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OBJECTIVE: Progression-free survival (PFS) is an important early efficacy endpoint in ovarian cancer (OC) and its relevance to patients should be assessed. PRIMA, a phase III trial, assessed niraparib in patients with OC; this post hoc analysis examined the relationship between disease progression in OC and health-related quality of life (HRQoL). METHODS: The PRIMA trial randomized patients with advanced OC responsive to first-line platinum-based chemotherapy to once daily maintenance oral niraparib or placebo. This post hoc analysis evaluated the impact of disease progression on HRQoL by comparing HRQoL at the last visit pre-progression to end of treatment (EoT), and after 4, 8, 12, and 24 weeks. Assessments included the Functional Assessment of Cancer Therapy-Ovarian Symptom Index (FOSI), the European Quality of Life Five Dimension Five Level questionnaire (EQ-5D-5L) and EQ Visual Analogue Scale (EQ-VAS), the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (EORTC-QLQ-C30), and the EORTC Quality of Life Questionnaire Ovarian Cancer module (EORTC-QLQ-OV28). RESULTS: This post hoc analysis included 733 patients. Mean FOSI, EQ-5D-5L, and EQ-VAS scores deteriorated from last visit pre-progression to EoT and remained low up to 24-week follow-up. Least squares mean changes from last visit pre-progression to EoT were -2.1 (95% confidence interval -2.4, -1.7) for FOSI, -4.6 (-5.6, -3.5) for the EQ-5D-5L index, and -7.9 (-9.6, -6.3) for EQ-VAS. CONCLUSIONS: Disease progression negatively impacted HRQoL in patients with OC. PFS is clinically relevant, and prolonging PFS may preserve HRQoL. ispartof: GYNECOLOGIC ONCOLOGY vol:166 issue:3 pages:494-502 ispartof: location:United States status: published

OBJECTIVE We sought to evaluate costs associated with public health screening for presymptomatic type 1 diabetes in 90,632 children as part of the Fr1da study in Bavaria and in forecasts for standard care. RESEARCH DESIGN AND METHODS We report on resource use and direct costs for screening-related procedures in the Fr1da study coordination center and laboratory and in participating pediatric practices and local diabetes clinics. Data were obtained from Fr1da study documents, an online survey among pediatricians, and interviews and records of Fr1da staff members. Data were analyzed with tree models that mimic procedures during the screening process. Cost estimates are presented as they were observed in the Fr1da study and as they can be expected in standard care for various scenarios. RESULTS The costs per child screened in the Fr1da study were €28.17 (95% CI 19.96; 39.63) and the costs per child diagnosed with presymptomatic type 1 diabetes were €9,117 (6,460; 12,827). Assuming a prevalence of presymptomatic type 1 diabetes of 0.31%, as in the Fr1da study, the estimated costs in standard care in Germany would be €21.73 (16.76; 28.19) per screened child and €7,035 (5,426; 9,124) per diagnosed child. Of the projected screening costs, €12.25 would be the costs in the medical practice, €9.34 for coordination and laboratory, and €0.14 for local diabetes clinics. CONCLUSIONS This study provides information for the planning and implementation of screening tests for presymptomatic type 1 diabetes in the general public and for the analysis of the cost-effectiveness of targeted prevention strategies.

Simulation modeling can be useful to estimate the long-term health and economic impacts of population-based dietary policies. We conducted a systematic scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guideline to map and critically appraise economic evaluations of population-based dietary policies using simulation models. We searched Medline, Embase, and EconLit for studies published in English after 2005. Modeling studies were mapped based on model type, dietary policy, and nutritional target, and modeled risk factor-outcome pathways were analyzed. We included 56 studies comprising 136 model applications evaluating dietary policies in 21 countries. The policies most often assessed were reformulation (34/136), taxation (27/136), and labeling (20/136); the most common targets were salt/sodium (60/136), sugar-sweetened beverages (31/136), and fruit and vegetables (15/136). Model types included Markov-type (35/56), microsimulation (11/56), and comparative risk assessment (7/56) models. Overall, the key diet-related risk factors and health outcomes were modeled, but only 1 study included overall diet quality as a risk factor. Information about validation was only reported in 19 of 56 studies and few studies (14/56) analyzed the equity impacts of policies. Commonly included cost components were health sector (52/56) and public sector implementation costs (35/56), as opposed to private sector (18/56), lost productivity (11/56), and informal care costs (3/56). Most dietary policies (103/136) were evaluated as cost-saving independent of the applied costing perspective. An analysis of the main limitations reported by authors revealed that model validity, uncertainty of dietary effect estimates, and long-term intervention assumptions necessitate a careful interpretation of results. In conclusion, simulation modeling is widely applied in the economic evaluation of population-based dietary policies but rarely takes dietary complexity and the equity dimensions of policies into account. To increase relevance for policymakers and support diet-related disease prevention, economic effects beyond the health sector should be considered, and transparent conduct and reporting of model validation should be improved.

ISPOR–The Professional Society for Health Economics and Outcomes Research Objectives: Health utility decrement estimates for diabetes and complications are needed for parametrization of simulation models that aim to assess the cost-utility of diabetes prevention and care strategies. Thisstudy estimates health utility decrements associated with diabetes and cardiovascular and microvascular complications from a cross-sectional population-based German study. Methods: Data were obtained from the population based cross-sectional KORA (Cooperative Health Research in the Region of Augsburg) health questionnaire 2016 and comprised n = 1072 individuals with type 2 diabetes and n = 7879 individuals without diabetes. Health utility was assessed through the EQ-5D-5L. We used linear regression models with an interaction term between type 2 diabetes and cardiovascular and microvascular complications while adjusting for demographic and socio-economic factors and other comorbidities. Results: Type 2 diabetes (β = −0.028, standard error [SE] = 0.014), stroke (β = −0.070, SE = 0.010), cardiac arrhythmia (β = −0.031, SE = 0.006), heart failure (β = −0.073, SE = 0.009), coronary heart disease (β = −0.028, SE = 0.010), myocardial infarction (β = −0.020, SE = 0.011, estimates of main effec), and neuropathy (β = −0.067, SE = 0.020), diabetic foot (β = −0.042, SE = 0.030), nephropathy (β = −0.032, SE = 0.025), and blindness (β = −0.094, SE = 0.056, estimates of interaction terms) were negatively associated with health utility. The interaction term for diabetes x stroke (β = −0.052, SE = 0.021) showed that the utility decrement for stroke is significantly larger in people with type 2 diabetes than in people without diabetes. Conclusions: Diabetes, cardiovascular, and microvascular conditions are associated with significant health utility decrements. Utility decrements for some conditions differ between people with and without type 2 diabetes. These results are of high relevance for the parametrization of decision analytic simulation models and applied health economic evaluations in the field of prevention and management of diabetes in Germany.

Aims Self-management behavior (SMB) is an important aspect in the management of diabetes. This study aimed to identify sociodemographic and disease-related factors associated with good SMB in people with type 2 diabetes (T2D). Methods We used data from 479 people with T2D aged 65 or older from the population-based KORA (Cooperative Health Research in the Area of Augsburg) Health Survey 2016 in Southern Germany. We estimated Poisson and logistic regression models testing the cross-sectional relationship between individual or disease-related characteristics and an established SMB sum index comprising six SMB dimensions stratified according to insulin treatment status. Results Mean age in the sample was 75 and mean diabetes duration was 13 years. The overall level of SMB was low. Higher SMB index scores were associated with higher age, treatment with insulin, participation in a diabetes education program, and, for people with insulin treatment, with a BMI below 30 kg/m2. Single item analyses generally supported these findings. Conclusions SMB in people with T2D needs to be improved with efficient interventions. Targeting obese individuals and those at an early stage of the disease with low-barrier, regular education or self-management programs may be a preferred strategy.

Florian M Karl,1,2 Rolf Holle,1,2 Lars Schwettmann,1 Annette Peters,2,3 Michael Laxy1,2 1Institute of Health Economics and Health Care Management, Helmholtz Zentrum München (GmbH), German Research Center for Environmental Health, Neuherberg, Germany; 2German Center for Diabetes Research (DZD), Neuherberg, Germany; 3Institute of Epidemiology II, Helmholtz Zentrum München (GmbH), German Research Center for Environmental Health, Neuherberg, Germany Background: Patient self-management is crucial to prevent complications and mortality in type 2 diabetes. From an economic perspective, time preference predicts short-sighted decision making and thus might help to explain non-adherence to self-anagement recommendations. However, recent studies on this association have shown mixed results. Purpose: In this study, we tested whether the combination of time preference and outcome expectancy can improve the predictions of self-management behavior. Patients and methods: Data from 665 patients with type 2 diabetes were obtained from the cross-sectional KORA (Cooperative Health Research in the Region of Augsburg) GEFU 4 study. Time preference and outcome expectancy were measured by one question each, which were answered on a 4-point Likert scale. Their association with six self-managing behaviors was tested in logistic and linear regression analyses. Likewise, we examined the association between self-management and the interaction of outcome expectancy and time preference. Results: A high time preference was associated with a significantly lower sum of self-management behaviors (β=-0.29, 95% CI [-0.54, -0.04]). Higher outcome expectancy was associated with a higher self-management score (β=0.21, 95% CI [-0.03, 0.45]). The interaction model showed that low time preference was only associated with better self-management when combined with a high outcome expectancy (β=0.05, 95% CI [-0.28, 0.39] vs β=0.27, 95% CI [-0.09, 0.63]). Conclusion: Time preference and outcome expectancy are interrelated predictors of patient self-management and could be used to identify and to intervene on patients with a potentially poor self-management. Keywords: behavioral economics, adherence, temporal discounting, health behavior

Background and aims Unrealistic comparative optimism (UO), as the erroneous judgement of personal risks to be lower than the risks of others, could help explain differences in diabetes self‐management. The present study tested the hypothesis that individuals with type 2 diabetes who underestimate their comparative heart attack risk, have a lower adherence regarding recommended self‐management. Methods We used data from individuals with type 2 diabetes participating in the German KORA (Cooperative Health Research in the Region of Augsburg) GEFU 4 (self‐administered health questionnaire 2016) study. UO was estimated by comparing participants' subjective comparative risk for having a heart attack within the next 5‐years (ie, “higher than others,” “average,” “lower than others”), with their objective comparative 10‐year cardiovascular disease risk based on the Framingham equations. We estimated binary logistic and linear regression models to analyze which characteristics were associated with UO and to test the association between UO and participants' self‐management behaviors (ie, regular self‐monitoring of body weight, blood sugar, and blood pressure, regular foot care, keeping a diabetes diary, and having a diet plan), and their sum score, respectively. All models were adjusted for socio‐demographic and disease‐related variables. Results The studied sample included n = 633 individuals with type 2 diabetes (mean age 70.7 years, 45% women). Smokers and males were more likely to show UO than nonsmokers and females. Furthermore, a higher blood pressure and a higher body mass index were associated with a higher likelihood of UO regarding heart attack risk. However, UO was not significantly associated with patient self‐management. Conclusions Unfavorable health behavior and risk factors are associated with UO. However, our results suggest that UO with regard to perceived heart attack risk may not be a relevant factor for patient self‐management in those with type 2 diabetes.

Background Physical inactivity (PIA) is an important risk factor for many chronic conditions and therefore might increase healthcare utilization and costs. This study aimed to analyze the association of PIA using device assessed and self-reported physical activity (PA) data with direct healthcare costs. Methods Cross-sectional data was retrieved from the population based KORA FF4 study (Cooperative Health Research in the Region of Augsburg) that was conducted in southern Germany from 2013 to 2014 (n = 2279). Self-reported PA was assessed with two questions regarding sports related PA in summer and winter and categorized into “high activity”, “moderate activity”, “low activity” and “no activity”. In a subsample (n = 477), PA was assessed with accelerometers and participants were categorized into activity quartiles (“very high”, “high”, “low” and “very low”) according to their mean minutes per day spent in light intensity, or in moderate-vigorous PA (MVPA). Self-reported healthcare utilization was used to estimate direct healthcare costs. We regressed direct healthcare costs on PA using a two-part gamma regression, adjusted for age, sex and socio-demographic variables. Additional models, including and excluding potential additional confounders and effect mediators were used to check the robustness of the results. Results Annual direct healthcare costs of individuals who reported no sports PA did not differ from those who reported high sports PA [+€189, 95% CI: -188, 598]. In the subsample with accelerometer data, participants with very low MVPA had significantly higher annual costs than participants with very high MVPA [+€986, 95% CI: 15, 1982]. Conclusion Device assessed but not self-reported PIA was associated with higher direct healthcare costs. The magnitude and significance of the association depended on the choice of covariates in the regression models. Larger studies with device assessed PA and longitudinal design are needed to be able to better quantify the impact of PIA on direct healthcare costs. Electronic supplementary material The online version of this article (10.1186/s12889-018-5906-7) contains supplementary material, which is available to authorized users.

Background: COPD is a costly disease. However, there is lack of evidence on differences in costs and health-related quality of life (HRQL) between COPD patients with and without a-1-antritrypsin deficiency (AATD). Methods: 131 COPD patients with AATD (106 with augmentation therapy (AT)) and 2,049 COPD patients without AATD participating in the baseline visit of the German COSYCONET cohort were compared. Information on healthcare utilization, work absence and premature retirement was used to calculate societal costs in the year 2012. HRQL was assessed by the CAT, SGRQ and the generic EQ-5D-3L questionnaire. The association of AATD (with/without AT) with costs and HRQL was analysed by generalized linear regression models controlling for GOLD grade, age, sex, education, smoking status, BMI and comorbidity as potential confounders. Results: Adjusted annual mean healthcare costs were €6.099 for AATD patients without AT, €7.117 for AATD patients with AT (excluding costs of AT, €70K per year) and €7.460 for COPD patients without AATD. Augmented AATD patients showed significantly higher outpatient (+270%), but lower inpatient costs (-35%) compared to COPD patients without AATD. The group of AATD patients had lower medication costs (-28%) than the control group (excluding costs of AT). Costs for work absence/ retirement and generic/COPD-specific HRQL scores did not differ between groups. Conclusion: Apart from the high costs of AT, COPD patients with AATD showed slightly lower healthcare costs than COPD patients without AATD in this cross-sectional analysis. To provide conclusive arguments in the controversy about the cost-effectiveness of AT, longitudinal data are needed

Background Bicycle injuries represent an important proportion of injuries among Canadian children. Since helmet use was mandated in 1996 in BC, Canada, use has increased and head injuries have decreased. Despite the law, many child cyclists don’t wear a helmet. This study determines additional factors that may influence child helmet use by studying caregiver attitudes and behaviours. We study whether intention to wear a bicycle helmet is moderated by planning skills of the individual, and whether individuals exposed to a social marketing campaign have higher scores in risk awareness, intention and behaviour as compared to propensity score (PS) matches without exposure to the campaign. Methods We use the Health Action Process Approach to identify single traits that lead to helmet use. PS is applied to address the lack of a control group: the social marketing campaign is a population-wide campaign. PS allows a matched group to be drawn, enabling comparative analysis of the impact of the social marketing campaign on bicycle helmet use. A survey collects detailed bicycle helmet use information from 25–55 yr olds (n = 300) in BC, as part of the continual monitoring and evaluation of a social marketing campaign. Data is examined using multiple regression to identify factors and moderating effects that influence bicycle helmet use. PS is calculated using socio-economic data and injury history over the past 12-months. PS is used to match pairs of individuals with equal PS but different levels of campaign exposure: exposed vs. not exposed. The matched groups are analysed using tests for independent groups. Results Data will be collected by Dec 2015. Data cleaning and analysis will be completed by Mar 2016, and final results will be presented at Safety 2016. Conclusions An important step to increasing bicycle helmet use is to determine additional factors, beyond laws, that may influence helmet use, such that social marketing campaigns can deliver targeted messages.