Evidence map›Paper›PMID 37554247›Full record

ReviewPerspectives in clinical research

Generating fit-for-purpose real-world evidence in Asia: How far are we from closing the gaps?

Wen-Yi Shau, Sajita Setia, Salil Shinde, Handoko Santoso, Daniel Furtner

Abstract readReview
In one paragraph

Review in Perspectives in clinical research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

5 authors.

Wen-Yi ShauMedical Affairs, Emerging Asia, Pfizer Corporation Hong Kong Limited, Quarry Bay, Hong Kong.
Sajita SetiaExecutive Office Transform Medical Communications Limited, Wanganui, New Zealand.
Salil ShindeMedical Affairs, Emerging Asia, Pfizer Corporation Hong Kong Limited, Quarry Bay, Hong Kong.
Handoko SantosoMedical Affairs, Emerging Asia, Pfizer Corporation Hong Kong Limited, Quarry Bay, Hong Kong.
Daniel FurtnerExecutive Office Transform Medical Communications Limited, Wanganui, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evidence generated by randomized controlled trials (RCTs) does not often represent the patient journey and clinical outcomes in the real world due to limited external validity or generalizability. Studies based on real-world data are intended to generalize results to the broader population; however, if the influence of external factors or confounders is not effectively managed, the cause-and-effect relationship and internal validity may be challenged, resulting in flawed results. The collection of quality real-world evidence (RWE) is crucial in Asia as there is often an underrepresentation of Asian populations in RCTs. In addition, few countries in Asia are catching up with the Western world in issuing practical foundational principles and guidance for conducting and adopting evidence for regulatory and reimbursement decisions. However, privacy and data protection laws are generally lagging behind technological developments in electronic medical records. While leveraging RWE in clinical and regulatory decision-making holds excellent potential, collective efforts across industry, governments, and research institutions are required for generating standardized practices and building capabilities for developing fit-for-purpose RWE in Asia.

Indexed as

Asiadecision-makinghealth technology assessmentrandomized controlled trialsreal-world datareal-world evidence

Identifiers

PMID37554247
PMCPMC10405531

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.