Evidence map›Paper›PMID 41656514›Full record

ArticleAmerican journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists2026

Evaluating treatment effectiveness: Complementing RCTs with real-world data.

Christina G Rivera, Essy Mozaffari, Stephanie H Read, Andre C Kalil

Abstract read
In one paragraph

Article in American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists, 2026. 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

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

4 authors.

Christina G RiveraDepartment of Pharmacy, Mayo Clinic, Rochester, MN, USA.
Essy MozaffariMedical Affairs, Gilead Sciences, Foster City, CA, USA.
Stephanie H ReadEvidence and Access, Certara, London, UK.
Andre C KalilDivision of Infectious Diseases, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWhile randomized controlled trials remain the gold standard for assessing treatment efficacy, studies using real-world data (RWD) offer valuable insights into treatment effectiveness across broader, more diverse patient populations. This commentary explores the importance of using fit-for-purpose data and emphasizes the need for rigorous evaluation of RWD quality to support valid and actionable evidence generation. SUMMARY: The utility of RWD-based studies depends heavily on the fitness-for-purpose of the data source, which requires careful assessment of 5 key quality dimensions: relevance, extensiveness, timeliness, coherence, and reliability. Practical examples from coronavirus disease 2019 (COVID-19) comparative effectiveness research are used to illustrate each data quality domain.

conclusionsAs the need for RWD increases, especially for post-COVID-19 pandemic decision-making, ensuring high data quality and appropriate study design is critical. Proper evaluation of RWD sources enhances the credibility of findings and supports their use in meta-analyses, clinical guidelines, and healthcare policy.

Indexed as

Comparative Effectiveness ResearchRandomized Controlled Trials as TopicResearch DesignCOVID-19Data AccuracyHumansPandemicsReproducibility of ResultsSARS-CoV-2Treatment Outcomecomparative effectiveness researchfeasibilityfitness-for-purposereal-world data

Identifiers

PMID41656514
PMCPMC13070689

What OpenQuestion holds

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LicenceCC BY
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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.