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

Author:

Cohen Camryn M1,Wentzensen Nicolas1ORCID,Lahrmann Bernd2,Tokugawa Diane3ORCID,Poitras Nancy3,Bartels Liam245,Krauthoff Alexandra245,Keil Andreas2,Miranda Felipe2,Castle Philip E16,Lorey Thomas3,Hare Brad7,Darragh Teresa M8,Grabe Niels245,Clarke Megan A1ORCID

Affiliation:

1. Division of Cancer Epidemiology & Genetics, National Cancer Institute , Rockville, Maryland , USA

2. Steinbeis Transfer Center for Medical Systems Biology , Heidelberg , Germany

3. Kaiser Permanente, Permanente Medical Group Regional Laboratory , Berkeley, California , USA

4. Hamamatsu Tissue Imaging and Analysis Center, BIOQUANT, University Heidelberg, Heidelberg , Germany

5. National Center of Tumor Diseases, Medical Oncology, University Hospital Heidelberg, Heidelberg , Germany

6. Division of Cancer Prevention, National Cancer Institute , Rockville, Maryland , USA

7. Permanente Medical Group , San Francisco, California , USA

8. University of California at San Francisco , San Francisco, California , USA

Abstract

Abstract 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.

Funder

National Institutes of Health

National Cancer Institute

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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