ORAL ABSTRACTS: CANCER OUTCOMES RESEARCH AND POLICY
Methods: We expanded a previously developed probabilistic decision-tree model that projected the health and economic consequences of alternative triage strategies for women with ASC-US/LSIL through a single screening round (i.e., three years). We compared the current Norwegian guidelines (i.e., reflex HPV DNA testing with delayed HPV testing and cytology for HPV positive), to 12 candidate triage strategies that involved alternative biomarkers (i.e., reflex HPV DNA and mRNA testing, p16/Ki67 dual-staining), in terms of the number of detected precancers (i.e., CIN2+) and resource use (i.e., societal costs and colposcopy referrals). To identify efficient strategies, we calculated the incremental cost-effectiveness ratios (ICER) in terms of the additional costs per additional detected precancer for each strategy compared with the next most costly strategy. In addition, we considered feasibility by calculating the expected increase in colposcopy referrals for each efficient strategy compared with current Norwegian guidelines.
Results: Four out of the 13 strategies were considered cost-efficient (ICER range: $3,796 to $45,897 per additional detected precancer). The current guidelines detected fewer precancers and required higher costs than alternative strategies. In comparison, a strategy involving HPV mRNA testing detected 13% more precancers and reduced costs by 14%, though required 14% more colposcopy referrals. Strategies involving HPV DNA testing with immediate colposcopy for HPV positive were expected to increase precancer detection by 50%, but would also require twice as many colposcopies compared to current guidelines.
Conclusion: Novel biomarkers may be used to improve the effectiveness and efficiency of cervical cancer screening for younger women with minor cervical lesions. However, the optimal strategy depends on decision-makers willingness to accept higher resource use (either costs and/or colposcopy referrals) as well as the potential capacity constraints of Norwegian pathology laboratories. Although the use of novel biomarkers is promising, models can be expanded to investigate the long-term consequences of these strategies.
Method: Using national data on the distribution of major risk factors in smokers, we simulated a panel of smokers aged 55-80 years. For each individual, we applied an existing quantitative model to estimate the gain in life expectancy associated with discussion of guidelines graded “A” or “B” by the US Preventive Services Task Force, controlling for patient characteristics (age, race, gender, lifestyle, and comorbidity). To estimate the probability that discussion of a guideline would result in patient action (for example, obtaining a lung CT), we applied estimates of individual adherence rates, characterized by guideline as “easy” or “difficult”. We assumed adherence rates of 70% for easy guidelines (including lung cancer screening) and 30% for difficult guidelines (including tobacco cessation) in the first year, with a steady decline thereafter. We rank-ordered guidelines by their increase in adherence-adjusted life expectancy, to compare the net benefits of lung cancer screening with other major preventive care recommendations.
Result: In a hypothetical 55-year-old white female current smoker with a 30 pack-year history, hypertension (BP=140/90), mildly elevated lipids (TC=240, LDL=110), obesity (BMI=30), and no family history of cancer, discussion of lung cancer screening was estimated to add 2 months to adherence-adjusted life expectancy. Discussion of lung cancer screening offered less health benefit than discussion of tobacco cessation (+6 months), blood pressure control (+4 months), and weight loss (+4 months); similar benefit to discussion of aspirin (+2 months); and more benefit than discussion of screenings for colorectal cancer and breast cancer (+1 month each). Therefore, despite the difficulty of quitting smoking, discussion of tobacco cessation was 3 times more likely to improve life expectancy than discussion of lung cancer screening. The rank-order of recommendations was similar for other races and genders, with the relative importance of discussing tobacco cessation highest in black males (+11 months for quitting smoking vs. +2 months for lung cancer screening). Discussion of lung cancer screening consistently offered more health benefit than discussion of screening for abdominal aortic aneurysm, which is guideline-recommended for male smokers, but offered <1 month of additional life expectancy.
Conclusion: Analytic models may help to put lung cancer screening guidelines in perspective.
The US Preventive Services Task Force recommends biennial breast cancer screening for women ages 50 to 74 with average risk of breast malignancy. Consensus exists regarding annual mammographic screening of selected high risk individuals. However there is uncertainty about screening women under age 50 with intermediate breast cancer risk. This study modeled lifetime breast cancer risk in the US population of women ages 35 to 49 to facilitate future development of risk-stratified screening.
Data from the US Census Bureau, National Cancer Institutes, Breast Cancer Screening Consortium, and the National Health Interview Survey were used to estimate breast cancer risk factor prevalence in the US population. Family history, parity, previous breast biopsy, breast density, and BRCA1&2 mutations were considered as informative risk factors. Monte Carlo simulation modeling was used to estimate proportions of the population with low to average (≤12.5%), intermediate (12.6%-30%), and high (>30%) lifetime breast cancer risk.
Women ages 35 to 49 make up 10% of the US population and 27% of all adult women. Estimates of risk factor prevalence demonstrated that 6% (95%CI: 5.8-7.1%) have at least one first degree relative with breast cancer, 24%(95%CI: 22.5-24.7%) are nulliparous, 2% (95%CI: 1.9-2.7) had a previous breast biopsy, 55% (95%CI: 54-55%) have BIRADS III or IV breast density, and 0.9% (95%CI: 0.5-1.2%) carried BRCA1 or 2 mutations. Based on this risk factor prevalence, an estimated 87% of women have low to average risk, 12% have intermediate risk, and 1% have a high lifetime risk of breast cancer.
A substantial proportion of women ages 35 to 49 in the US are estimated to have intermediate lifetime risk of breast cancer. Therefore further development of risk-stratified screening in this age group is warranted.
Method: We created two separate Markov models for HIV-positive and HIV-negative MSM evaluating the cost-effectiveness for inclusion of qHPV vaccine as adjuvant/secondary prevention strategy after treatment for initial HSIL. The vaccine efficacy was defined as the decrease in the hazards of developing recurrent HSIL. Using the outputs from the probabilistic sensitivity analysis, we estimated the population-level expected value of perfect information (pEVPI), and population-level expected value of partial perfect information (pEVPPI) for key model parameters including HSIL to anal cancer progression vaccine efficacy, probability of HSIL recurrences, HPV 16/18 incidence, and utilities. The population-level values were estimated for the number of MSM who would be potentially benefited from the vaccination over the next 20 years at an annual discount rate of 3%.
Result: The pEVPI in HIV-positive and HIV-negative MSM at willingness-to-pay threshold of $100,000/quality-adjusted life year (QALY) were $0 and $580,000, respectively. The two parameters with highest expected value of partial perfect information (pEVPPI) were vaccine efficacy (at $0/QALY ICER in HIV-positive and $200,000/QALY in HIV-negative MSM) and HSIL to anal cancer progression (at $0/QALY ICER in HIV-negative and $195,000/QALY in HIV-positive MSM). The EVPPI for other parameters—probability of HSIL recurrences, HPV 16/18 incidence, and utilities—were low.
Conclusion: In HIV-positive MSM, a future clinical trial may not be worthwhile, and implementation of the vaccination policy sooner rather than later should be a priority. In HIV-negative MSM, a future research could be potentially worthwhile if the fixed cost of research is less than $580,000. In both HIV-positive and HIV-negative MSM, further research regarding the estimation of HSIL to anal cancer progression may not be worthwhile. The lower EVPPI associated with the parameters like probability of HSIL does not mean that additional research about these inputs should take a lower priority, the low values indicate that precise estimates could be obtained from less expensive observational studies.
Health utility is a preference-based measure of quality of life that informs healthcare resource allocation decisions. Utilities are commonly measured using generic instruments, such as the EuroQol-5D (EQ-5D), that are applicable to diverse disease areas. The quality of life of patients with myleofibrosis, however, is often measured using disease-specific profile instruments, including the Myelofibrosis Symptom Assessment Form (MF-SAF) and Myeloproliferative Symptom Assessment Form (MPN-SAF). In order to estimate utilities and compare the quality of life of patients with myleofibrosis to patients with other conditions, we mapped the MFSAF and MPN-SAF instruments to EQ-5D utility scores.
174 patients with myelofibrosis completed the MF-SAF, MPN-SAF and EQ-5D by online survey and mail. Patients were recruited from English-speaking countries (Canada, US, UK, and Australia) through a local myelofibrosis patient support group and websites of national and international support groups. We fitted two linear regression models for each myelofibrosis instrument, one using the original EQ-5D scores as a response variable and one which applied the Box-Cox power transformation to EQ-5D scores. Models were selected using stepwise selection and Akaike Information Criterion (AIC) and adjusted R2 criterion approach. Bootstrap was used to validate and assess any overfitting in the models. The predictive accuracy of the models was assessed with Root Mean Square Error (RMSE). Spearman Correlation between the predicted and observed utility scores was calculated to measure predictive ability.
The best-fitting model for both the MF-SAF and MPN-SAF used the power of two-transformed EQ-5D utility scores. Prior to transformation, a small constant (of 0.466) needed to be added to the utility scores to ensure their value was positive. The R2 values were 0.40 and 0.55 for the MF-SAF and MPN-SAF, respectively, and the RMSE were small at 0.46 (MF-SAF) and 0.39 (MPN-SAF)
Our mapping algorithm predicts EQ-5D scores from MF-SAF and MPN-SAF scores, thus allowing estimation of utilities for groups of myelofibrosis patients who completed only the MF-SAF or MPN-SAF in clinical studies. However, as in previous mapping studies, our model is less accurate in predicting utilities for individual patients. We are exploring various statistical techniques with the goal of improving the accuracy of models to map utilities from descriptive instruments. Our next step will be to create a mapping algorithm using different types of regression.
Method: We used a patient-level microsimulation model from the perspective of a US public insurance payer to assess different initial evaluation strategies for urinary tract cancers in a hypothetical cohort of 100,000 adult AMH patients. The analytic horizon was one urology clinic visit. We compared the benefits and trade-offs in terms of costs per patient, cancer detection rates (including missed cancer cases), secondary cancers and related mortality from radiation exposure as well as the burden of procedural complications and incidental findings. We also calculated the incremental cost effectiveness ratios (ICERs) for the different evaluation strategies as incremental cost per additional cancer case detected.
Result: The American Urological Association (AUA) guidelines recommending extensive evaluations for all AMH patients, including multi-phasic computed tomography (CT), were associated with a greater number of detected cancer cases at a higher cost than the alternative risk-stratification evaluation strategies. The AUA strategy had an ICER of over $200,000 per additional cancer case detected compared to an evaluation strategy stratifying patients in three risk groups using a Hematuria Risk Index. In addition, the AUA guidelines were associated with a higher number of radiation-induced cancer cases, deaths from radiation-induced cancer, short-term procedural complications, and incidental findings than the alternative evaluation strategies using patient risk-stratification.
Conclusion: Risk-stratification of AMH patients is an important way to avoid unnecessary workup and complications by tailoring initial evaluation based on patients’ risk for developing urinary tract malignancies. The results from this study suggest that low-risk AMH patients can avoid extensive workup altogether while medium-risk AMH patients can undergo a less intensive initial evaluation than that recommended by the AUA.