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# Evidence Synthesis and Guideline Integration Guide
## Overview
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.
## Major Clinical Practice Guidelines
### Oncology Guidelines
**NCCN (National Comprehensive Cancer Network)**
- **Scope**: 60+ cancer types, supportive care guidelines
- **Update Frequency**: Continuous (online), 1-3 updates per year per guideline
- **Evidence Categories**:
- **Category 1**: High-level evidence, uniform NCCN consensus
- **Category 2A**: Lower-level evidence, uniform consensus (appropriate)
- **Category 2B**: Lower-level evidence, non-uniform consensus (appropriate)
- **Category 3**: Major disagreement or insufficient evidence
- **Access**: Free for patients, subscription for providers (institutional access common)
- **Application**: US-focused, most widely used in clinical practice
**ASCO (American Society of Clinical Oncology)**
- **Scope**: Evidence-based clinical practice guidelines
- **Methodology**: Systematic review, GRADE-style evidence tables
- **Endorsements**: Often endorses NCCN, ESMO, or other guidelines
- **Focused Topics**: Specific clinical questions (e.g., biomarker testing, supportive care)
- **Guideline Products**: Full guidelines, rapid recommendations, endorsements
- **Quality**: Rigorous methodology, peer-reviewed publication
**ESMO (European Society for Medical Oncology)**
- **Scope**: European guidelines for cancer management
- **Evidence Levels**:
- **I**: Evidence from at least one large RCT or meta-analysis
- **II**: Evidence from at least one well-designed non-randomized trial, cohort study
- **III**: Evidence from well-designed non-experimental study
- **IV**: Evidence from expert committee reports or opinions
- **V**: Evidence from case series, case reports
- **Recommendation Grades**:
- **A**: Strong evidence for efficacy, substantial clinical benefit (strongly recommended)
- **B**: Strong or moderate evidence, limited clinical benefit (generally recommended)
- **C**: Insufficient evidence, benefit not sufficiently well established
- **D**: Moderate evidence against efficacy or for adverse effects (not recommended)
- **E**: Strong evidence against efficacy (never recommended)
- **ESMO-MCBS**: Magnitude of Clinical Benefit Scale (grades 1-5 for meaningful benefit)
### Cardiovascular Guidelines
**AHA/ACC (American Heart Association / American College of Cardiology)**
- **Scope**: Cardiovascular disease prevention, diagnosis, management
- **Class of Recommendation (COR)**:
- **Class I**: Strong recommendation - should be performed/administered
- **Class IIa**: Moderate recommendation - is reasonable
- **Class IIb**: Weak recommendation - may be considered
- **Class III - No Benefit**: Not recommended
- **Class III - Harm**: Potentially harmful
- **Level of Evidence (LOE)**:
- **A**: High-quality evidence from >1 RCT, meta-analyses
- **B-R**: Moderate-quality evidence from ≥1 RCT
- **B-NR**: Moderate-quality evidence from non-randomized studies
- **C-LD**: Limited data from observational studies, registries
- **C-EO**: Expert opinion based on clinical experience
- **Example**: "Statin therapy is recommended for adults with LDL-C ≥190 mg/dL (Class I, LOE A)"
**ESC (European Society of Cardiology)**
- **Scope**: European cardiovascular guidelines
- **Class of Recommendation**:
- **I**: Recommended or indicated
- **II**: Should be considered
- **III**: Not recommended
- **Level of Evidence**: A (RCTs), B (single RCT or observational), C (expert opinion)
### Other Specialties
**IDSA (Infectious Diseases Society of America)**
- Antimicrobial guidelines, infection management
- GRADE methodology
- Strong vs weak recommendations
**ATS/ERS (American Thoracic Society / European Respiratory Society)**
- Respiratory disease management
- GRADE methodology
**ACR (American College of Rheumatology)**
- Rheumatic disease guidelines
- Conditionally recommended vs strongly recommended
**KDIGO (Kidney Disease: Improving Global Outcomes)**
- Chronic kidney disease, dialysis, transplant
- GRADE-based recommendations
## GRADE Methodology
### Assessing Quality of Evidence
**Initial Quality Assignment**
**Randomized Controlled Trials**: Start at HIGH quality (⊕⊕⊕⊕)
**Observational Studies**: Start at LOW quality (⊕⊕○○)
### Factors Decreasing Quality (Downgrade)
**Risk of Bias** (-1 or -2 levels)
- Lack of allocation concealment
- Lack of blinding
- Incomplete outcome data
- Selective outcome reporting
- Other sources of bias
**Inconsistency** (-1 or -2 levels)
- Unexplained heterogeneity in results across studies
- Wide variation in effect estimates
- Non-overlapping confidence intervals
- High I² statistic in meta-analysis (>50-75%)
**Indirectness** (-1 or -2 levels)
- Different population than target (younger patients in trials, applying to elderly)
- Different intervention (higher dose in trial than used in practice)
- Different comparator (placebo in trial, comparing to active treatment)
- Surrogate outcomes (PFS) when interested in survival (OS)
**Imprecision** (-1 or -2 levels)
- Wide confidence intervals crossing threshold of benefit/harm
- Small sample size, few events
- Optimal information size (OIS) not met
- Rule of thumb: <300 events for continuous outcomes, <200 events for dichotomous
**Publication Bias** (-1 level)
- Funnel plot asymmetry (if ≥10 studies)
- Known unpublished studies with negative results
- Selective outcome reporting
- Industry-sponsored studies only
### Factors Increasing Quality (Upgrade - Observational Only)
**Large Magnitude of Effect** (+1 or +2 levels)
- +1: RR >2 or <0.5 (moderate effect)
- +2: RR >5 or <0.2 (large effect)
- No plausible confounders would reduce effect
**Dose-Response Gradient** (+1 level)
- Clear dose-response or duration-response relationship
- Strengthens causal inference
**All Plausible Confounders Would Reduce Effect** (+1 level)
- Observed effect despite confounders biasing toward null
- Rare, requires careful justification
### Final Quality Rating
After adjustments, assign final quality:
- **High (⊕⊕⊕⊕)**: Very confident in effect estimate
- **Moderate (⊕⊕⊕○)**: Moderately confident; true effect likely close to estimate
- **Low (⊕⊕○○)**: Limited confidence; true effect may be substantially different
- **Very Low (⊕○○○)**: Very little confidence; true effect likely substantially different
## Systematic Reviews and Meta-Analyses
### PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)
**Search Strategy**
- **Databases**: PubMed/MEDLINE, Embase, Cochrane Library, Web of Science
- **Search Terms**: PICO (Population, Intervention, Comparator, Outcome)
- **Date Range**: Typically last 10-20 years or comprehensive
- **Language**: English only or all languages with translation
- **Grey Literature**: Conference abstracts, trial registries, unpublished data
**Study Selection**
```
PRISMA Flow Diagram:
Records identified through database searching (n=2,450)
Additional records through other sources (n=15)
↓
Records after duplicates removed (n=1,823)
↓
Records screened (title/abstract) (n=1,823) → Excluded (n=1,652)
↓ - Not relevant topic (n=1,120)
Full-text articles assessed (n=171) - Animal studies (n=332)
↓ - Reviews (n=200)
Studies included in qualitative synthesis (n=38) → Excluded (n=133)
↓ - Wrong population (n=42)
Studies included in meta-analysis (n=24) - Wrong intervention (n=35)
- No outcomes reported (n=28)
- Duplicate data (n=18)
- Poor quality (n=10)
```
**Data Extraction**
- Study characteristics: Design, sample size, population, intervention
- Results: Outcomes, effect sizes, confidence intervals, p-values
- Quality assessment: Risk of bias tool (Cochrane RoB 2.0 for RCTs)
- Dual extraction: Two reviewers independently, resolve disagreements
### Meta-Analysis Methods
**Fixed-Effect Model**
- **Assumption**: Single true effect size shared by all studies
- **Weighting**: By inverse variance (larger studies have more weight)
- **Application**: When heterogeneity is low (I² <25%)
- **Interpretation**: Estimate of common effect across studies
**Random-Effects Model**
- **Assumption**: True effect varies across studies (distribution of effects)
- **Weighting**: By inverse variance + between-study variance
- **Application**: When heterogeneity moderate to high (I² ≥25%)
- **Interpretation**: Estimate of average effect (center of distribution)
- **Wider CI**: Accounts for heterogeneity, more conservative
**Heterogeneity Assessment**
**I² Statistic**
- Percentage of variability due to heterogeneity rather than chance
- I² = 0-25%: Low heterogeneity
- I² = 25-50%: Moderate heterogeneity
- I² = 50-75%: Substantial heterogeneity
- I² = 75-100%: Considerable heterogeneity
**Q Test (Cochran's Q)**
- Test for heterogeneity
- p<0.10 suggests significant heterogeneity (liberal threshold)
- Low power when few studies, use I² as primary measure
**Tau² (τ²)**
- Estimate of between-study variance
- Used in random-effects weighting
**Subgroup Analysis**
- Explore sources of heterogeneity
- Pre-specified subgroups: Disease stage, biomarker status, treatment regimen
- Test for interaction between subgroups
**Forest Plot Interpretation**
```
Study n HR (95% CI) Weight
─────────────────────────────────────────────────────────────
Trial A 2018 450 0.62 (0.45-0.85) ●───┤ 28%
Trial B 2019 320 0.71 (0.49-1.02) ●────┤ 22%
Trial C 2020 580 0.55 (0.41-0.74) ●──┤ 32%
Trial D 2021 210 0.88 (0.56-1.38) ●──────┤ 18%
Overall (RE model) 1560 0.65 (0.53-0.80) ◆──┤
Heterogeneity: I²=42%, p=0.16
0.25 0.5 1.0 2.0 4.0
Favors Treatment Favors Control
```
## Guideline Integration
### Concordance Checking
**Multi-Guideline Comparison**
```
Recommendation: First-line treatment for advanced NSCLC, PD-L1 ≥50%
Guideline Version Recommendation Strength
─────────────────────────────────────────────────────────────────────────────
NCCN v4.2024 Pembrolizumab monotherapy (preferred) Category 1
ESMO 2023 Pembrolizumab monotherapy (preferred) I, A
ASCO 2022 Endorses NCCN guidelines Strong
NICE (UK) 2023 Pembrolizumab approved Recommended
Synthesis: Strong consensus across guidelines for pembrolizumab monotherapy.
Alternative: Pembrolizumab + chemotherapy also Category 1/I-A recommended.
```
**Discordance Resolution**
- Identify differences and reasons (geography, cost, access, evidence interpretation)
- Note date of each guideline (newer may incorporate recent trials)
- Consider regional applicability
- Favor guidelines with most rigorous methodology (GRADE-based)
### Regulatory Approval Landscape
**FDA Approvals**
- Track indication-specific approvals
- Accelerated approval vs full approval
- Post-marketing requirements
- Contraindications and warnings
**EMA (European Medicines Agency)**
- May differ from FDA in approved indications
- Conditional marketing authorization
- Additional monitoring (black triangle)
**Regional Variations**
- Health Technology Assessment (HTA) agencies
- NICE (UK): Cost-effectiveness analysis, QALY thresholds
- CADTH (Canada): Therapeutic review and recommendations
- PBAC (Australia): Reimbursement decisions
## Real-World Evidence (RWE)
### Sources of RWE
**Electronic Health Records (EHR)**
- Clinical data from routine practice
- Large patient numbers
- Heterogeneous populations (more generalizable than RCTs)
- Limitations: Missing data, inconsistent documentation, selection bias
**Claims Databases**
- Administrative claims for billing/reimbursement
- Large scale (millions of patients)
- Outcomes: Mortality, hospitalizations, procedures
- Limitations: Lack clinical detail (labs, imaging, biomarkers)
**Cancer Registries**
- **SEER (Surveillance, Epidemiology, and End Results)**: US cancer registry
- **NCDB (National Cancer Database)**: Hospital registry data
- Population-level survival, treatment patterns
- Limited treatment detail, no toxicity data
**Prospective Cohorts**
- Framingham Heart Study, Nurses' Health Study
- Long-term follow-up, rich covariate data
- Expensive, time-consuming
### RWE Applications
**Comparative Effectiveness**
- Compare treatments in real-world settings (less strict eligibility than RCTs)
- Complement RCT data with broader populations
- Example: Effectiveness of immunotherapy in elderly, poor PS patients excluded from trials
**Safety Signal Detection**
- Rare adverse events not detected in trials
- Long-term toxicities
- Drug-drug interactions in polypharmacy
- Postmarketing surveillance
**Treatment Patterns and Access**
- Guideline adherence in community practice
- Time to treatment initiation
- Disparities in care delivery
- Off-label use prevalence
**Limitations of RWE**
- **Confounding by indication**: Sicker patients receive more aggressive treatment
- **Immortal time bias**: Time between events affecting survival estimates
- **Missing data**: Incomplete or inconsistent data collection
- **Causality**: Association does not prove causation without randomization
**Strengthening RWE**
- **Propensity score matching**: Balance baseline characteristics between groups
- **Multivariable adjustment**: Adjust for measured confounders in Cox model
- **Sensitivity analyses**: Test robustness to unmeasured confounding
- **Instrumental variables**: Use natural experiments to approximate randomization
## Meta-Analysis Techniques
### Binary Outcomes (Response Rate, Event Rate)
**Effect Measures**
- **Risk Ratio (RR)**: Ratio of event probabilities
- **Odds Ratio (OR)**: Ratio of odds (less intuitive)
- **Risk Difference (RD)**: Absolute difference in event rates
**Example Calculation**
```
Study 1:
- Treatment A: 30/100 responded (30%)
- Treatment B: 15/100 responded (15%)
- RR = 0.30/0.15 = 2.0 (95% CI 1.15-3.48)
- RD = 0.30 - 0.15 = 0.15 or 15% (95% CI 4.2%-25.8%)
- NNT = 1/RD = 1/0.15 = 6.7 (treat 7 patients to get 1 additional response)
```
**Pooling Methods**
- **Mantel-Haenszel**: Common fixed-effect method
- **DerSimonian-Laird**: Random-effects method
- **Peto**: For rare events (event rate <1%)
### Time-to-Event Outcomes (Survival, PFS)
**Hazard Ratio Pooling**
- Extract HR and 95% CI (or log(HR) and SE) from each study
- Weight by inverse variance
- Pool using generic inverse variance method
- Report pooled HR with 95% CI, heterogeneity statistics
**When HR Not Reported**
- Extract from Kaplan-Meier curves (Parmar method, digitizing software)
- Calculate from log-rank p-value and event counts
- Request from study authors
### Continuous Outcomes (Quality of Life, Lab Values)
**Standardized Mean Difference (SMD)**
- Application: Different scales used across studies
- SMD = (Mean₁ - Mean₂) / Pooled SD
- Interpretation: Cohen's d effect size (0.2 small, 0.5 medium, 0.8 large)
**Mean Difference (MD)**
- Application: Same scale/unit used across studies
- MD = Mean₁ - Mean₂
- More directly interpretable than SMD
## Network Meta-Analysis
### Purpose
Compare multiple treatments simultaneously when no head-to-head trials exist
**Example Scenario**
- Drug A vs placebo (Trial 1)
- Drug B vs placebo (Trial 2)
- Drug C vs Drug A (Trial 3)
- **Question**: How does Drug B compare to Drug C? (no direct comparison)
### Methods
**Fixed-Effect Network Meta-Analysis**
- Assumes consistency (transitivity): A vs B effect = (A vs C effect) - (B vs C effect)
- Provides indirect comparison estimates
- Ranks treatments by P-score or SUCRA
**Random-Effects Network Meta-Analysis**
- Allows heterogeneity between studies
- More conservative estimates
**Consistency Checking**
- Compare direct vs indirect evidence for same comparison
- Node-splitting analysis
- Loop consistency (if closed loops in network)
### Interpretation Cautions
- **Transitivity assumption**: May not hold if studies differ in important ways
- **Indirect evidence**: Less reliable than direct head-to-head trials
- **Rankings**: Probabilistic, not definitive ordering
- **Clinical judgment**: Consider beyond statistical rankings
## Evidence Tables
### Constructing Evidence Summary Tables
**PICO Framework**
- **P (Population)**: Patient characteristics, disease stage, biomarker status
- **I (Intervention)**: Treatment regimen, dose, schedule
- **C (Comparator)**: Control arm (placebo, standard of care)
- **O (Outcomes)**: Primary and secondary endpoints
**Evidence Table Template**
```
Study Design n Population Intervention vs Comparator Outcome Result Quality
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Smith 2020 RCT 450 Advanced NSCLC Drug A 10mg vs Median PFS 12 vs 6 months High
EGFR+ standard chemo (95% CI) (10-14 vs 5-7) ⊕⊕⊕⊕
HR (95% CI) 0.48 (0.36-0.64)
p-value p<0.001
ORR 65% vs 35%
Grade 3-4 AEs 42% vs 38%
Jones 2021 RCT 380 Advanced NSCLC Drug A 10mg vs Median PFS 10 vs 5.5 months High
EGFR+ placebo HR (95% CI) 0.42 (0.30-0.58) ⊕⊕⊕⊕
p-value p<0.001
Pooled Effect Pooled HR 0.45 (0.36-0.57) High
(Meta-analysis) I² 12% (low heterogeneity) ⊕⊕⊕⊕
```
### Evidence to Decision Framework
**Benefits and Harms**
- Magnitude of desirable effects (ORR, PFS, OS improvement)
- Magnitude of undesirable effects (toxicity, quality of life impact)
- Balance of benefits and harms
- Net benefit calculation
**Values and Preferences**
- How do patients value outcomes? (survival vs quality of life)
- Variability in patient values
- Shared decision-making importance
**Resource Considerations**
- Cost of intervention
- Cost-effectiveness ($/QALY)
- Budget impact
- Equity and access
**Feasibility and Acceptability**
- Is treatment available in practice settings?
- Route of administration feasible? (oral vs IV vs subcutaneous)
- Monitoring requirements realistic?
- Patient and provider acceptability
## Guideline Concordance Documentation
### Synthesizing Multiple Guidelines
**Concordant Recommendations**
```
Clinical Question: Treatment for HER2+ metastatic breast cancer, first-line
Guideline Summary:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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