Evidence-based Healthcare–Colorectal Cancer
The Paradigm Shift of Cancer Screening Policy in Parallel with Evolution of Heath Care
- Evidence-based Stool-based and Endoscopy-based Screening
- Multimodal (FIT/Sigmoidscopy/Colonoscopy/Stool DNA) Precision Interval Screening
- Metaverse-enabled Smart Multilevel and Multimodal Smart Interventions
Scientific Flowchart of Evidence-based Medicine
- Primary Studies (Randomized Controlled Trials)-Refers to Consort Checklist
- Systematic Literature Review-Focusing on Population-based Screening
- Meta-analysis-Refers to PRISMA Checklist
- Decision Analysis- Metaverse Smart Screening/ Precision Screening/Universal Screening/No Screening
- Economic Evaluation- CEA/CUA/CBA Analysis
- Policy Decision-making – Voting from All Stakeholders
Demonstrate Long-term effectiveness of CRC Mortality Reduction
1. Population-based Randomized Controlled Trials
- g-FOBT
- Sigmoidoscopy
- Colonoscopy
2. Population-based Service Screening for CRC
3. Fecal Immunological Test (FIT)
Global Meta-analysis Findings Support Evidence-based Population-based Screening
- Population-based g-FOBT screening was supported by 16% (95% CI:0.79-0.80) CRC mortality reduction based on global meta-analysis.
- Population-based Sigmoidoscopy screening was supported by 29% (95% CI, 19-39%) CRC mortality reduction.
decision analysis /
Cost-effectiveness analysis
- Building Markov Cycle Decision Trees by Screening Strategies
- Deterministic CEA/CUA/CBA analysis gives base-case results: ICER(ICUR) (Incremental Cost-effectiveness (Utility) ratio and Benefit/Cost (B/C) Ratio
- Probabilistic sensitivity analysis, allowing for both second order of variation regarding the uncertainty of all parameters and first-order of random variations gives the probability of being cost-effective based on a series of ICERs on C-E plane with Markov Chain Monte Carlo (MCMC) Simulations and acceptability curve according the maximum of willingness to pay after n iterations.
- Population-based FIT screening is often cost-effective (the ICER point estimate lies in the quadrant I but below 1 or 2 GDP) and even cost-saving (-ICER) and has high probability of being cost-effective. The higher the amount of willingness to pay the more likely it is it is to accept more costly screening modality in the light of order g-FOBT/FIT/FSIG/Colonoscopy. Note that new alternative screening modalities such as stool DNA tets, CTC and capsule endoscopy were not cost-effective.
- Precision FIT screening is cost-effective and probably cost-saving in the light of AI machine learning algorithm analysis.
policy decision-making
We used the evolution of colorectal cancer screening policy in Taiwan as an illustration.
- High-risk Approach with Index Cases of Family History 1992-1997
- Community-based Integrated Screening with FIT test 2000-2003
- Nationwide universal FIT screening 2004
