841 lines
33 KiB
Markdown
841 lines
33 KiB
Markdown
# Evidence Synthesis and Guideline Integration Guide
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## Overview
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Evidence synthesis involves systematically reviewing, analyzing, and integrating research findings to inform clinical recommendations. This guide covers guideline sources, evidence hierarchies, systematic reviews, meta-analyses, and integration of multiple evidence streams for clinical decision support.
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## Major Clinical Practice Guidelines
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### Oncology Guidelines
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**NCCN (National Comprehensive Cancer Network)**
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- **Scope**: 60+ cancer types, supportive care guidelines
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- **Update Frequency**: Continuous (online), 1-3 updates per year per guideline
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- **Evidence Categories**:
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- **Category 1**: High-level evidence, uniform NCCN consensus
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- **Category 2A**: Lower-level evidence, uniform consensus (appropriate)
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- **Category 2B**: Lower-level evidence, non-uniform consensus (appropriate)
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- **Category 3**: Major disagreement or insufficient evidence
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- **Access**: Free for patients, subscription for providers (institutional access common)
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- **Application**: US-focused, most widely used in clinical practice
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**ASCO (American Society of Clinical Oncology)**
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- **Scope**: Evidence-based clinical practice guidelines
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- **Methodology**: Systematic review, GRADE-style evidence tables
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- **Endorsements**: Often endorses NCCN, ESMO, or other guidelines
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- **Focused Topics**: Specific clinical questions (e.g., biomarker testing, supportive care)
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- **Guideline Products**: Full guidelines, rapid recommendations, endorsements
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- **Quality**: Rigorous methodology, peer-reviewed publication
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**ESMO (European Society for Medical Oncology)**
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- **Scope**: European guidelines for cancer management
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- **Evidence Levels**:
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- **I**: Evidence from at least one large RCT or meta-analysis
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- **II**: Evidence from at least one well-designed non-randomized trial, cohort study
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- **III**: Evidence from well-designed non-experimental study
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- **IV**: Evidence from expert committee reports or opinions
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- **V**: Evidence from case series, case reports
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- **Recommendation Grades**:
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- **A**: Strong evidence for efficacy, substantial clinical benefit (strongly recommended)
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- **B**: Strong or moderate evidence, limited clinical benefit (generally recommended)
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- **C**: Insufficient evidence, benefit not sufficiently well established
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- **D**: Moderate evidence against efficacy or for adverse effects (not recommended)
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- **E**: Strong evidence against efficacy (never recommended)
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- **ESMO-MCBS**: Magnitude of Clinical Benefit Scale (grades 1-5 for meaningful benefit)
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### Cardiovascular Guidelines
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**AHA/ACC (American Heart Association / American College of Cardiology)**
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- **Scope**: Cardiovascular disease prevention, diagnosis, management
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- **Class of Recommendation (COR)**:
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- **Class I**: Strong recommendation - should be performed/administered
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- **Class IIa**: Moderate recommendation - is reasonable
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- **Class IIb**: Weak recommendation - may be considered
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- **Class III - No Benefit**: Not recommended
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- **Class III - Harm**: Potentially harmful
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- **Level of Evidence (LOE)**:
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- **A**: High-quality evidence from >1 RCT, meta-analyses
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- **B-R**: Moderate-quality evidence from ≥1 RCT
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- **B-NR**: Moderate-quality evidence from non-randomized studies
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- **C-LD**: Limited data from observational studies, registries
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- **C-EO**: Expert opinion based on clinical experience
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- **Example**: "Statin therapy is recommended for adults with LDL-C ≥190 mg/dL (Class I, LOE A)"
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**ESC (European Society of Cardiology)**
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- **Scope**: European cardiovascular guidelines
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- **Class of Recommendation**:
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- **I**: Recommended or indicated
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- **II**: Should be considered
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- **III**: Not recommended
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- **Level of Evidence**: A (RCTs), B (single RCT or observational), C (expert opinion)
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### Other Specialties
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**IDSA (Infectious Diseases Society of America)**
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- Antimicrobial guidelines, infection management
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- GRADE methodology
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- Strong vs weak recommendations
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**ATS/ERS (American Thoracic Society / European Respiratory Society)**
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- Respiratory disease management
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- GRADE methodology
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**ACR (American College of Rheumatology)**
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- Rheumatic disease guidelines
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- Conditionally recommended vs strongly recommended
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**KDIGO (Kidney Disease: Improving Global Outcomes)**
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- Chronic kidney disease, dialysis, transplant
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- GRADE-based recommendations
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## GRADE Methodology
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### Assessing Quality of Evidence
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**Initial Quality Assignment**
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**Randomized Controlled Trials**: Start at HIGH quality (⊕⊕⊕⊕)
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**Observational Studies**: Start at LOW quality (⊕⊕○○)
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### Factors Decreasing Quality (Downgrade)
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**Risk of Bias** (-1 or -2 levels)
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- Lack of allocation concealment
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- Lack of blinding
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- Incomplete outcome data
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- Selective outcome reporting
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- Other sources of bias
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**Inconsistency** (-1 or -2 levels)
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- Unexplained heterogeneity in results across studies
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- Wide variation in effect estimates
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- Non-overlapping confidence intervals
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- High I² statistic in meta-analysis (>50-75%)
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**Indirectness** (-1 or -2 levels)
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- Different population than target (younger patients in trials, applying to elderly)
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- Different intervention (higher dose in trial than used in practice)
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- Different comparator (placebo in trial, comparing to active treatment)
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- Surrogate outcomes (PFS) when interested in survival (OS)
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**Imprecision** (-1 or -2 levels)
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- Wide confidence intervals crossing threshold of benefit/harm
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- Small sample size, few events
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- Optimal information size (OIS) not met
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- Rule of thumb: <300 events for continuous outcomes, <200 events for dichotomous
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**Publication Bias** (-1 level)
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- Funnel plot asymmetry (if ≥10 studies)
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- Known unpublished studies with negative results
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- Selective outcome reporting
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- Industry-sponsored studies only
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### Factors Increasing Quality (Upgrade - Observational Only)
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**Large Magnitude of Effect** (+1 or +2 levels)
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- +1: RR >2 or <0.5 (moderate effect)
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- +2: RR >5 or <0.2 (large effect)
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- No plausible confounders would reduce effect
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**Dose-Response Gradient** (+1 level)
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- Clear dose-response or duration-response relationship
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- Strengthens causal inference
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**All Plausible Confounders Would Reduce Effect** (+1 level)
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- Observed effect despite confounders biasing toward null
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- Rare, requires careful justification
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### Final Quality Rating
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After adjustments, assign final quality:
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- **High (⊕⊕⊕⊕)**: Very confident in effect estimate
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- **Moderate (⊕⊕⊕○)**: Moderately confident; true effect likely close to estimate
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- **Low (⊕⊕○○)**: Limited confidence; true effect may be substantially different
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- **Very Low (⊕○○○)**: Very little confidence; true effect likely substantially different
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## Systematic Reviews and Meta-Analyses
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### PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)
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**Search Strategy**
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- **Databases**: PubMed/MEDLINE, Embase, Cochrane Library, Web of Science
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- **Search Terms**: PICO (Population, Intervention, Comparator, Outcome)
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- **Date Range**: Typically last 10-20 years or comprehensive
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- **Language**: English only or all languages with translation
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- **Grey Literature**: Conference abstracts, trial registries, unpublished data
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**Study Selection**
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```
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PRISMA Flow Diagram:
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Records identified through database searching (n=2,450)
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Additional records through other sources (n=15)
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↓
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Records after duplicates removed (n=1,823)
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↓
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Records screened (title/abstract) (n=1,823) → Excluded (n=1,652)
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↓ - Not relevant topic (n=1,120)
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Full-text articles assessed (n=171) - Animal studies (n=332)
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↓ - Reviews (n=200)
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Studies included in qualitative synthesis (n=38) → Excluded (n=133)
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↓ - Wrong population (n=42)
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Studies included in meta-analysis (n=24) - Wrong intervention (n=35)
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- No outcomes reported (n=28)
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- Duplicate data (n=18)
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- Poor quality (n=10)
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```
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**Data Extraction**
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- Study characteristics: Design, sample size, population, intervention
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- Results: Outcomes, effect sizes, confidence intervals, p-values
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- Quality assessment: Risk of bias tool (Cochrane RoB 2.0 for RCTs)
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- Dual extraction: Two reviewers independently, resolve disagreements
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### Meta-Analysis Methods
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**Fixed-Effect Model**
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- **Assumption**: Single true effect size shared by all studies
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- **Weighting**: By inverse variance (larger studies have more weight)
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- **Application**: When heterogeneity is low (I² <25%)
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- **Interpretation**: Estimate of common effect across studies
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**Random-Effects Model**
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- **Assumption**: True effect varies across studies (distribution of effects)
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- **Weighting**: By inverse variance + between-study variance
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- **Application**: When heterogeneity moderate to high (I² ≥25%)
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- **Interpretation**: Estimate of average effect (center of distribution)
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- **Wider CI**: Accounts for heterogeneity, more conservative
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**Heterogeneity Assessment**
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**I² Statistic**
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- Percentage of variability due to heterogeneity rather than chance
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- I² = 0-25%: Low heterogeneity
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- I² = 25-50%: Moderate heterogeneity
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- I² = 50-75%: Substantial heterogeneity
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- I² = 75-100%: Considerable heterogeneity
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**Q Test (Cochran's Q)**
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- Test for heterogeneity
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- p<0.10 suggests significant heterogeneity (liberal threshold)
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- Low power when few studies, use I² as primary measure
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**Tau² (τ²)**
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- Estimate of between-study variance
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- Used in random-effects weighting
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**Subgroup Analysis**
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- Explore sources of heterogeneity
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- Pre-specified subgroups: Disease stage, biomarker status, treatment regimen
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- Test for interaction between subgroups
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**Forest Plot Interpretation**
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```
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Study n HR (95% CI) Weight
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─────────────────────────────────────────────────────────────
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Trial A 2018 450 0.62 (0.45-0.85) ●───┤ 28%
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Trial B 2019 320 0.71 (0.49-1.02) ●────┤ 22%
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Trial C 2020 580 0.55 (0.41-0.74) ●──┤ 32%
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Trial D 2021 210 0.88 (0.56-1.38) ●──────┤ 18%
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Overall (RE model) 1560 0.65 (0.53-0.80) ◆──┤
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Heterogeneity: I²=42%, p=0.16
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0.25 0.5 1.0 2.0 4.0
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Favors Treatment Favors Control
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```
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## Guideline Integration
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### Concordance Checking
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**Multi-Guideline Comparison**
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```
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Recommendation: First-line treatment for advanced NSCLC, PD-L1 ≥50%
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Guideline Version Recommendation Strength
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─────────────────────────────────────────────────────────────────────────────
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NCCN v4.2024 Pembrolizumab monotherapy (preferred) Category 1
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ESMO 2023 Pembrolizumab monotherapy (preferred) I, A
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ASCO 2022 Endorses NCCN guidelines Strong
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NICE (UK) 2023 Pembrolizumab approved Recommended
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Synthesis: Strong consensus across guidelines for pembrolizumab monotherapy.
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Alternative: Pembrolizumab + chemotherapy also Category 1/I-A recommended.
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```
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**Discordance Resolution**
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- Identify differences and reasons (geography, cost, access, evidence interpretation)
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- Note date of each guideline (newer may incorporate recent trials)
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- Consider regional applicability
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- Favor guidelines with most rigorous methodology (GRADE-based)
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### Regulatory Approval Landscape
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**FDA Approvals**
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- Track indication-specific approvals
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- Accelerated approval vs full approval
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- Post-marketing requirements
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- Contraindications and warnings
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**EMA (European Medicines Agency)**
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- May differ from FDA in approved indications
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- Conditional marketing authorization
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- Additional monitoring (black triangle)
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**Regional Variations**
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- Health Technology Assessment (HTA) agencies
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- NICE (UK): Cost-effectiveness analysis, QALY thresholds
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- CADTH (Canada): Therapeutic review and recommendations
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- PBAC (Australia): Reimbursement decisions
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## Real-World Evidence (RWE)
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### Sources of RWE
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**Electronic Health Records (EHR)**
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- Clinical data from routine practice
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- Large patient numbers
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- Heterogeneous populations (more generalizable than RCTs)
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- Limitations: Missing data, inconsistent documentation, selection bias
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**Claims Databases**
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- Administrative claims for billing/reimbursement
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- Large scale (millions of patients)
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- Outcomes: Mortality, hospitalizations, procedures
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- Limitations: Lack clinical detail (labs, imaging, biomarkers)
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**Cancer Registries**
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- **SEER (Surveillance, Epidemiology, and End Results)**: US cancer registry
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- **NCDB (National Cancer Database)**: Hospital registry data
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- Population-level survival, treatment patterns
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- Limited treatment detail, no toxicity data
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**Prospective Cohorts**
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- Framingham Heart Study, Nurses' Health Study
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- Long-term follow-up, rich covariate data
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- Expensive, time-consuming
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### RWE Applications
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**Comparative Effectiveness**
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- Compare treatments in real-world settings (less strict eligibility than RCTs)
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- Complement RCT data with broader populations
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- Example: Effectiveness of immunotherapy in elderly, poor PS patients excluded from trials
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**Safety Signal Detection**
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- Rare adverse events not detected in trials
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- Long-term toxicities
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- Drug-drug interactions in polypharmacy
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- Postmarketing surveillance
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**Treatment Patterns and Access**
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- Guideline adherence in community practice
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- Time to treatment initiation
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- Disparities in care delivery
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- Off-label use prevalence
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**Limitations of RWE**
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- **Confounding by indication**: Sicker patients receive more aggressive treatment
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- **Immortal time bias**: Time between events affecting survival estimates
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- **Missing data**: Incomplete or inconsistent data collection
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- **Causality**: Association does not prove causation without randomization
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**Strengthening RWE**
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- **Propensity score matching**: Balance baseline characteristics between groups
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- **Multivariable adjustment**: Adjust for measured confounders in Cox model
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- **Sensitivity analyses**: Test robustness to unmeasured confounding
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- **Instrumental variables**: Use natural experiments to approximate randomization
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## Meta-Analysis Techniques
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### Binary Outcomes (Response Rate, Event Rate)
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**Effect Measures**
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- **Risk Ratio (RR)**: Ratio of event probabilities
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- **Odds Ratio (OR)**: Ratio of odds (less intuitive)
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- **Risk Difference (RD)**: Absolute difference in event rates
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**Example Calculation**
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```
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Study 1:
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- Treatment A: 30/100 responded (30%)
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- Treatment B: 15/100 responded (15%)
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- RR = 0.30/0.15 = 2.0 (95% CI 1.15-3.48)
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- RD = 0.30 - 0.15 = 0.15 or 15% (95% CI 4.2%-25.8%)
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- NNT = 1/RD = 1/0.15 = 6.7 (treat 7 patients to get 1 additional response)
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```
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**Pooling Methods**
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- **Mantel-Haenszel**: Common fixed-effect method
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- **DerSimonian-Laird**: Random-effects method
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- **Peto**: For rare events (event rate <1%)
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### Time-to-Event Outcomes (Survival, PFS)
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**Hazard Ratio Pooling**
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- Extract HR and 95% CI (or log(HR) and SE) from each study
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- Weight by inverse variance
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- Pool using generic inverse variance method
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- Report pooled HR with 95% CI, heterogeneity statistics
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**When HR Not Reported**
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- Extract from Kaplan-Meier curves (Parmar method, digitizing software)
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- Calculate from log-rank p-value and event counts
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- Request from study authors
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### Continuous Outcomes (Quality of Life, Lab Values)
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**Standardized Mean Difference (SMD)**
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- Application: Different scales used across studies
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- SMD = (Mean₁ - Mean₂) / Pooled SD
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- Interpretation: Cohen's d effect size (0.2 small, 0.5 medium, 0.8 large)
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**Mean Difference (MD)**
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- Application: Same scale/unit used across studies
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- MD = Mean₁ - Mean₂
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- More directly interpretable than SMD
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## Network Meta-Analysis
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### Purpose
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Compare multiple treatments simultaneously when no head-to-head trials exist
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**Example Scenario**
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- Drug A vs placebo (Trial 1)
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- Drug B vs placebo (Trial 2)
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- Drug C vs Drug A (Trial 3)
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- **Question**: How does Drug B compare to Drug C? (no direct comparison)
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### Methods
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**Fixed-Effect Network Meta-Analysis**
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- Assumes consistency (transitivity): A vs B effect = (A vs C effect) - (B vs C effect)
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- Provides indirect comparison estimates
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- Ranks treatments by P-score or SUCRA
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**Random-Effects Network Meta-Analysis**
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- Allows heterogeneity between studies
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- More conservative estimates
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**Consistency Checking**
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- Compare direct vs indirect evidence for same comparison
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- Node-splitting analysis
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- Loop consistency (if closed loops in network)
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### Interpretation Cautions
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- **Transitivity assumption**: May not hold if studies differ in important ways
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- **Indirect evidence**: Less reliable than direct head-to-head trials
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- **Rankings**: Probabilistic, not definitive ordering
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- **Clinical judgment**: Consider beyond statistical rankings
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## Evidence Tables
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### Constructing Evidence Summary Tables
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**PICO Framework**
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- **P (Population)**: Patient characteristics, disease stage, biomarker status
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- **I (Intervention)**: Treatment regimen, dose, schedule
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- **C (Comparator)**: Control arm (placebo, standard of care)
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- **O (Outcomes)**: Primary and secondary endpoints
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**Evidence Table Template**
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```
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Study Design n Population Intervention vs Comparator Outcome Result Quality
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────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
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Smith 2020 RCT 450 Advanced NSCLC Drug A 10mg vs Median PFS 12 vs 6 months High
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EGFR+ standard chemo (95% CI) (10-14 vs 5-7) ⊕⊕⊕⊕
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HR (95% CI) 0.48 (0.36-0.64)
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p-value p<0.001
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ORR 65% vs 35%
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Grade 3-4 AEs 42% vs 38%
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Jones 2021 RCT 380 Advanced NSCLC Drug A 10mg vs Median PFS 10 vs 5.5 months High
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EGFR+ placebo HR (95% CI) 0.42 (0.30-0.58) ⊕⊕⊕⊕
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p-value p<0.001
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Pooled Effect Pooled HR 0.45 (0.36-0.57) High
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(Meta-analysis) I² 12% (low heterogeneity) ⊕⊕⊕⊕
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```
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### Evidence to Decision Framework
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**Benefits and Harms**
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- Magnitude of desirable effects (ORR, PFS, OS improvement)
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- Magnitude of undesirable effects (toxicity, quality of life impact)
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- Balance of benefits and harms
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- Net benefit calculation
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**Values and Preferences**
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- How do patients value outcomes? (survival vs quality of life)
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- Variability in patient values
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- Shared decision-making importance
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**Resource Considerations**
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- Cost of intervention
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- Cost-effectiveness ($/QALY)
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- Budget impact
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- Equity and access
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**Feasibility and Acceptability**
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- Is treatment available in practice settings?
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- Route of administration feasible? (oral vs IV vs subcutaneous)
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- Monitoring requirements realistic?
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- Patient and provider acceptability
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## Guideline Concordance Documentation
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### Synthesizing Multiple Guidelines
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**Concordant Recommendations**
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```
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Clinical Question: Treatment for HER2+ metastatic breast cancer, first-line
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Guideline Summary:
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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NCCN v3.2024 (Category 1):
|
||
Preferred: Pertuzumab + trastuzumab + taxane
|
||
Alternative: T-DM1, other HER2-targeted combinations
|
||
|
||
ESMO 2022 (Grade I, A):
|
||
Preferred: Pertuzumab + trastuzumab + docetaxel
|
||
Alternative: Trastuzumab + chemotherapy (if pertuzumab unavailable)
|
||
|
||
ASCO 2020 Endorsement:
|
||
Endorses NCCN guidelines, recommends pertuzumab-based first-line
|
||
|
||
Synthesis:
|
||
Strong consensus for pertuzumab + trastuzumab + taxane as first-line standard.
|
||
Evidence: CLEOPATRA trial (Swain 2015): median OS 56.5 vs 40.8 months (HR 0.68, p<0.001)
|
||
|
||
Recommendation:
|
||
Pertuzumab 840 mg IV loading then 420 mg + trastuzumab 8 mg/kg loading then 6 mg/kg
|
||
+ docetaxel 75 mg/m² every 3 weeks until progression.
|
||
|
||
Strength: Strong (GRADE 1A)
|
||
Evidence: High-quality, multiple RCTs, guideline concordance
|
||
```
|
||
|
||
**Discordant Recommendations**
|
||
```
|
||
Clinical Question: Adjuvant osimertinib for resected EGFR+ NSCLC
|
||
|
||
NCCN v4.2024 (Category 1):
|
||
Osimertinib 80 mg daily × 3 years after adjuvant chemotherapy
|
||
Evidence: ADAURA trial (median DFS not reached vs 28 months, HR 0.17)
|
||
|
||
ESMO 2023 (II, B):
|
||
Osimertinib may be considered
|
||
Note: Cost-effectiveness concerns, OS data immature
|
||
|
||
NICE (UK) 2022:
|
||
Not recommended for routine use
|
||
Reason: QALY analysis unfavorable at current pricing
|
||
|
||
Synthesis:
|
||
Efficacy demonstrated in phase 3 trial (ADAURA), FDA/EMA approved.
|
||
Guideline discordance based on cost-effectiveness, not clinical efficacy.
|
||
|
||
US practice: NCCN Category 1, widely adopted
|
||
European/UK: Variable adoption based on national HTA decisions
|
||
|
||
Recommendation Context-Dependent:
|
||
US: Strong recommendation if accessible (GRADE 1B)
|
||
Countries with cost constraints: Conditional recommendation (GRADE 2B)
|
||
```
|
||
|
||
## Quality Assessment Tools
|
||
|
||
### RCT Quality Assessment (Cochrane Risk of Bias 2.0)
|
||
|
||
**Domains**
|
||
1. **Bias from randomization process**: Sequence generation, allocation concealment
|
||
2. **Bias from deviations from intended interventions**: Blinding, protocol adherence
|
||
3. **Bias from missing outcome data**: Attrition, intention-to-treat analysis
|
||
4. **Bias in outcome measurement**: Blinded assessment, objective outcomes
|
||
5. **Bias in selection of reported result**: Selective reporting, outcome switching
|
||
|
||
**Judgment**: Low risk, some concerns, high risk (for each domain)
|
||
|
||
**Overall Risk of Bias**: Based on highest-risk domain
|
||
|
||
### Observational Study Quality (Newcastle-Ottawa Scale)
|
||
|
||
**Selection (max 4 stars)**
|
||
- Representativeness of exposed cohort
|
||
- Selection of non-exposed cohort
|
||
- Ascertainment of exposure
|
||
- Outcome not present at start
|
||
|
||
**Comparability (max 2 stars)**
|
||
- Comparability of cohorts (design/analysis adjustment for confounders)
|
||
|
||
**Outcome (max 3 stars)**
|
||
- Assessment of outcome
|
||
- Follow-up duration adequate
|
||
- Adequacy of follow-up (low attrition)
|
||
|
||
**Total Score**: 0-9 stars
|
||
- **High quality**: 7-9 stars
|
||
- **Moderate quality**: 4-6 stars
|
||
- **Low quality**: 0-3 stars
|
||
|
||
## Translating Evidence to Recommendations
|
||
|
||
### Recommendation Development Process
|
||
|
||
**Step 1: PICO Question Formulation**
|
||
```
|
||
Example PICO:
|
||
P - Population: Adults with type 2 diabetes and cardiovascular disease
|
||
I - Intervention: SGLT2 inhibitor (empagliflozin)
|
||
C - Comparator: Placebo (added to standard care)
|
||
O - Outcomes: Major adverse cardiovascular events (3P-MACE), hospitalization for heart failure
|
||
```
|
||
|
||
**Step 2: Systematic Evidence Review**
|
||
- Identify all relevant studies
|
||
- Assess quality using standardized tools
|
||
- Extract outcome data
|
||
- Synthesize findings (narrative or meta-analysis)
|
||
|
||
**Step 3: GRADE Evidence Rating**
|
||
- Start at high (RCTs) or low (observational)
|
||
- Downgrade for risk of bias, inconsistency, indirectness, imprecision, publication bias
|
||
- Upgrade for large effect, dose-response, confounders reducing effect (observational only)
|
||
- Assign final quality rating
|
||
|
||
**Step 4: Recommendation Strength Determination**
|
||
|
||
**Strong Recommendation (Grade 1)**
|
||
- Desirable effects clearly outweigh undesirable effects
|
||
- High or moderate quality evidence
|
||
- Little variability in patient values
|
||
- Intervention cost-effective
|
||
|
||
**Conditional Recommendation (Grade 2)**
|
||
- Trade-offs: Desirable and undesirable effects closely balanced
|
||
- Low or very low quality evidence
|
||
- Substantial variability in patient values/preferences
|
||
- Uncertain cost-effectiveness
|
||
|
||
**Step 5: Wording the Recommendation**
|
||
```
|
||
Strong: "We recommend..."
|
||
Example: "We recommend SGLT2 inhibitor therapy for adults with type 2 diabetes and
|
||
established cardiovascular disease to reduce risk of hospitalization for heart failure
|
||
and cardiovascular death (Strong recommendation, high-quality evidence - GRADE 1A)."
|
||
|
||
Conditional: "We suggest..."
|
||
Example: "We suggest considering GLP-1 receptor agonist therapy for adults with type 2
|
||
diabetes and CKD to reduce risk of kidney disease progression (Conditional recommendation,
|
||
moderate-quality evidence - GRADE 2B)."
|
||
```
|
||
|
||
## Incorporating Emerging Evidence
|
||
|
||
### Early-Phase Trial Data
|
||
|
||
**Phase 1 Trials**
|
||
- Purpose: Dose-finding, safety
|
||
- Outcomes: Maximum tolerated dose (MTD), dose-limiting toxicities (DLTs), pharmacokinetics
|
||
- Evidence level: Very low (expert opinion, case series)
|
||
- Clinical application: Investigational only, clinical trial enrollment
|
||
|
||
**Phase 2 Trials**
|
||
- Purpose: Preliminary efficacy signal
|
||
- Design: Single-arm (ORR primary endpoint) or randomized (PFS comparison)
|
||
- Evidence level: Low to moderate
|
||
- Clinical application: May support off-label use in refractory settings, clinical trial enrollment preferred
|
||
|
||
**Phase 3 Trials**
|
||
- Purpose: Confirmatory efficacy and safety
|
||
- Design: Randomized controlled trial, OS or PFS primary endpoint
|
||
- Evidence level: High (if well-designed and executed)
|
||
- Clinical application: Regulatory approval basis, guideline recommendations
|
||
|
||
**Phase 4 Trials**
|
||
- Purpose: Post-marketing surveillance, additional indications
|
||
- Evidence level: Variable (depends on design)
|
||
- Clinical application: Safety monitoring, expanded usage
|
||
|
||
### Breakthrough Therapy Designation
|
||
|
||
**FDA Fast-Track Programs**
|
||
- **Breakthrough Therapy**: Preliminary evidence of substantial improvement over existing therapy
|
||
- **Accelerated Approval**: Approval based on surrogate endpoint (PFS, ORR)
|
||
- Post-marketing requirement: Confirmatory OS trial
|
||
- **Priority Review**: Shortened FDA review time (6 vs 10 months)
|
||
|
||
**Implications for Guidelines**
|
||
- May receive NCCN Category 2A before phase 3 data mature
|
||
- Upgrade to Category 1 when confirmatory data published
|
||
- Monitor for post-market confirmatory trial results
|
||
|
||
### Updating Recommendations
|
||
|
||
**Triggers for Update**
|
||
- New phase 3 trial results (major journal publication)
|
||
- FDA/EMA approval for new indication or agent
|
||
- Guideline update from NCCN, ASCO, ESMO
|
||
- Safety alert or drug withdrawal
|
||
- Meta-analysis changing effect estimates
|
||
|
||
**Rapid Update Process**
|
||
- Critical appraisal of new evidence
|
||
- Assess impact on current recommendations
|
||
- Revise evidence grade and recommendation strength if needed
|
||
- Disseminate update to users
|
||
- Version control and change log
|
||
|
||
## Conflicts of Interest and Bias
|
||
|
||
### Identifying Potential Bias
|
||
|
||
**Study Sponsorship**
|
||
- **Industry-sponsored**: May favor sponsor's product (publication bias, outcome selection)
|
||
- **Academic**: May favor investigator's hypothesis
|
||
- **Independent**: Government funding (NIH, PCORI)
|
||
|
||
**Author Conflicts of Interest**
|
||
- Consulting fees, research funding, stock ownership
|
||
- Disclosure statements required by journals
|
||
- ICMJE Form for Disclosure of Potential COI
|
||
|
||
**Mitigating Bias**
|
||
- Register trials prospectively (ClinicalTrials.gov)
|
||
- Pre-specify primary endpoint and analysis plan
|
||
- Independent data monitoring committee (IDMC)
|
||
- Blinding of outcome assessors
|
||
- Intention-to-treat analysis
|
||
|
||
### Transparency in Evidence Synthesis
|
||
|
||
**Pre-Registration**
|
||
- PROSPERO for systematic reviews
|
||
- Pre-specify PICO, search strategy, outcomes, analysis plan
|
||
- Prevents post-hoc changes to avoid negative findings
|
||
|
||
**Reporting Checklists**
|
||
- PRISMA for systematic reviews/meta-analyses
|
||
- CONSORT for RCTs
|
||
- STROBE for observational studies
|
||
|
||
**Data Availability**
|
||
- Individual patient data (IPD) sharing increases transparency
|
||
- Repositories: ClinicalTrials.gov results database, journal supplements
|
||
|
||
## Practical Application
|
||
|
||
### Evidence Summary for Clinical Document
|
||
|
||
```
|
||
EVIDENCE SYNTHESIS: Osimertinib for EGFR-Mutated NSCLC
|
||
|
||
Clinical Question:
|
||
Should adults with treatment-naïve advanced NSCLC harboring EGFR exon 19 deletion
|
||
or L858R mutation receive osimertinib versus first-generation EGFR TKIs?
|
||
|
||
Evidence Review:
|
||
┌──────────────────────────────────────────────────────────────────────┐
|
||
│ FLAURA Trial (Soria et al., NEJM 2018) │
|
||
├──────────────────────────────────────────────────────────────────────┤
|
||
│ Design: Phase 3 RCT, double-blind, 1:1 randomization │
|
||
│ Population: EGFR exon 19 del or L858R, stage IIIB/IV, ECOG 0-1 │
|
||
│ Sample Size: n=556 (279 osimertinib, 277 comparator) │
|
||
│ Intervention: Osimertinib 80 mg PO daily │
|
||
│ Comparator: Gefitinib 250 mg or erlotinib 150 mg PO daily │
|
||
│ Primary Endpoint: PFS by investigator assessment │
|
||
│ Secondary: OS, ORR, DOR, CNS progression, safety │
|
||
│ │
|
||
│ Results: │
|
||
│ - Median PFS: 18.9 vs 10.2 months (HR 0.46, 95% CI 0.37-0.57, p<0.001)│
|
||
│ - Median OS: 38.6 vs 31.8 months (HR 0.80, 95% CI 0.64-1.00, p=0.046)│
|
||
│ - ORR: 80% vs 76% (p=0.24) │
|
||
│ - Grade ≥3 AEs: 34% vs 45% │
|
||
│ - Quality: High (well-designed RCT, low risk of bias) │
|
||
└──────────────────────────────────────────────────────────────────────┘
|
||
|
||
Guideline Recommendations:
|
||
NCCN v4.2024: Category 1 preferred
|
||
ESMO 2022: Grade I, A
|
||
ASCO 2022: Endorsed
|
||
|
||
GRADE Assessment:
|
||
Quality of Evidence: ⊕⊕⊕⊕ HIGH
|
||
- Randomized controlled trial
|
||
- Low risk of bias (allocation concealment, blinding, ITT analysis)
|
||
- Consistent results (single large trial, consistent with phase 2 data)
|
||
- Direct evidence (target population and outcomes)
|
||
- Precise estimate (narrow CI, sufficient events)
|
||
- No publication bias concerns
|
||
|
||
Balance of Benefits and Harms:
|
||
- Large PFS benefit (8.7 month improvement, HR 0.46)
|
||
- OS benefit (6.8 month improvement, HR 0.80)
|
||
- Similar ORR, improved tolerability (lower grade 3-4 AEs)
|
||
- Desirable effects clearly outweigh undesirable effects
|
||
|
||
Patient Values: Little variability (most patients value survival extension)
|
||
|
||
Cost: Higher cost than first-gen TKIs, but widely accessible in developed countries
|
||
|
||
FINAL RECOMMENDATION:
|
||
Osimertinib 80 mg PO daily is recommended as first-line therapy for adults with
|
||
advanced NSCLC harboring EGFR exon 19 deletion or L858R mutation.
|
||
|
||
Strength: STRONG (Grade 1)
|
||
Quality of Evidence: HIGH (⊕⊕⊕⊕)
|
||
GRADE: 1A
|
||
```
|
||
|
||
## Keeping Current
|
||
|
||
### Literature Surveillance
|
||
|
||
**Automated Alerts**
|
||
- PubMed My NCBI (save searches, email alerts)
|
||
- Google Scholar alerts for specific topics
|
||
- Journal table of contents alerts (NEJM, Lancet, JCO)
|
||
- Guideline update notifications (NCCN, ASCO, ESMO email lists)
|
||
|
||
**Conference Monitoring**
|
||
- ASCO Annual Meeting (June)
|
||
- ESMO Congress (September)
|
||
- ASH Annual Meeting (December, hematology)
|
||
- AHA Scientific Sessions (November, cardiology)
|
||
- Plenary and press releases for practice-changing trials
|
||
|
||
**Trial Results Databases**
|
||
- ClinicalTrials.gov results database
|
||
- FDA approval letters and reviews
|
||
- EMA European public assessment reports (EPARs)
|
||
|
||
### Critical Appraisal Workflow
|
||
|
||
**Weekly Review**
|
||
1. Screen new publications (title/abstract)
|
||
2. Full-text review of relevant studies
|
||
3. Quality assessment using checklists
|
||
4. Extract key findings
|
||
5. Assess impact on current recommendations
|
||
|
||
**Monthly Synthesis**
|
||
1. Review accumulated evidence
|
||
2. Identify practice-changing findings
|
||
3. Update evidence tables
|
||
4. Revise recommendations if warranted
|
||
5. Disseminate updates to clinical teams
|
||
|
||
**Annual Comprehensive Review**
|
||
1. Systematic review of guideline updates
|
||
2. Re-assess all recommendations
|
||
3. Incorporate year's evidence
|
||
4. Major version release
|
||
5. Continuing education activities
|
||
|