ESTRO 36 Abstract Book

S103 ESTRO 36 2017 _______________________________________________________________________________________________

the wider spectrum of Health Technology Assessment (HTA). Although more limited types of evaluations exist, only the formal comparison of costs and effects between two or more alternative interventions is considered to be a full economic evaluation. To date, economic evaluation has been mainly applied to pharmaceutical interventions. Less attention has been paid to other types of intervention, including those involving advanced health technologies in radiotherapy. Overall, the fundamental problem in determine the cost-effectiveness for new technologies is the lack of valid data on effects as well as costs. While randomized trials provide the most robust clinical evidence of comparative efficacy, it is widely recognized that high-level evidence is rarely achievable with new technology, due to methodological and ethical problems. Decision making in high technology areas is therefore more challenging since adequate data is often lacking. The number of published well performed economic evaluations of radiotherapy using appears quite low. As a consequence, there is limited robust evidence on the effectiveness and cost effectiveness of radiotherapy in cancer. Besides, it seems that results of apparently similar cost-effectiveness studies are often not comparable, since there is no uniformity on used input variables – e.g. patient and tumor characteristics, assumed impact of the treatment on outcome, treatment costs – which is essential for the final result of the analysis. Therefore, comparing results of for example Markov model analysis were different variables are used doesn’t make sense. Let’s take a closer look at the case of proton therapy. It seems hard, or even impossible, to estimate the cost-effectiveness of proton therapy based on the published literature, mainly due to a lack of data. This does not, however, relieve the many proton centers that have recently become operational from the moral duty to generate prospective evidence in terms of clinical outcome and value for money. Even if they do, this will take many years, whereas guidance in how to most optimally allocate resources to these novel treatments is urgently needed. Of course, more and better data, will result in better outcome and more robust conclusions, however this lack of data was already obvious ten years ago, we might wonder if an adequate dataset will ever be available. A model-based approach could be the solution based on subgroup or individual patients. Applying NTCP models forms the decisive link can generate evidence regarding the value of proton therapy, and helps to create enriched cohorts of patients who are likely to benefit from protons. Next, it is possible to quantitatively assess the effectiveness of proton therapy for individual patients, comparing photon and proton treatments on dose metric, toxicity and cost-effectiveness levels, retrieved from a decision support system. Gathering good clinical and cost data remains essential in defining the cost-effectiveness of new technologies, such as proton therapy. In the absence of level 1 evidence, well-performed modelling studies taking the uncertainties, available cost and outcome parameters into account, can help to tackle the problem. Because it is evident that protons will not be cost-effective for a total group of patients but for a subset of patients, we shouldn’t look at the whole population anymore but at an individual patient level. Well-designed decision support systems will play an important role here. Whereas agreement on used input variables and primary endpoints remains still essential. SP-0206 Tips and tricks for safe and effective routine clinical application F. Duprez 1 1 Universitair Ziekenhuis Gent, Radiotherapie-Oncologie, Gent, Belgium Since almost a decade, adaptive (ART) and multimodality image guided radiotherapy (IGRT) have been investigated with the aim of improving radiotherapy in many settings.

Several planning studies, observational studies and prospective trials have demonstrated the feasibility and theoretical advantages of ART and IGRT. However, the implementation of ART and IGRT also imply incremental work load, use of imaging techniques and extra or longer hospital visits for patients that can already be overwhelmed by standard procedures in their ill status. Unlike the fact that there is yet no large-scale evidence of the safety or cost effectiveness of these techniques in clinical routine, dedicated hardware and software for ART and IGRT are commercially available and implemented in an increasing number of centers. This lecture will focus on the clinician-oriented point of view. ART might be planned before start of therapy, e.g. consecutive plannings at certain timepoints in the radiation course, while it might also be decided during the course of radiotherapy based on clinical findings or changing anatomy: both indications for ART will be discussed in the lecture. Unanswered questions and caveats will be covered, e.g. how to report and interpret final delivered doses, how to handle with volume shrinkage in targets/organs-at-risk and how to identify triggers to decide to adapt treatment. During the lecture, practical tips and tricks for implementation of ART and multimodality IGRT will be given. SP-0207 Do we have the tools for safe application of adaptive radiotherapy? L.B. Hysing 1,2 , S. Thörnqvist 1,2 1 Haukeland University Hospital, Oncology and Medical physics, Bergen, Norway 2 University of Bergen, Physics and Technology, Bergen, Norway Radiotherapy (RT) is traditionally administered as an ‘open loop-process’ of pre-treatment imaging, planning and fractionated treatment delivery. But why don’t we just image the patient at each treatment fraction, make a plan on the fly and administer this plan to the patient while he/she is lying on the treatment table? In the context of adaptive radiotherapy (ART) this would be referred to as online re-planning. ART is the process where the original treatment plan can be modified if motivated by feedback from previous fractions during the course of RT (Yan et al. PMB 1997;42:123-32). Whereas feedback in the vast majority of the clinical ART workflows in pelvic RT are based on daily images acquired at each fraction, the type, timing and frequency of adaptations can vary greatly from daily online tracking and re-planning approaches, daily plan selection or updating of the plan once during the course of treatment (Thörnqvist S. Acta Oncol 2016;55:943-58). As of January 2015, the online re- planning scenario above had been applied to 1409 patients, all receiving brachytherapy for gynecological cancer. However, for external beam therapy online re- planning was common among in-silico simulation studies (36% of prostate studies, 56% of gyne studies and 22% of bladder studies as of Jan 2015), but it had not yet been applied clinically. Identified bottle necks for clinical application were limited in-room imaging quality (mostly CBCT) together with manual contouring which was a pre- requisite in 70% of the in-silico studies. For external photon therapy, MRI is becoming an alternative to CBCT with better soft tissue contrast thus also aiding contour propagation based on deformable image registration. However, for particle therapy where ART is expected to be needed more frequently as well as for a larger fraction of patients, in-room imaging will remain a big challenge. For photon therapy, tools are being developed by both research teams and vendors to allow for fast re-planning at each treatment fraction. Such solutions should include i) target generation ii) evaluation of the dose distribution iii) QA of the MU calculation of beam parameters. Is such a workflow feasible and realistic in clinical practice? Is it safe? How and which dose should be reported and