Dataset Information

Understanding patient preferences in anti-VEGF treatment options for age-related macular degeneration.

ABSTRACT:

Purpose

(1) To investigate the relative importance of convenience (consultation frequency and injection frequency) against treatment outcomes (visual and anatomical outcomes) and out-of-pocket medical costs via a discrete choice experiment (DCE), and (2) to investigate how patient characteristics affect patient treatment preferences.

Methods

Eligibility criteria were: (1) receiving a neovascular age-related macular degeneration (nAMD) diagnosis; (2) receiving anti-VEGF treatment; (3) being ≥21 years old, and (4) being able to speak and understand English/Mandarin. Patients were presented with eight choice tasks and asked to choose between their current treatment and two hypothetical treatments that varied by six attributes: number of clinic visits in a year, number of injections in a year, vision quality, control of swelling in retina, drug labelling and out-of-pocket cost.

Results

This analysis involved 180 patients. Based on latent class logistic regressions, vision quality was the most important attribute (34%) followed by cost (24%). The frequency of total clinic visits (15%) was the third most-important attribute, closely followed by labelling (12%) and control of retina swelling (11%). Injection frequency was the least important attribute (4%).

Conclusions

Vision quality was the most important attribute followed by the out-of-pocket costs. Given the same outcomes, patients preferred treatment regimens which require fewer total clinic visits. In comparison, injection frequency alone did not influence patient preferences. With increasing treatment options for nAMD, understanding patients' preferences can help clinicians in selecting agents and treatment regimen most preferred for each patient, which may lead to improved long-term adherence and outcomes.

SUBMITTER: Ozdemir S

PROVIDER: S-EPMC9371344 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Understanding patient preferences in anti-VEGF treatment options for age-related macular degeneration.

Ozdemir Semra S Finkelstein Eric E Lee Jia Jia JJ Too Issac Horng Khit IHK Teo Kelvin Yi Chong KYC Tan Anna Chen Sim ACS Wong Tien Yin TY Cheung Gemmy Chui Ming GCM

PloS one 20220811 8

<h4>Purpose</h4>(1) To investigate the relative importance of convenience (consultation frequency and injection frequency) against treatment outcomes (visual and anatomical outcomes) and out-of-pocket medical costs via a discrete choice experiment (DCE), and (2) to investigate how patient characteristics affect patient treatment preferences.<h4>Methods</h4>Eligibility criteria were: (1) receiving a neovascular age-related macular degeneration (nAMD) diagnosis; (2) receiving anti-VEGF treatment; ...[more]

PMID: 35951503

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Project description:PurposeTo probabilistically forecast needed anti-vascular endothelial growth factor (anti-VEGF) treatment frequency using volumetric spectral domain-optical coherence tomography (SD-OCT) biomarkers in neovascular age-related macular degeneration from real-world settings.MethodsSD-OCT volume scans were segmented with a custom deep-learning-based analysis pipeline. Retinal thickness and reflectivity values were extracted for the central and the four inner Early Treatment Diabetic Retinopathy Study (ETDRS) subfields for six retinal layers (inner retina, outer nuclear layer, inner segments [IS], outer segments [OS], retinal pigment epithelium-drusen complex [RPEDC] and the choroid). Machine-learning models were probed to predict the anti-VEGF treatment frequency within the next 12 months. Probabilistic forecasting was performed using natural gradient boosting (NGBoost), which outputs a full probability distribution. The mean absolute error (MAE) between the predicted versus actual anti-VEGF treatment frequency was the primary outcome measure.ResultsIn a total of 138 visits of 99 eyes with neovascular AMD (96 patients) from two clinical centers, the prediction of future anti-VEGF treatment frequency was observed with an accuracy (MAE [95% confidence interval]) of 2.60 injections/year [2.25-2.96] (R2 = 0.390) using random forest regression and 2.66 injections/year [2.31-3.01] (R2 = 0.094) using NGBoost, respectively. Prediction intervals were well calibrated and reflected the true uncertainty of NGBoost-based predictions. Standard deviation of RPEDC-thickness in the central ETDRS-subfield constituted an important predictor across models.ConclusionsThe proposed, fully automated pipeline enables probabilistic forecasting of future anti-VEGF treatment frequency in real-world settings.Translational relevancePrediction of a probability distribution allows the physician to inspect the underlying uncertainty. Predictive uncertainty estimates are essential to highlight cases where human-inspection and/or reversion to a fallback alternative is warranted.

Project description:IntroductionTo identify patient preference drivers related to the management of wet age-related macular degeneration (wet AMD).MethodsIn this cross-sectional study, a self-explicated 'conjoint analysis' survey was administered online to eligible patients with wet AMD (receiving anti-vascular endothelial growth factor [VEGF] treatment for at least 12 months) from the USA, Canada, UK, France, Spain, Germany, Italy, Japan, Taiwan, and Australia. The survey consisted of six domains with 21 attributes, which were selected on the basis of a literature review, social media listening, and tele-interviews/discussions with patients, clinical experts, and patient groups. Utility and relative importance scores were generated for each attribute and utility difference significance testing was performed using 'unequal variances t tests'. The Patient Activation Measure (PAM-13) questionnaire was administered to assess patients' knowledge, skill, and confidence in self-management.ResultsA total of 466 patients (mean age, 68 years; women, 54%; binocular wet AMD, 28%) with an average anti-VEGF treatment duration of 3.9 years completed the survey. The most important preference domains were 'treatment effects on vision' (non-significant) and 'vision-related symptom burdens' (p < 0.001), followed by 'treatment risk' (p < 0.05), 'impact on daily activities' (p < 0.05), 'burden of clinic/hospital visits' (p < 0.001), and 'impact on psychological well-being'. The five most important attributes in order of importance were clarity of vision, treatment effect on symptoms, quality of vision, time to treatment effect, and time to re-administration. The two most important attributes globally were also in the top three attributes across countries. The majority of participants in the study were level 3 or level 4 of the PAM-13 questionnaire.ConclusionsThis study identified the most important disease and treatment attributes to patients using patient-centred methods. The data showed the degree of harmonization of preferences across geographies and that participants actively adopt behaviours required for improved treatment outcomes. The identified preference drivers may inform future clinical development.

Dataset Information

Understanding patient preferences in anti-VEGF treatment options for age-related macular degeneration.

Purpose

Methods

Results

Conclusions

Publications

Understanding patient preferences in anti-VEGF treatment options for age-related macular degeneration.

Similar Datasets

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