Development and electronic health record validation of an algorithm for identifying patients with Duchenne muscular dystrophy in US administrative claims.

BACKGROUND: Muscular dystrophies (MDs) comprise a heterogenous group of genetically inherited conditions characterized by progressive muscle weakness and increasing disability. The lack of separate diagnosis codes for Duchenne MD (DMD) and Becker MD, 2 of the most common forms of MD, has limited the conduct of DMD-specific real-world studies. OBJECTIVE: To develop and validate administrative claims-based algorithms for identifying patients with DMD and capturing their nonambulatory and ventilation-dependent status. METHODS: This was a retrospective cohort study using the statistically deidentified Optum Market Clarity Database (including patient claims linked with electronic health records [EHRs] data) to develop and validate the following algorithms: DMD diagnosis, nonambulatory status, and ventilation-dependent status. The initial study sample consisted of US patients in the database who had a diagnosis code for Duchenne/Becker MD (DBMD) between October 1, 2018, and September 30, 2020, who were male, aged 40 years or younger on their first DBMD diagnosis, and met continuous enrollment and 1-day minimal clinical activities requirement in a 12-month measurement period between October 1, 2017, and September 30, 2020. The algorithms, developed by a cross-functional team of DMD specialists (including patient advocates), were based on administrative claims data with International Classification of Diseases, Tenth Revision, Clinical Modifications coding, using information of diagnosis codes for DBMD, sex, age, treatment, and disease severity (eg, evidence of ambulation assistance/support and/or evidence of ventilation support or dependence). Patients who met each algorithm and had EHR notes available were then validated against structured fields and unstructured provider notes from their own linked EHR to confirm patients' DMD diagnoses, nonambulatory status, and ventilation-dependent status. Algorithm performance was assessed by positive predictive value with 95% CIs. RESULTS: A total of 1,300 patients were included in the initial study sample. Of these, EHR were available and reviewed for 303 patients. The mean age of the 303 patients was 14.8 years, with 61.7% being non-Hispanic White. A majority had a Charlson comorbidity index score of 0 (59.4%) or 1-2 (27.7%). Positive predictive value (95% CI) was 91.6% (85.8%-95.6%) for the DMD diagnosis algorithm, 88.4% (80.2%-94.1%) for the nonambulatory status algorithm, and 77.8% (62.9%-88.8%) for the ventilation-dependent status algorithm. CONCLUSIONS: This work provides the means to more accurately identify patients with DMD from administrative claims data without a specific diagnosis code. The algorithms validated in this study can be applied to assess treatment effectiveness and other outcomes among patients with DMD treated in clinical practice. DISCLOSURES: This study was funded by Pfizer, which contracted with Optum to perform the study and provide medical writing assistance. Ms Schrader reports being an employee of Parent Project Muscular Dystrophy. Mr Posner reports being an employee and stockholder of Pfizer and receiving support from Pfizer for attending conferences not related to this manuscript. Dr Dorling reports being an employee and stockholder of Pfizer at the time the study was conducted and is a current employee of Chiesi USA, Inc. Ms Senerchia reports being an employee of Optum and owning stock in Pfizer and UnitedHealth Group, the parent company of Optum. Dr Chen reports being an employee and stockholder of Pfizer. Ms Beaverson reports being an employee of Pfizer and owning stock in Pfizer and Amicus Therapeutics. Dr Seare reports being an employee of Optum at the time the study was conducted. Dr Garnier and Ms Merla report being employees of Pfizer. Ms Walker reports being an employee of Optum. Dr Alvir reports being an employee and stockholder of Pfizer. Dr Mahn reports being an employee and stockholder of Pfizer. Dr Zhang reports being an employee of Optum. Ms Landis reports being an employee of Optum. Ms Buikema reports being an employee of Optum and holding stock in UnitedHealth Group, the parent company of Optum.

Binding and neutralizing anti-AAV antibodies: Detection and implications for rAAV-mediated gene therapy.

Assessment of anti-adeno-associated virus (AAV) antibodies in patients prior to systemic gene therapy administration is an important consideration regarding efficacy and safety of the therapy. Approximately 30%-60% of individuals have pre-existing anti-AAV antibodies. Seroprevalence is impacted by multiple factors, including geography, age, capsid serotype, and assay type. Anti-AAV antibody assays typically measure (1) transduction inhibition by detecting the neutralizing capacity of antibodies and non-antibody neutralizing factors, or (2) total anti-capsid binding antibodies, regardless of neutralizing activity. Presently, there is a paucity of head-to-head data and standardized approaches associating assay results with clinical outcomes. In addition, establishing clinically relevant screening titer cutoffs is complex. Thus, meaningful comparisons across assays are nearly impossible. Although complex, establishing screening assays in routine clinical practice to identify patients with antibody levels that may impact favorable treatment outcomes is achievable for both transduction inhibition and total antibody assays. Formal regulatory approval of such assays as companion diagnostic tests will confirm their suitability for specific recombinant AAV gene therapies. This review covers current approaches to measure anti-AAV antibodies in patient plasma or serum, their potential impact on therapeutic safety and efficacy, and investigative strategies to mitigate the effects of pre-existing anti-AAV antibodies in patients.

Mortality and vascular morbidity in older adults with asymptomatic versus symptomatic peripheral artery disease.

BACKGROUND: Our aim was to assess the mortality and vascular morbidity risk of elderly individuals with asymptomatic versus symptomatic peripheral artery disease (PAD) in the primary care setting. METHODS AND RESULTS: This prospective cohort study included 6880 representative unselected patients >or=65 years of age with monitored follow-up over 5 years. According to physician diagnosis, 5392 patients had no PAD, 836 had asymptomatic PAD (ankle brachial index <0.9 without symptoms), and 593 had symptomatic PAD (lower-extremity peripheral revascularization, amputation as a result of PAD, or intermittent claudication symptoms regardless of ankle brachial index). The risk of symptomatic compared with asymptomatic PAD patients was significantly increased for the composite of all-cause death or severe vascular event (myocardial infarction, coronary revascularization, stroke, carotid revascularization, or lower-extremity peripheral vascular events; hazard ratio, 1.48; 95% confidence interval, 1.21 to 1.80) but not for all-cause death alone (hazard ratio, 1.13; 95% confidence interval, 0.89 to 1.43), all-cause death/myocardial infarction/stroke (excluding lower-extremity peripheral vascular events and any revascularizations; hazard ratio, 1.18; 95% confidence interval, 0.92 to 1.52), cardiovascular events alone (hazard ratio, 1.20; 95% confidence interval, 0.89 to 1.60), or cerebrovascular events alone (hazard ratio, 1.33; 95% confidence interval, 0.80 to 2.20). Lower ankle brachial index categories were associated with increased risk. PAD was a strong factor for the prediction of the composite end point in an adjusted model. CONCLUSIONS: Asymptomatic PAD diagnosed through routine screening in the offices of primary care physicians carries a high mortality and/or vascular event risk. Notably, the risk of mortality was similar in symptomatic and asymptomatic patients with PAD and was significantly higher than in those without PAD. In the primary care setting, the diagnosis of PAD has important prognostic value.

Reproducibility and reliability of the ankle-brachial index as assessed by vascular experts, family physicians and nurses.

The reliability of ankle-brachial index (ABI) measurements performed by different observer groups in primary care has not yet been determined. The aims of the study were to provide precise estimates for all effects influencing the variability of the ABI (patients' individual variability, intra- and inter-observer variability), with particular focus on the performance of different observer groups. Using a partially balanced incomplete block design, 144 unselected individuals aged > or = 65 years underwent double ABI measurements by one vascular surgeon or vascular physician, one family physician and one nurse with training in Doppler sonography. Three groups comprising a total of 108 individuals were analyzed (only two with ABI < 0.90). Errors for two repeated measurements for all three observer groups did not differ (experts 8.5%, family physicians 7.7%, and nurses 7.5%, p = 0.39). There was no relevant bias among observer groups. Intra-observer variability expressed as standard deviation divided by the mean was 8%, and inter-observer variability was 9%. In conclusion, reproducibility of the ABI measurement was good in this cohort of elderly patients who almost all had values in the normal range. The mean error of 8-9% within or between observers is smaller than with established screening measures. Since there were no differences among observers with different training backgrounds, our study confirms the appropriateness of ABI assessment for screening peripheral arterial disease (PAD) and generalized atherosclerosis in the primary case setting. Given the importance of the early detection and management of PAD, this diagnostic tool should be used routinely as a standard for PAD screening. Additional studies will be required to confirm our observations in patients with PAD of various severities.

Profound influence of different methods for determination of the ankle brachial index on the prevalence estimate of peripheral arterial disease.

BACKGROUND: The ankle brachial index (ABI) is an efficient tool for objectively documenting the presence of lower extremity peripheral arterial disease (PAD). However, different methods exist for ABI calculation, which might result in varying PAD prevalence estimates. To address this question, we compared five different methods of ABI calculation using Doppler ultrasound in 6,880 consecutive, unselected primary care patients > or = 65 years in the observational get ABI study. METHODS: In all calculations, the average systolic pressure of the right and left brachial artery was used as the denominator (however, in case of discrepancies of > or = 10 mmHg, the higher reading was used). As nominators, the following pressures were used: the highest arterial ankle pressure of each leg (method #1), the lowest pressure (#2),only the systolic pressure of the tibial posterior artery (#3), only the systolic pressure of the tibial anterior artery (#4),and the systolic pressure of the tibial posterior artery after exercise (#5). An ABI < 0.9 was regarded as evidence of PAD. RESULTS: The estimated prevalence of PAD was lowest using method #1 (18.0%) and highest using method #2 (34.5%),while the differences in methods #3-#5 were less pronounced. Method #1 resulted in the most accurate estimation of PAD prevalence in the general population. Using the different approaches, the odds ratio for the association of PAD and cardiovascular (CV) events varied between 1.7 and 2.2. CONCLUSION: The data demonstrate that different methods for ABI determination clearly affect the estimation of PAD prevalence, but not substantially the strength of the associations between PAD and CV events. Nonetheless, to achieve improved comparability among different studies, one mode of calculation should be universally applied, preferentially method #1.