Iakovos Toumazis

Development and validation of a histology-specific natural history model of ovarian cancer

Ovarian cancer is the second leading cause of death from gynecologic cancers, yet no effective screening program exists for the general population. Past screening trials evaluated the effectiveness of annual ovarian cancer screening and concluded that it does not yield substantial mortality reduction. Future investments on ovarian cancer screening trials would require convincing preliminary evidence on the effectiveness of interventions of interest. Simulation modeling is an effective, fast, cost-efficient, and safe approach to gain insights on the effectiveness of interventions, that is increasingly being used to inform guidelines for cancer screening programs. Models that simulate the natural progression of diseases in the absence of any intervention, commonly referred to as natural history models, are the cornerstone of such analyses, because they provide a reference point for evaluating interventions. Currently, no histology-specific natural history model exists for ovarian cancer despite major differences among subtypes. Develop and validate a histology-specific ovarian cancer natural history model. We developed natural history models for the most common histological subtypes of epithelial ovarian cancer: high-grade serous carcinoma, low-grade serous carcinoma, mucinous carcinoma, clear cell carcinoma, endometrioid carcinoma, carcinosarcoma, and not otherwise specified. Each natural history model simulates the natural progression of ovarian cancer from disease's onset until death from any cause. We modeled ovarian cancer progression as a state-transition model comprising of 13 mutually exclusive and collectively exhaustive health states. We informed the model input parameters using observed, nationally representative estimates, whenever possible. Unobserved parameters (eg, preclinical transitions) were estimated through calibration to histology-specific data from the Surveillance, Epidemiology, and End Results registry. We validated the natural history models on the control arms of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial and the United Kingdom Collaborative Trial of Ovarian Cancer Screening trials, in terms of ovarian cancer incidence and mortality rates, and stage distribution at diagnosis. Differences between observed and estimated outcomes were assessed using traditional statistical tests. The calibrated natural history models reproduced the observed Surveillance, Epidemiology, and End Results data (range of weighted root mean square error across histological subtypes: 0.0081-0.0185) as well as individual calibration targets; survival after diagnosis, stage distribution at diagnosis, and age distribution at diagnosis (ranges of mean square error across histological subtypes: 0.0029-0.0204, 0.0005-0.0203, and 0.0637-0.0816, respectively). The natural history models reproduced the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial's observed incidence and mortality rates, and stage at diagnosis (P value=.411 for incidence, P value=.195 for mortality, and P value=.200 for stage distribution at diagnosis) and the United Kingdom Collaborative Trial of Ovarian Cancer Screening's observed ovarian cancer incidence (P value=.607) and mortality (P value=.624) rates. The average duration of the preclinical phase ranges between 1 and 3 years, which partly explains screening's failure to yield mortality reduction. Moreover, stage II ovarian cancer, independent of histological subtype, is a transient state characterized by noticeably shorter average duration when compared to stages I, III, and IV. The developed natural history models accurately describe the histology-specific natural progression of ovarian cancer and provide important insights into the natural history of the disease. The models may be used to evaluate the impact of future and emerging ovarian cancer interventions, thus providing valuable information to decision-makers and policymakers.

Estimating sojourn time and sensitivity of screening for ovarian cancer using a Bayesian framework

Abstract Background Ovarian cancer is among the leading causes of gynecologic cancer-related death. Past ovarian cancer screening trials using combination of cancer antigen 125 testing and transvaginal ultrasound failed to yield statistically significant mortality reduction. Estimates of ovarian cancer sojourn time—that is, the period from when the cancer is first screen detectable until clinical detection—may inform future screening programs. Methods We modeled ovarian cancer progression as a continuous time Markov chain and estimated screening modality–specific sojourn time and sensitivity using a Bayesian approach. Model inputs were derived from the screening arms (multimodal and ultrasound) of the UK Collaborative Trial of Ovarian Cancer Screening and the Prostate, Lung, Colorectal and Ovarian cancer screening trials. We assessed the quality of our estimates by using the posterior predictive P value. We derived histology-specific sojourn times by adjusting the overall sojourn time based on the corresponding histology-specific survival from the Surveillance, Epidemiology, and End Results Program. Results The overall ovarian cancer sojourn time was 2.1 years (posterior predictive P value = .469) in the Prostate, Lung, Colorectal and Ovarian studies, with 65.7% screening sensitivity. The sojourn time was 2.0 years (posterior predictive P value = .532) in the United Kingdom Collaborative Trial of Ovarian Cancer Screening’s multimodal screening arm and 2.4 years (posterior predictive P value = .640) in the ultrasound screening arm, with sensitivities of 93.2% and 64.5%, respectively. Stage-specific screening sensitivities in the Prostate, Lung, Colorectal and Ovarian studies were 39.1% and 82.9% for early-stage and advanced-stage disease, respectively. The histology-specific sojourn times ranged from 0.8 to 1.8 years for type II ovarian cancer and 2.9 to 6.6 years for type I ovarian cancer. Conclusions Annual screening is not effective for all ovarian cancer subtypes. Screening sensitivity for early-stage ovarian cancers is not sufficient for substantial mortality reduction.

Use Patterns of Levonorgestrel-Releasing Intrauterine System among American Women

Abstract Levonorgestrel-releasing intrauterine system (LNG-IUS) use is approved by the FDA for contraception and heavy menorrhagia. More importantly, it effectively treats endometrial hyperplasia, a precursor to endometrial cancer. Therefore, LNG-IUS use is associated with potential endometrial cancer risk reduction, but current use patterns in the United States are unknown. We analyzed LNG-IUS use prevalence among women ages 18 to 50 years using a weighted statistical analysis of the 2017 to 2019 National Survey of Family Growth. Summary statistics were stratified by race and ethnic group and known endometrial cancer sociodemographic and health risk factors and assessed statistically with bivariate Rao–Scott χ2 tests. A multivariable logistic regression model was developed to explore LNG-IUS use predictors. Current LNG-IUS use in the United States was 6.9% [95% confidence interval (CI), 5.9%–8.1%]. LNG-IUS use was lower in Hispanic women compared with White women [adjusted OR (AOR), 0.7; 95% CI, 0.5–1.0]. Compared with women with ≤high school education, LNG-IUS use was higher for women with ≥college degree (AOR, 2.0; 95% CI, 1.3–3.1). Parous (AOR, 2.6; 95% CI, 1.7–3.9) and insured (AOR, 1.7; 95% CI, 1.0–3.1) women had higher odds of LNG-IUS use, whereas women with diabetes (AOR, 0.3; 95% CI, 0.1–0.7) had lower odds of LNG-IUS use. No differences in LNG-IUS use were observed by endometrial cancer risk factors of women’s body mass index, age of menarche, hypertension, and personal history of cancer. More research is needed to establish the potential benefits of LNG-IUS use on endometrial cancer, which will further highlight potential opportunities for population-level primary prevention to address the growing incidence of endometrial cancer. Prevention Relevance: This study describes the characteristics of American women using the LNG-IUS. Reproductive-age women (especially Hispanic, with lower education, nulliparous, uninsured, and with diabetes) have lower LNG-IUS use odds. These groups may benefit from LNG-IUS use for endometrial cancer primary prevention, conditioned that LNG-IUS use is proven effective in reducing endometrial cancer incidence.