Contextualizing single-arm trials with real-world data: An emulated target trial comparing therapies for neovascular age-related macular degeneration

Comparison of Methods of Clinical Trial Emulation Utilizing Data From the Comparison of AMD Treatment Trial (CATT) and the IRIS® Registry

Purpose

We used exact matching and inverse propensity score weighting (IPSW) using real-world data (RWD) from the American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight) to emulate the 2 pro re nata (prn) treatment arms from the Comparison of AMD Treatment Trial (CATT) and to compare the outcomes of the RWD arms to the 2 monthly treatment arms from the clinical trial.

Design

Retrospective cohort study utilizing deidentified electronic health record registry data and patient-level deidentified clinical trial data.

Subjects

All treatment-naive patient eyes with neovascular age-related macular degeneration treated with ranibizumab or bevacizumab only for 1 year from either the CATT or the IRIS Registry.

Methods

Patients were identified in the IRIS Registry between October 1, 2015 and December 31, 2019. After all nonimaging-based inclusion and exclusion criteria from the CATT were applied, patient eyes receiving bevacizumab or ranibizumab only on a prn basis were identified as the eligible cohort. Exact matching and ISPW was applied based on age, gender, and baseline visual acuity.

Main Outcome Measures

Mean change in visual acuity, in approximated ETDRS letters, between baseline and 1 year for the IRIS Registry prn treatment arms generated by exact matching and IPSW.

Results

We identified 427 eyes treated with ranibizumab prn and 771 eyes treated with bevacizumab prn. Using exact matching, 98% (n = 281) of CATT patient eyes in the bevacizumab monthly treatment arm and 87% (n = 261) of CATT patient eyes in the ranibizumab monthly treatment arm were matched to a patient eye in the IRIS Registry. For the ranibizumab prn treatment arm, patient eyes generated using exact matching gained 1.9 letters and those generated using IPSW gained 2.8 letters (exact matching: 1.9 letters ± 14.0 vs. IPSW: 2.8 letters ± 15.0 letters, P = 0.43). For the bevacizumab prn treatment arm, patient eyes generated using exact matching gained 2.4 letters and those generated using IPSW gained 2.1 letters (exact matching: 2.4 letters ± 15.4 vs. IPSW: 2.1 letters ± 16.0 letters, P = 0.79).

Conclusions

Both exact matching and IPSW produced similar results in emulating the prn treatment arms of the CATT using IRIS Registry data and patient-level clinical trial data. Similar to prior real-world studies, the clinical outcomes were significantly worse in the IRIS Registry treatment arms compared with the clinical trial.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Tube Versus Trabeculectomy IRIS Registry Study: 1-Year Secondary Treatment Outcomes

PURPOSE

To describe 1-year secondary outcomes in the Tube Versus Trabeculectomy IRIS® (Intelligent Registry In Sight) Registry Study (TVTIRIS), and to compare to the TVT randomized controlled trial (TVTRCT).

DESIGN

TVTIRIS was a retrospective cohort study.

METHODS

The 2013-2017 IRIS Registry was used to identify eyes that received a tube shunt (tube) or trabeculectomy after a previous trabeculectomy and/or cataract surgery and had 1 year of follow-up. The TVTRCT compared a Baerveldt 350-mm2 glaucoma implant to trabeculectomy in similar eyes.

RESULTS

In the TVTIRIS cohort, the tube (n = 236, 56.3%) and trabeculectomy (n = 183, 43.7%) groups had similar and significant reductions in intraocular pressure (IOP) from baseline to 1 year. In the tube group, IOP (mean ± SD) decreased from 26.6 ± 6.5 mm Hg at baseline to 14.3 ± 4.8 mm Hg at 1 year. In the trabeculectomy group, IOP decreased from 25.3 ± 6.4 mm Hg at baseline to 13.5 ± 5.2 mm Hg at 1 year. The trabeculectomy groups from both studies had similar 1-year IOP reduction (P = .18), although the TVTRCT cohort used fewer medications at all time points (P < .01). There were more pronounced differences in the mean IOP and medications between the tube groups in the 2 studies, presumably due to the inclusion of valved tubes in TVTIRIS. More reoperations occurred in TVTIRIS.

CONCLUSIONS

The TVTIRIS tube and trabeculectomy groups had comparable 1-year IOP reduction, although trabeculectomy eyes used fewer glaucoma medications. The trabeculectomy group in TVTIRIS and TVTRCT had similar IOP and medication reduction at 1 year. Randomized controlled trials and electronic health record data both provide invaluable insight into surgical outcomes.

Reporting of Observational Studies Explicitly Aiming to Emulate Randomized Trials: A Systematic Review

Importance

Observational (nonexperimental) studies that aim to emulate a randomized trial (ie, the target trial) are increasingly informing medical and policy decision-making, but it is unclear how these studies are reported in the literature. Consistent reporting is essential for quality appraisal, evidence synthesis, and translation of evidence to policy and practice.

Objective

To assess the reporting of observational studies that explicitly aimed to emulate a target trial.

Evidence Review

We searched Medline, Embase, PsycINFO, and Web of Science for observational studies published between March 2012 and October 2022 that explicitly aimed to emulate a target trial of a health or medical intervention. Two reviewers double-screened and -extracted data on study characteristics, key predefined components of the target trial protocol and its emulation (eligibility criteria, treatment strategies, treatment assignment, outcome[s], follow-up, causal contrast[s], and analysis plan), and other items related to the target trial emulation.

Findings

A total of 200 studies that explicitly aimed to emulate a target trial were included. These studies included 26 subfields of medicine, and 168 (84%) were published from January 2020 to October 2022. The aim to emulate a target trial was explicit in 70 study titles (35%). Forty-three studies (22%) reported use of a published reporting guideline (eg, Strengthening the Reporting of Observational Studies in Epidemiology). Eighty-five studies (43%) did not describe all key items of how the target trial was emulated and 113 (57%) did not describe the protocol of the target trial and its emulation.

Conclusion and Relevance

In this systematic review of 200 studies that explicitly aimed to emulate a target trial, reporting of how the target trial was emulated was inconsistent. A reporting guideline for studies explicitly aiming to emulate a target trial may improve the reporting of the target trial protocols and other aspects of these emulation attempts.

Artificial intelligence-based predictions in neovascular age-related macular degeneration

PURPOSE OF REVIEW

Predicting treatment response and optimizing treatment regimen in patients with neovascular age-related macular degeneration (nAMD) remains challenging. Artificial intelligence-based tools have the potential to increase confidence in clinical development of new therapeutics, facilitate individual prognostic predictions, and ultimately inform treatment decisions in clinical practice.

RECENT FINDINGS

To date, most advances in applying artificial intelligence to nAMD have focused on facilitating image analysis, particularly for automated segmentation, extraction, and quantification of imaging-based features from optical coherence tomography (OCT) images. No studies in our literature search evaluated whether artificial intelligence could predict the treatment regimen required for an optimal visual response for an individual patient. Challenges identified for developing artificial intelligence-based models for nAMD include the limited number of large datasets with high-quality OCT data, limiting the patient populations included in model development; lack of counterfactual data to inform how individual patients may have fared with an alternative treatment strategy; and absence of OCT data standards, impairing the development of models usable across devices.

SUMMARY

Artificial intelligence has the potential to enable powerful prognostic tools for a complex nAMD treatment landscape; however, additional work remains before these tools are applicable to informing treatment decisions for nAMD in clinical practice.