Evidence map›Paper›PMID 41292642›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Comparative Mortality Risk of Aripiprazole, Olanzapine, Quetiapine and Risperidone in Alzheimer's Disease: A Real World Cohort Study with Treatment Effect Heterogeneity Analysis.

Chen Jiang, Josh Krivinko, Zeshui Yu, Robert A Sweet, Lang Zeng, Hui Wang, Ying Ding, Zheng Zeng, Julia Kofler, Lirong Wang

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Chen JiangDepartment of Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, PA, USA.ORCID 0000-0001-8336-6814
Josh KrivinkoDepartment of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Zeshui YuLumbrita LLC, Los Gatos, CA, USA.
Robert A SweetDepartment of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Lang ZengDepartment of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, USA.
Hui WangLumbrita LLC, Los Gatos, CA, USA.
Ying DingDepartment of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, USA.
Zheng ZengLumbrita LLC, Los Gatos, CA, USA.
Julia KoflerDivision of Neuropathology, Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Lirong WangDepartment of Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, PA, USA.ORCID 0000-0003-1797-9967

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3M
Research Education ComponentP30AG066468 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOWARD J AIZENSTEIN · 2020 to 2026
$29.4M
CLINICAL RESEARCH TRAINING IN LATE-LIFE MOOD DISORDERST32MH019986 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOWARD J AIZENSTEIN, Carmen Andreescu · 1997 to 2026
$6.9M
Synaptic Resilience to Psychosis in Alzheimer DiseaseR01MH116046 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Julia K Kofler, ROBERT A SWEET · 2018 to 2026
$6.6M
High-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574k
NCATS NIH HHS UL1 TR001857NIA NIH HHS P30 AG066468NIH HHS S10 OD028483NIMH NIH HHS R01 MH116046NIMH NIH HHS T32 MH019986
6 · The paper itself

Abstract

Background: Second-generation antipsychotics (SGAs) are frequently used off-label to manage behavioral symptoms in Alzheimer's disease (AD), despite ongoing concerns about their safety. Comparative evidence on mortality risk across specific SGAs remains limited. Objective: To compare all-cause mortality among AD patients treated with commonly prescribed SGAs and to explore treatment effect heterogeneity using causal machine learning. Methods: We conducted a retrospective cohort study using de-identified electronic health records from the Truveta platform (2018-2024). Patients with incident AD initiating treatment with aripiprazole, risperidone, quetiapine, or olanzapine were identified using an active-comparator, new-user design. Drug exposure was modeled as a time-varying covariate in Cox proportional hazards models, with propensity score matching applied to control for confounding. Causal tree and targeted maximum likelihood estimation (TMLE) were used to identify subgroups with heterogeneous treatment effects. Results: Among 17,004 AD patients, aripiprazole was associated with significantly lower mortality than olanzapine (HR = 0.667, 95% CI: 0.472-0.941) and quetiapine (HR = 0.677, 95% CI: 0.462-0.990). Quetiapine was also associated with lower mortality than olanzapine (HR = 0.833, 95% CI: 0.702-0.990) and risperidone (HR = 0.830, 95% CI: 0.705-0.978). Causal tree analysis revealed treatment effect heterogeneity by clinical characteristics, particularly among patients using type 2 diabetes (T2DM) medications. In subgroup analyses, aripiprazole remained protective in T2DM users (HR = 0.604 vs. quetiapine and risperidone, p = 0.002). Conclusions: Mortality risks vary substantially across SGAs in AD patients. Aripiprazole and quetiapine were associated with lower mortality compared to olanzapine and risperidone. Treatment effect heterogeneity suggests the need for individualized prescribing based on patient characteristics such as comorbid T2DM.

Identifiers

PMID41292642
PMCPMC12642724

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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.