Abstract
OBJECTIVE
To identify prevalence, risk factors, and visual outcomes associated with occurrence and duration of lapses in proliferative diabetic retinopathy (PDR) care.
RESEARCH DESIGN AND METHODS
This was a retrospective national cohort study (2008–2023) of adults with PDR and ≥6 months of follow-up who were participating in the Sight Outcomes Research Collaborative. We used multivariable regressions to assess factors associated with lapse occurrence and duration, and compared post-lapse visual acuity by lapse duration.
RESULTS
Among 15,211 individuals, 71.8% experienced a lapse in care; 14.2% of the lapses lasted >24 months. Lapses were more common among non-Hispanic Black, younger, and individuals with disability, and less common in those with poor vision or prior PDR treatment. Older age and PDR treatment predicted shorter lapses, and residence in distressed areas predicted longer lapses. Visual acuity worsened after lapses, with greater declines after longer lapses.
CONCLUSIONS
Prolonged lapses in PDR care are common, disproportionately affect vulnerable groups, and are associated with persistent vision loss.
Graphical Abstract
Introduction
Proliferative diabetic retinopathy (PDR) affects ∼7% of individuals with diabetes and requires consistent follow‐up to prevent irreversible vision loss (1). Lapses in PDR care are common, but most prior studies of risk factors and associated outcomes were small, single‐center analyses that did not characterize the lapse duration (2–5). In this multicenter national study, we assessed the occurrence and duration of lapses in PDR care and evaluated associated risk factors and visual outcomes.
Research Design and Methods
This was a retrospective cohort study of 13 active sites in the Sight Outcomes Research Collaborative (SOURCE) (https://www.sourcecollaborative.org) (6). The SOURCE contains electronic health record (EHR) data (deidentified by Datavant, Inc. [San Francisco, CA]) of all patients who received eye care at participating academic health systems. This study was granted exemption by the Yale University Institutional Review Board, New Haven, CT.
We included adults aged ≥18 years who had PDR and ≥6 months of ophthalmic follow-up between 2008 and 2023. We excluded individuals with exudative age-related macular degeneration. In accordance with clinical guidelines and prior studies, we defined a lapse in care as any interval ≥6 months between ophthalmology visits (2,4,5,7). We assessed risk factors for lapse occurrence and duration, including sociodemographics, neighborhood distress, clinical and treatment history, and systemic health (8). The status “having disability” was defined as documented unemployment due to disability in the EHR, and was not based on any particular diagnosis or legal eligibility. We assessed hemoglobin A1c only in univariable models, due to a large (>50%) proportion of missing data.
We recorded visual acuity at the visit before and after each interval >28 days, and at 6 and 12 months after return (with a 60-day window before and after the target date). We grouped visit intervals into duration categories, chosen to reflect clinically meaningful distinctions (Supplementary Fig. 1). We assessed visual acuity in Early Treatment Diabetic Retinopathy Study (ETDRS) letter score in the better-seeing eye and in the eye with PDR (if unilateral disease) or worse-seeing eye (if bilateral or unspecified laterality) to capture both functional and underlying vision loss. We conducted a sensitivity analysis stratifying by presence of diabetic macular edema (DME).
We used logistic regressions to identify risk factors for lapse occurrence and linear mixed-effects models (log transformed) for lapse duration, with random subject effects to account for multiple lapses per patient. Multivariable models included age, sex, race and ethnicity, site, and variables with P < 0.20 in unadjusted models. We performed a sensitivity analysis of missing data using multiple imputation by chained equations with five imputations. To determine the effect of lapse duration on visual acuity over time, we used multivariable linear mixed-effects models with estimated marginal means and Tukey-adjusted pairwise comparisons. Analyses were completed using RStudio 2024.04.2, with P < 0.05 considered statistically significant.
Results
We included 15,211 individuals, of whom 10,915 (71.8%) experienced a lapse in care. The mean (SD) age was 57.6 (12.9) years and 7,472 (49.1%) were female. Mean follow-up time (SD) was longer for those with one or more lapses (4.3 [2.6] vs. 2.1 [1.9] years) (Table 1). Mean lapse duration was 383 days (SD, 303); 2,154 individuals (14.2%) had a lapse >24 months (Supplementary Fig. 1). Among those with a lapse, the average number was 3.9 lapses in care (range, 1–15), totaling 26,743 lapses in the cohort (Supplementary Fig. 2). In a sensitivity analysis of visits prior to the COVID-19 pandemic (March 2020), 62.5% of individuals had a lapse in care.
Table 1.
Baseline characteristics of individuals with PDR, grouped by lapse in care (defined as ≥6 months between ophthalmic visits)
| Variable | Ever had a lapse (n = 10,915) | No lapse (n = 4,296) |
|---|---|---|
| Total follow-up duration, years | 4.34 (2.60) | 2.09 (1.87) |
| Median (IQR) | 3.84 (2.24–6.14) | 1.39 (0.83–2.64) |
| Number of visits | 15.8 (13.6) | 20.3 (18.7) |
| Median (IQR) | 12.0 (6.0–22.0) | 14.0 (8.0–26.0) |
| Time from PDR diagnosis to first visit, years | 0.14 (0.63) | 0.09 (0.46) |
| PDR laterality | ||
| Bilateral (n = 10,214) | 7,263 (66.3) | 2,978 (69.3) |
| Unilateral (n = 1,522) | 1,005 (9.2) | 517 (12.0) |
| Unspecified (n = 3,475) | 2,674 (24.5) | 801 (18.6) |
| Age at first visit, years | ||
| ≤55 (n = 6,169) | 4,412 (40.4) | 1,757 (40.9) |
| 56–65 (n = 4,683) | 3,312 (30.3) | 1,371 (31.9) |
| >65 (n = 4,359) | 3,191 (29.2) | 1,168 (27.2) |
| Sex | ||
| Female (n = 7,472) | 5,510 (50.5) | 1,962 (45.7) |
| Male (n = 7,739) | 5,405 (49.5) | 2,334 (54.3) |
| Distressed Communities Index* | ||
| ≤20 (n = 3,749) | 2,696 (24.7) | 1,053 (24.5) |
| 21–40 (n = 2,249) | 1,605 (14.7) | 644 (15.0) |
| 41–60 (n = 2,298) | 1,594 (14.6) | 705 (16.4) |
| 61–80 (n = 2,246) | 1,528 (14.0) | 717 (16.7) |
| 81–100 (n = 2,332) | 1,670 (15.3) | 662 (15.4) |
| Unreported (n = 2,338) | 1,823 (16.7) | 516 (12.0) |
| RUCA | ||
| Metropolitan (n = 12,198) | 8,681 (79.5) | 3,517 (81.9) |
| Nonmetropolitan (n = 1,523) | 1,001 (9.2) | 522 (12.2) |
| Unreported (n = 1,490) | 1,233 (11.3) | 257 (6.0) |
| Race and ethnicity | ||
| Non-Hispanic White (n = 6,701) | 4,759 (43.6) | 1,942 (45.2) |
| Non-Hispanic Black (n = 4,449) | 3,362 (30.8) | 1,087 (25.3) |
| Hispanic (n = 2,270) | 1,526 (14.0) | 744 (17.3) |
| Other (n = 1,028) | 735 (6.7) | 293 (6.8) |
| Unreported (n = 763) | 533 (4.9) | 230 (5.4) |
| Health insurance status | ||
| Private (n = 3,749) | 2,610 (23.9) | 1,139 (26.5) |
| Medicaid (n = 1,237) | 847 (7.8) | 390 (9.1) |
| Medicare (n = 6,559) | 4,991 (45.7) | 1,568 (36.5) |
| Unknown (n = 3,356) | 2,266 (20.8) | 1,090 (25.4) |
| Other (n = 310) | 201 (1.8) | 109 (2.5) |
| Employment status | ||
| Full-time (n = 2,553) | 1,762 (16.1) | 791 (18.4) |
| Retired (n = 4,063) | 3,088 (28.3) | 975 (22.7) |
| Unemployed (n = 2,588) | 1,798 (16.5) | 790 (18.4) |
| Having disability (n = 2,075)† | 1,593 (14.6) | 482 (11.2) |
| Other (n = 600) | 428 (3.9) | 172 (4.0) |
| Unreported (n = 3,332) | 2,246 (20.6) | 1,086 (25.3) |
| Marital status | ||
| Married (n = 6,897) | 4,994 (45.8) | 1,903 (44.3) |
| Single (n = 4,509) | 3,235 (29.6) | 1,274 (29.7) |
| Divorced (n = 12,512) | 910 (8.3) | 341 (7.9) |
| Widowed (n = 1,259) | 952 (8.7) | 307 (7.1) |
| Other (n = 484) | 340 (3.1) | 144 (3.4) |
| Unreported (n = 811) | 484 (4.4) | 327 (7.6) |
| Diabetes type | ||
| Type 2 (n = 11,825) | 8,328 (76.3) | 3,497 (81.4) |
| Type 1 (n = 3,132) | 2,423 (22.2) | 709 (16.5) |
| Other (n = 254) | 164 (1.5) | 90 (2.1) |
| Underlying health status | ||
| HTN status | ||
| None (n = 6,313) | 4,411 (40.4) | 1,902 (44.3) |
| Uncomplicated (n = 7,427) | 5,382 (49.3) | 2,045 (47.6) |
| Complicated (n = 1,471)‡ | 1,122 (10.3) | 349 (8.1) |
| Dyslipidemia (n = 7,053) | 5,291 (48.5) | 1,762 (41.0) |
| Diabetes complications | ||
| Neuropathy (n = 4,500) | 3,398 (31.1) | 1,002 (25.7) |
| Nephropathy (n = 4,495) | 3,424 (31.4) | 1,071 (24.9) |
| Nonhealing diabetic ulcer (n = 1,524) | 1,179 (10.8) | 345 (8.0) |
| Amputation (n = 607) | 480 (4.4) | 127 (3.0) |
| Treatment modality | ||
| PRP only (n = 1,547) | 1,216 (11.1) | 331 (7.7) |
| IVI only (n = 3,510) | 2,072(19.0) | 1,483 (33.5) |
| Both (n = 4,382) | 2,739 (25.1) | 1,643 (38.2) |
| Neither (n = 5,772) | 4,888 (44.8) | 884 (20.5) |
| Initial visual acuity | ||
| 20/40 or better (n = 9,379) | 7,028 (64.4) | 2,351 (54.7) |
| 20/50-20/200 (n = 4,268) | 2,883 (26.4) | 1,385 (32.2) |
| Worse than 20/200 (n = 1,256) | 849 (7.8) | 407 (9.5) |
| Unreported (n = 308) | 155 (1.4) | 153 (3.6) |
| Initial HbA1c | ||
| <9.0 (n = 5,139) | 3,977 (36.4) | 1,162 (27.0) |
| ≥9.0 (n = 2,067) | 1,592 (14.6) | 475 (11.1) |
| Unreported (n = 8,005) | 5,346 (49.0) | 2,659 (61.9) |
Data are presented as no. (%) or mean (SD).
*The Distressed Communities Index is a composite score for a geographic area measured as a percentile from 0 to 100, with higher scores indicating greater community distress.
†The status “having disability” was defined as documented unemployment due to disability in the EHR and was not based on diagnosis or legal eligibility.
‡Complicated HTN defined as history of HTN and history of arrhythmia, transient ischemic attack, stroke, myocardial infarction, peripheral or pulmonary thrombosis/embolus, or heart failure. HTN, hypertension; IVI, intravitreal injection; RUCA, rural urban commuting area.
In multivariable analysis, odds of a lapse were higher for non-Hispanic Black individuals (vs. White: odds ratio [OR], 1.26; 95% CI 1.07–1.48), individuals with disability (vs. full-time employment: OR, 1.52; 95% CI 1.23–1.88), and those with complicated hypertension (OR, 1.34; 95% CI 1.02–1.77). Odds of a lapse were lower among older (age 56–65 vs. ≤55 years: OR, 0.81; 95% CI 0.69–0.93; age >65 vs. ≤55 years: OR, 0.79; 95% CI 0.64–0.96), worse-seeing (20/50 to 20/200 vs. 20/40 or better: OR, 0.79; 95% CI 0.70–0.90; worse than 20/200 vs. 20/40 or better: OR, 0.79; 95% CI 0.64–0.98), and treated (panretinal photocoagulation [PRP] vs. none: OR, 0.60; 95% CI 0.48–0.75; anti–vascular endothelial growth factor [VEGF] intravitreal injections [IVI] vs. none: OR, 0.23; 95% CI 0.20–0.27; both PRP and IVI vs. none: OR, 0.22; 95% CI 0.18–0.25) individuals (Fig. 1; Supplementary Table 1). These results were consistent in a sensitivity analysis imputing missing data (Supplementary Table 1).
Figure 1.
Multivariable logistic regression model of factors associated with having a lapse in care ≥6 months between ophthalmic visits for individuals with PDR. DCI, distressed communities index; Dx, diagnosis; HTN, hypertension; RUCA, rural urban commuting area; VA, visual acuity (in the better seeing eye).
Lapses were longer among individuals with longer PDR duration (mean lapse duration ratio, 1.03; 95% CI 1.01–1.04), those in the most socioeconomically distressed areas (vs. least; mean lapse duration ratio, 1.06; 95% CI 1.02–1.10), and during or after the COVID-19 pandemic (mean lapse duration ratio, 1.16; 95% CI 1.14–1.18). Lapses were shorter among older individuals (age 56–65 vs. ≤55 years: mean lapse duration ratio, 0.94; 95% CI 0.91–0.98; age >65 vs. ≤55 years: mean lapse duration ratio, 0.87; 95% CI 0.84–0.91), those with unilateral PDR (vs. bilateral; mean lapse duration ratio, 0.94; 95% CI 0.91–0.98), type 1 diabetes (vs. type 2; mean lapse duration ratio, 0.95; 95% CI 0.93–0.98), and prior treatment (PRP vs. none: mean lapse duration ratio, 0.96; 95% CI 0.92–1.00; IVI alone vs. none: mean lapse duration ratio, 0.94; 95% CI 0.91–0.97; both PRP and IVI vs. none: mean lapse duration ratio, 0.93; 95% CI 0.90–0.96) (Fig. 2; Supplementary Table 2).
Figure 2.
Multivariable linear mixed effects model for factors associated with the duration of each lapse in ophthalmic care for individuals with PDR (clustered by patient). Dx, diagnosis; HTN, hypertension; VA, visual acuity (in the better seeing eye).
Visual acuity declined after all lapses. One year after a >24-month lapse, visual acuity worsened from 69.5 ± 0.24 to 65.7 ± 0.46 ETDRS letters in the better-seeing eye (P < 0.001), and 52.7 ± 0.34 to 44.0 ± 0.66 in the eye with PDR or worse-seeing eye (P < 0.001). There was greater vision loss after longer lapses (Fig. 3). Trends were similar in a sensitivity analysis stratified by DME status (Supplementary Fig. 3).
Figure 3.
Visual acuity (VA) in the better-seeing eye (top) and in the eye with PDR or, for individuals with bilateral disease or unspecified laterality, in the worse-seeing eye (bottom) over time after a nonlapse (i.e., 1–6 months), short lapse (6–12 months), long lapse (12–24 months), or very long lapse (>24 months) in ophthalmic care for adults with PDR in a national cohort. We adjusted for age, sex, treatment modality, total follow-up duration, number of lapses, site, and baseline VA, accounting for the correlation of multiple observations on the same individual.
Conclusions
This large multicenter study builds on prior work by characterizing not only occurrence but the duration of lapses in PDR care. In our cohort of 15,211 adults with PDR, >70% experienced a lapse lasting ≥6 months, and nearly one in seven had a lapse >24 months. We identified characteristics associated with lapse occurrence and duration and found that longer lapses were associated with persistent vision loss. These findings highlight the challenge of maintaining continuity of care and the need for interventions that support follow-up.
Follow-up delays are strikingly common even under optimal conditions in highly structured clinical trials (55% in Diabetic Retinopathy Clinical Research Network Protocol S) (9). Real-world adherence is likely worse. Our lapse rate was similar to those reported by previous studies, though differences in patient population (e.g., private vs. academic, inclusion of untreated eyes) and methodology may explain some variability (2–4). Notably, lapses were longer and more frequent during the COVID-19 pandemic, which significantly disrupted the health care landscape (10).
Improving continuity of care requires addressing the complex interplay of patient-, institution-, and system-level barriers. We found that non-Hispanic Black individuals and those in socioeconomically distressed communities had higher odds of lapses and longer lapse duration. This aligns with the findings from prior studies and reflects structural inequities in health care and social systems (4,11,12). Strategies to target these barriers may include policies for more equitable resource distribution, institutional integration of equity metrics, culturally responsive patient education, and personalized health care navigation. Medically complex individuals and those with disability had more lapses in care. These patients may have limited mobility or may miss ophthalmic visits due to competing appointments and hospitalizations (13,14). Efforts should explore integrated models of chronic disease management that streamline ophthalmic follow-up. Additionally, outreach is needed for younger patients, those with preserved vision, and those with type 2 diabetes, who may have lower disease awareness and underestimate the urgency of care (3,15–17). Because vision loss is a late finding that often occurs after substantial retinal injury, it is critical to engage asymptomatic patients in regular care.
Treated individuals were less likely to have a lapse, and when they did, they had shorter lapses. This may reflect greater disease severity prompting better engagement in care. Undergoing treatment may also increase awareness of the risks of vision loss and reinforce the need for regular follow-up. This association was stronger for anti-VEGF IVIs than PRP, which parallels the more frequently required treatment sessions, though it is unclear whether this represents a causal effect or selection bias in treatment assignment (3,4,17). Discomfort associated with PRP may also deter consistent follow-up (18).
Longer lapses in PDR care were consistently associated with worse visual outcomes. After a >24-month lapse, we observed a 3.8-letter decrease in the better-seeing eye, and an 8.7-letter loss in the eye with PDR or worse-seeing eye. The larger, persistent vision loss in the worse-seeing eye poses long-term consequences from loss of binocular vision, including risk for falls, depression, and reduced quality of life (19). This clinical impact of a lapse in PDR care is consistent with findings from other studies (3,5,9).
This study has limitations. As a retrospective EHR-based study, it is subject to misclassified data, although billing data generally align well with the medical record (20). We lacked data on individual-level socioeconomic status, insulin use, and glycemic control, which likely play a role in access to care. However, we evaluated neighborhood-level socioeconomics and comorbid conditions correlated with diabetes severity. We could not track ophthalmic care received outside of SOURCE institutions, but because we included only completed lapses with a return visit, it is less likely that patients received continuous care elsewhere. Strengths of this study include the large sample size and inclusion of 13 geographically diverse institutions, which increases generalizability beyond single-center studies. Our findings provide a foundation for future work to design interventions that improve continuity of care and prevent irreversible vision loss in PDR.
This article contains supplementary material online at https://doi.org/10.2337/figshare.30005956.
Article Information
Acknowledgments. We acknowledge Maximilian Wegener, biomedical informatics librarian at the Harvey Cushing/John Hay Whitney Medical Library, for data visualization support.
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health and Richard K. Gershon Endowed Medical Student Research Fellowship. The sponsor or funding organization had no role in the design or conduct of this research.
Duality of Interest. No potential conflicts of interest relevant to this article were reported.
Author Contributions. S.S.A., J.J.F., and K.H.N. were involved in the study conception and design and in acquisition of data. S.S.A., Y.D., M.K., and K.H.N. were involved in the conduct of the study and the analysis and interpretation of the data. S.S.A. wrote the first draft of the manuscript, and all authors edited, reviewed, and approved the final version of the manuscript. K.H.N. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Prior Presentation. This work was presented as a poster at the Association of Research in Vision and Ophthalmology annual meeting, Salt Lake City, UT, 4–8 May 2025.
Handling Editors. The journal editors responsible for overseeing the review of the manuscript were Steven E. Kahn and Meghana D. Gadgil.
Funding Statement
This publication was made possible by the National Eye Institute (grant 1 K23 EY030530-01). This work has been supported in part by an unrestricted/challenge award to Yale Eye Center from the Research to Prevent Blindness, Inc. Research reported in this article was also supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health and Richard K. Gershon Endowed Medical Student Research Fellowship.
Footnotes
*A list of members of the SOURCE consortium can be found in the supplementary material online.
Contributor Information
Kristen H. Nwanyanwu, Email: k.nwanyanwu@yale.edu.
Sight Outcomes Research Collaborative (SOURCE) Consortium:
Sejal Amin, Paul A. Edwards, Divya Srikumaran, Fasika Woreta, Jeffrey S. Schultz, Anurag Shrivastava, Baseer Ahmad, Louis R. Pasquale, Paul J. Bryar, Dustin D. French, Michelle Hribar, Merina Thomas, Brian L. Vanderbeek, Suzann Pershing, Sophia Y. Wang, Michael Deiner, Catherine Sun, Jennifer Patnaik, Prem Subramanian, Saleha Munir, Wuqaas Munir, Joshua Stein, Lindsey De Lott, Rajeev Ramachandran, Robert Feldman, Brian C. Stagg, Barbara Wirostko, Brian McMillian, Arsham Sheybani, Soshian Sarrafpour, Kristen Harris-Nwanyanwu, Joshua Stein, and Chris Andrews
Supporting information
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