The roles of magnetic resonance and endoscopic retrograde cholangiopancreatography (MRCP and ERCP) in the diagnosis of patients with suspected sclerosing cholangitis: a cost-effectiveness analysis
Bibliographic record
Abstract
BACKGROUND AND STUDY AIMS: The optimal approach for diagnosing sclerosing cholangitis remains unclear in the face of competing imaging technologies. We aimed to determine the most cost-effective strategy. PATIENTS AND METHODS: A decision model compared three approaches in the work-up of patients with suspected sclerosing cholangitis; all included an initial test, with, if unsuccessful, performance of a second cholangiographic method. They were magnetic resonance cholangiopancreatography (MRCP) and endoscopic retrograde cholangiopancreatography (ERCP), termed "MRCP_ERCP", ERCP and MRCP ("ERCP_MRCP"), or ERCP and a repeat ERCP ("ERCP_ERCP"). The implications of true and false positive and negative results with regard to costs and procedural complications were considered, including that of a liver biopsy, if indicated as a result of a negative work-up in the face of persistent clinical suspicion. The unit of effectiveness adopted was that of a correct diagnosis. Probability assumptions were derived from published literature, while cost estimates were derived from time-motion microanalyses or a national database, and expressed in Canadian dollars at 2004 values. Sensitivity analyses, including clinically relevant threshold analyses, were carried out. RESULTS: The average cost-effectiveness ratios were $414 for MRCP_ERCP, $1101 for ERCP_MRCP and $1123 for ERCP_ERCP, per correct diagnosis. The ERCP_MRCP strategy was dominated (more expensive and less effective) by MRCP_ERCP, while ERCP_ERCP was more effective and more costly than MRCP_ERCP, at $289,292 per additional correct diagnosis. Sensitivity and threshold analyses confirmed the robustness of these findings. CONCLUSIONS: Based on the model assumptions, a strategy of initial MRCP, followed, if negative, by ERCP is currently the most cost-effective approach to the work-up of patients with suspected sclerosing cholangitis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".