Endpoints In Clinical Trials Research Articles

Priorities and barriers for research related to primary ciliary dyskinesia.

Despite advances in primary ciliary dyskinesia (PCD) research, many questions remain; diagnosis is complex and no disease-specific therapies exist. Using a mixed-methods approach, we aimed to identify priorities for clinical and epidemiological research and explore barriers to research. To obtain rich, relevant, diverse data, we performed in-depth semi-structured interviews with PCD specialists selected using purposive sampling. We transcribed, coded and analysed interview data using thematic analysis. Based on interview themes that we identified, we developed an anonymous survey and circulated it widely through the BEAT-PCD network. We interviewed 28 participants from 15 countries across different disciplines and expertise levels. The main themes identified as priorities for PCD research were improving diagnosis; understanding prevalence and disease course; phenotypic variability; disease monitoring; treatment strategies; clinical trial end-points; and poorly researched areas. In total, 136 participants (49% paediatric pulmonologists) from 36 countries completed the survey. Most commonly reported barriers for research were low awareness about PCD and difficulties securing funding - in more than one-third of cases, participants reported undertaking predominantly unfunded research. Research questions ranked highest included priorities related to further improving diagnosis, treating PCD, managing upper and lower airway problems, and studying clinical variability and disease prognosis. We need to overcome barriers of limited funding and low awareness and promote collaborations between centres, disciplines, experts and patients to address identified PCD priorities effectively. Our results contribute to the ongoing efforts of guiding the use of existing limited research resources and setting up a roadmap for future research activities.

Identifying disease-modifying potential in myelofibrosis clinical trials

AbstractThe ultimate goal of bringing most new drugs to the clinic in hematologic malignancy is to improve overall survival. However, the use of surrogate end points for overall survival is increasingly considered standard practice, because a well validated surrogate end point can accelerate the outcome assessment and facilitate better clinical trial design. Established examples include monitoring minimal residual disease in chronic myeloid leukemia and acute leukemia, and metabolic response assessment in lymphoma. However, what happens when a clinical trial end point that is not a good surrogate for disease-modifying potential becomes ingrained as an expected outcome, and new agents are expected or required to meet this end point to demonstrate “efficacy”? Janus kinase (JAK) inhibitors for myelofibrosis (MF) have a specific impact on reducing symptom burden and splenomegaly but limited impact on the natural history of the disease. Since the introduction of ruxolitinib more than a decade ago there has been modest incremental success in clinical trials for MF but no major leap forward to alter the natural history of the disease. We argue that the clinical development of novel agents for MF will be accelerated by moving away from using end points that are specifically tailored to measure the beneficial effects of JAK inhibitors. We propose that specific measures of relevant disease burden, such as reduction in mutation burden as determined by molecular end points, should replace established end points. Careful reanalysis of existing data and trials in progress is needed to identify the most useful surrogate end points for future MF trials and better serve patient interest.

Volumetric Assessment of Traumatic Intracranial Hematomas: Is ABC/2 Reliable?

Accurate measurement of traumatic intracranial hematoma volume is important for assessing disease progression and prognosis, as well as for serving as an important end-point in clinical trials aimed at preventing hematoma expansion. While the ABC/2 formula has traditionally been used for volume estimation in spontaneous intracerebral hemorrhage, its adaptation to traumatic hematomas lacks validation. This study aimed to compare the accuracy of ABC/2 with computer-assisted volumetric analysis (CAVA) in estimating the volumes of traumatic intracranial hematomas. We performed a dual-center observational study that included adult patients with moderate-to-severe traumatic brain injury. Volumes of intracerebral, subdural (SDHs), and epidural hematomas from admission computed tomography scans were measured using ABC/2 and CAVA, and compared using the Wilcoxon signed-rank test, Spearman's rank correlation, Lin's concordance correlation coefficient (CCC), and Bland-Altman plots. Prognostic significance for outcomes was evaluated through logistic and linear regression models. In total, 1,179 patients with 1,543 hematomas were included. Despite a high correlation (Spearman coefficients between 0.95 and 0.98) and excellent concordance (Lin's CCC from 0.89 to 0.96) between ABC/2 and CAVA, ABC/2 overestimated hematoma volumes compared with CAVA, in some instances exceeding 50 ml. Bland-Altman analysis highlighted wide limits of agreement, especially in SDH. While both methods demonstrated comparable accuracy in predicting outcomes, CAVA was slightly better at predicting craniotomies and midline shift. We conclude that while ABC/2 provides a generally reliable volumetric assessment suitable for descriptive purposes and as baseline variables in studies, CAVA should be the gold standard in clinical situations and studies requiring more precise volume estimations, such as those using hematoma expansion as an outcome.

Circulating tumor tissue modified viral (TTMV)-HPV DNA in Recurrent, metastatic HPV-driven oropharyngeal cancer

BackgroundHuman papillomavirus (HPV) is causally linked to oropharyngeal squamous cell carcinoma (OPSCC). Testing for plasma tumor tissue modified viral (TTMV)-HPV DNA has emerged as a biomarker strategy for post-treatment surveillance to identify recurrent disease. We aimed to understand the prognostic and predictive potential of TTMV-HPV DNA when monitoring patients who had developed recurrent or metastatic (R/M) HPV+OPSCC. MethodsThis retrospective observational cohort study included 80 patients from 4 academic centers with R/M HPV+OPSCC if they had ≥ 1 plasma TTMV-HPV DNA test obtained at any point during their R/M disease course. Physician-reported clinical data and treatment history were captured in a centralized database, along with investigator-assessed response to therapy and survival. Descriptive statistics and non-parametric tests of association were employed along with survival analyses (Kaplan-Meier method). ResultsSixteen (20 %) patients had ≥ 5 test results over time. Consecutive TTMV-HPV DNA tests were performed a median of 73 days apart. Median TTMV-HPV DNA scores were higher with an increasing per-patient number of metastatic sites (<2 vs. 2+; p < 0.01). Score changes over time were influenced by R/M treatment modality and became undetectable in 67 % (12/18) of patients who achieved a complete response to R/M therapy. Patients with detectable scores at last follow-up had significantly worse survival compared with those who were undetectable (log-rank test, p < 0.01). ConclusionsTTMV-HPV DNA appears useful as a prognostic tool for monitoring response to therapy in the R/M setting. In the future, TTMV-HPV DNA could be explored as an exploratory clinical trial endpoint in the metastatic setting.

Regulatory Pathways for Qualification andAcceptance of Digital Health Technology-Derived Clinical Trial Endpoints: Considerations for Sponsors.

Despite widespread interest and substantial investment in the adoption of sensor-based digital health technologies (sDHTs) for remote data capture in drug development trials, no drug has been approved based on an sDHT-derived primary endpoint in the United States (US). One reason for this lack of advancement is the complexity of obtaining regulatory endorsement for those endpoints within current US regulatory pathways. The goal of our review is to describe the two choices currently available to pharmaceutical study Sponsors: (i) they may navigate the traditional route of compiling the evidence to support the sDHT-derived endpoint in their investigational new drug (IND) application, requiring specific expertise and substantial resources; or (ii) they may navigate the drug development tool (DDT) pathway with the goal of qualifying their sDHT-derived endpoint as a biomarker or clinical outcome assessment applicable to a broader context of use (COU), either alone or as part of a partnership or consortium. We describe the nuances of each pathway; the evidentiary requirements for supporting an sDHT-derived endpoint and the technology used to capture it; and the impact that an sDHT's regulatory status may have on a Sponsor's decision to use it for data capture. By systematically comparing the IND and DDT pathways, our over-arching goals are to support the increasing deployment of sDHTs within the clinical research setting and help advance regulatory science in the field of digital medicine.

Inhaled Nitric Oxide in Fibrotic Lung Disease: A Randomized, Double-Blind, Placebo-Controlled Trial.

Inhaled nitric oxide (iNO) has been shown to result in benefits in moderate to vigorous physical activity (MVPA) in patients with fibrotic interstitial lung disease (if-ILD) on supplemental oxygen in two independent trials. This phase 3 randomized double-blind placebo-controlled study sought to validate the benefit of ambulatory iNO in patients with f-ILD requiring supplemental oxygen. Patients with f-ILD on supplemental long-term oxygen were randomized in a 1:1 fashion to inhaled nitric oxide at 45 µg/kg ideal body weight/hour or placebo for 16 weeks. The primary outcome was the change from baseline to week 16 in MVPA assessed by accelerometry. Secondary outcomes included overall activity, six-minute walk distance and patient reported outcomes. 145 patients were enrolled; 75 were assigned to receive iNO and 70 to placebo. The change from baseline in MVPA at 16 weeks was -9.2 minute/day (SE 3.51) in the iNO45 group versus -3.7 (3.76) minute/day in the placebo group (difference, 5.5; P=0.265). No statistically significant differences between the two treatment arms were found for any of the secondary outcomes. A subgroup analysis of patients with intermediate or high probability of pulmonary hypertension on echocardiography did not demonstrate any benefit. The most common adverse events reported were respiratory tract infections, but the therapy was generally very well tolerated. There was no demonstrable benefit to iNO in patients with f-ILD on supplemental oxygen in daily physical activity assessed by actigraphy, a potential novel clinical trial endpoint. Clinical trial registration available at www. gov, ID: NCT03267108.

Improving the clinical meaning of surrogate endpoints: An empirical assessment of clinical progression in phase III oncology trials.

Disease progression in clinical trials is commonly defined by radiologic measures. However, clinical progression may be more meaningful to patients, may occur even when radiologic criteria for progression are not met, and often requires a change in therapy in clinical practice. The objective of this study was to determine the utilization of clinical progression criteriawithin progression-based trial endpoints among phase III trials testing systemic therapies for metastatic solid tumors. The primary manuscripts and protocols of phase III trials were reviewed for whether clinical events, such as refractory pain, tumor bleeding, or neurologic compromise, could constitute a progression event. Univariable logistic regression computed odds ratios (OR) and 95% CI for associations between trial-level covariates and clinical progression. A total of 216 trials enrolling 148,190 patients were included, with publication dates from 2006 through 2020. A major change in clinical status was included in the progression criteria of 13% of trials (n = 27), most commonly as a secondary endpoint (n = 22). Only 59% of trials (n = 16) reported distinct clinical progression outcomes that constituted the composite surrogate endpoint. Compared with other disease sites, genitourinary trials were more likely to include clinical progression definitions (16/33 [48%] vs. 11/183 [6%]; OR, 14.72; 95% CI, 5.99 to 37.84; p < .0001). While major tumor-related clinical events were seldom considered as disease progression events, increased attention to clinical progression may improve the meaningfulness and clinical applicability of surrogate endpoints for patients with metastatic solid tumors.

BrainAgeNeXt: Advancing Brain Age Modeling for Individuals with Multiple Sclerosis.

Aging is associated with structural brain changes, cognitive decline, and neurodegenerative diseases. Brain age, an imaging biomarker sensitive to deviations from healthy aging, offers insights into structural aging variations and is a potential prognostic biomarker in neurodegenerative conditions. This study introduces BrainAgeNeXt, a novel convolutional neural network inspired by the MedNeXt framework, designed to predict brain age from T1-weighted magnetic resonance imaging (MRI) scans. BrainAgeNeXt was trained and validated on 11,574 MRI scans from 33 private and publicly available datasets of healthy volunteers, aged 5 to 95 years, imaged with 3T and 7T MRI. Performance was compared against three state-of-the-art brain age prediction methods. BrainAgeNeXt achieved a mean absolute error (MAE) of 2.78 ± 3.64 years, lower than the compared methods (MAE = 3.55, 3.59, and 4.16 years, respectively). We tested all methods also across different levels of image quality, and BrainAgeNeXt performed well even with motion artifacts and less common 7T MRI data. In three longitudinal multiple sclerosis (MS) cohorts (273 individuals), brain age was, on average, 4.21 ± 6.51 years greater than chronological age. Longitudinal analysis indicated that brain age increased by 1.15 years per chronological year in individuals with MS (95% CI = [1.05, 1.26]). Moreover, in early MS, individuals with worsening disability had a higher annual increase in brain age compared to those with stable clinical assessments (1.24 vs. 0.75, p < 0.01). These findings suggest that brain age is a promising prognostic biomarker for MS progression and potentially a valuable endpoint for clinical trials.

Different meanings of a three-point decline in MMSE score in Alzheimer's disease and depressive disorder.

The Mini-Mental State Examination (MMSE) is a composite scale that is included in diagnostic algorithms and in procedures to assess severity of cognitive impairment and efficacy of therapeutic interventions. It is unclear, however, whether the MMSE provides information about the same deficits in different diseases. To assess patterns of MMSE scores in patients with confirmed diagnosis of Alzheimer's disease or depressive disorder. We used data from a previously published cross-sectional retrospective observational clinical cohort study. The final analysis included only patients in whom biomarker analysis showed results characteristic of Alzheimer's disease (n = 167) and patients with depressive disorder in whom Alzheimer's disease had been ruled out by analysis of biomarkers (n = 69). A three-point decline in MMSE score from 30 to 27 reflected impairment of memory recall in patients with Alzheimer's disease, whereas it reflected impairments in calculation and memory recall in patients with depressive disorder. A further three-point decline in MMSE score from 27 to 24 predominantly reflected additional calculation impairment in patients with Alzheimer's disease. Our results indicate that memory performance is the most important measure of disease severity and the main contributor to the decline in MMSE score at onset of clinical manifestation of Alzheimer's disease. In general, this suggests that memory should be the primary measure used in routine clinical care and the primary endpoint in clinical trials involving patients with Alzheimer's disease at onset of clinical manifestation. Changes in other measures of cognition should prompt consideration of possible comorbidities as a cause, rather than the impact of Alzheimer's disease itself.

Statistical approaches for component-wise censored composite endpoints.

Composite endpoints defined as the time to the earliest of two or more events are often used as primary endpoints in clinical trials. Component-wise censoring arises when different components of the composite endpoint are censored differently. We focus on a composite of death and a non-fatal event where death time is right censored and the non-fatal event time is interval censored because the event can only be detected during study visits. Such data are most often analysed using methods for right censored data, treating the time the non-fatal event was first detected as the time it occurred. This can lead to bias, particularly when the time between assessments is long. We describe several approaches for estimating the event-free survival curve and the effect of treatment on event-free survival via the hazard ratio that are specifically designed to handle component-wise censoring. We apply the methods to a randomized study of breastfeeding versus formula feeding for infants of mothers infected with human immunodeficiency virus.

Long-term natural history of ellipsoid zone width in USH2A-retinopathy

AimsTo investigate the long-term natural history of ellipsoid zone (EZ) width in USH2A-retinopathy.MethodsEZ width measurements from optical coherence tomography were retrospectively obtained from 110 eyes of 55 participants with molecularly...

Digital endpoints in clinical trials: emerging themes from a multi-stakeholder Knowledge Exchange event

BackgroundDigital technologies, such as wearable devices and smartphone applications (apps), can enable the decentralisation of clinical trials by measuring endpoints in people’s chosen locations rather than in traditional clinical settings. Digital endpoints can allow high-frequency and sensitive measurements of health outcomes compared to visit-based endpoints which provide an episodic snapshot of a person’s health. However, there are underexplored challenges in this emerging space that require interdisciplinary and cross-sector collaboration. A multi-stakeholder Knowledge Exchange event was organised to facilitate conversations across silos within this research ecosystem.MethodsA survey was sent to an initial list of stakeholders to identify potential discussion topics. Additional stakeholders were identified through iterative discussions on perspectives that needed representation. Co-design meetings with attendees were held to discuss the scope, format and ethos of the event. The event itself featured a cross-disciplinary selection of talks, a panel discussion, small-group discussions facilitated via a rolling seating plan and audience participation via Slido. A transcript was generated from the day, which, together with the output from Slido, provided a record of the day’s discussions. Finally, meetings were held following the event to identify the key challenges for digital endpoints which emerged and reflections and recommendations for dissemination.ResultsSeveral challenges for digital endpoints were identified in the following areas: patient adherence and acceptability; algorithms and software for devices; design, analysis and conduct of clinical trials with digital endpoints; the environmental impact of digital endpoints; and the need for ongoing ethical support. Learnings taken for next generation events include the need to include additional stakeholder perspectives, such as those of funders and regulators, and the need for additional resources and facilitation to allow patient and public contributors to engage meaningfully during the event.ConclusionsThe event emphasised the importance of consortium building and highlighted the critical role that collaborative, multi-disciplinary, and cross-sector efforts play in driving innovation in research design and strategic partnership building moving forward. This necessitates enhanced recognition by funders to support multi-stakeholder projects with patient involvement, standardised terminology, and the utilisation of open-source software.

Sample size considerations for single-arm clinical trials with time-to-event endpoint using the gamma distribution

BackgroundTime-to-event (TTE) endpoints are evaluated as the primary endpoint in single-arm clinical trials; however, limited options are available in statistical software for sample size calculation. In single-arm trials with TTE endpoints, the non-parametric log-rank test is commonly used. Parametric options for single-arm design assume survival times follow exponential distribution or Weibull distribution. MethodsThe exponential- or Weibull-distributed survival time assumption does not always reflect hazard pattern of real-life diseases. We therefore propose gamma distribution as an alternative parametric option for designing single-arm studies with TTE endpoints. We outline a sample size calculation approach using gamma distribution with a known shape parameter and explain how to extract the gamma shape estimate from previously published resources. In addition, we conduct simulations to assess the accuracy of the extracted gamma shape parameter and to explore the impact on sample size calculation when survival time distribution is misspecified. ResultsOur simulations show that if a previously published study (sample sizes ≥ 60 and censoring proportions ≤ 20 %) reported median and inter-quartile range of survival time, we can obtain a reasonably accurate gamma shape estimate, and use it to design new studies. When true survival time is Weibull-distributed, sample size calculation could be underestimated or overestimated depending on the hazard shape. ConclusionsWe show how to use gamma distribution in designing a single-arm trial, thereby offering more options beyond the exponential and Weibull. We provide a simulation-based assessment to ensure an accurate estimation of the gamma shape and recommend caution to avoid misspecification of the underlying distribution.

RWC Update: Dislocated DSEK Flap; Ellipsoid Zone as a Surrogate Efficacy Endpoint in Clinical Trials; Retinal Tear Associated With Lattice Degeneration.

RWC Update: Dislocated DSEK Flap; Ellipsoid Zone as a Surrogate Efficacy Endpoint in Clinical Trials; Retinal Tear Associated With Lattice Degeneration.

Advantages of Lissamine Green Vital Staining as an Endpoint in Dry Eye Clinical Trials.

The absence of a standardized diagnostic method for clinical signs of Dry Eye Disease (DED) complicates clinical trials for future treatments. This paper evaluated Lissamine Green (LG) conjunctival staining as a valid, stable and modifiable endpoint for both clinical practice and clinical trials. Screening and pre-randomization data from two identically designed clinical trials for DED resulted in a pooled dataset of 494 subjects. Inclusion was based on reported symptoms, lissamine green (LG) conjunctival staining, Fluorescein (Fl) corneal and conjunctival staining, and Schirmer's Test (ST). Outcome measures were assessed based on the modifiability of LG staining to exposure to a Controlled Adverse Environment (CAE®), correlation of LG to Fl staining, relative variation of LG staining scores and Schirmer test scores, and the correlation of LG staining with symptom scores. The modifiability of LG conjunctival staining to environmental exposure was demonstrated, with nasal LG and FL staining displaying the most similar percent change. Nasal LG conjunctival staining scores for subjects with ST scores of less than 8mm were significantly higher than for subjects with ST greater than 8mm. LG staining scores were more consistent (25% change from baseline threshold) than ST scores. Finally, statistically significant correlations were found between LG staining and a number of symptom scores. This evaluation demonstrates the superiority of the utilization of a clinical endpoint focused on ocular surface damage. The reproducibility and modifiability of LG conjunctival staining to controlled adverse environment, coupled with its significant correlation with symptoms, positions it as an exemplary clinical sign endpoint for clinical management and in clinical trials. Our findings advocate for the adoption of LG conjunctival staining as a primary endpoint in both clinical research and drug development, offering a more effective means of identifying and addressing ocular surface damage in the realm of DED.

The consideration of appropriate surrogate endpoint in premarket clinical trials of drug coated balloon catheter for the treatment of femoropopliteal artery stenosis

The consideration of appropriate surrogate endpoint in premarket clinical trials of drug coated balloon catheter for the treatment of femoropopliteal artery stenosis

Digital health technologies to strengthen patient-centred outcome assessment in clinical trials in inflammatory arthritis.

Common to all inflammatory arthritides, namely rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis, and juvenile idiopathic arthritis, is a potential for reduced mobility that manifests through joint pain, swelling, stiffness, and ultimately joint damage. Across these conditions, consensus has been reached on the need to capture outcomes related to mobility, such as functional capacity and physical activity, as core domains in randomised controlled trials. Existing endpoints within these core domains rely wholly on self-reported questionnaires that capture patients' perceptions of their symptoms and activities. These questionnaires are subjective, inherently vulnerable to recall bias, and do not capture the granularity of fluctuations over time. Several early adopters have integrated sensor-based digital health technology (DHT)-derived endpoints to measure physical function and activity in randomised controlled trials for conditions including Parkinson's disease, Duchenne's muscular dystrophy, chronic obstructive pulmonary disease, and heart failure. Despite these applications, there have been no sensor-based DHT-derived endpoints in clinical trials recruiting patients with inflammatory arthritis. Borrowing from case studies across medicine, we outline the opportunities and challenges in developing novel sensor-based DHT-derived endpoints that capture the symptoms and disease manifestations most relevant to patients with inflammatory arthritis.

Assessing the net financial benefits of employing digital endpoints in clinical trials.

In the last few decades, developers of new drugs, biologics, and devices have increasingly leveraged digital health technologies (DHTs) to assess clinical trial digital endpoints. To our knowledge, a comprehensive assessment of the financial net benefits of digital endpoints in clinical trials has not been conducted. We obtained data from the Digital Medicine Society (DiMe) Library of Digital Endpoints and the US clinical trials registry, ClinicalTrials.gov. The benefit metrics are changes in trial phase duration and enrollment associated with the use of digital endpoints. The cost metric was obtained from an industry survey of the costs of including digital endpoints in clinical trials. We developed an expected net present value (eNPV) model of the cash flows for new drug development and commercialization to assess financial value. The value measure is the increment in eNPV that occurs when digital endpoints are employed. We also calculated a return on investment (ROI) as the ratio of the estimated increment in eNPV to the mean digital endpoint implementation cost. For phase II trials, the increase in eNPV varied from $2.2 million to $3.3 million, with ROIs between 32% and 48% per indication. The net benefits were substantially higher for phase III trials, with the increase in eNPV varying from $27 million to $40 million, with ROIs that were four to six times the investment. The use of digital endpoints in clinical trials can provide substantial extra value to sponsors developing new drugs, with high ROIs.

Contribution of Clinical Trial Event Data by Data Source

Pragmatic randomized clinical trials (RCTs) often use multiple data sources to examine clinical events, but the relative contribution of data sources to clinical end-point rates is understudied. To assess the contribution of data sources (electronic health records [EHRs], public/private insurance claims, and/or participant-reported data) to clinical end points among ADAPTABLE participants who had available data. The ADAPTABLE study was an open-label, pragmatic RCT from April 2016 through June 2019 conducted in research networks within clinical practice. Participants had existing atherosclerotic cardiovascular disease and available data to analyze. The characteristics of patients by combinations of data source availability were compared to examine the contribution of each of the data sources to end-point ascertainment. Data for this prespecified analysis were examined from January 2022 to June 2023. Randomized exposure to 81 mg or 325 mg of aspirin daily. Number of events for the primary end point (composite of death, hospitalization for myocardial infarction, and hospitalization for stroke) that were contributed by EHR or claims data and then number of events contributed by each additional data source. Of 15 006 participants randomized with at least 1 other source of data available beyond participant-reported data, there were 8756 (58.3%) with participant-reported and EHR data; 4291 (28.6%) with participant-reported, EHR, and claims data; 1412 (9.4%) with EHR-only data; 262 (1.7%) with participant-reported and claims data; 202 (1.3%) with EHR and claims data; and 83 (0.6%) with claims-only data. Participants with EHR-only data were younger (median age, 63.7 years; IQR, 55.8-71.4) compared with the other groups (range, 65.6-71.9 years). Among participants with both EHR and claims data, with or without participant-reported data (n = 4493), for each outcome, most events (92%-100%) were identified in the EHR or in claims data. For all clinical end points, participant-reported data contributed less than 10% of events not otherwise available from claims or EHR data. In this analysis of a pragmatic RCT, claims and EHR data provided the most clinical end-point data when compared with participant-reported events. These findings provide a framework for collecting end points in pragmatic clinical trials. Further work is needed to understand the data source combinations that most effectively provide clinical end-point data in RCTs.

The Progression of Stargardt Disease as Determined by Spectral-Domain Optical Coherence Tomography over a 24-Month Period (ProgStar Report No. 18).

The aim of this study was to evaluate the progression of atrophy as determined by spectral-domain optical coherence tomography (SD-OCT) in patients with molecularly confirmed ABCA4-associated Stargardt disease type 1 (STGD1) over a 24-month period in a multicenter prospective cohort study. SD-OCT images from 428 eyes of 236 patients were analyzed. Change of mean thickness (MT) and intact area were estimated after semiautomated segmentation for the following individual layers in the central subfield (CS), inner ring (IR), and outer ring (OR) of the ETDRS grid: retinal pigment epithelium (RPE), outer segments (OSs), inner segments (IS), outer nuclear layer (ONL) inner retina (IR), and total retina. Statistically significant decreases of all outer retinal layers (RPE, OS, IS, and ONL) could be observed over a 24-month period both in decline of mean retinal thickness and intact area (p &lt; 0.0001, respectively), whereas the IR showed an increase of retinal thickness in the CS and IR and remained unchanged in the OR. Significant loss could be detected in outer retinal layers by SD-OCT over a 24-month period in patients with STGD1. Loss of thickness and/or intact area of such layers may serve as potential endpoints for clinical trials that aim to slow down the disease progression of STGD1.