Investigator

Kate T Simms

Postdoctoral Research Fellow · Cancer Council NSW, Cancer Research Division

KTSKate T Simms
Papers(3)
Estimating the Natura…Benefits and harms of…Benefits, harms and c…
Collaborators(7)
Michaela HallMichael CaruanaEmily Annika BurgerFernando Alarid-Escud…Karen CanfellNicolas WentzensenMegan A. Smith
Institutions(5)
Cancer Council NswThe University Of Syd…Harvard UniversityStanford University S…Division Of Cancer Ep…

Papers

Estimating the Natural History of Cervical Carcinogenesis Using Simulation Models: A CISNET Comparative Analysis

Abstract Background The natural history of human papillomavirus (HPV)-induced cervical cancer (CC) is not directly observable, yet the age of HPV acquisition and duration of preclinical disease (dwell time) influences the effectiveness of alternative preventive policies. We performed a Cancer Intervention and Surveillance Modeling Network (CISNET) comparative modeling analysis to characterize the age of acquisition of cancer-causing HPV infections and implied dwell times for distinct phases of cervical carcinogenesis. Methods Using four CISNET-cervical models with varying underlying structures but fit to common US epidemiological data, we estimated the age of acquisition of causal HPV infections and dwell times associated with three phases of cancer development: HPV, high-grade precancer, and cancer sojourn time. We stratified these estimates by HPV genotype under both natural history and CC screening scenarios, because screening prevents cancer development that affects the mix of detected cancers. Results The median time from HPV acquisition to cancer detection ranged from 17.5 to 26.0 years across the four models. Three models projected that 50% of unscreened women acquired their causal HPV infection between ages 19 and 23 years, whereas one model projected these infections occurred later (age 34 years). In the context of imperfect compliance with US screening guidelines, the median age of causal infection was 4.4–15.9 years later compared with model projections in the absence of screening. Conclusions These validated CISNET-CC models, which reflect some uncertainty in the development of CC, elucidate important drivers of HPV vaccination and CC screening policies and emphasize the value of comparative modeling when evaluating public health policies.

Benefits, harms and cost-effectiveness of cervical screening, triage and treatment strategies for women in the general population

Abstract In 2020, the World Health Organization (WHO) launched a strategy to eliminate cervical cancer as a public health problem. To support the strategy, the WHO published updated cervical screening guidelines in 2021. To inform this update, we used an established modeling platform, Policy1-Cervix , to evaluate the impact of seven primary screening scenarios across 78 low- and lower-middle-income countries (LMICs) for the general population of women. Assuming 70% coverage, we found that primary human papillomavirus (HPV) screening approaches were the most effective and cost-effective, reducing cervical cancer age-standardized mortality rates by 63–67% when offered every 5 years. Strategies involving triaging women before treatment (with 16/18 genotyping, cytology, visual inspection with acetic acid (VIA) or colposcopy) had close-to-similar effectiveness to HPV screening without triage and fewer pre-cancer treatments. Screening with VIA or cytology every 3 years was less effective and less cost-effective than HPV screening every 5 years. Furthermore, VIA generated more than double the number of pre-cancer treatments compared to HPV. In conclusion, primary HPV screening is the most effective, cost-effective and efficient cervical screening option in LMICs. These findings have directly informed WHO’s updated cervical screening guidelines for the general population of women, which recommend primary HPV screening in a screen-and-treat or screen-triage-and-treat approach, starting from age 30 years with screening every 5 years or 10 years.

36Works
3Papers
7Collaborators
Papillomavirus InfectionsEarly Detection of CancerHIV InfectionsCytodiagnosisDisease Management

Positions

2012–

Postdoctoral Research Fellow

Cancer Council NSW · Cancer Research Division

2006–

Transport Modeller

AECOM Sydney

Education

2012

PhD

University of Adelaide · School of Mathematics

2005

Bachelor of Science

University of New South Wales · School of Mathematics

Country

AU