risk-of-bias

name	risk-of-bias
description	Use when assessing risk of bias or study quality. Covers RoB 2 for RCTs, Newcastle-Ottawa Scale for cohorts, ROBINS-I for non-randomized interventions, and QUADAS-2 for diagnostic studies. Invoke for quality assessment.

Risk of Bias Assessment Skill

This skill guides risk of bias and study quality assessment for systematic reviews.

When to Use

Invoke this skill when the user:

• Asks to assess risk of bias
• Needs quality assessment of studies
• Mentions RoB 2, NOS, ROBINS-I, or QUADAS-2
• Wants to evaluate study quality
• Needs a risk of bias table or plot

Tool Selection

Study Design	Assessment Tool
Randomized Controlled Trial	RoB 2 (Cochrane)
Cohort study	Newcastle-Ottawa Scale
Case-control study	Newcastle-Ottawa Scale
Non-randomized intervention	ROBINS-I
Diagnostic accuracy study	QUADAS-2

---

RoB 2 (Cochrane Risk of Bias 2)

For randomized controlled trials.

Domains

Domain	Key Questions
D1: Randomization	Was allocation sequence random? Was it concealed? Were there baseline imbalances?
D2: Deviations from intervention	Were participants/personnel aware of assignment? Were there deviations? Was analysis appropriate?
D3: Missing outcome data	Was outcome data complete? Could missingness depend on outcome?
D4: Outcome measurement	Was the method appropriate? Could assessment be influenced by knowledge of intervention?
D5: Selection of reported result	Was the result pre-specified? Were multiple analyses performed?

Judgments

• Low risk: No concerns in this domain
• Some concerns: Some concern but not definitely high risk
• High risk: Definitely high risk in this domain

Overall Judgment

If ALL domains are "Low risk" → Overall: Low risk
If ANY domain is "High risk" → Overall: High risk
Otherwise → Overall: Some concerns

R Code for Visualization

library(robvis)

# Prepare data
rob_data <- data.frame(
  Study = c("Smith 2020", "Jones 2021", "Brown 2022"),
  D1 = c("Low", "Some concerns", "Low"),
  D2 = c("Low", "Low", "High"),
  D3 = c("Low", "Low", "Low"),
  D4 = c("Some concerns", "Low", "Low"),
  D5 = c("Low", "Low", "Low"),
  Overall = c("Some concerns", "Some concerns", "High")
)

# Traffic light plot
png("rob_traffic_light.png", width=1000, height=600, res=150)
rob_traffic_light(rob_data, tool = "ROB2")
dev.off()

# Summary plot
png("rob_summary.png", width=800, height=400, res=150)
rob_summary(rob_data, tool = "ROB2")
dev.off()

---

Newcastle-Ottawa Scale (NOS)

For observational studies (cohort and case-control).

Cohort Studies (max 9 stars)

Selection (max 4 stars)

Item	Criteria	Stars
Representativeness of exposed	Truly representative or somewhat representative	1
Selection of non-exposed	Same community as exposed	1
Ascertainment of exposure	Secure record or structured interview	1
Outcome not present at start	Yes	1

Comparability (max 2 stars)

Item	Criteria	Stars
Controls for confounders	For most important factor	1
	For additional factor	1

Outcome (max 3 stars)

Item	Criteria	Stars
Assessment of outcome	Independent blind or record linkage	1
Adequate follow-up length	Sufficient for outcome	1
Adequacy of follow-up	≥80% complete or dropout analysis	1

Quality Categories

7-9 stars: High quality
4-6 stars: Moderate quality
0-3 stars: Low quality

---

ROBINS-I

For non-randomized studies of interventions.

Domains

Domain	Focus
Confounding	Baseline confounding
Selection	Selection into the study
Classification	Classification of interventions
Deviations	Deviations from intended interventions
Missing data	Missing outcome data
Measurement	Measurement of outcomes
Reporting	Selection of reported result

Judgments

• Low risk: Comparable to well-performed RCT
• Moderate risk: Sound for non-randomized study
• Serious risk: Important problems
• Critical risk: Study too problematic to provide evidence
• No information: Insufficient information

Overall Judgment

If ALL domains are "Low" → Overall: Low risk
If highest is "Moderate" → Overall: Moderate risk
If ANY domain is "Serious" → Overall: Serious risk
If ANY domain is "Critical" → Overall: Critical risk

---

QUADAS-2

For diagnostic accuracy studies.

Domains

Domain	Risk of Bias	Applicability
Patient Selection	Was a consecutive/random sample used? Was case-control design avoided? Did the study avoid inappropriate exclusions?	Do included patients match review question?
Index Test	Was the index test interpreted without knowledge of reference standard? Was a threshold pre-specified?	Is the test applicable to the review question?
Reference Standard	Is the reference standard likely to correctly classify the condition? Was it interpreted without knowledge of index test?	Is the reference standard applicable?
Flow and Timing	Was there appropriate interval between tests? Did all patients receive the reference standard? Did all patients receive the same reference standard? Were all patients included in the analysis?	-

---

Output Format

Risk of Bias Table

risk_of_bias:
  - study_id: "Smith2023"
    tool: "RoB2"
    domains:
      D1_randomization: "Low"
      D2_deviations: "Some concerns"
      D3_missing_data: "Low"
      D4_measurement: "Low"
      D5_reporting: "Low"
    overall: "Some concerns"
    support: "Blinding of outcome assessors unclear"

Summary Reporting

## Risk of Bias Assessment

We used the Cochrane RoB 2 tool for randomized trials.

**Summary:**
- Low risk: 5 studies (45%)
- Some concerns: 4 studies (36%)
- High risk: 2 studies (18%)

**Key concerns:**
- Outcome assessment blinding unclear in 4 studies
- Per-protocol analysis without addressing deviations in 2 studies

---

Best Practices

1. Two reviewers: Independent assessment
2. Pilot testing: Calibrate on 2-3 studies
3. Support quotes: Document rationale with paper quotes
4. Domain-level: Report each domain, not just overall
5. Sensitivity analysis: Exclude high risk studies

Integration with Meta-Analysis

# Subgroup by risk of bias
forest(ma, subgroup = rob_overall,
       subgroup.levels = c("Low", "Some concerns", "High"))

# Sensitivity: low risk only
ma_low <- update(ma, subset = rob_overall == "Low")
summary(ma_low)