ArticleBMC medical research methodology2025
Poor reporting quality and high proportion of missing data in economic evaluations alongside pragmatic trials: a cross-sectional survey.
Article in BMC medical research methodology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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, 1 synthesis or guideline pooled it.
- Pooled it
- A Machine Learning and Large Language Model Tool for Systematic Literature Reviews of Health Economic Evidence: A Validation Study.PharmacoEconomics · 2026Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundLack of data integrity is a common problem in randomized clinical trials and is more serious in economic evaluations conducted alongside explanatory clinical trials. Despite pragmatic randomized controlled trials (pRCTs) becoming recognized as the best design for economic evaluations, information on the proportion, handling approaches, and reporting quality of missing data in pRCTs-based economic evaluations remains limited. This study aimed to investigate the quantity and reporting quality of missing data in economic evaluations conducted alongside pragmatic clinical trials.
methodsIn this cross-sectional survey, data were extracted from PubMed and OVID (Embase, CENTRAL, HTA database, and NHS EED) from January 1, 2010, to April 24, 2022. Economic evaluations conducted alongside pRCTs were included. Two independent reviewer groups identified relevant articles, and data were extracted by three groups comprising two reviewers each. Descriptive analyses were performed to assess the characteristics of the included studies, missingness in the included studies, and handling of missing data.
resultsOverall, 715 studies were identified, of which 152 met the inclusion criteria. In total, 113, 119, and 132 articles reported missing data, costs, and effects, respectively. More than 50% (58/113) of the articles reported the proportion or quantity of overall missingness, and 64.71% and 54.55% reported missing costs and effects, respectively. The proportion of missingness of < 5% in the overall group was 3.45%, whereas the proportions of missing costs and effects were both < 10% (5.26% vs. 8.45%, respectively). In terms of the proportion of missing data, the overall missingness rate was 30.22% in 58 studies, whereas the median proportion of missing data was slightly higher than that of missing effects (30.92% vs. 27.78%). Of the included studies, 56 (36.84%) conducted a sensitivity analysis on handling missing data. Of these, 12.50% reported missing mechanisms, and 83.93% examined handling methods.
conclusionsInsufficient description and reporting of missing data, along with a high proportion of missing data in pRCT-based economic evaluations, could decrease the reliability and extrapolation of conclusions, leading to misleading decision-making.
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What OpenQuestion 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 OpenQuestion graph.