Changes in Breast Cancer Risk Associated with Benign Breast Disease from 1967 to 2013.

Background: Benign breast disease (BBD) increases breast cancer (BC) risk progressively for women diagnosed with non-proliferative (NP) change, proliferative disease without atypia (PDWA), and atypical hyperplasia (AH). Leveraging data from 18,704 women in the Mayo BBD Cohort (1967-2013), we evaluated temporal trends in BBD diagnoses and how they have influenced associated BC risk over four decades.

Methods: BC risk trends associated with BBD were evaluated using standardized incidence ratios (SIRs) and age-period-cohort modeling across four eras-pre-mammogram (1967-1981), pre-core needle biopsy (CNB) (1982-1992), transition to CNB (1993-2001), and CNB era (2002-2013).

A Literature Review and Pooled Case Analysis of Cardiofaciocutaneous Syndrome to Estimate Cancer Risk.

Background: Cardiofaciocutaneous syndrome (CFC) is a rare disorder with multiple congenital anomalies including macrocephaly, failure to thrive, and neurocognitive delay. CFC is part "RASopathy" syndromes caused by pathogenic germline variants in and To estimate cancer risk in CFC we conducted a systematic review using case reports and series.

Methods: We reviewed articles and abstracted CFC cases to form a retrospective cohort based on PRISMA guidelines.

Does Sex Matter? Temporal Analyses of Melanoma Trends among Men and Women Suggest Etiologic Heterogeneity.

The incidence and distribution of cutaneous melanoma differ between the sexes, but it is unclear whether these differences have been constant through time or across generations. We compared incidence trends by age, sex, and anatomic site by analyzing long-term melanoma data (1982-2018) in 3 populations residing at high-, moderate-, and low-ambient sun exposure: Queensland, Australia; United States White; and Scotland. We fit age-period-cohort models and compared trends in the male-to-female incidence rate ratio by site and sex.

Cancer Incidence Trends in Successive Social Generations in the US.

Importance: The incidence of some cancers in the US is increasing in younger age groups, but underlying trends in cancer patterns by birth year remain unclear.

Objective: To estimate cancer incidence trends in successive social generations.

Design, Setting, And Participants: In this cohort study, incident invasive cancers were ascertained from the Surveillance, Epidemiology, and End Results (SEER) program's 13-registry database (November 2020 submission, accessed August 14, 2023).

Prognostic Value of Fibroblast Growth Factor Receptor Genetic Alterations in Metastatic Urothelial Carcinoma.

Introduction: Evidence is limited on whether fibroblast growth factor receptor gene alterations (FGFRalt) impact clinical outcomes in patients with locally advanced or metastatic urothelial cancer (mUC). This study evaluated progression-free survival (PFS) in patients with mUC based on FGFRalt status in the first-line setting (1L).

Patients And Methods: Data on mUC patients were retrieved via convenience sampling of oncologists/urologists surveyed between August and September 2020 who treated at least 1 FGFRalt patient between July 2017 and June 2019.

Advances in statistical methods for cancer surveillance research: an age-period-cohort perspective.

Background: Analysis of Lexis diagrams (population-based cancer incidence and mortality rates indexed by age group and calendar period) requires specialized statistical methods. However, existing methods have limitations that can now be overcome using new approaches.

Methods: We assembled a "toolbox" of novel methods to identify trends and patterns by age group, calendar period, and birth cohort.

Projected Incidence of Hepatobiliary Cancers and Trends Based on Age, Race, and Gender in the United States.

Background: Identifying the projected incidence of hepatobiliary cancers and recognizing patient cohorts at increased risk can help develop targeted interventions and resource allocation. The expected incidence of subtypes of hepatobiliary cancers in different age groups, races, and genders remains unknown.

Methods: Historical epidemiological data from the Surveillance, Epidemiology, and End Results (SEER) database was used to project future incidence of hepatobiliary malignancies in the United States and identify trends by age, race, and gender.

Effects of stopping criterion on the growth of trees in regression random forests.

Random forests are a powerful machine learning tool that capture complex relationships between independent variables and an outcome of interest. Trees built in a random forest are dependent on several hyperparameters, one of the more critical being the node size. The original algorithm of Breiman, controls for node size by limiting the size of the parent node, so that a node cannot be split if it has less than a specified number of observations.

Eita! Reaching Communities and Young People to Drive Demand for Oral Pre-Exposure Prophylaxis in South Africa.

Purpose: This paper describes a holistic but flexible demand creation strategy for pre-exposure prophylaxis (PrEP) in national public health-care settings in low-income to middle-income countries.

Methods: We describe the development and implementation of a model to drive demand for oral PrEP uptake and use as part of comprehensive sexual and reproductive health services in South Africa: The Eita!

Model: The project adapted two existing response hierarchy models (marketing models used to describe the stages individuals move through from being unaware to using a product), to formulate the Eita!

Model: Using the RE-AIM framework, we report on the reach, effectiveness, adoption, implementation, and maintenance of the Eita!

Results: More than 34 million connections were made from December 2018 to 2021 through a variety of channels: social media and websites, at events and mobile clinic outreach, and radio and community dialogs. There were 42,447 adolescent girls and young women reached in-person during this time, 16,823 adolescent girls and young women presented for sexual and reproductive health services, and of those 14,637 (87%) initiated on PrEP.

Comparative age-period-cohort analysis.

Background: Cancer surveillance researchers analyze incidence or mortality rates jointly indexed by age group and calendar period using age-period-cohort models. Many studies consider age- and period-specific rates in two or more strata defined by sex, race/ethnicity, etc. A comprehensive characterization of trends and patterns within each stratum can be obtained using age-period-cohort (APC) estimable functions (EF).

Smoothing Lexis diagrams using kernel functions: A contemporary approach.

Lexis diagrams are rectangular arrays of event rates indexed by age and period. Analysis of Lexis diagrams is a cornerstone of cancer surveillance research. Typically, population-based descriptive studies analyze multiple Lexis diagrams defined by sex, tumor characteristics, race/ethnicity, geographic region, etc.

Global epidemiologic patterns of oropharyngeal cancer incidence trends.

Background: The emergence of human papillomavirus (HPV)-positive oropharyngeal cancer and evolving tobacco use patterns have changed the landscape of head and neck cancer epidemiology internationally. We investigated updated trends in oropharyngeal cancer incidence worldwide.

Methods: We analyzed cancer incidence data between 1993 and 2012 from 42 countries using the Cancer Incidence in Five Continents database volumes V through XI.

Alternative stopping rules to limit tree expansion for random forest models.

Random forests are a popular type of machine learning model, which are relatively robust to overfitting, unlike some other machine learning models, and adequately capture non-linear relationships between an outcome of interest and multiple independent variables. There are relatively few adjustable hyperparameters in the standard random forest models, among them the minimum size of the terminal nodes on each tree. The usual stopping rule, as proposed by Breiman, stops tree expansion by limiting the size of the parent nodes, so that a node cannot be split if it has less than a specified number of observations.

Incidence of in Situ vs Invasive Melanoma: Testing the "Obligate Precursor" Hypothesis.

Background: Melanoma incidence has been rising in populations with predominantly European ancestry (White), speculated to be partly driven by heightened detection of indolent tumors. If in situ melanomas are destined to evolve to invasive cancers, detecting and removing them should deplete the pool of invasive lesions, and people with in situ melanoma should, on average, be younger than those with invasive melanoma.

Methods: We analyzed long-term incidence trends (1982-2018) for in situ and invasive melanomas in 3 predominantly White populations with high, medium, and low melanoma rates: Queensland (Australia), United States White, and Scotland.

Reverse engineering the FRAX algorithm: Clinical insights and systematic analysis of fracture risk.

The Fracture Risk Assessment Tool (FRAX) is a computational tool developed to predict the 10-year probability of hip fracture and major osteoporotic fracture based on inputs of patient characteristics, bone mineral density (BMD), and a set of seven clinical risk factors. While the FRAX tool is widely available and clinically validated, its underlying algorithm is not public. The relative contribution and necessity of each input parameter to the final FRAX score is unknown.

Decreasing Incidence of Estrogen Receptor-Negative Breast Cancer in the United States: Trends by Race and Region.

Background: Incidence of estrogen receptor (ER)-negative breast cancer, an aggressive subtype, is highest in US African American women and in Southern residents but has decreased overall since 1992. We assessed whether ER-negative breast cancer is decreasing in all age groups and cancer registries among non-Hispanic White (NHW), non-Hispanic Black (NHB), and Hispanic White (HW) women.

Methods: We analyzed 17 Surveillance, Epidemiology, and End-Results (SEER) Program registries (12 for 1992-2016; 5 for 2000-2016) to assess NHW, NHB, and HW trends by ER status and age group (30-39 years, 40-49 years, 50-69 years, 70-84 years).

Geographic disparities of breast cancer incidence in Portugal at the district level: A spatial age-period-cohort analysis, 1998-2011.

Background: Breast cancer is the most common malignancy in women world-wide and the most common cause of cancer deaths, which can often be managed with early diagnosis and subsequent treatment. Here, we focus on geographic disparities in incidence within Portugal for three age groups of women (30-49; 50-69; 70-84 years).

Methods: Age-period-cohort (APC) models are widely used in cancer surveillance, and these models have recently been extended to allow spatially-varying effects.

A Genome-First Approach to Characterize DICER1 Pathogenic Variant Prevalence, Penetrance, and Phenotype.

Importance: Genetic disorders are historically defined through phenotype-first approaches. However, risk estimates derived from phenotype-linked ascertainment may overestimate severity and penetrance. Pathogenic variants in DICER1 are associated with increased risks of rare and common neoplasms and thyroid disease in adults and children.