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A new perspective on breast cancer diagnostic guidelines to reduce overdiagnosis

ABSTRACT: Abstract Overdiagnosis of breast cancer, defined as diagnosing a cancer that would otherwise not cause symptoms or death in a patient's lifetime, costs U.S. health care system over $1.2 billion annually. Overdiagnosis rates, estimated to be around 10%–40%, may be reduced if indolent breast findings can be identified and followed with noninvasive imaging rather than biopsy. However, there are no validated guidelines for radiologists to decide when to choose imaging options recognizing cancer grades and types. The aim of this study is to optimize breast cancer diagnostic decisions based on cancer types using a large‐scale finite‐horizon Markov decision process (MDP) model with 4.6 million states to help reduce overdiagnosis. We prove the optimality of a divide‐and‐search algorithm that relies on tight upper bounds on the optimal decision thresholds to find an exact optimal solution. We project the high‐dimensional MDP onto two lower dimensional MDPs and obtain feasible upper bounds on the optimal decision thresholds. We use real data from two private mammography databases and demonstrate our model performance through a previously validated simulation model that has been used by the policy makers to set the national screening guidelines in the United States. We find that a decision‐analytical framework optimizing diagnostic decisions while accounting for breast cancer types has a strong potential to improve the quality of life and alleviate the immense costs of overdiagnosis. Our model leads to a 20% reduction in overdiagnosis on the screening population, which translates into an annual savings of approximately $300 million for the U.S. health care system.

SUBMITTER: Tunc S

PROVIDER: S-EPMC9313854 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMammography screening can lead to overdiagnosis-that is, screen-detected breast cancer that would not have caused symptoms or signs in the remaining lifetime. There is no consensus about the frequency of breast cancer overdiagnosis.ObjectiveTo estimate the rate of breast cancer overdiagnosis in contemporary mammography practice accounting for the detection of nonprogressive cancer.DesignBayesian inference of the natural history of breast cancer using individual screening and diagnosis records, allowing for nonprogressive preclinical cancer. Combination of fitted natural history model with life-table data to predict the rate of overdiagnosis among screen-detected cancer under biennial screening.SettingBreast Cancer Surveillance Consortium (BCSC) facilities.ParticipantsWomen aged 50 to 74 years at first mammography screen between 2000 and 2018.MeasurementsScreening mammograms and screen-detected or interval breast cancer.ResultsThe cohort included 35 986 women, 82 677 mammograms, and 718 breast cancer diagnoses. Among all preclinical cancer cases, 4.5% (95% uncertainty interval [UI], 0.1% to 14.8%) were estimated to be nonprogressive. In a program of biennial screening from age 50 to 74 years, 15.4% (UI, 9.4% to 26.5%) of screen-detected cancer cases were estimated to be overdiagnosed, with 6.1% (UI, 0.2% to 20.1%) due to detecting indolent preclinical cancer and 9.3% (UI, 5.5% to 13.5%) due to detecting progressive preclinical cancer in women who would have died of an unrelated cause before clinical diagnosis.LimitationsExclusion of women with first mammography screen outside BCSC.ConclusionOn the basis of an authoritative U.S. population data set, the analysis projected that among biennially screened women aged 50 to 74 years, about 1 in 7 cases of screen-detected cancer is overdiagnosed. This information clarifies the risk for breast cancer overdiagnosis in contemporary screening practice and should facilitate shared and informed decision making about mammography screening.Primary funding sourceNational Cancer Institute.

Project description:ObjectiveTo elicit women's responses to information about the nature and extent of overdiagnosis in mammography screening (detecting disease that would not present clinically during the woman's lifetime) and explore how awareness of overdiagnosis might influence attitudes and intentions about screening.DesignQualitative study using focus groups that included a presentation explaining overdiagnosis, incorporating different published estimates of its rate (1-10%, 30%, 50%) and information on the mortality benefit of screening, with guided group discussionsSettingSydney, AustraliaParticipantsFifty women aged 40-79 years with no personal history of breast cancer and with varying levels of education and participation in screening.ResultsPrior awareness of breast cancer overdiagnosis was minimal. Women generally reacted with surprise, but most came to understand the issue. Responses to overdiagnosis and the different estimates of its magnitude were diverse. The highest estimate (50%) made some women perceive a need for more careful personal decision making about screening. In contrast, the lower and intermediate estimates (1-10% and 30%) had limited impact on attitudes and intentions, with many women remaining committed to screening. For some women, the information raised concerns, not about whether to screen but whether to treat a screen detected cancer or consider alternative approaches (such as watchful waiting). Information preferences varied: many women considered it important to take overdiagnosis into account and make informed choices about whether to have screening, but many wanted to be encouraged to be screened.ConclusionsWomen from a range of socioeconomic backgrounds could comprehend the issue of overdiagnosis in mammography screening, and they generally valued information about it. Effects on screening intentions may depend heavily on the rate of overdiagnosis. Overdiagnosis will be new and counterintuitive for many people and may influence screening and treatment decisions in unintended ways, underscoring the need for careful communication.

Project description:ObjectiveTo investigate conceptual knowledge about mammographic screening among Norwegian women.DesignWe administered a cross-sectional, web-based survey. We used multiple-choice questions and a grading rubric published by a research group from Australia.SettingOur Norwegian-language survey was open from April to June 2020 and targeted women aged 45-74 years.Participants2033 women completed our questionnaire. We excluded 13 women outside the target age range and 128 women with incomplete data. Responses from 1892 women were included in the final study sample.Primary and secondary outcome measuresThe questionnaire focused on women's knowledge about the breast cancer mortality reduction, false positive results and overdiagnosis associated with mammographic screening. The primary outcome was the mean number of marks assigned in each of the three themes and overall. There were three potential marks for questions about breast cancer mortality, one for false positives and six for overdiagnosis.ResultsMost women (91.7%) correctly reported that screened women are less likely to die of breast cancer than non-screened women. 39.7% of women reported having heard of a 'false positive screening result' and 86.2% identified the term's definition; 51.3% of women had heard of 'overdiagnosis' and 14.8% identified the term's definition. The mean score was 2.59 of 3 for questions about breast cancer mortality benefit and 0.93 of 1 for the question about false positive screening results. It was 2.23 of 6 for questions about overdiagnosis.ConclusionsMost participants correctly answered questions about the breast cancer mortality benefit and false positive results associated with screening. The proportion of correct responses to questions about overdiagnosis was modest, indicating that conceptual knowledge about overdiagnosis was lower. Qualitative studies that can obtain in-depth information about women's understanding of overdiagnosis may help improve Norwegian-language information about this challenging topic.

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A new perspective on breast cancer diagnostic guidelines to reduce overdiagnosis

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