Table 1.

Adapted QUIPS 'Risk of bias' assessment instrument for prognostic factor studies

Biases	Issues to consider for judging overall rating of risk of bias
Instructions to assess the risk of each potential bias	These issues will guide your thinking and judgement about the overall risk of bias within each of the six domains. These issues are taken together to inform the overall judgement of potential bias for each of the six domains
1. Study participation	Goal: to judge the risk of selection bias (likelihood that relationship between density reductions and outcome is different for participants and eligible non‐participants).
Source of target population	The source population or population of interest is adequately described for: a) treatment: (i) proportion with DCIS, (ii) cointerventions (chemotherapy/targeted therapy), (iii) severity of cancer at baseline (stage, % regional spread); b) prevention: level of risk in population, including whether some or all are BRCA1/2 mutation carriers, (ii) prior hormone replacement therapy use, (iii) cointerventions such as diet or exercise regimens, or both.
Method used to identify population	The sampling frame and recruitment are adequately described, including methods to identify the sample sufficient to limit potential bias.
Recruitment period	Period of recruitment is adequately described.
Place of recruitment	Place of recruitment (setting and geographic location) are adequately described.
Inclusion and exclusion criteria	Inclusion and exclusion criteria are adequately described.
Adequate study participation	There is adequate participation in the study by eligible individuals.
Baseline characteristics	The baseline study sample (i.e. individuals entering the study) is adequately described for (treatment and prevention) age, menopausal status, cointerventions; (treatment) % DCIS, disease severity; (prevention) breast cancer risk, prior hormone replacement therapy use.
Summary study participation	The study sample represents the population of interest on key characteristics, sufficient to limit potential bias of the observed relationship between density change and outcome.
2. Study attrition	Goal: to judge the risk of attrition bias (likelihood that relationship between density reductions and outcome are different for completing and non‐completing participants).
Proportion of baseline sample available for analysis	Response rate (i.e. proportion of study sample allocated treatment who received treatment) is adequate.
Attempts to collect information on participants who dropped out	Attempts to collect information on participants who dropped out of the study are described.
Reasons and potential impact of subjects lost to follow‐up	Reasons for loss to follow‐up are provided.
Outcome and prognostic factor information on those lost to follow‐up	Participants lost to follow‐up are adequately described for age at entry and cointerventions (if any), and for a) treatment: (i) DCIS, (ii) disease severity; b) prevention: (i) risk of breast cancer including BRCA1/2 carriers and testing. Whether loss to follow‐up or inability to retrieve mammograms, or both, was likely related to the study outcome.
Study attrition summary	There are no important differences between these characteristics in participants who completed the study and those who did not. Loss to follow‐up (from baseline sample to study population analysed) is not associated with key characteristics (i.e. the study data adequately represent the sample) sufficient to limit potential bias to the observed relationship between density change and outcome.
3. Prognostic factor measurement	Goal: to judge the risk of measurement bias related to how mammographic density was measured (differential measurement of mammographic density related to the level of outcome).
Definition of the prognostic factor	A clear definition or description of mammographic density is provided (e.g. including the method of measurement, if subjective then who undertook it, if treatment then whether contralateral breast assessed).
Valid and reliable measurement of prognostic factor	Method of mammographic density change measurement is adequately valid and reliable to limit misclassification bias (e.g. may include relevant outside sources of information on measurement properties; also characteristics, such as measurement blinded to case status).
	Continuous variables are reported or appropriate cutpoints (i.e. not data‐dependent (except for percentiles)) are used.
Method and setting of prognostic factor measurement	The method and setting of measurement of mammographic density is the same for all study participants. The same mammogram type (film/digital) is used for both baseline and follow‐up. The time at which baseline and follow‐up mammograms have low variability between participants.
Proportion of data on prognostic factor available for analysis	Adequate proportion of the study sample has complete data for the change in mammographic density variable.
Method used for missing data	Appropriate methods of imputation are used for missing mammographic density data.
Summary	Prognostic factor is adequately measured in study participants to sufficiently limit potential bias.
4. Outcome measurement	Goal: to judge the risk of bias related to the measurement of outcome (differential measurement of outcome related to the density reductions).
Definition of the outcome	A clear definition of outcome is provided, including duration of follow‐up and level and extent of the outcome construct.
Valid and reliable measurement of outcome	The method of outcome measurement used is adequately valid and reliable to limit misclassification bias.
Method and setting of outcome measurement	The method and setting of outcome measurement is the same for all study participants, including by age and obesity groups.
Outcome measurement summary	Outcome of interest is adequately measured in study participants to sufficiently limit potential bias.
5. Study confounding	Goal: to judge the risk of bias due to confounding (i.e. the effect of density reductions is distorted by another factor that is related to density reductions and the outcome).
Important confounders measured	Age, BMI, or another measure of adiposity are measured.
Definition of the confounding factor	Clear definitions are provided.
Valid and reliable measurement of confounders	Measurement of all important confounders is adequately valid and reliable.
Method and setting of confounding measurement	The method and setting of confounding measurement are the same for all study participants.
Method used for missing data	Appropriate methods are used if imputation is used for missing confounder data.
Appropriate accounting for confounding	The primary analysis will be adjusted for at least age, either through the study design and analysis, or through adjustment in the analysis only; and other prognostic factors.
Study confounding summary	Important potential confounders are appropriately accounted for, limiting potential bias with respect to the relationship between prognostic factor and outcome.
6. Statistical analysis and reporting	Goal: to judge the risk of bias related to the statistical analysis and presentation of results.
Presentation of analytical strategy, model development strategy	There is sufficient presentation of data to assess the adequacy of the analysis.
Model development strategy	The strategy for model building (i.e. inclusion of variables in the statistical model) is appropriate and is based on a conceptual framework or model.
Reporting of results	The selected statistical model is adequate for the design of the study. There is no selective reporting of results.
Statistical analysis and presentation summary	The statistical analysis is appropriate for the design of the study, limiting potential for presentation of invalid or spurious results.

BMI: body mass index DCIS: ductal carcinoma in situ