The Covid-19 pandemic has interrupted and disrupted the delivery of health care on many levels. This was particularly evident with breast cancer screening and diagnostic imaging as mammograms were postponed.
“As Covid-19 case rates continue to increase in waves, radiology facilities face significant scheduling challenges in addressing the backlog of postponed mammograms, reduced staff, and reduced number of mammogram appointment times required to maintain physical distancing and safety protocols, resulting in markedly diminished imaging availability,” Diana L. Miglioretti, PhD, from the Division of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, and colleagues wrote in JAMA Network Open.
But if Covid-19 has taught the medical community anything, it is how to pivot and find new ways for care delivery — for example, moving to more virtual care via telehealth. Although breast cancer screening cannot be done remotely, Miglioretti and colleagues asked if there was a way to triage patients who were more at risk for developing breast cancer and getting them their needed mammograms during times when facilities are operating at a decreased capacity, such as during a pandemic.
These researchers undertook a population-based cohort study based on data culled from mammography exams performed from 2014 to 2019 at 92 radiology facilities in the Breast Cancer Surveillance Consortium; they analyzed data from 898,415 individuals, comprising 1,878,924 mammograms. They looked at “clinical indications and individual characteristics associated with high, moderate, and low cancer detection rates,” and developed a risk stratification that facilities could use during times of limited capacity.
“Clinicians could use our results to counsel individuals about how urgently they should seek breast imaging based on their breast symptoms, breast cancer history, age, and time since last mammogram,” Miglioretti and colleagues wrote. “We demonstrate that triaging individuals at highest risk of having cancer detected could result in detecting the most cancers while performing the fewest examinations compared with a non–risk based approach. For example, a non–risk-based approach resulted in 11.5 cancers detected per 1,000 mammograms (corresponding to the overall cancer detection rate in our study) while a risk-based approach limiting to the 12.1% of mammograms with high or very high risk of cancer detection detected 55.0%of cancers and resulted in at least a 3- to 10-fold greater cancer detection rate (36-122 cancers per 1,000 mammograms). In contrast, the cancer detection rate for the 44.2% of mammograms with the lowest risk was 3.8 cancers or less per 1000 and accounted for 13.1% of detected cancers. The low cancer detection rate in these individuals should be considered, along with patient preferences, when deciding about the safety of postponing imaging owing to limited capacity, such as during pandemic surges when individuals may also experience risks and anxiety about contracting an infectious disease.”
But is this approach practical?
Sarah M. Friedewald, MD, and Dipti Gupta, MD, both from the Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, noted in an accompanying editorial that in a pandemic setting, the triage parameters set out by Miglioretti and colleagues might not be doable.
“[I]n the context of an acute crisis when a rapid reduction in patient volume is needed, it often is impractical for clinicians to sift through patient records to capture the information needed to triage,” Friedewald and Gupta wrote. “Furthermore, asking nonclinical schedulers to be adept at culling data at this level at the time the patient calls to make an appointment is unrealistic. Although a series of predetermined questions could be asked of the patient regarding their personal history and reason for examination to ease the burden on schedulers, this system is vulnerable to patients who provide inaccurate or incomplete information.”
They noted that the Society of Breast Imaging, the American College of Breast Surgeons, and the American College of Radiology recommended that all screenings be postponed until the pandemic was under control.
The editorialists also pointed out that risk/benefit analyses in screening also need to take into account the risk patients may have of contracting Covid-19.
“An older patient is at a higher risk for breast cancer and is also at a higher risk for Covid-19–related complications,” they wrote. “On the other hand, a younger woman with early detection of a breast cancer by screening mammography who is less likely to die of infection with SARS-CoV-2 would gain more life-years than an older patient.”
Friedewald and Gupta also noted that patients have been avoiding going to emergency departments during the pandemic even when having strokes or heart attacks, “leading to potentially preventable morbidity and mortality. The downstream effect of delaying cancer diagnosis may similarly lead to unintended consequences but may take longer to become apparent.”
Moreover, they wrote that operational constraints may deter offering screenings, and that “subcategorizing patients based on risk may lead ot underuse of facilities that could accommodate more patients. For example, a screening-only facility offering appointments to patients with moderate to very high risk of breast cancer would be minimally used (4.8% of all patients).”
Miglioretti and colleagues reported that in their study, the nearly two million mammograms were interpreted by 448 radiologists, and 1,722,820 of those were in individuals without a personal history of breast cancer, and 156,104 mammograms in those with a history of breast cancer. The mean age (standard deviation) was 58.6 (11.2) years at mammogram.
For imaging, most were age 50-69 years: “(1,113,174 mammograms [59.2%]), and 204 305 (11.2%) were Black, 206 087 (11.3%) were Asian or Pacific Islander, 126 677 (7.0%) were Hispanic or Latina, and 40,021 (2.2%) were another race/ethnicity or mixed race/ethnicity,” the study authors wrote.
There was a wide variety of cancer detection rates when clinical indication, breast symptoms, personal history of breast cancer, and age were taken into account.
“The 12% of mammograms with very high (89.6 [95%CI, 82.3-97.5] to 122.3 [95%CI, 108.1-138.0] cancers detected per 1,000 mammograms) or high (36.1 [95%CI, 33.1-39.3] to 47.5 [95%CI, 42.4-53.3] cancers detected per 1,000 mammograms) cancer detection rates accounted for 55% of all detected cancers and included mammograms to evaluate an abnormal mammogram or breast lump in individuals of all ages regardless of breast cancer history, to evaluate breast symptoms other than lump in individuals with of all ages regardless of breast cancer history, to evaluate breast symptoms other than lump in individuals with a breast cancer history or without a history but aged 60 years or older, and for short-interval follow-up in individuals aged 60 years or older without a breast cancer history.
“The 44.2% of mammograms with very low cancer detection rates accounted for 13.1% of detected cancers and included annual screening mammograms in individuals aged 50 to 69 years (3.8 [95%CI, 3.5-4.1] cancers detected per 1,000 mammograms) and all screening mammograms in individuals younger than 50 years regardless of screening interval (2.8 [95%CI, 2.6-3.1] cancers detected per 1,000 mammograms),” they wrote.
Despite the hurdles pointed out by the editorialists, Miglioretti and colleagues wrote that triaging by risk for breast cancer complements the American College of Radiology’s “Return to Mammography Care” toolkit with evidence supporting risk-based scheduling.
Limitations of their study include the fact that not all facilities collect of the risk factors used in their models. They also pointed out, as did the editorialists, that their algorithms did not consider personal preferences or worries about contracting either cancer or Covid-19.
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Compared with a non–risk based approach, triaging individuals at highest risk of having cancer detected could result in mammography detecting the most cancers while performing the fewest examinations.
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This model could be used when incidents such as a pandemic limit capacity of screening and diagnostic clinics.
Candace Hoffmann, Managing Editor, BreakingMED™
This work was supported through a Patient-Centered Outcomes Research Institute program award (No. PCS-1504-30370). Data collection for this research was additionally supported by the Breast Cancer Surveillance Consortium with funding from the National Cancer Institute (grants P01CA154292, U54CA163303), the Agency for Healthcare Research and Quality (grant No. R01 HS018366-01A1) and the University of Vermont Cancer Center with funds awarded by the Lake Champlain Cancer Research Organization (grant No. 032800). The collection of Sacramento Area Breast Imaging Registry data was supported by the UC Davis Comprehensive Cancer Center, the Placer County Breast Cancer Foundation, and the UC Davis Clinical and Translational Science Center. Cancer and vital status data collection was supported by several state public health departments and cancer registries.
Miglioretti reported receiving royalties from Elsevier outside the submitted work.
Friedewald reported receiving grants from Hologic Research during the conduct of the study.
Cat ID: 22
Topic ID: 78,22,730,22,691,192,925
