Search

Objectives: Public health decision making is a complex process based on thorough and comprehensive health technology assessments involving the comparison of different strategies, values and tradeoffs under uncertainty. This process must be based on best available evidence and plausible assumptions. Causal inference and health decision science are two methodological approaches providing information to help guide decision making in health care. Both approaches are quantitative methods that use statistical and modeling techniques and simplifying assumptions to mimic the complexity of the real world. We intend to review and lay out both disciplines with their aims, strengths and limitations based on a combination of textbook knowledge and expert experience.Methods: To help understanding and differentiating the methodological approaches of causal inference and health decision science, we reviewed both methods with the focus on aims, research questions, methods, assumptions, limitations and challenges, and software. For each methodological approach, we established a group of four experts from our own working group to carefully review and summarize each method, followed by structured discussion rounds and written reviews, in which the experts from all disciplines including HTA and medicine were involved. The entire expert group discussed objectives, strengths and limitations of both methodological areas, and potential synergies. Finally, we derived recommendations for further research and provide a brief outlook on future trends.Results: Causal inference methods aim for drawing causal conclusions from empirical data on the relationship of pre-specified interventions on a specific target outcome and apply a counterfactual framework and statistical techniques to derive causal effects of exposures or interventions from these data. Causal inference is based on a causal diagram, more specifically, a directed acyclic graph (DAG), which encodes the assumptions regarding the causal relations between variables. Depending on the type of confounding and selection bias, traditional statistical methods or more complex g-methods are needed to derive valid causal effects. Besides the correct specification of the DAG and the statistical model, assumptions such as consistency, positivity, and exchangeability must be checked when aiming at causal inference.Health decision science aims for guiding policy decision making regarding health interventions considering and balancing multiple competing objectives of a decision based on data from multiple sources and studies, for example prevalence studies, clinical trials and long-term observational routine effectiveness studies, and studies on preferences and costs. It involves decision analysis, a systematic, explicit and quantitative framework to guide decisions under uncertainty. Decision analyses are based on decision-analytic models to mimic the course of disease as well as aspects and consequences of the intervention in order to quantitatively optimize the decision. Depending on the type of decision problem, decision trees, state-transition models, discrete event simulation models, dynamic transmission models, or other model types are applied. Models must be validated against observed data, and comprehensive sensitivity analyses must be performed to assess uncertainty. Besides the appropriate choice of the model type and the valid specification of the model structure, it must be checked if input parameters of effects can be interpreted as causal parameters in the model. Otherwise results will be biased.Conclusions: Both causal inference and health decision science aim for providing best causal evidence for informed health decision making. The strengths and limitations of both methods differ and a good understanding of both methods is essential for correct application but also for correct interpretation of findings from the described methods. Importantly, decision-analytic modeling should be combined with causal inference when developing guidance and recommendations regarding decisions on health care interventions.

Purpose: To analyze the predictive value of parameters of submaximal and maximal cardiopulmonary exercise performance on International Ski Federation (Fédération Internationale de Ski) World Cup ranking (FIS ranking) in elite Austrian Alpine skiers. Methods: Over 7 World Cup seasons (2012–2018), exercise data (maximal oxygen uptake and maximum power output, lactate threshold 2, and ventilatory threshold 2, based on stepwise cycle spiroergometry) were analyzed to determine whether there was a correlation between world FIS ranking and exercise capacity of male and female elite Alpine skiers. Results: The data of 39 male skiers (age: 27.67 [4.20] y, body mass index: 26.03 [1.25] kg/m2) and 36 female skiers (age: 25.49 [3.18] y, body mass index: 22.97 [1.71] kg/m2) were included in this study. The maximum oxygen uptake and maximum power output ranged from 4.37 to 4.42 W/kg and 53.41 to 54.85 mL/kg/min in men and from 4.17 to 4.30 W/kg and 45.96 to 49.16 mL/kg/min in women, respectively, over the 7 seasons; the yearly mean FIS ranking ranged from 17 to 24 in men and 9 to 18 in women. In a fixed-effects model used for the subsequent panel regression analysis, no statistically significant effect on FIS ranking was found for the exercise parameters of interest. Conclusions: Neither maximal aerobic tests nor maximum power output significantly predicted competitive performance, as indexed by the FIS ranking. This reinforces the assumption that no single parameter determines competition performance in this complex sport. Therefore, identifying the optimum amount of endurance training remains a major challenge for athletes and coaches, as does identifying and improving the factors that determine performance. [ABSTRACT FROM AUTHOR]

Background: Clear evidence on the benefit-harm balance and cost effectiveness of population-based screening for colorectal cancer (CRC) is missing. We aim to systematically evaluate the long-term effectiveness, harms and cost effectiveness of different organized CRC screening strategies in Austria.Methods: A decision-analytic cohort simulation model for colorectal adenoma and cancer with a lifelong time horizon was developed, calibrated to the Austrian epidemiological setting and validated against observed data. We compared four strategies: 1) No Screening, 2) FIT: annual immunochemical fecal occult blood test age 40-75 years, 3) gFOBT: annual guaiac-based fecal occult blood test age 40-75 years, and 4) COL: 10-yearly colonoscopy age 50-70 years. Predicted outcomes included: benefits expressed as life-years gained [LYG], CRC-related deaths avoided and CRC cases avoided; harms as additional complications due to colonoscopy (physical harm) and positive test results (psychological harm); and lifetime costs. Tradeoffs were expressed as incremental harm-benefit ratios (IHBR, incremental positive test results per LYG) and incremental cost-effectiveness ratios [ICER]. The perspective of the Austrian public health care system was adopted. Comprehensive sensitivity analyses were performed to assess uncertainty.Results: The most effective strategies were FIT and COL. gFOBT was less effective and more costly than FIT. Moving from COL to FIT results in an incremental unintended psychological harm of 16 additional positive test results to gain one life-year. COL was cost saving compared to No Screening. Moving from COL to FIT has an ICER of 15,000 EUR per LYG.Conclusions: Organized CRC-screening with annual FIT or 10-yearly colonoscopy is most effective. The choice between these two options depends on the individual preferences and benefit-harm tradeoffs of screening candidates. [ABSTRACT FROM AUTHOR]

Background: Infrapopliteal endovascular interventions (EVT) strategies in diabetic patients are still in debate because the lesions are more likely to be diffuse with a different pattern of collateral arteries ranging from reduced to normal caliber. The aim of this all-comers study was to analyse the outcome of two different infrapopliteal EVT strategies (Group I: angiosome-based direct revascularization - DR vs. Group II: complete (direct + indirect) revascularization strategy - CR) in diabetic patients with chronic limb-threatening ischemia (CLTI) in 2 time-periods. Furthermore we analysed the outcome if DR or CR failed and only indirect revascularization (IR) or no revascularization was possible. Both groups were differentiated in patients with collaterals, defined as an intact pedal arch (immediate or after pedal PTA). Patients and methods: The database includes 91 consecutive EVT with two intrapopliteal interventional strategies performed in 68 diabetic patients (pts. 24 female, 44 male, mean age 73±10 years) between 2013-2016 and 2017-2022. Positive clinical outcome was defined as wound healing with or w/o minor amputation, combined with a symptom improvement to Rutherford category 0 or 1 after 6 months. The clinical outcome proportions were compared using the Fisher's exact test. Results: Successful DR (59%) and successful CR (47%) strategy demonstrated a similar positive clinical outcome (92.6% vs. 90.5%; p =0.594). Indirect revascularization (Group I: 26%; Group II: 44%) showed a significantly lower positive outcome in comparison to a successful DR as well as CR strategy (33.3% vs. 92.6%, p =0.0003; 40% vs 90.5%, p =0.001). IR outcome improved by the presence of collaterals (66.7% vs. 30.8%). Conclusions: In case of successful intervention, both strategies (DR and CR) yielded a similarly high proportion of positive clinical outcome. The role of collaterals and the pedal arch on the clinical outcome are important in patients in whom only IR was possible.

Purpose: Medication-related osteonecrosis of the jaw (MRONJ) is one of the most important toxicities of antiresorptive therapy, which is standard practice for patients with breast cancer and bone metastases. However, the population-based incidence of MRONJ is not well established. We therefore performed a retrospective multicenter study to assess the incidence for a whole Austrian federal state (Tyrol)., Materials and Methods: This retrospective multicenter study was conducted between 2000 and 2020 at all nine breast centers across Tyrol, Austria. Using the cancer registry, the total Tyrolean population was screened for all patients with breast cancer. All patients with breast cancer and bone metastases receiving antiresorptive therapy were finally included in the study., Results: From 8,860 patients initially screened, 639 individuals were eligible and included in our study. Patients received antiresorptive therapy once per month without de-escalation of therapy. MRONJ was diagnosed in 56 (8.8%, 95% CI, 6.6 to 11.0) patients. The incidence of MRONJ was 11.6% (95% CI, 8.0 to 15.3) in individuals treated with denosumab only, 2.8% (95% CI, 0.7 to 4.8) in those treated with bisphosphonates only, and 16.3% (95% CI, 8.8 to 23.9) in the group receiving bisphosphonates followed by denosumab. Individuals developed MRONJ significantly earlier when treated with denosumab. Time to MRONJ after treatment initiation was 4.6 years for individuals treated with denosumab only, 5.1 years for individuals treated with bisphosphonates only, and 8.4 years for individuals treated with both consecutively., Conclusion: MRONJ incidence in breast cancer patients with bone metastases was found to be considerably higher, especially for patients receiving denosumab, when compared with available data in the literature. Additionally, patients treated with denosumab developed MRONJ significantly earlier.