The role of health economic evidence in clinical practice guidelines for colorectal cancer: a comparative analysis across countries
Bibliographic record
Abstract
Aim: Colorectal cancer (CRC) is among the most prevalent malignancies globally and causes massive resource consumption and economic burden. Health economic evidence (HEE) has been used in clinical practice guidelines (CPGs) for cancer to facilitate the rational allocation of health resources. However, in certain guideline development organizations, HEE is not yet utilized as a formal decision-making criterion. This study aimed to compare the discrepancies in the utilization of health economics as evidence in CRC CPGs across different countries and review specific features of economic evidence concerning the guidelines’ applicability. Materials & methods: A systematic review was conducted using databases including Medline, Embase, CNKI, WanFang, and other guidelines databases to identify CPGs for CRC published in English or Chinese from January 2017 to September 2023. Data on the incorporation and application of HEE were extracted, and the method and quality of cost–effectiveness analysis (CEA) studies were evaluated. Descriptive analyses were used to summarize the results. Results: Out of 53 CPGs from 14 countries, most originated from the USA (n = 17 of 53 [32%]) and Canada (n = 9 of 53 [17%]). Sixty-eight percent (36/53) considered cost justification, and 57% (30/53) incorporated health economics studies as evidence. The included HEE cited in CPGs ranged from 1990 to 2021 and were not aligned with the countries in which the guidelines were issued. Among these CEA studies, 52% (26/50) were related to screening strategies, and 32% (16/50) pertained to treatment measures. The Markov model was the most frequently used (n = 27 of 50 [54%]). Based on the CHEQUE tool, the methodological quality of these CEA studies was inadequate in areas such as multiple data sources, approaches to select data sources, assessing the quality of data, and relevant equity or distribution. Conclusion: In summary, 57% of guidelines incorporated health economics studies as evidence, with a variation between different countries. The included HEE still had deficiencies in methodology and reporting quality. In the future, it is suggested that health economics research should use a standardized methodology and reporting approach to assist in clinical decision making.
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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 | 0.267 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".