Quality, technology and outcomes: evolution and evaluation of new treatments and/or new technology

A systematic literature review of definitions and classification systems for radiotherapy innovation: A first step towards building a value-based assessment tool for radiation oncology

INTRODUCTION

Timely access to radiotherapy innovations remains suboptimal, partly because there is no commonly agreed appraisal system suitable for the broad range of radiotherapy interventions. The Health Economics in Radiation Oncology (HERO) programme of ESTRO therefore engaged in building a radiotherapy-specific value-based framework. We report on a first step towards that aim, documenting the available definitions and classification systems for radiotherapy interventions.

METHODS

A systematic literature search was carried out in Pubmed and Embase, following PRISMA methodology and using search terms on 'innovation', 'radiotherapy', 'definition' and 'classification'. Data were extracted from articles that met prespecified inclusion criteria.

RESULTS

Out of 13,353 articles, 25 met the inclusion criteria, resulting in the identification of 7 definitions of innovation and 15 classification systems applicable to radiation oncology. Iterative appraisal divided the classification systems into two groups. A first group of 11 systems categorized innovations according to the perceived magnitude of innovation, typically 'minor' versus 'major'. The remaining 4 systems categorised innovations according to radiotherapy-specific characteristics, such as the type of radiation equipment or radiobiological properties. Here, commonly used terms as 'technique' or 'treatment' were found to be used in different meanings.

DISCUSSION

There is no widely accepted definition or classification system for radiotherapy innovations. The data however suggest that unique properties of radiotherapy interventions can be used to categorise innovations in radiation oncology. Still, there remains a need for clear terminology denoting radiotherapy-specific characteristics.

CONCLUSION

Building on this review, the ESTRO-HERO project will define what is required for a radiotherapy-specific value-based assessment tool.

Implementation of MR-linac and proton therapy in two radiotherapy departments in The Netherlands: Recommendations based on lessons learned

Recently, two new treatment techniques, i.e. proton therapy and MR-linac based radiotherapy (RT), have been introduced in Dutch RT centres with major impact on daily practice. The content and context of these techniques are frequently described in scientific literature while little is reported about the implementation phase. This process is complex due to a variety of aspects, such as the involvement of multiple stakeholders, significant unpredictability in the start-up phase, the impact of the learning curve, standard operating procedures under development, new catchment areas, and extensive training programs. Insight about implementation in daily care is utterly important for clinics that are about to introduce these new technologies in order to prevent that every centre needs to reinvent the wheel. This position paper gives an overview of the implementation of proton therapy and MR-linac based RT in two large academic RT centres in the Netherlands, i.e. Maastro and Radboudumc respectively. With this paper we aim to report our lessons learned, in order to facilitate other RT centres that consider introducing these and other new techniques in their departments.

Master Protocol Trial Design for Efficient and Rational Evaluation of Novel Therapeutic Oncology Devices

Historically, the gold standard for evaluation of cancer therapeutics, including medical devices, has been the randomized clinical trial. Although high-quality clinical data are essential for safe and judicious use of therapeutic oncology devices, class II devices require only preclinical data for US Food and Drug Administration approval and are often not rigorously evaluated prior to widespread uptake. Herein, we review master protocol design in medical oncology and its application to therapeutic oncology devices, using examples from radiation oncology. Unique challenges of clinical testing of radiation oncology devices (RODs) include patient and treatment heterogeneity, lack of funding for trials by industry and health-care payers, and operator dependence. To address these challenges, we propose the use of master protocols to optimize regulatory, financial, administrative, quality assurance, and statistical efficiency of trials evaluating RODs. These device-specific master protocols can be extrapolated to other devices and encompass multiple substudies with the same design, statistical considerations, logistics, and infrastructure. As a practical example, we outline our phase I and II master protocol trial of stereotactic magnetic resonance imaging–guided adaptive radiotherapy, which to the best of our knowledge is the first master protocol trial to test a ROD. Development of more efficient clinical trials is needed to promote thorough evaluation of therapeutic oncology devices, including RODs, in a resource-limited environment, allowing more practical and rapid identification of the most valuable advances in our field.

Late locoregional complications associated with adjuvant radiotherapy in the treatment of breast cancer: Systematic review and meta-analysis

This systematic review with meta-analysis addressed late locoregional complications associated with adjuvant radiotherapy (RT) in breast cancer. Among 2120 titles, ten comparative studies in patients undergoing surgery vs surgery and radiotherapy reporting complications were evaluated. RT was associated with an increased risk of capsular contracture and decreased the mobility of the upper limb. A borderline association of lymphedema risk using RT was noted in the random-effects model but was significant in the fixed-effects model.

R-IDEAL: A Framework for Systematic Clinical Evaluation of Technical Innovations in Radiation Oncology

The pace of innovation in radiation oncology is high and the window of opportunity for evaluation narrow. Financial incentives, industry pressure, and patients' demand for high-tech treatments have led to widespread implementation of innovations before, or even without, robust evidence of improved outcomes has been generated. The standard phase I-IV framework for drug evaluation is not the most efficient and desirable framework for assessment of technological innovations. In order to provide a standard assessment methodology for clinical evaluation of innovations in radiotherapy, we adapted the surgical IDEAL framework to fit the radiation oncology setting. Like surgery, clinical evaluation of innovations in radiation oncology is complicated by continuous technical development, team and operator dependence, and differences in quality control. Contrary to surgery, radiotherapy innovations may be used in various ways, e.g., at different tumor sites and with different aims, such as radiation volume reduction and dose escalation. Also, the effect of radiation treatment can be modeled, allowing better prediction of potential benefits and improved patient selection. Key distinctive features of R-IDEAL include the important role of predicate and modeling studies (Stage 0), randomization at an early stage in the development of the technology, and long-term follow-up for late toxicity. We implemented R-IDEAL for clinical evaluation of a recent innovation in radiation oncology, the MRI-guided linear accelerator (MR-Linac). MR-Linac combines a radiotherapy linear accelerator with a 1.5-T MRI, aiming for improved targeting, dose escalation, and margin reduction, and is expected to increase the use of hypofractionation, improve tumor control, leading to higher cure rates and less toxicity. An international consortium, with participants from seven large cancer institutes from Europe and North America, has adopted the R-IDEAL framework to work toward coordinated, evidence-based introduction of the MR-Linac. R-IDEAL holds the promise for timely, evidence-based introduction of radiotherapy innovations with proven superior effectiveness, while preventing unnecessary exposure of patients to potentially harmful interventions.

Evaluating the Impact of In Vivo EPID Dosimetry on Intensity-Modulated Radiation Therapy Treatment Delivery Workflow: A Stakeholder Perspective

INTRODUCTION

In vivo electronic portal imaging device (EPID) dosimetry is an advanced imaging technique that can obtain patient-specific dose data for quality assurance purposes. However, clinical integration of this technique remains a challenge. This study evaluates the impact of implementing an in vivo EPID technique into the treatment delivery workflow for head and neck cancer (HNC) patients in a large cancer centre setting.

MATERIALS/METHODS

Intensity-modulated radiation therapy treatment delivery was simulated on a phantom for 10 HNC cases with and without in vivo EPID dosimetry. Investigators performed the EPID technique by using a preliminary protocol written by medical physicists. Process maps were created to illustrate changes in treatment delivery workflow.

RESULTS

Treatment delivery times increased by an average of 2.34 minutes (P = .0006) when the EPID technique was used. Factors that increased treatment times included the time for storing captured EPID data, adjustment of the imaging panel position as a function of field size, and an inability to use automatic field sequencing when acquiring images.

CONCLUSIONS

The involvement of stakeholders in protocol development allows for the identification of usability issues and staff training needs. Findings from this study have identified limitations of the in vivo EPID technique that may negatively impact treatment delivery workflow. Efficiencies within in vivo EPID dosimetry systems can be improved by enabling automatic field sequencing with automatic image-saving capabilities.

Information and communication technology for managing pain in palliative care: a review of the literature

BACKGROUND

Information and communication technology (ICT) systems are being developed for electronic symptom reporting across different stages of the cancer trajectory with research in palliative care at an early stage.

AIM/DESIGN

This paper presents the first systematic search of the literature to review existing ICT systems intended to support management of pain in palliative care patients with cancer. The review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews and meta-analyses.

DATA SOURCES

Four databases (Embase, MEDLINE, PsycINFO and Healthcare Management Information Consortium) from 1990 to December 2012 were searched, with exclusion of papers based on their description of ICT systems and language used.

RESULTS

24 articles met the inclusion criteria, many of which reported the use of non-experimental research designs. Studies were identified at different stages of development with no systems having reached implementation. Most systems captured pain as part of quality-of-life measurement with wide variation in approaches to pain assessment.

CONCLUSIONS

ICT systems for symptom reporting are emerging in the palliative care context. Future development of ICT systems need to increase the quality and scale of development work, consider how recommendations for pain measurement can be integrated and explore how to effectively use system feedback with patients.

A comprehensive quality assurance program for personnel and procedures in radiation oncology: value of voluntary error reporting and checklists

PURPOSE

This report describes the value of a voluntary error reporting system and the impact of a series of quality assurance (QA) measures including checklists and timeouts on reported error rates in patients receiving radiation therapy.

METHODS AND MATERIALS

A voluntary error reporting system was instituted with the goal of recording errors, analyzing their clinical impact, and guiding the implementation of targeted QA measures. In response to errors committed in relation to treatment of the wrong patient, wrong treatment site, and wrong dose, a novel initiative involving the use of checklists and timeouts for all staff was implemented. The impact of these and other QA initiatives was analyzed.

RESULTS

From 2001 to 2011, a total of 256 errors in 139 patients after 284,810 external radiation treatments (0.09% per treatment) were recorded in our voluntary error database. The incidence of errors related to patient/tumor site, treatment planning/data transfer, and patient setup/treatment delivery was 9%, 40.2%, and 50.8%, respectively. The compliance rate for the checklists and timeouts initiative was 97% (P<.001). These and other QA measures resulted in a significant reduction in many categories of errors. The introduction of checklists and timeouts has been successful in eliminating errors related to wrong patient, wrong site, and wrong dose.

CONCLUSIONS

A comprehensive QA program that regularly monitors staff compliance together with a robust voluntary error reporting system can reduce or eliminate errors that could result in serious patient injury. We recommend the adoption of these relatively simple QA initiatives including the use of checklists and timeouts for all staff to improve the safety of patients undergoing radiation therapy in the modern era.

Predicting outcomes in radiation oncology--multifactorial decision support systems

With the emergence of individualized medicine and the increasing amount and complexity of available medical data, a growing need exists for the development of clinical decision-support systems based on prediction models of treatment outcome. In radiation oncology, these models combine both predictive and prognostic data factors from clinical, imaging, molecular and other sources to achieve the highest accuracy to predict tumour response and follow-up event rates. In this Review, we provide an overview of the factors that are correlated with outcome-including survival, recurrence patterns and toxicity-in radiation oncology and discuss the methodology behind the development of prediction models, which is a multistage process. Even after initial development and clinical introduction, a truly useful predictive model will be continuously re-evaluated on different patient datasets from different regions to ensure its population-specific strength. In the future, validated decision-support systems will be fully integrated in the clinic, with data and knowledge being shared in a standardized, instant and global manner.

Quality indicators in radiation oncology

Oncologic specialty societies and multidisciplinary collaborative groups have dedicated considerable effort to developing evidence-based quality indicators (QIs) to facilitate quality improvement, accreditation, benchmarking, reimbursement, maintenance of certification, and regulatory reporting. In particular, the field of radiation oncology has a long history of organized quality assessment efforts and continues to work toward developing consensus quality standards in the face of continually evolving technologies and standards of care. This report provides a comprehensive review of the current state of quality assessment in radiation oncology. Specifically, this report highlights implications of the healthcare quality movement for radiation oncology and reviews existing efforts to define and measure quality in the field, with focus on dimensions of quality specific to radiation oncology within the "big picture" of oncologic quality assessment efforts.

Monte Carlo role in radiobiological modelling of radiotherapy outcomes

Radiobiological models are essential components of modern radiotherapy. They are increasingly applied to optimize and evaluate the quality of different treatment planning modalities. They are frequently used in designing new radiotherapy clinical trials by estimating the expected therapeutic ratio of new protocols. In radiobiology, the therapeutic ratio is estimated from the expected gain in tumour control probability (TCP) to the risk of normal tissue complication probability (NTCP). However, estimates of TCP/NTCP are currently based on the deterministic and simplistic linear-quadratic formalism with limited prediction power when applied prospectively. Given the complex and stochastic nature of the physical, chemical and biological interactions associated with spatial and temporal radiation induced effects in living tissues, it is conjectured that methods based on Monte Carlo (MC) analysis may provide better estimates of TCP/NTCP for radiotherapy treatment planning and trial design. Indeed, over the past few decades, methods based on MC have demonstrated superior performance for accurate simulation of radiation transport, tumour growth and particle track structures; however, successful application of modelling radiobiological response and outcomes in radiotherapy is still hampered with several challenges. In this review, we provide an overview of some of the main techniques used in radiobiological modelling for radiotherapy, with focus on the MC role as a promising computational vehicle. We highlight the current challenges, issues and future potentials of the MC approach towards a comprehensive systems-based framework in radiobiological modelling for radiotherapy.

Radiation therapy for the treatment of recurrent glioblastoma: an overview

Despite the therapeutic advances in neuro-oncology, most patients with glioblastoma ultimately experience local progression/relapse. Re-irradiation has been poorly viewed in the past, mainly due to the overestimated risk of side effects using conventional radiotherapy. To date, thanks to the improvement of several delivery techniques, together with improved imaging capabilities, re-irradiation is a viable salvage treatment option to manage such clinical scenario. A literature overview on the feasibility and efficacy of the different irradiation modalities for recurrent glioblastoma along with considerations on areas of improvement are provided.