Multistate models for the natural history of cancer progression.

BACKGROUND: Multistate models can be effectively used to characterise the natural history of cancer. Inference from such models has previously been useful for setting screening policies. METHODS: We introduce the basic elements of multistate models and the challenges of applying these models to cancer data. Through simulation studies, we examine (1) the impact of assuming time-homogeneous Markov transition intensities when the intensities depend on the time since entry to the current state (i.e., the process is time-inhomogenous semi-Markov) and (2) the effect on precancer risk estimation when observation times depend on an unmodelled intermediate disease state. RESULTS: In the settings we examined, we found that misspecifying a time-inhomogenous semi-Markov process as a time-homogeneous Markov process resulted in biased estimates of the mean sojourn times. When screen-detection of the intermediate disease leads to more frequent future screening assessments, there was minimal bias induced compared to when screen-detection of the intermediate disease leads to less frequent screening. CONCLUSIONS: Multistate models are useful for estimating parameters governing the process dynamics in cancer such as transition rates, sojourn time distributions, and absolute and relative risks. As with most statistical models, to avoid incorrect inference, care should be given to use the appropriate specifications and assumptions.

2019 ASCCP Risk-Based Management Consensus Guidelines: Methods for Risk Estimation, Recommended Management, and Validation.

OBJECTIVE: To manage cervical screening abnormalities, the 2019 ASCCP management consensus guidelines will recommend clinical action on the basis of risk of cervical precancer and cancer. This article details the methods used to estimate risk, to determine the risk-based management, and to validate that the risk-based recommendations are of general use in different settings. METHODS: Based on 1.5 million patients undergoing triennial cervical screening by cotesting at the Kaiser Permanente Northern California from 2003 to 2017, we estimated risk profiles for different clinical scenarios and combinations of past and current human papillomavirus and cytology test results. We validated the recommended management by comparing with the estimated risks in several external data sources. RESULTS: Risk and management tables are presented separately by Egemen et al. and Demarco et al. Risk-based management derived from the Kaiser Permanente Northern California largely agreed with the management implied from the estimated risks of the other data sources. CONCLUSIONS: The new risk-based guidelines present management of abnormal cervical screening results. By describing the steps used to develop these guidelines, the methods presented in this article can provide a basis for future extensions of the risk-based guidelines.

Risk Estimates Supporting the 2019 ASCCP Risk-Based Management Consensus Guidelines.

The 2019 American Society for Colposcopy and Cervical Pathology Risk-Based Management Consensus Guidelines for the management of cervical cancer screening abnormalities recommend 1 of 6 clinical actions (treatment, optional treatment or colposcopy/biopsy, colposcopy/biopsy, 1-year surveillance, 3-year surveillance, 5-year return to regular screening) based on the risk of cervical intraepithelial neoplasia grade 3, adenocarcinoma in situ, or cancer (CIN 3+) for the many different combinations of current and recent past screening results. This article supports the main guidelines presentation by presenting and explaining the risk estimates that supported the guidelines. METHODS: From 2003 to 2017 at Kaiser Permanente Northern California (KPNC), 1.5 million individuals aged 25 to 65 years were screened with human papillomavirus (HPV) and cytology cotesting scheduled every 3 years. We estimated immediate and 5-year risks of CIN 3+ for combinations of current test results paired with history of screening test and colposcopy/biopsy results. RESULTS: Risk tables are presented for different clinical scenarios. Examples of important results are highlighted; for example, the risk posed by most current abnormalities is greatly reduced if the prior screening round was HPV-negative. The immediate and 5-year risks of CIN 3+ used to decide clinical management are shown. CONCLUSIONS: The new risk-based guidelines present recommendations for the management of abnormal screening test and histology results; the key risk estimates supporting guidelines are presented in this article. Comprehensive risk estimates are freely available online at https://CervixCa.nlm.nih.gov/RiskTables.

A Study of Partial Human Papillomavirus Genotyping in Support of the 2019 ASCCP Risk-Based Management Consensus Guidelines.

INTRODUCTION: The 2019 ASCCP Risk-Based Management Consensus Guidelines include recommendations for partial human papillomavirus (HPV) genotyping in management of abnormal cervical cancer screening results. The guidelines are based on matching estimates of cervical intraepithelial neoplasia (CIN) 3+ risk to consensus clinical action thresholds. In support of the guidelines, this analysis addresses the risks predicted by individual identification of HPV 16 and HPV 18. METHODS: Risk estimates were drawn from a subset of women in the Kaiser Permanente Northern California screening program, whose residual cervical specimens were HPV typed as part of the HPV Persistence and Progression study. We calculated risk of CIN 3+ to assess how identification of HPV 16, HPV 18, or 12 other "high-risk" HPV types would influence recommended clinical management of new abnormal screening results, taking into account current cytologic results and recent screening history. Immediate and/or 5-year risks of CIN 3+ were matched to clinical actions identified in the guidelines. RESULTS: Identification of HPV 16 at the first visit including HPV testing elevated immediate risk of diagnosing CIN 3+ sufficiently to mandate colposcopic referral even when cytology was Negative for Intraepithelial Lesions or Malignancy and to support a preference for treatment of cytologic high-grade squamous intraepithelial lesion. HPV 18 less clearly elevated CIN 3+ risk. CONCLUSIONS: Identification of HPV 16 clearly mandated consideration in clinical management of new abnormal screening results. HPV 18 positivity must be considered as a special situation because of established disproportionate risk of invasive cancer. More detailed genotyping and use beyond initial management will be considered in guideline updates.

Mixture models for undiagnosed prevalent disease and interval-censored incident disease: applications to a cohort assembled from electronic health records.

For cost-effectiveness and efficiency, many large-scale general-purpose cohort studies are being assembled within large health-care providers who use electronic health records. Two key features of such data are that incident disease is interval-censored between irregular visits and there can be pre-existing (prevalent) disease. Because prevalent disease is not always immediately diagnosed, some disease diagnosed at later visits are actually undiagnosed prevalent disease. We consider prevalent disease as a point mass at time zero for clinical applications where there is no interest in time of prevalent disease onset. We demonstrate that the naive Kaplan-Meier cumulative risk estimator underestimates risks at early time points and overestimates later risks. We propose a general family of mixture models for undiagnosed prevalent disease and interval-censored incident disease that we call prevalence-incidence models. Parameters for parametric prevalence-incidence models, such as the logistic regression and Weibull survival (logistic-Weibull) model, are estimated by direct likelihood maximization or by EM algorithm. Non-parametric methods are proposed to calculate cumulative risks for cases without covariates. We compare naive Kaplan-Meier, logistic-Weibull, and non-parametric estimates of cumulative risk in the cervical cancer screening program at Kaiser Permanente Northern California. Kaplan-Meier provided poor estimates while the logistic-Weibull model was a close fit to the non-parametric. Our findings support our use of logistic-Weibull models to develop the risk estimates that underlie current US risk-based cervical cancer screening guidelines. Published 2017. This article has been contributed to by US Government employees and their work is in the public domain in the USA.