ArticleJournal of oncology practice2012
Effort required in eligibility screening for clinical trials.
Article in Journal of oncology practice, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 2 of them syntheses 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
60 citing papers in PubMed, 2 syntheses or guidelines pooled it, 92 citations in OpenAlex.
- Identifying and Addressing Barriers to Live Primary Prostate Cancer Cell Research in Veterans.Cancer research communications · 2026Pooled it
- A systematic review on natural language processing systems for eligibility prescreening in clinical research.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- Automating the Management of Extraspinal Findings in Magnetic Resonance Imaging Spine Studies Using a Privacy-Preserving Large Language Model: Retrospective Validation Study.Journal of medical Internet research · 2026Article
- TrialTriage, a Semiautonomous Prescreening Workflow for Resolving Ambiguity in Phase I Oncology Trial Eligibility: Development and Proof-of-Concept Study Using Synthetic Cases.JMIR formative research · 2026Article
- Evaluation of Large Language Models for Structured Data Extraction From Interstitial Lung Disease Clinical Notes: Comparative Study.Journal of medical Internet research · 2026Article
- Leveraging structured EMR data for efficient patient prescreening: a practical approach to reducing screen-failure rates in Light Touch Trial.Eye (London, England) · 2026Article
- TrialMatchAI: an end-to-end AI-powered clinical trial recommendation system to streamline patient-to-trial matching.Nature communications · 2026Article
- The potential of artificial intelligence in clinical trials.European journal of clinical investigation · 2026Review
- Matching Patients With Cell Surface-Targeted Clinical Trials Using Large Language Models.JCO precision oncology · 2026Article
- The Utility of Speech and Language Analytics for Screening Alzheimer's Disease.Neuro-degenerative diseases · 2026Review
- BASECAMP-1 screening study: a model for efficient enrolment in precision oncology clinical trials.BMJ oncology · 2026Article
- Screening failure in systemic sclerosis randomized trials: reporting, rates, causes and trends over time.Rheumatology advances in practice · 2026Article
- Computational Framework for Structuring and Analyzing Clinical Trial Criteria for AI-Guided Fine-grained Matching.Journal of medical systems · 2025Article
- Real-world validation of a multimodal LLM-powered pipeline for high-accuracy clinical trial patient matching.Communications medicine · 2025Article
- Large language models in clinical trials: applications, technical advances, and future directions.BMC medicine · 2025Review
- Representation is power: traditional, hybrid, and digital recruitment results from a non-randomized clinical trial engaging adolescents.NPJ digital medicine · 2025Article
- "The Truth Is, We Must Miss Some": A Qualitative Study of the Patient Eligibility Screening Process, and Automation Perspectives, for Cancer Clinical Trials.Cancer medicine · 2024Article
- Distilling large language models for matching patients to clinical trials.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Utilizing Large Language Models for Enhanced Clinical Trial Matching: A Study on Automation in Patient Screening.Cureus · 2024Article
- Evaluation of an artificial intelligence-based clinical trial matching system in Chinese patients with hepatocellular carcinoma: a retrospective study.BMC cancer · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeDetermining eligibility for a clinical trial (CT) typically requires a lengthy manual review of data for a single evaluation. The cost associated with eligibility screening is typically not compensated through contracts supporting CTs.
methodsWe used a real-time tracking system that captures CT evaluations and provides information on evaluation outcomes and time spent on each eligibility screening by research staff. Using these data, we describe the effort and costs of eligibility screening overall and per enrolled patient for cancer CTs. The study sample included all completed eligibility assessment (evaluation) records for the 18-month study period. We used generalized multinomial modeling to predict evaluation outcomes and then used the resulting parameter coefficients to estimate the effort associated with each participant, adjusted for probability of being enrolled. From these data, we calculated cost associated with eligibility screening.
resultsWe found substantial variation in attributed cost by study type and phase. The cost of eligibility screening ranged by study phase from $129.15 to $336.48 per enrolled patient. The estimated annual cost of screening was more than $90,000.
conclusionThis study provides results based on prospectively captured effort to estimate the largely nonreimbursed costs of eligibility screening and suggests that screening can be a significant financial burden to an institution. Centers performing CTs may need to acknowledge the differences in screening costs for different study types when negotiating contracts with funding organizations. Information such as that captured here could support such negotiations to reduce the gap between reimbursed and nonreimbursed costs.
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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.