Findings on Atrial Fibrillation Reported by Investigators at Heidelberg University Hospital (A Prediction Model for Nonpersistence or Nonadherence To Direct Oral Anticoagulants In Hospitalized Patients With Atrial Fibrillation): Heart Disorders and Diseases – Atrial Fibrillation

2022 DEC 14 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Current study results on Heart Disorders and Diseases - Atrial Fibrillation have been published. According to news reporting from Heidelberg, Germany, by NewsRx journalists, research stated, “Medication adherence and persistence is fundamental for drug effectiveness, which is also true for the prevention of strokes in patients with atrial fibrillation (AF). Adherence to direct oral anticoagulants (DOACs) as first-line agents is often high in the early posthospital period.”

The news correspondents obtained a quote from the research from Heidelberg University Hospital, “However, adherence often sharply declines (or eventually leads to nonpersistence) in the post-discharge ambulatory period, rendering stroke prevention ineffective. If patients at high risk of nonpersistence or nonadher-ence could be identified early, they could be offered early intervention measures to improve adherence and/or persistence. To develop and internally validate a predictive model for medication nonadherence and nonpersistence to DOAC treatment in patients with AF after discharge using health insurance claims data. We selected health insurance claims data between 2011 and 2016 from 8,055 patients with AF who were newly treated with rivaroxaban or apixaban after a hospital admission for stroke, transient ischemic attack, or AF. In the post-discharge ambulatory period, medication adherence was derived as the proportion of days covered, calculated from drug dispensation data. A maximum permissible 90-day gap between the end of a prescription and the next dispensation was used to estimate persistence. Candidate predictors were either derived from the index hospital admission or summarized from the previous year (eg, comorbidities or medication adherence to long-term treatments, such as beta-blockers, renin-angiotensin system inhibitors, statins, and thyroid hormones). A regularized logistic regression model was fitted using the least absolute shrinkage and selection operator in a split-sample approach (66.7% training data; 33.3% test data) to predict a composite of medication nonadherence/nonpersistence. Discrimination performance was assessed using the area under the receiver operating characteristic curve, the maximum sensitivity/specificity, and the scaled Brier score. A calibration curve fitted by linear regression was used to evaluate model calibration. The average age of the study par-ticipants was 79.7 years, 62% were female, and 3,515 patients (44%) were adherent and persistent (median follow-up of 185 days). Medication adherence to previous long-term treatments showed strong predictive prop-erties. The developed model discriminated well (concordance statistic: 0.755), was well calibrated, and showed a scaled Brier score of 0.202 for identification of patients at risk. The model successfully predicted medication non-adherence/nonpersistence to DOAC treatment after discharge.”

According to the news reporters, the research concluded: “Such a model could help ensure that targeted interventions are already in place at the time of hospital discharge, potentially preventing strokes and reducing costs.”

This research has been peer-reviewed.

For more information on this research see: A Prediction Model for Nonpersistence or Nonadherence To Direct Oral Anticoagulants In Hospitalized Patients With Atrial Fibrillation. Journal of Managed Care & Specialty Pharmacy, 2022;28(10):1161-1172. Journal of Managed Care & Specialty Pharmacy can be contacted at: Acad Managed Care Pharmacy, 100 N Pitt St, 400, Alexandria, VA 22314-3134, USA.

Our news journalists report that additional information may be obtained by contacting Andreas Meid, Heidelberg University Hospital, Ctr Internal Med, Dept. of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg, Germany. Additional authors for this research include Lucas Wirbka, Carmen Ruff and Walter E. Haefeli.

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