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The Role of Regular Mammograms in Finding Interval Breast Cancer

2020· article· en· W3112492529 on OpenAlexaboutno aff
Amy Gallagher

Bibliographic record

VenueOncology Times · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerMammographyCancerBreast cancer screeningOverdiagnosisIncidence (geometry)OncologyMammography screeningGynecologyInternal medicineMedical physics

Abstract

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Mammogram: MammogramStrategies beyond current mammographic screening practices are needed to reduce incidence, improve detection, and reduce deaths from interval breast cancers, according to a conclusive statement from a research study led by author Saroj Niraula, MD, MSc, a medical oncologist at CancerCare Manitoba and Assistant Professor at the University of Manitoba, Winnipeg, Canada. “While screenings are based on noble principles, they do have harms,” said Niraula. “By and large, mammogram screenings are for healthy people.” Accumulating 6 years of research data, the comparative study analyzed breast cancer tumor characteristics diagnosed within 2 years of normal screening mammogram, referred to as “interval” with respect to interval breast cancer (IBC), with screen-detected breast cancers (SBC) to identify the tumor differences and similarities in characteristics, incidences, and outcomes of breast cancer-specific mortality of IBC with SBC. IBC is the cancer detected after a normal screening mammogram and prior to the next scheduled mammogram. “By its very definition, IBC defies assumptions necessary for screening mammography to be maximally effective,” he said. “A regular mammogram screening does not improve the outcome of an IBC because it does not capture it.” Challenging the Effectiveness of Screenings The researcher's results shed light on the heterogeneity of breast cancer that poses three assumptions to prove the effectiveness of mammographic screening: 1) breast cancer likely grows in anatomic linearity starting in the breast, then metastasizes to distant organs mostly via regional lymph nodes; 2) breast cancers are mostly mammogram-sensitive; and 3) frequency of screening is coherent with natural history of breast cancer so that most cancers, particularly the more lethal and/or treatable ones, are detected early by screening. “These conditions must be fulfilled for a mammogram screening to be effective,” said Niraula. “Because IBC is not detected by regular screenings, the question then becomes: Is the balance of benefit and the risk of only detecting SBC favorable enough?” Evidence collected from the study suggests that breast cancer represents a heterogeneous group of highly indolent to fatally aggressive conditions, which presents as a major impediment in the effectiveness of mammographic screening. Study Design, Setting & Participants In this registry-based cohort study, Niraula and his team collected data about relevant tumor- and patient-related variables on women diagnosed with breast cancer between January 2004 and June 2010 who participated in the population-based screening program in Manitoba, Canada, and those diagnosed with breast cancer outside the screening program in the province. “We performed multinomial logistic regression analysis to assess tumor and patient characteristics associated with a diagnosis of IBC compared with SBC, while competing risk analysis was performed to examine risk of death by cancer detection method,” Niraula explained. The cohort of 69,025 women showed that IBCs accounted for one-fourth of breast cancers in routinely screened women, were 6 times more likely to be grade 3, and had 3.5 times increased hazards of breast cancer death compared with screen-detected cancers. Main Outcomes & Measures Niraula stated that, of the 1,687 women diagnosed with breast cancer, 705 were detected during the regular screening, with 206 diagnosed in-between screenings, thus the IBC when the cancer develops between the two mammogram screenings. “This means that one-third of the patient cohort was IBC; 1 in 3 undiagnosed patients that are categorically more aggressive is unacceptable,” he said. “These are the patients who are dying.” The IBC patient is 4 times more likely to die; the outcome for the IBC patient is looking terrible, added Niraula. The results in differences in tumor characteristics and breast cancer–specific mortality showed that, after a median follow-up of 7 years, 170 women had died from breast cancer and 55 women died of other causes. Of the breast cancer deaths, 20 had SBC, 29 had IBC, 27 were noncompliant, and 94 were non–screening program detected. Survival analysis demonstrated that, for a sojourn time of 2 years, the unadjusted risk of death from breast cancer was significantly higher for IBC compared with SBC (HR 3.55; 95% CI, 2.01-6.28). Compared with SBC, IBC was more likely to be of high grade and estrogen receptor-negative (odds ratios, 6.33 [95% CI, 3.73-10.75; P < 0.001] and 2.88 [95% CI, 2.01-4.13; P < 0.001], respectively). Breast cancer-specific mortality was higher for IBC during a median follow-up of 7 years compared with SBC. Conclusions & Relevance In this cohort study, IBCs were highly prevalent in women participating in population screening, represented a worse biology, and had a hazard for breast cancer death more than 3 times that for SBC. “Improvement of breast cancer deaths and overall population mortality requires strategies above and beyond conventional screening mammography,” said Niraula. Such strategies could be personalized screening strategies individualizing the screening test based on baseline risks; exploring other methods (e.g., tomosynthesis, magnetic resonance imaging after carefully defining target population, and demonstrating in clinical trials that these approaches improve outcomes at acceptable level of harms); use of artificial intelligence platforms to empower radiology professionals (our group is involved in one); a different frequency of screening, with attention to potential for and consequences of over diagnosis; and being open for reevaluation of population-based screening mammography concept based on risk-benefit ratio in the contemporary context. In an action step to improve screening strategies, Niraula plans to expand the population of this study, looking at trends nationally, or perhaps a comparative analysis internationally with other countries. Amy Gallagher is a contributing writer. A Collection of Articles on Breast Cancer Review the latest research and stay up-to-date on new treatments for breast cancer. Sign up to be notified every time a new item is added. Explore the online collection at https://bit.ly/36tkjiE.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.348
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
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