Conducting clinical trials—costs, impacts, and the value of clinical trials networks: A scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: A significant barrier to conducting clinical trials is their high cost, which is driven primarily by the time and resources required to activate trials and reach accrual targets. The high cost of running trials has a substantial impact on their long-term feasibility and the type of clinical research undertaken. METHODS: A scoping review of the empirical literature on the costs associated with conducting clinical trials was undertaken for the years 2001-2015. Five reference databases were consulted to elicit how trials costs are presented in the literature. A review instrument was developed to extract the content of in-scope papers. Findings were characterized by date and place of publication, clinical disease area, and network/cooperative group designation, when specified. Costs were captured and grouped by patient accrual and management, infrastructure, and the opportunity costs associated with industry funding for trials research. Cost impacts on translational research and health systems were also captured, as were recommendations to reduce trial expenditures. Since articles often cited multiple costs, multiple cost coding was used during data extraction to capture the range and frequency of costs. RESULTS: A total of 288 empirical articles were included. The distribution of reported costs was: patient management and accrual costs (132 articles), infrastructure costs (118 articles) and the opportunity costs of industry sponsorship (72 articles). 221 articles reported on the impact of undertaking costly trials on translational research and health systems; of these, the most frequently reported consequences were to research integrity (52% of articles), research capacity (36% of articles) and running low-value trials (34% of articles). 254 articles provided recommendations to reduce trial costs; of these, the most frequently reported recommendations related to improvements in: operational efficiencies (33% of articles); patient accrual (24% of articles); funding for trials and transparency in trials reporting (18% of articles, each). CONCLUSION: Key findings from the review are: 1) delayed trial activation has costs to budgets and research; 2) poor accrual leads to low-value trials and wasted resources; 3) the pharmaceutical industry can be a pragmatic, if problematic, partner in clinical research; 4) organizational know-how and successful research collaboration are benefits of network/cooperative groups; and 5) there are spillover benefits of clinical trials to healthcare systems, including better health outcomes, enhanced research capacity, and drug cost avoidance. There is a need for more economic evaluations of the benefits of clinical research, such as health system use (or avoidance) and health outcomes in cities and health authorities with institutions that conduct clinical research, to demonstrate the affordability of clinical trials, despite their high cost.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.838 | 0.789 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.067 | 0.020 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.012 | 0.025 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it