Within-subject biological variation estimated using real-world data strategies (RWD): a systematic review

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Real-world data (RWD) strategies provide a comprehensive method for estimating within-subject biological variation, but require further algorithmic development to address limitations related to data standardization and statistical complexity. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

Fernándo Marqués-García; Ana Belén Nieto Librero; Xavier Tejedor-Ganduxé; Cristina Martinez-Bravo

doi:10.1080/10408363.2025.2464244

March 9, 2025Critical Reviews in Clinical Laboratory Sciences

Within-subject biological variation estimated using real-world data strategies (RWD): a systematic review

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Key Points

This research aims to systematically review methods for estimating biological variation (BV) using real-world data (RWD).
Conducted a systematic review of existing RWD methods for estimating BV.
Evaluated the capacity of these methods to overcome limitations found in other approaches.
Discussed the need for robust RWD algorithms to improve BV estimation accuracy.
Confirmed that RWD methods can calculate confidence intervals for BV estimates, a key advantage.
Identified limitations related to data anonymization and electronic medical record standardization.
Highlighted the need for further development of RWD algorithms to enhance estimation robustness.

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Implication

Systematic review demonstrates challenges and opportunities in estimating biological variation with real-world data.

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Marqués-García et al. (2025) studied this question.

synapsesocial.com/papers/6a20180135281a23f90dea0c https://doi.org/10.1080/10408363.2025.2464244

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Within-subject biological variation estimated using real-world data strategies (RWD): a systematic review

Key Points

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Discussion

Cite This Study

Within-subject biological variation estimated using real-world data strategies (RWD): a systematic review

Key Points

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Implication

Abstract

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