Evidence map›Paper›PMID 33837463›Full record

ReviewWiener klinische Wochenschrift2021

Real-world evidence and product development: Opportunities, challenges and risk mitigation.

Poobalan Naidoo, Célia Bouharati, Virendra Rambiritch, Nadina Jose, Sumanth Karamchand, Robert Chilton, Rory Leisegang

Abstract readReview
In one paragraph

Review in Wiener klinische Wochenschrift, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
–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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Real-world data: a comprehensive literature review on the barriers, challenges, and opportunities associated with their inclusion in the health technology assessment process.Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2024
    Pooled it
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  12. Observational
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  15. Collaborative privacy-preserving analysis of oncological data using multiparty homomorphic encryption.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
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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

7 authors.

Poobalan NaidooDepartment of Nephrology, Inkosi Albert Luthuli Central Hospital, Durban, South Africa.
Célia BouharatiClinical Operations and Medical Affairs, Sanofi, Midrand, South Africa. celia.bouharati@gmail.com.ORCID http://orcid.org/0000-0002-2833-2731
Virendra RambiritchDiscipline of Pharmaceutical Sciences, University of KwaZulu-Natal, Durban, South Africa.
Nadina JoseDepartment of Health Informatics, Rutgers School of Health Professions, The State University of New Jersey, Newark, New Jersey, United States.
Sumanth KaramchandDepartment of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Robert ChiltonFaculty of Medicine, Division of Cardiology and Interventional Cardiology, University of Texas Health Science Centre at San Antonio, San Antonio, Texas, United States.
Rory LeisegangFaculty of Pharmacy, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-world evidence (RWE) is derived from real-world data (RWD) sources including electronic health records, claims data, registries (disease, product) and pragmatic clinical trials. The importance of RWE derived from RWD has been once again demonstrated during the coronavirus disease 2019 (COVID-19) pandemic, as it can improve patient care by complementing information obtained from traditional clinical trial programs. Additionally, RWE can generate insights into disease mechanisms, epidemiology, patient flows in and out of healthcare systems, and drivers and barriers to optimal clinical care in real-world settings. Identifying unmet medical needs is crucial as it often can inform which investigational new drugs enter clinical trial testing, and RWE studies from hospital settings have contributed substantial progress here. RWE can also optimize the design of clinical studies, inform benefit risk assessments and use networks of pragmatic studies to help with clinical trial feasibilities and eventual trial initiation. The challenges of RWD include data quality, reproducibility and accuracy which may affect validity. RWD and RWE must be fit for purpose and one must be cognizant of inherent biases.

Indexed as

COVID-19Delivery of Health CareElectronic Health RecordsHumansReproducibility of ResultsSARS-CoV-2Cost ReductionProduct lifecycleReal-world dataRoutine clinical practiceSystematic error

Identifiers

PMID33837463
PMCPMC8034870

What OpenQuestion holds

Textmetadata
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.