with trials investigating fully approved drugs, medical devices, procedures, diagnostic imaging, and behavioral changes. Further investigation of these characteristics may lead to a more robust and resilient understanding of the causes of early termination of these clinical trials.

show abstract

Geographic Access Disparities of Clinical Trials in Neovascular Age-Related Macular Degeneration in the United States

Cited by 9 publications

References 21 publications

Characteristics of Participants in Diabetic Retinopathy Clinical Research Clinical Trials Who Were Lost to Follow up

Characteristics of Participants in Diabetic Retinopathy Clinical Research Clinical Trials Who Were Lost to Follow up

The evolving field of Big Data: understanding geographic information systems analysis and its transformative potential in ophthalmic research

The impact of the COVID-19 pandemic on early termination of ophthalmology clinical trials: A cross-sectional analysis of ClinicalTrials.gov

Contact Info

Product

Resources

About