Evidence map›Paper›PMID 41368590›Full record

Observational studyDrug design, development and therapy2025

Dose Optimization of Rivaroxaban in Elderly Chinese Patients with Non-Valvular Atrial Fibrillation: Analysis of Populations Pharmacokinetics and Exposure-Response Relationships.

Tian-Yu Li, Xin Liu, Lian Tang, Wei Cai, Jun Zhang, Ya Su, Chao Yu, Bi-Jue Liu, Lin-Feng Jiang, Chun Liu and 1 more

Abstract readObservational Study
In one paragraph

Observational study in Drug design, development and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Tian-Yu LiDepartment of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, People's Republic of China.ORCID 0000-0001-5208-6481
Xin LiuDepartment of Clinical Pharmacy, School of Pharmaceutical Science, Fudan University, Shanghai, People's Republic of China.ORCID 0009-0009-5595-3195
Lian TangDepartment of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, People's Republic of China.
Wei CaiDepartment of Cardiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, People's Republic of China.
Jun ZhangDepartment of Cardiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, People's Republic of China.
Ya SuDepartment of Pharmacy, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, People's Republic of China.
Chao YuDepartment of Pharmacy, Ruijin Hospital Wuxi Branch, Shanghai Jiao Tong University School of Medicine, Wuxi, People's Republic of China.
Bi-Jue LiuDepartment of Clinical Pharmacy, School of Pharmaceutical Science, Fudan University, Shanghai, People's Republic of China.
Lin-Feng JiangCollege of Pharmacy, Nanjing Medical University, Nanjing, People's Republic of China.
Chun LiuDepartment of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, People's Republic of China.ORCID 0000-0002-2479-0866
Yan-Xia YuDepartment of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to develop a population pharmacokinetic (PopPK) model in elderly Chinese patient with NVAF, characterize the pharmacokinetic variability, identify relevant covariates affecting rivaroxaban disposition, and explore the exposure-response relationship. Patients and Methods: A prospective observational study was conducted with rivaroxaban plasma samples collected and analyzed. A PopPK model was developed using the nonlinear mixed-effects modeling approach. Monte Carlo simulations were employed to explore the correlation between significant covariates and estimated drug exposure. AUC Results: Ninety-three elderly Chinese NVAF patients contributed 256 plasma concentrations were well described by a one-compartment PopPK model. Creatinine clearance (CrCL) and concomitant use of amiodarone were identified as significantly influencing clearance (CL). The simulation results revealed the following: (1) For patients with normal or mildly impaired renal function (CrCL ≥50 mL/min), both a 20 mg once-daily dosage without amiodarone and a 10 mg with amiodarone were acceptable; (2) For those with moderate to severe renal impairment (CrCL 15-49 mL/min), a 10 mg once-daily dosage was appropriate regardless of amiodarone coadministration; (3) Although a 15 mg once-daily dosage was generally suitable from the pharmacokinetic standpoint, concomitant use of amiodarone significantly increased bleeding risk in patients (RR = 8.00, p = 0.039); (4) AUC Conclusion: For elderly Chinese NVAF patients, a reduced-dose rivaroxaban regimen, specifically 10 mg once daily with amiodarone, is recommended for all patients regardless of renal function, whereas 15 mg once daily is a more optimal option for those not taking amiodarone. Based on the risk-benefit assessment, maintaining AUC

Indexed as

Atrial FibrillationFactor Xa InhibitorsRivaroxabanAgedAged, 80 and overChinaDose-Response Relationship, DrugEast Asian PeopleFemaleHumansMaleMiddle AgedMonte Carlo MethodProspective StudiesFactor Xa InhibitorsRivaroxabanatrial fibrillationdrug–drug interactionselderly Chinese patientsexposure-response analysispopulation pharmacokineticrivaroxaban

Identifiers

PMID41368590
PMCPMC12683255

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.