Calendar-period trends in cervical precancer and cancer diagnoses since the introduction of human papillomavirus and cytology co-testing into routine cervical cancer screening at Kaiser Permanente Northern California.

OBJECTIVES: The longer-term impact of introducing human papillomavirus (HPV) testing into routine cervical cancer screening on precancer and cancer rates by histologic type has not been well described. Calendar trends in diagnoses were examined using data from Kaiser Permanente Northern California, which introduced triennial HPV and cytology co-testing in 2003 for women aged ≥30 years. METHODS: We examined trends in cervical precancer (cervical intraepithelial neoplasia grade 3 [CIN3] and adenocarcinoma in situ [AIS]) and cancer (squamous cell carcinoma [SCC] and adenocarcinoma [ADC]) diagnoses per 1000 screened during 2003-2018. We examined ratios of squamous vs. glandular diagnoses (SCC:ADC and CIN3:AIS). RESULTS: CIN3 and AIS diagnoses increased approximately 2% and 3% annually, respectively (ptrend < 0.001 for both). While SCC diagnoses decreased by 5% per annually (ptrend < 0.001), ADC diagnoses did not change. These patterns were generally observed within each age group (30-39, 40-49, and 50-64 years). ADC diagnoses per 1000 screened did not change even among those who underwent co-testing starting in 2003-2006. SCC:ADC decreased from approximately 2.5:1 in 2003-2006 to 1.3:1 in 2015-2018 while the CIN3:AIS remained relatively constant, ∼10:1. CONCLUSIONS: Since its introduction at KPNC, co-testing increased the detection of CIN3 over time, which likely caused a subsequent reduction of SCC. However, there has been no observed decrease in ADC. One possible explanation for lack of effectiveness against ADC is the underdiagnosis of AIS. Novel strategies to identify and treat women at high risk of ADC need to be developed and clinically validated.

Anal Cancer and Anal Cancer Screening.

This chapter provides an overview of anal cancer and contemporary approaches for anal precancer detection, beginning with a discussion of the biology and natural history of anal squamous cell carcinoma, the predominant human papillomavirus -associated histologic subtype of anal cancer. This section is followed by a description of the epidemiology of anal cancer, including trends in incidence and mortality, a discussion of populations with elevated risk for anal cancer and an overview of associated risk factors. The remainder of the chapter provides the most up-to-date evidence on tools and approaches for anal cancer prevention, screening, and early detection; including, the role of human papillomavirus vaccination for primary prevention; anal cytology, high resolution anoscopy and novel biomarkers for secondary prevention; and digital anal-rectal examination for early detection.

Automated Evaluation of p16/Ki-67 Dual-Stain Cytology as a Biomarker for Detection of Anal Precancer in Men Who Have Sex With Men and Are Living With Human Immunodeficiency Virus.

BACKGROUND: Human papillomavirus-related biomarkers such as p16/Ki-67 "dual-stain" (DS) cytology have shown promising clinical performance for anal cancer screening. Here, we assessed the performance of automated evaluation of DS cytology (automated DS) to detect anal precancer in men who have sex with men (MSM) and are living with human immunodeficiency virus (HIV). METHODS: We conducted a cross-sectional analysis of 320 MSM with HIV undergoing anal cancer screening and high-resolution anoscopy (HRA) in 2009-2010. We evaluated the performance of automated DS based on a deep-learning classifier compared to manual evaluation of DS cytology (manual DS) to detect anal intraepithelial neoplasia grade 2 or 3 (AIN2+) and grade 3 (AIN3). We evaluated different DS-positive cell thresholds quantified by the automated approach and modeled performance compared with other screening strategies in a hypothetical population of MSM with HIV. RESULTS: Compared with manual DS, automated DS had significantly higher specificity (50.9% vs 42.2%; P < .001) and similar sensitivity (93.2% vs 92.1%) for detection of AIN2+. Human papillomavirus testing with automated DS triage was significantly more specific than automated DS alone (56.5% vs 50.9%; P < .001), with the same sensitivity (93.2%). In a modeled analysis assuming a 20% AIN2+ prevalence, automated DS detected more precancers than manual DS and anal cytology (186, 184, and 162, respectively) and had the lowest HRA referral rate per AIN2+ case detected (3.1, 3.5, and 3.3, respectively). CONCLUSIONS: Compared with manual DS, automated DS detects the same number of precancers, with a lower HRA referral rate.

Racial and Ethnic Disparities in Cervical Cancer Incidence, Survival, and Mortality by Histologic Subtype.

PURPOSE: We conducted an integrated population-based analysis of histologic subtype-specific cervical cancer incidence, survival, and incidence-based mortality by race and ethnicity, with correction for hysterectomy prevalence. METHODS: Using the SEER 21 and 18 registries, we selected primary cases of malignant cervical cancer diagnosed among women ≥ 15 years. We evaluated age-adjusted incidence rates among cases diagnosed between 2000 and 2018 (SEER21) and incidence-based mortality rates among deaths from 2005 to 2018 (SEER18), per 100,000 person-years. Rates were stratified by histologic subtype and race/ethnicity (incidence and mortality), and stage, age at diagnosis, and county-level measures of social determinants of health (incidence only). Incidence and mortality rates were corrected for hysterectomy using data from the Behavioral Risk Factor Surveillance System. We estimated 5-year relative survival by histologic subtype and stratified by stage at diagnosis. RESULTS: Incidence rates of cervical squamous cell carcinoma were highest in Black and Hispanic women, while incidence rates of cervical adenocarcinoma (ADC) were highest among Hispanic and White women, particularly for localized ADC. County-level income and education variables were inversely associated with squamous cell carcinoma incidence rates in all racial and ethnic groups but had less influence on ADC incidence rates. Black women had the highest overall mortality rates and lowest 5-year relative survival, irrespective of subtype and stage. Disparities in survival were particularly pronounced for Black women with regional and distant ADC, compared with other racial/ethnic groups. CONCLUSION: Although Black women are less likely to be diagnosed with ADC compared with all other racial/ethnic groups, they experience the highest mortality rates for this subtype, likely attributed to the poor survival observed for Black women with regional and distant ADC.

Opportunities, challenges, and future directions for simulation modeling the effects of structural racism on cancer mortality in the United States: a scoping review.

PURPOSE: Structural racism could contribute to racial and ethnic disparities in cancer mortality via its broad effects on housing, economic opportunities, and health care. However, there has been limited focus on incorporating structural racism into simulation models designed to identify practice and policy strategies to support health equity. We reviewed studies evaluating structural racism and cancer mortality disparities to highlight opportunities, challenges, and future directions to capture this broad concept in simulation modeling research. METHODS: We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension guidelines. Articles published between 2018 and 2023 were searched including terms related to race, ethnicity, cancer-specific and all-cause mortality, and structural racism. We included studies evaluating the effects of structural racism on racial and ethnic disparities in cancer mortality in the United States. RESULTS: A total of 8345 articles were identified, and 183 articles were included. Studies used different measures, data sources, and methods. For example, in 20 studies, racial residential segregation, one component of structural racism, was measured by indices of dissimilarity, concentration at the extremes, redlining, or isolation. Data sources included cancer registries, claims, or institutional data linked to area-level metrics from the US census or historical mortgage data. Segregation was associated with worse survival. Nine studies were location specific, and the segregation measures were developed for Black, Hispanic, and White residents. CONCLUSIONS: A range of measures and data sources are available to capture the effects of structural racism. We provide a set of recommendations for best practices for modelers to consider when incorporating the effects of structural racism into simulation models.