ReviewTherapeutic innovation & regulatory science2025
Consideration for Assessing Data/Models/Tools Expiration Supporting Drug Development and Clinical Decision Making.
Review in Therapeutic innovation & regulatory science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- The anchoring effect and availability bias in healthcare decision-making.Frontiers in health services · 2026Article
- Improvements in Data Quality Can Boost Efficiency and Reduce Development Costs: A Pharmacometric CRO's Perspective.The AAPS journal · 2025Article
- Exploring pediatricians' off-label prescribing behavior in China: A theory of planned behavior-based study.International journal of clinical pharmacy · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Decision making of any kind is informed by data and often by models, tools or other solutions built from data. Data are evaluated for such purposes within a specific context of use (COU) but implicitly we often believe the data to be relevant, accurate and of high quality. In reality, this is not always the case. The status of data for various COUs must constantly be revisited for relevance and information value over time. Using drug development as an example, we postulate that there are indeed occasions where data value diminishes over time and consideration for data expiration with respect to its relevance for decision making should be entertained and at least identified with respect to a time-dependent change in status. Other situations exist which will also necessitate periodic review and condition reassessment. For example, considerations for patient privacy and consent along with compliance to regulatory standards must factor into future recommendations as well. Actions regarding data expiration are proposed as initial thoughts to be expanded upon but this assessment is primarily an attempt to explore factors which impact opinions about data information value for both drug development and clinical decision making.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.