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Trajectories of Adherence to Biologic Disease-Modifying Anti-Rheumatic Drugs in Tuscan Administrative Databases: The Pathfinder Study.

ABSTRACT: Scanty information on clustering longitudinal real-world data is available in the medical literature about the adherence implementation phase in rheumatoid arthritis (RA). To identify and characterize trajectories by analyzing the implementation phase of adherence to biologic Disease-Modifying Anti-Rheumatic Drugs (DMARDs), we conducted a retrospective cohort drug-utilization study using Tuscan administrative databases. RA patients were identified by a validated algorithm, including the first biologic DMARD supply from 2010 to 2015, RA specialist visit in the year before or after the first supply date and RA diagnosis in the five years before or in the year after the first supply date. We observed users for three years or until death, neoplasia, or pregnancy. We evaluated adherence quarterly through the Medication Possession Ratio. Firstly, we identified adherence trajectories and described the baseline characteristics; then, we focused on the trajectory most populated to distinguish the related sub-trajectories. We identified 952 first ever-biologic DMARD users in RA (712 females, mean age 52.7 years old, standard deviation 18.8). The biologic DMARD mostly supplied was etanercept (387 users) followed by adalimumab (233). Among 935 users with at least 3 adherence values, we identified 49 fully-adherent users, 829 continuous users, and 57 early-discontinuing users. Significant differences were observed among the index drugs. After focusing on the continuous users, three sub-trajectories were identified: continuous-steady users (556), continuous-alternate users (207), and continuous-declining users (66). No relevant differences emerged at the baseline. The majority of first ever-biologic DMARD users showed a continuous adherence behavior in RA. The role of adherence potential predictors and the association with effectiveness and safety outcomes should be explored by further studies.

SUBMITTER: Convertino I

PROVIDER: S-EPMC8708974 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Validation of algorithms for selecting patients from healthcare administrative databases (HAD) is recommended. This PATHFINDER study section is aimed at testing algorithms to select rheumatoid arthritis (RA) patients from Tuscan HAD (THAD) and assessing RA diagnosis time interval between the medical chart date and that of THAD. A population was extracted from THAD. The information of the medical charts at the Rheumatology Unit of Pisa University Hospital represented the reference. We included first ever users of biologic disease modifying anti-rheumatic drugs (bDMARDs) between 2014 and 2016 (index date) with at least a specialist visit at the Rheumatology Unit of the Pisa University Hospital recorded from 2013 to the index date. Out of these, we tested four index tests (algorithms): (1) RA according to hospital discharge records or emergency department admissions (ICD-9 code, 714*); (2) RA according to exemption code from co-payment (006); (3) RA according to hospital discharge records or emergency department admissions AND RA according to exemption code from co-payment; (4) RA according to hospital discharge records or emergency department admissions OR RA according to exemption code from co-payment. We estimated sensitivity, specificity, positive and negative predicted values (PPV and NPV) with 95% confidence interval (95% CI) and the RA diagnosis median time interval (interquartile range, IQR). Two sensitivity analyses were performed. Among 277 reference patients, 103 had RA. The fourth algorithm identified 96 true RA patients, PPV 0.78 (95% CI 0.70-0.85), sensitivity 0.93 (95% CI 0.86-0.97), specificity 0.84 (95% CI 0.78-0.90), and NPV 0.95 (95% CI 0.91-0.98). The sensitivity analyses confirmed performance. The time measured between the actual RA diagnosis date recorded in medical charts and that assumed in THAD was 2.2 years (IQR 0.5-8.4). In conclusion, this validation showed the fourth algorithm as the best. The time interval elapsed between the actual RA diagnosis date in medical charts and that extrapolated from THAD has to be considered in the design of future studies.

Dataset Information

Trajectories of Adherence to Biologic Disease-Modifying Anti-Rheumatic Drugs in Tuscan Administrative Databases: The Pathfinder Study.

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