# Tool to Assess Risk of Bias in Cohort Studies

__Tool to Assess
Risk of Bias in Cohort Studies__

__Tool to Assess Risk of Bias in Cohort Studies__

This tool has been contributed by the CLARITY Group at McMaster University

It can be downloaded from Evidence Partners: Link to tools

### 1. **Was selection of exposed and non-exposed
cohorts drawn from the same population?**

** **

Definitely yes Probably yes Probably no Definitely no

* **(low
risk of bias)** ** ** ** **(high risk of bias)*

**Examples of low risk of bias:**Exposed and unexposed drawn for same administrative data base of patients presenting at same points of care over the same time frame

**exposed and unexposed presenting to different points of care or over a different time frame**

Examples of high risk of bias:

Examples of high risk of bias:

**2.
Can we be confident in the assessment of exposure?**

Definitely yes Probably
yes Probably no Definitely no

* **(low
risk of bias)** **(high
risk of bias)*

**Examples of low risk of bias:** Secure record [e.g. surgical records, pharmacy records]; Repeated interview or other ascertainment asking about current use/exposure**Examples of higher risk of bias:** Structured interview at a single point in time; Written self report; Individuals who are asked to retrospectively confirm their exposure status may be subject to recall bias – less likely to recall an exposure if they have not developed an adverse outcome, and more likely to recall an exposure (whether an exposure occurred or not) if they have developed an adverse outcome. **Examples of high risk of bias:** uncertain how exposure information obtained

**3. Can we be confident that the outcome
of interest was not present at start of study **

** **

Definitely yes Probably
yes Probably no Definitely no

* **(low
risk of bias)** **(high
risk of bias)*

**4. Did the study match exposed
and unexposed for all variables that are associated with the outcome of
interest or did the statistical analysis adjust for these prognostic variables?**

Definitely yes Mostly
yes Mostly no Definitely no

* **(low
risk of bias)** **(high
risk of bias)*

**Examples of low risk of bias:** comprehensive matching or adjustment for all plausible prognostic variables

**Examples of higher risk of bias**: matching or adjustment for most plausible prognostic variables**Examples of high risk of bias: **matching or adjustment for a minority of plausible prognostic variables, or no matching or adjustment at all. Statements of no differences between groups or that differences were not statistically significant are not sufficient for establishing comparability.

### 5.** Can we be confident in the assessment
of the presence or absence of prognostic factors?**

Definitely yes Probably
yes Probably no Definitely no

* **(low
risk of bias)** **(high
risk of bias)*

**Examples of low risk of bias:** Interview of all participants; self-completed survey from all participants; review of charts with reproducibility demonstrated; from data base with documentation of accuracy of abstraction of prognostic data**Examples of higher risk of bias:** Chart review without demonstration of reproducibility; data base with uncertain quality of abstraction of prognostic information**Examples of high risk of bias:** Prognostic information from data base with no available documentation of quality of abstraction of prognostic variables

** **

**6. Can we be confident in the
assessment of outcome? **

Definitely yes Probably yes Probably no Definitely no

(low risk of bias) (high risk of bias)

**Examples of low risk of
bias:** Independent blind assessment; Record linkage; For some outcomes (e.g.
fractured hip), reference to the medical record is sufficient to satisfy the
requirement for confirmation of the fracture.

**Examples
of higher risk of bias:** Independent assessment unblinded; self-report; For some
outcomes (e.g. vertebral fracture where reference to x-rays would be required)
reference to the medical record would not be adequate outcomes.

Examples of high risk of bias: uncertain (no description)

**7. Was the follow up of cohorts
adequate? **

Definitely yes Probably yes Probably no Definitely no

(low risk of bias) (high risk of bias)

**Examples of low risk of
bias:** No missing outcome data; Reasons for missing outcome data unlikely to be
related to true outcome (for survival data, censoring is unlikely to introduce
bias); Missing outcome data balanced in numbers across intervention groups,
with similar reasons for missing data across groups; For dichotomous outcome
data, the proportion of missing outcomes compared with observed event risk is not
enough to have a important impact on the intervention effect estimate; For
continuous outcome data, plausible effect size (difference in means or
standardized difference in means) among missing outcomes is not large enough to
have an important impact on the observed effect size; Missing data have been
imputed using appropriate methods.

**Examples of high risk of
bias:** Reason for missing outcome data likely to be related to true outcome,
with either imbalance in numbers or reasons for missing data across
intervention groups; For dichotomous outcome data, the proportion of missing
outcomes compared with observed event risk is enough to induce important bias
in intervention effect estimate; For continuous outcome data, plausible effect
size (difference in means or standardized difference in means) among missing
outcomes is large enough to induce clinically relevant bias in the observed
effect size.

**8. Were co-Interventions similar
between groups?**

** **

Definitely yes Probably yes Probably no Definitely no

(low risk of bias) (high risk of bias)

**Examples of low risk of
bias:** Most or all relevant
co-interventions that might influence the outcome of interest are documented to
be similar in the exposed and unexposed.

**Examples of high risk of
bias:** Few or no relevant co-interventions that might influence the outcome of
interest are documented to be similar in the exposed and unexposed.