Laura J Havrilesky

Trends in uterine cancer incidence and mortality: insights from a natural history model

Abstract Background Uterine cancer incidence and mortality are increasing, with concomitant disparities in outcomes between racial groups. Natural history modeling can evaluate risk factors, predict future trends, and simulate approaches to reducing mortality and disparities. Methods We designed a natural history model of uterine cancer using a multistage clonal expansion design. The model is informed by National Health and Nutrition Examination Survey, National Health Examination Survey, age, time period, birth cohort, and birth certificate data on reproductive histories and body mass index (BMI). We fit and calibrated the model to Surveillance, Epidemiology, and End Results data by race and ethnicity as well as histologic subgroup. We projected future incidence and estimated the degree of contribution of BMI, reproductive history, and competing hysterectomy to excess uterine cancer incidence. Results The model accurately replicated Surveillance, Epidemiology, and End Results incidence for endometrioid, nonendometrioid, and sarcoma subgroups for non-Hispanic Black and non-Hispanic White patients. For endometrioid, nonendometrioid, and sarcomas, BMI-attributable risks are greater for non-Hispanic White than for non-Hispanic Black patients; reproductive history–attributable risks are greater for non-Hispanic Black patients. Between 2018 and 2050, endometrioid incidence is projected to rise by 64.9% in non-Hispanic Black individuals and17.5% in non-Hispanic White individuals; the projected rise for the nonendometrioid subgroup is 41.4% in non-Hispanic Black individuals and 22.5% in non-Hispanic White individuals; the sarcoma incidence projected increase is 36% in non-Hispanic Black individuals and 29.2% in non-Hispanic White individuals. Conclusions Uterine cancer risk is substantially explained by reproductive history and BMI, with differences observed between non-Hispanic Black and non-Hispanic White individuals and future projections indicating perpetuation of disparities. Lower rates of hysterectomy and rising obesity rates will likely contribute to continued increases in uterine cancer incidence.

Patient preferences for maintenance PARP inhibitor therapy in ovarian cancer treatment

To measure preferences of women with ovarian cancer regarding risks, side effects, costs and benefits afforded by maintenance therapy (MT) with a poly ADP ribose polymerase (PARP) inhibitor. A discrete-choice experiment elicited preferences of women with ovarian cancer regarding 6 attributes (levels in parentheses) relevant to decisions for MT versus treatment break: (1) overall survival (OS; 36, 38, 42 months); (2) progression-free survival (PFS; 15, 17, 21 months); (3) nausea (none, mild, moderate); (4) fatigue (none, mild, moderate); (5) probability of death from myelodysplastic syndrome/acute myelogenous leukemia (MDS/AML; 0% to 10%); (6) monthly out-of-pocket cost ($0 to $1000). Participants chose between 2 variable MT scenarios and a static scenario representing treatment break, with multiple iterations. Random-parameters logit regression was applied to model choices as a function of attribute levels. 95 eligible participants completed the survey; mean age was 62, 48% had recurrence, and 17% were ever-PARP inhibitor users. Participants valued OS (average importance weight 24.5 out of 100) and monthly costs (24.6) most highly, followed by risk of death from MDS/AML (17.9), nausea (14.7), PFS (10.5) and fatigue (7.8). Participants would accept 5% risk of MDS/AML if treatment provided 2.2 months additional OS or 4.8 months PFS. Participants would require gains of 2.6 months PFS to accept mild treatment-related fatigue and 4.4 months to accept mild nausea. When considering MT, women with ovarian cancer are most motivated by gains in OS. Women expect at least 3-4 months of PFS benefit to bear mild side effects of treatment.

Opportunities to Advance the Delivery of High-Quality, Goal-Concordant End-of-Life Care in Ovarian Cancer

Cost-Effectiveness of Venous Thromboembolism Prophylaxis During Neoadjuvant Chemotherapy for Ovarian Cancer

PURPOSE: Two recent clinical trials have demonstrated that direct oral anticoagulants (DOACs) are effective as venous thromboembolism (VTE) prophylaxis in patients with moderate-to-high risk ambulatory cancer initiating chemotherapy. Patients with advanced ovarian cancer receiving neoadjuvant chemotherapy are at particularly increased risk of VTE. We performed a cost-effectiveness analysis from a health system perspective to determine if DOACs are a feasible prophylactic strategy in this population. METHODS: A simple decision tree was created from a health system perspective, comparing two strategies: prophylactic DOAC taken for 18 weeks during chemotherapy versus no VTE prophylaxis. Rates of VTE (7.3% DOAC v 13.6% no treatment), major bleeding (2.6% v 1.3%), and clinically relevant nonmajor bleeding (4.6% v 3.3%) were modeled. Cost estimates were obtained from wholesale drug costs, published studies, and Medicare reimbursement data. Probabilistic, one-way, and two-way sensitivity analyses were performed. RESULTS: In the base case model, DOAC prophylaxis is more costly and more effective than no therapy (incremental cost-effectiveness ratio = $256,218 in US dollars/quality-adjusted life year). In one-way sensitivity analyses, reducing the DOAC cost by 32% or raising the baseline VTE rate above 18% renders this strategy potentially cost-effective with an incremental cost-effectiveness ratio below $150,000 in US dollars/quality-adjusted life year. CONCLUSION: Further confirmation of the true baseline VTE rate among women initiating neoadjuvant chemotherapy for ovarian cancer will determine whether prophylactic dose DOAC is a value-based strategy. Less costly VTE prophylaxis options such as generic DOACs (once available) and aspirin also warrant investigation.

Projected Trends in the Incidence and Mortality of Uterine Cancer in the United States

Abstract Background: To develop a natural history model for uterine cancer calibrated to population-based incidence and mortality data to project future trends in the disease through 2050. Methods: We developed a state-transition microsimulation model of uterine cancer. The model begins at 18 years of age and simulates Black and White patients, includes transition states for precursor lesions, and separately models endometrioid and nonendometrioid tumors. The model was calibrated to population-based incidence and mortality data using parameter extrapolation. Results: The model closely fit population-based incidence and mortality data of uterine cancer. From 2020 to 2050, the incidence of uterine cancer is projected to increase in White women to 74.2 cases per 100,000 (compared with 57.7 cases per 100,000 in 2018) and increase to 86.9 per 100,000 (compared with 56.8 cases per 100,000 in 2018) in Black women. Among White women, incidence-based mortality will increase from 6.1 per 100,000 in 2018 to 11.2 per 100,000 in 2050, whereas incidence-based mortality in Black women will increase from 14.1 per 100,000 to 27.9 per 100,000. Endometrioid tumors are expected to increase considerably in both White and Black women; White women will experience only a slight increase in nonendometrioid tumors, whereas the incidence of these tumors will increase substantially in Black women. Conclusions: The incidence and mortality of uterine cancer are projected to increase substantially over the next three decades. Black women will experience a disproportionate increase in the disease. Impact: Projecting the incidence and mortality of uterine cancer can facilitate future cancer control efforts.