Prevalence of Subclinical Papillary Thyroid Cancer by Age: Meta-analysis of Autopsy Studies

It is not known how underlying subclinical papillary thyroid cancer (PTC) differs by age. This meta-analysis of autopsy studies investigates how subclinical PTC prevalence changes over the lifetime. Methods: We searched PubMed, Embase, and Web of Science databases from inception to May 2021 for studies that reported the prevalence of PTC found at autopsy. Two investigators extracted the number of subclinical PTCs detected in selected age groups and extent of examination. A quality assessment tool was used to assess bias. Logistic regression models with random intercepts were used to pool the age-specific subclinical PTC prevalence estimates. Results: Of 1773 studies screened, 16 studies with age-specific data met the inclusion criteria (n = 6286 autopsies). The pooled subclinical PTC prevalence was 12.9% (95% CI 7.8-16.8) in whole gland and 4.6% (2.5- 6.6) in partial gland examination. Age-specific prevalence estimates were ≤40 years, 11.5% (6.8-16.1); 41-60 years, 12.1% (7.6-16.5); 61-80 years, 12.7% (8-17.5); and 81+ years, 13.4% (7.9-18.9). Sex did not affect age-specific prevalence and there was no difference in prevalence between men and women in any age group. In the regression model, the OR of prevalence increasing by age group was 1.06 (0.92-1.2, P = .37). Conclusion: This meta-analysis shows the prevalence of subclinical PTC is stable across the lifespan. There is not a higher subclinical PTC prevalence in middle age, in contrast to higher observed incidence rates in this age group. These findings offer unique insights into the prevalence of subclinical PTC and its relationship to age

Effect of time to diagnostic testing for breast, cervical, and colorectal cancer screening abnormalities on screening efficacy: A modeling study

Background: Patients who receive an abnormal cancer screening result require follow-up for diagnostic testing, but the time to follow-up varies across patients and practices. Methods: We used a simulation study to estimate the change in lifetime screening benefits when time to follow-up for breast, cervical, and colorectal cancers was increased. Estimates were based on four independently developed microsimulation models that each simulated the life course of adults eligible for breast (women ages 50–74 years), cervical (women ages 21–65 years), or colorectal (adults ages 50–75 years) cancer screening. We assumed screening based on biennial mammography for breast cancer, triennial Papanicolaou testing for cervical cancer, and annual fecal immunochemical testing for colorectal cancer. For each cancer type, we simulated diagnostic testing immediately and at 3, 6, and 12 months after an abnormal screening exam. Results: We found declines in screening benefit with longer times to diagnostic testing, particularly for breast cancer screening. Compared to immediate diagnostic testing, testing at 3 months resulted in reduced screening benefit, with fewer undiscounted life years gained per 1,000 screened (breast: 17.3%, cervical: 0.8%, colorectal: 2.0% and 2.7%, from two colorectal cancer models), fewer cancers prevented (cervical: 1.4% fewer, colorectal: 0.5% and 1.7% fewer, respectively), and, for breast and colorectal cancer, a less favorable stage distribution. Conclusions: Longer times to diagnostic testing after an abnormal screening test can decrease screening effectiveness, but the impact varies substantially by cancer type. Impact: Understanding the impact of time to diagnostic testing on screening effectiveness can help inform quality improvement efforts. Cancer Epidemiol Biomarkers Prev; 27(2); 158–64. 2017 AACR

Modeling Ductal Carcinoma In Situ (DCIS): An Overview of CISNET Model Approaches

Background. Ductal carcinoma in situ (DCIS) can be a precursor to invasive breast cancer. Since the advent of screening mammography in the 1980’s, the incidence of DCIS has increased dramatically. The value of screen detection and treatment of DCIS, however, is a matter of controversy, as it is unclear the extent to which detection and treatment of DCIS prevents invasive disease and reduces breast cancer mortality. The aim of this paper is to provide an overview of existing Cancer Intervention and Surveillance Modelling Network (CISNET) modeling approaches for the natural history of DCIS, and to compare these to other modeling approaches reported in the literature. Design. Five of the 6 CISNET models currently include DCIS. Most models assume that some, but not all, lesions progress to invasive cancer. The natural history of DCIS cannot be directly observed and the CISNET models differ in their assumptions and in the data sources used to estimate the DCIS model parameters. Results. These model differences translate into variation in outcomes, such as the amount of overdiagnosis of DCIS, with estimates ranging from 34% to 72% for biennial screening from ages 50 to 74 y. The other models described in the literature also report a large range in outcomes, with progression rates varying from 20% to 91%. Limitations. DCIS grade was not yet included in the CISNET models. Conclusion. In the future, DCIS data by grade from active surveillance trials, the development of predictive markers of progression probability, and evidence from other screening modalities, such as tomosynthesis, may be used to inform and improve the models’ representation of DCIS, and might lead to convergence of the model estimates. Until then, the CISNET model results consistently show a considerable amount of overdiagnosis of DCIS, supporting the safety and value of observational trials for low-risk DCIS

Breast Cancer Screening Among Childhood Cancer Survivors Treated Without Chest Radiation: Clinical Benefits and Cost-Effectiveness

BACKGROUND: Early initiation of breast cancer screening is recommended for high-risk women, including survivors of childhood cancer treated with chest radiation. Recent studies suggest that female survivors of childhood leukemia or sarcoma treated without chest radiation are also at elevated early onset breast cancer risk. However, the potential clinical benefits and cost-effectiveness of early breast cancer screening among these women are uncertain. METHODS: Using data from the Childhood Cancer Survivor Study, we adapted 2 Cancer Intervention and Surveillance Modeling Network simulation models to reflect the elevated risks of breast cancer and competing mortality among leukemia and sarcoma survivors. Costs and utility weights were based on published studies and databases. Outcomes included breast cancer deaths averted, false-positive screening results, benign biopsies, and incremental cost-effectiveness ratios. RESULTS: In the absence of screening, the lifetime risk of dying from breast cancer among survivors was 6.8% to 7.0% across models. Early initiation of annual mammography with breast magnetic resonance imaging screening between ages 25 and 40 years would avert 52.6% to 64.3% of breast cancer deaths. When costs and quality-of-life impacts were considered, screening starting at age 40 years was the only strategy with an incremental cost-effectiveness ratio below the $100 000 per quality-adjusted life-year (QALY) gained cost-effectiveness threshold ($27 680 to $44 380 per QALY gained across models). CONCLUSIONS: Among survivors of childhood leukemia or sarcoma, early initiation of breast cancer screening at age 40 years may reduce breast cancer deaths by half and is cost-effective. These findings could help inform screening guidelines for survivors treated without chest radiation

Tailoring breast cancer screening intervals by breast density and risk for women aged 50 years or older: Collaborative modeling of screening outcomes

Background: Biennial screening is generally recommended for average-risk women aged 50 to 74 years, but tailored screening may provide greater benefits. Objective: To estimate outcomes for various screening intervals after age 50 year

Benefits, harms, and costs for breast cancer screening after US implementation of digital mammography

Background Compared with film, digital mammography has superior sensitivity but lower specificity for women aged 40 to 49 years and women with dense breasts. Digital has replaced film in virtually all US facilities, but overall population health and cost from use of this technology are unclear. Methods Using five independent models, we compared digital screening strategies starting at age 40 or 50 years applied annually, biennially, or based on density with biennial film screening from ages 50 to 74 years and with no screening. Common data elements included cancer incidence and test performance, both modified by breast density. Lifetime outcomes included mortality, quality-adjusted life-years, and screening and treatment costs. Results For every 1000 women screened biennially from age 50 to 74 years, switching to digital from film yielded a median within-model improvement of 2 life-years, 0.27 additional deaths averted, 220 additional false-positive results, and $0.35 million more in costs. For an individual woman, this translates to a health gain of 0.73 days. Extending biennial digital screening to women ages 40 to 49 years was cost-effective, although results were sensitive to quality-of-life decrements related to screening and false positives. Targeting annual screening by density yielded similar outcomes to targeting by age. Annual screening approaches could increase costs to$5.26 million per 1000 women, in part because of higher numbers of screens and false positives, and were not efficient or cost-effective. Conclusions The transition to digital breast cancer screening in the United States increased total costs for small added health benefits. The value of digital mammography screening among women aged 40 to 49 years depends on women's preferences regarding false positives

Collaborative modeling of the benefits and harms associated with different U.S. Breast cancer screening strategies

Background: Controversy persists about optimal mammography screening strategies. Objective: To evaluate screening outcomes, taking into account advances in mammography and treatment of breast cancer. Design: Collaboration of 6 simulation models using national data on incidence, digital mammography performance, treatment effects, and other-cause mortality. Setting: United States. Patients: Average-risk U.S. female population and subgroups with varying risk, breast density, or comorbidity. Intervention: Eight strategies differing by age at which screening starts (40, 45, or 50 years) and screening interval (annual, biennial, and hybrid [annual for women in their 40s and biennial thereafter]). All strategies assumed 100% adherence and stopped at age 74 years. Measurements: Benefits (breast cancer-specific mortality reduction, breast cancer deaths averted, life-years, and qualityadjusted life-years); number of mammograms used; harms (false-positive results, benign biopsies, and overdiagnosis); and ratios of harms (or use) and benefits (efficiency) per 1000 screens. Results: Biennial strategies were consistently the most efficient for average-risk women. Biennial screening from age 50 to 74 years avoided a median of 7 breast cancer deaths versus no screening; annual screening from age 40 to 74 years avoided an additional 3 deaths, but yielded 1988 more false-positive results and 11 more overdiagnoses per 1000 women screened. Annual screening from age 50 to 74 years was inefficient (similar bene-fits, but more harms than other strategies). For groups with a 2-to 4-fold increased risk, annual screening from age 40 years had similar harms and benefits as screening average-risk women biennially from 50 to 74 years. For groups with moderate or severe comorbidity, screening could stop at age 66 to 68 years. Limitation: Other imaging technologies, polygenic risk, and nonadherence were not considered. Conclusion: Biennial screening for breast cancer is efficient for average-risk populations. Decisions about starting ages and intervals will depend on population characteristics and the decision makers' weight given to the harms and benefits of screening