Patient preferences for breast cancer screening: a systematic review update to inform recommendations by the Canadian Task Force on Preventive Health Care
Authors: Pillay Jennifer , Guitard Samantha , Rahman Sholeh , Saba Sabrina , Rahman Ashiqur , Bialy Liza , Gehring Nicole , Tan Maria , Melton Alex , Hartling Lisa 
Published: February 2024

Background
Different guideline panels, and individuals, may make different decisions based in part by their preferences. This systematic review update examined the relative importance placed by patients aged ≥ 35 years on the potential outcomes of breast-cancer screening.
Methods
We updated our searches to June 19, 2023 in MEDLINE, PsycINFO, and CINAHL. We screened grey literature, submissions by stakeholders, and reference lists. We sought three types of preferences, directly through i) utilities of screening and curative treatment health states (measuring the impact of the outcome on one’s health-related quality of life), and ii) other preference-based data, such as outcome trade-offs, and indirectly through iii) the relative importance of benefits versus harms inferred from attitudes, intentions, and behaviors towards screening among informed patients. For screening we used machine learning as one of the reviewers after at least 50% of studies had been reviewed in duplicate by humans; full-text selection used independent review by two humans. Data extraction and risk of bias assessments used a single reviewer with verification. Our main analysis for utilities used data from utility-based health-related quality of life tools (e.g., EQ-5D) in patients. When suitable, we pooled utilities and explored heterogeneity. Disutilities were calculated for screening health states and between different treatment states. Non-utility data were grouped into categories and synthesized with creation of summary statements. Certainty assessments followed GRADE guidance.
Findings
Eighty-two studies (38 on utilities) were included. The estimated disutilities were 0.07 for a positive screening result (moderate certainty), 0.03-0.04 for a false positive (FP; “additional testing” resolved as negative for cancer) (low certainty), and 0.08 for untreated screen-detected cancer (moderate certainty) or (low certainty) an interval cancer. At ≤12 months, disutilities of mastectomy (vs. breast-conserving therapy), chemotherapy (vs. none) (low certainty), and radiation therapy (vs. none) (moderate certainty) were 0.02-0.03, 0.02-0.04, and little-to-none, respectively. Over the longer term, there was moderate certainty for little-to-no disutility from mastectomy versus breast-conserving surgery/lumpectomy with radiation and from radiation. There was moderate certainty that a majority (>50%) and possibly large majority (>75%) of women probably accept up to six cases of overdiagnosis to prevent one breast-cancer death.Low certainty evidence suggested that a large majority may accept that screening may reduce breast-cancer but not all-cause mortality, at least when presented with relatively high rates of breast-cancer mortality reductions (n=2; 2 and 5 fewer per 1000 screened), and at least a majority accept that to prevent one breast-cancer death at least a few hundred patients will receive a FP result and 10-15 will have a FP resolved through biopsy. When using data from studies assessing attitudes, intentions, and screening behaviors, across all age groups but most evident for women in their 40s, preferences reduced as the net benefit presented by study authors decreased in magnitude. In a relatively low net-benefit scenario, a majority of patients in their 40s may not weigh the benefits as greater than the harms from screening (low certainty evidence). A large majority of patients aged 70-71 years probably think the benefits outweigh the harms for continuing to screen. A majority of women in their mid-70s to early 80s may prefer to continue screening.
Conclusions
Evidence across a range of data sources on how informed patients value the potential outcomes from breast-cancer screening will be useful during decision-making for recommendations. Further, the evidence supports providing easily understandable information on possible magnitudes of effects to enable informed decision-making.
Systematic review registration: Protocol available at Open Science Framework https://osf.io/xngsu/