Design of a multicentre randomized trial to evaluate CT colonography versus colonoscopy or barium enema for diagnosis of colonic cancer in older symptomatic patients: The SIGGAR study
Bibliographic record
Abstract
BACKGROUND AND AIMS: The standard whole-colon tests used to investigate patients with symptoms of colorectal cancer are barium enema and colonoscopy. Colonoscopy is the reference test but is technically difficult, resource intensive, and associated with adverse events, especially in the elderly. Barium enema is safer but has reduced sensitivity for cancer. CT colonography ("virtual colonoscopy") is a newer alternative that may combine high sensitivity for cancer with safety and patient acceptability. The SIGGAR trial aims to determine the diagnostic efficacy, acceptability, and economic costs associated with this new technology. METHODS: The SIGGAR trial is a multi-centre randomised comparison of CT colonography versus standard investigation (barium enema or colonoscopy), the latter determined by individual clinician preference. Diagnostic efficacy for colorectal cancer and colonic polyps measuring 1 cm or larger will be determined, as will the physical and psychological morbidity associated with each diagnostic test, the latter via questionnaires developed from qualitative interviews. The economic costs of making or excluding a diagnosis will be determined for each diagnostic test and information from the trial and other data from the literature will be used to populate models framed to summarise the health effects and costs of alternative approaches to detection of significant colonic neoplasia in patients of different ages, prior risks and preferences. This analysis will focus particularly on the frequency, clinical relevance, costs, and psychological and physical morbidity associated with detection of extracolonic lesions by CT colonography. RESULTS: Recruitment commenced in March 2004 and at the time of writing (July 2007) 5025 patients have been randomised. A lower than expected prevalence of end-points in the barium enema sub-trial has caused an increase in sample size. In addition to the study protocol, we describe our approach to recruitment, notably the benefits of extensive piloting, the use of a sham-randomisation procedure, which was employed to determine whether centres interested in participating were likely to be effective in practice, and the provision of funding for dedicated sessions for a research nurse at each centre to devote specifically to this trial. TRIAL REGISTRATION: Current Controlled Trials ISRCTN95152621.
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.
How this classification was reachedexpand
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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".