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To make recommendations on managing the surveillance of patients with stage I, II, III or resectable IV melanoma who are clinically free of disease following treatment with curative intent. This guideline was developed by Ontario Health's (Cancer Care Ontario's) Program in Evidence-Based Care and the Melanoma Disease Site Group (including seven medical oncologists, four surgical oncologists, three dermatologists, one radiation oncologist and one patient representative). The MEDLINE, EMBASE, Cochrane Library, PROSPERO databases and the main relevant guideline websites were searched. Internal and external reviews were conducted, with final approval by the Program in Evidence-Based Care and the Melanoma Disease Site Group. The Grading of Recommendations, Assessment, Development and Evaluation approach was followed, and the Modified Delphi method was used. Based on the current evidence (eight eligible original study papers and four relevant guidelines) and the clinical opinions of the authors of this guideline, the initial recommendations were made. To reach 75% agreement for each recommendation, the Melanoma Disease Site Group (16 members) voted twice and one recommendation was voted on three times. After a comprehensive internal and external review process (including national and international reviewers), 12 recommendations, three weak recommendations and six qualified statements were ultimately made. After a systematic review, a comprehensive internal and external review process and a consensus process, the current guideline has been created. The guideline authors believe that this guideline will help clinicians, patients and policymakers make well-informed healthcare decisions that will guide them in clinical melanoma surveillance and ultimately assist in improving patient outcomes. [ABSTRACT FROM AUTHOR]

Auto-contouring could revolutionise future planning of radiotherapy treatment. The lack of consensus on how to assess and validate auto-contouring systems currently limits clinical use. This review formally quantifies the assessment metrics used in studies published during one calendar year and assesses the need for standardised practice. A PubMed literature search was undertaken for papers evaluating radiotherapy auto-contouring published during 2021. Papers were assessed for types of metric and the methodology used to generate ground-truth comparators. Our PubMed search identified 212 studies, of which 117 met the criteria for clinical review. Geometric assessment metrics were used in 116 of 117 studies (99.1%). This includes the Dice Similarity Coefficient used in 113 (96.6%) studies. Clinically relevant metrics, such as qualitative, dosimetric and time-saving metrics, were less frequently used in 22 (18.8%), 27 (23.1%) and 18 (15.4%) of 117 studies, respectively. There was heterogeneity within each category of metric. Over 90 different names for geometric measures were used. Methods for qualitative assessment were different in all but two papers. Variation existed in the methods used to generate radiotherapy plans for dosimetric assessment. Consideration of editing time was only given in 11 (9.4%) papers. A single manual contour as a ground-truth comparator was used in 65 (55.6%) studies. Only 31 (26.5%) studies compared auto-contours to usual inter- and/or intra-observer variation. In conclusion, significant variation exists in how research papers currently assess the accuracy of automatically generated contours. Geometric measures are the most popular, however their clinical utility is unknown. There is heterogeneity in the methods used to perform clinical assessment. Considering the different stages of system implementation may provide a framework to decide the most appropriate metrics. This analysis supports the need for a consensus on the clinical implementation of auto-contouring. • A systematic review of auto-contouring assessment publications was performed. • Variation in the metrics used in auto-contouring research is demonstrated. • Geometric metrics are the most popular, but these may not be clinically meaningful. • There is significant heterogeneity in the "clinically relevant" assessment metrics. • There is a need to standardise auto-contouring assessment, to enable clinical use. [ABSTRACT FROM AUTHOR]

Patient factors affect the risk of radiotherapy toxicity, but many are poorly defined. Studies have shown that race affects cancer incidence, survival, drug response, molecular pathways and epigenetics. Effects on radiosensitivity and radiotherapy toxicity are not well studied. The aim of the present study was to identify the effects of race and ethnicity on the risk of radiotherapy toxicity. A systematic review was carried out of PubMed, Ovid Medline and Ovid Embase with no year limit. PRISMA 2020 guidelines were followed. Two independent assessors reviewed papers. Of 607 papers screened, 46 fulfilled the inclusion criteria. Papers were published between 1996 and 2021 and involved 30–28,354 individuals (median 433). Most involved patients with prostate (33%), breast (26%) and lung (9%) cancer. Both early and late toxicities were studied. Some studies reported a higher risk of toxicity in White men with prostate cancer compared with other races and ethnicities. For breast cancer patients, some reported an increased risk of toxicity in White women compared with other race and ethnic groups. In general, it was difficult to draw conclusions due to insufficient reporting and analysis of race and ethnicity in published literature. Reporting of race and ethnicity in radiotherapy studies must be harmonised and improved and frameworks are needed to improve the quality of reporting. Further research is needed to understand how ancestral heritage might affect radiosensitivity and risk of radiotherapy toxicity. • Ancestral heritage is likely to affect risk of some radiation toxicities. • Insufficient evidence from reviewing effects of race and ethnicity on toxicity. • Reporting race and ethnicity in radiation studies must be harmonised and improved. • Socioeconomic and comorbidity effects must be addressed. • Radiogenomic research needs diversifying beyond euro-centricity. [ABSTRACT FROM AUTHOR]

A patient view paper focused on hopes and challenges facing the never smoker lung cancer population – from lived experience, unexpected diagnosis, treatment and subsequent immersion in lung cancer research and patient advocacy over many years, citing examples, references and events organised to explore the subject by UK research institutions. Based on lived experience, invited patient perspective conference presentations including National Cancer Research Institute (NCRI) never smoker lung cancer research strategy event opening presentation and subsequent article, includes references to relevant papers/findings and points raised during research events/group discussions, alongside personal experiences and beliefs. Discussions with clinicians, events, surveys, meetings and virtual discussions all revealed a dearth of evidence available to identify the best way to deal with this patient cohort at almost every aspect of their experience – from missed/late diagnosis, to screening potential (non-existent), mutation driven treatments (what about those ineligible?), and psychosocial/psychological aspects given their different life stage from older traditional lung cancer patients. More effort and focus are needed to better understand what is driving these cases, how best to detect them sooner and respond/refer to treatments as well as developing screening methods alongside increased public and healthcare professional awareness raising and tools to support clinicians in earlier detection. [ABSTRACT FROM AUTHOR]

The NHS England Radiotherapy Service Specification calls for routine use of patient-reported outcome measures (PROMs). However, barriers exist at patient, healthcare professional and service levels. The aim of the present study was to determine the current use of PROMs within radiotherapy services in England. The current attitudes, barriers and enablers to the implementation of PROMs in radiotherapy practice were evaluated and practical recommendations to inform future implementation were developed. A mixed-methods approach was adopted to obtain quantitative and qualitative data. An online questionnaire was developed and disseminated to all radiotherapy operational delivery network managers across England. The questionnaire consisted of 12 open and closed questions relating to PROMs use, with the option to provide free-text responses. Inductive thematic analysis was conducted on free-text comments, whereas descriptive statistics were used to analyse quantitative data. In total, 182 responses were received from 40 of the 50 radiotherapy providers, resulting in a response rate of 84%. The current use of PROMs was analysed, including rationale for use, tools used, format of PROMs collection and timing within the radiotherapy pathway. Most respondents indicated that PROMs were used in the context of clinical trials only. Through thematic analysis, four identical key themes were identified relating to both barriers and enablers to PROMs use; these included IT infrastructure, time, human/financial resources and training/education. A fifth theme, standardisation, was identified as a key enabler to PROMs use. Our findings show that outside of clinical trials, PROMs are not routinely used in radiotherapy services due to barriers identified at professional and service levels. Here we provide recommendations to mitigate the barriers identified and implement PROMs in radiotherapy, including training for healthcare professionals and standardisation of PROMs tools and storage. This study provides a key first step in driving PROMs implementation within radiotherapy services across England. • Outside of clinical trials, PROMs were not widely used within radiotherapy services. • Common PROMs used included QOL, anxiety/depression and urinary/bowel function tools. • PROMs are completed using either paper or electronic forms, by staff or patients. • Barriers include IT infrastructure, time, resources (staff/finances) and training. • Enablers included IT, time, resources, training and standardisation. [ABSTRACT FROM AUTHOR]

Advances in cancer treatment with resultant dramatic improvements in long-term survival have led to increasing awareness of the wide range of medical and social issues faced by survivors of malignancy. The potential deleterious effects on fertility are a significant worry of women and trans gender men, and the rising trend in delaying childbearing and the higher proportion of patients who have not completed their family at the time of diagnosis increases the demand for an optimised fertility-preservation service. Fertility preservation for this group following a diagnosis of cancer is a rapidly expanding area of reproductive medicine, although provision for such treatment often varies by region. In the past, there were few treatment options, but with dramatic improvements in oocyte cryopreservation and, more recently, ovarian tissue cryopreservation, this area of fertility care has broadened substantially. This review will be exploring areas that apply to all cisgender women, but not necessarily all trans men and non-binary individuals. There are specific considerations in fertility preservation for trans people, which are beyond the scope of this paper. All individuals with female reproductive organs should be offered the opportunity to discuss fertility preservation prior to starting potential gonadotoxic treatment. Failure to do this may negatively influence their anticancer treatment choices and adherence to treatment regimens. There are currently few networks streamlined around offering this service and as demand for these treatment options increases, it is recognised that these complex patients require specialist management within recognised care pathways. Here we are looking to describe some of the unique challenges associated with providing a state-of-the-art service, particularly in a financially unpredictable climate in the midst of the COVID-19 pandemic. • The potential deleterious effects of cancer treatment on fertility are a significant worry of and this increases the demand for an optimised fertility-preservation service. • A service that engages patients and provides them with suitable guidance to aid their decision-making is needed. • Regional fertility preservation networks, in conjunction with reproductive and oncology teams would help with this. • Post-covid medicine is a rapidly changing landscape for a group of patients who already have a large burden, making long-term predictions impossible to assess. [ABSTRACT FROM AUTHOR]

Normal tissue complication probability (NTCP) models can guide clinical decision making in radiotherapy. In recent years, they have been used for patient selection for proton beam therapy (PBT) for some anatomical tumour sites. This review synthesizes the published evidence regarding the use of NTCP models to predict the toxicity of PBT, for different end points in patients with brain tumours. A search of Medline and Embase using the Patients, Intervention, Comparison, Outcome (PICO) criteria was undertaken. In total, 37 articles were deemed relevant and were reviewed in detail. Nineteen articles on NTCP modelling of toxicity end points were included. Of these, 11 were comparative NTCP studies of PBT versus conventional photon radiotherapy (XRT), which evaluated differences in plan dosimetry and then assumed that XRT-derived literature estimates of NTCP would be applicable to both. Seven papers derived NTCP models based on PBT outcome data, two of which provided model parameters. Among analysed end points, the reduced risk of secondary tumours with PBT as compared with XRT is estimated – through modelling studies – to be considerable and was highlighted by most authors. For other analysed end points, the clinical benefit of PBT mainly depends on tumour location in relation to organs at risk as well as prescription doses. NTCP models can be useful tools for treatment plan comparison. However, most published toxicity data were derived from XRT cohorts; this review has highlighted the need for further studies relating dose-volume parameters to observed toxicity in PBT-treated patients. Specifically, there is a need for PBT-specific NTCP models that can be implemented in the clinical practice. NTCP models built on robust clinical data for the most common radiotherapy toxicities in the brain would potentially redefine the current indications for PBT. [ABSTRACT FROM AUTHOR]

Proton therapy is a radiation technique that yields less dose in normal tissues than photon therapy. In the Netherlands, proton therapy is reimbursed if the reduced dose to normal tissues is predicted to translate into a prespecified reduction in toxicity, based on nationally approved validated models. The aim of this paper is to present the development of a national indication protocol for proton therapy (NIPP) for model-based selection of breast cancer patients and to report on first clinical experiences. A national proton therapy working group for breast cancer (PWG-BC) screened the literature for prognostic models able to estimate the individual risk of specific radiation-induced side-effects. After critical appraisal and selection of suitable models, a NIPP for breast cancer was written and subjected to comments by all stakeholders. The approved NIPP was subsequently introduced to select breast cancer patients who would benefit most from proton therapy. The model of Darby et al. (N Engl J Med 2013; 368:987–82) was the only model fulfilling the criteria prespecified by the PWG-BC. The model estimates t he relative risk of an acute coronary event (ACE) based on the mean heart dose. The absolute lifetime risk of ACE <80 years was calculated by applying this model to the Dutch absolute incidence of ACE for female and male patients, between 40 and 70 years at breast cancer radiotherapy, with/without cardiovascular risk factors. The NIPP was approved for reimbursement in January 2019. Based on a threshold value of a 2% absolute lower risk on ACE for proton therapy compared with photons, 268 breast cancer patients have been treated in the Netherlands with proton therapy between February 2019 and January 2021. The NIPP includes a model that allows the estimation of the absolute risk on ACE <80 years based on mean heart dose. In the first 2 years, 268 breast cancer patients have been treated with proton therapy in The Netherlands. • Selection protocol was determined for proton therapy for breast cancer patients. • Prediction of lifetime risk of acute coronary events based on mean heart dose. • About 3–4% of breast cancer patients are expected to benefit from proton therapy. [ABSTRACT FROM AUTHOR]

Quality assurance in radiotherapy (QART) is essential to ensure the scientific integrity of a clinical trial. This paper reports the findings of the retrospective QART assessment for all centres that participated in PORTEC-3; a randomised controlled trial that compared pelvic radiotherapy with concurrent chemoradiotherapy to the pelvis followed by adjuvant chemotherapy. The trial showed an overall survival benefit for the addition of the chemotherapy in the management of women with high-risk endometrial cancer. Clinicians were invited to upload a randomly selected case/s treated at each of the participating sites. Panel reviewers analysed the contours to certify that the target volumes and organ at risk structures were contoured according to guidelines. The results were categorised into acceptable, minor variation, major variation or unevaluable. The radiotherapy plans were dosimetrically evaluated using the well-established Trans-Tasman Radiation Oncology Group (TROG) protocol. Between August 2010 and January 2018, data from 146 patients of 686 consecutively treated patients were retrospectively reviewed. All 16 Australia and New Zealand and 71 of 77 international centres uploaded data for evaluation. In total, 3514 dosimetric and contour variables were reviewed. Of these, 3136 variables were deemed acceptable (89.2%), with 335 minor (9.6%) and 43 major variations (1.2%). Major contour variations included the clinical target volume vaginal vault, clinical target volume parametria and differential planning target volume vault expansion. The results of the QART assessment confirmed high uniformity and low rates of both minor and major deviations in contouring and dosimetry in all sites. This supports the safe introduction of the PORTEC-3 treatment protocol into routine clinical practice. • Radiotherapy benchmarking reduces the major and minor deviations noted in contouring and dosimetry. • Incorporation of a quality QART programme reduces source bias and facilitates adoption of the trial results. • Inclusion of real-time QART will improve and standardise international radiotherapy quality in future trials. [ABSTRACT FROM AUTHOR]

Lung cancer's radiomic phenotype may potentially inform clinical decision-making with respect to radical radiotherapy. At present there are no validated biomarkers available for the individualisation of radical radiotherapy in lung cancer and the mortality rate of this disease remains the highest of all other solid tumours. MEDLINE was searched using the terms 'radiomics' and 'lung cancer' according to the Preferred Reporting Items for Systematic Reviews and Met-Analyses (PRISMA) guidance. Radiomics studies were defined as those manuscripts describing the extraction and analysis of at least 10 quantifiable imaging features. Only those studies assessing disease control, survival or toxicity outcomes for patients with lung cancer following radical radiotherapy ± chemotherapy were included. Study titles and abstracts were reviewed by two independent reviewers. The Radiomics Quality Score was applied to the full text of included papers. Of 244 returned results, 44 studies met the eligibility criteria for inclusion. End points frequently reported were local (17%), regional (17%) and distant control (31%), overall survival (79%) and pulmonary toxicity (4%). Imaging features strongly associated with clinical outcomes include texture features belonging to the subclasses Gray level run length matrix, Gray level co-occurrence matrix and kurtosis. The median cohort size for model development was 100 (15–645); in the 11 studies with external validation in a separate independent population, the median cohort size was 84 (21–295). The median number of imaging features extracted was 184 (10–6538). The median Radiomics Quality Score was 11% (0–47). Patient-reported outcomes were not incorporated within any studies identified. No studies externally validated a radiomics signature in a registered prospective study. Imaging-derived indices attained through radiomic analyses could equip thoracic oncologists with biomarkers for treatment response, patterns of failure, normal tissue toxicity and survival in lung cancer. Based on routine scans, their non-invasive nature and cost-effectiveness are major advantages over conventional pathological assessment. Improved tools are required for the appraisal of radiomics studies, as significant barriers to clinical implementation remain, such as standardisation of input scan data, quality of reporting and external validation of signatures in randomised, interventional clinical trials. [ABSTRACT FROM AUTHOR]

Artificial intelligence, and in particular deep learning using convolutional neural networks, has been used extensively for image classification and segmentation, including on medical images for diagnosis and prognosis prediction. Use in radiotherapy prognostic modelling is still limited, however, especially as applied to toxicity and tumour response prediction from radiation dose distributions. We review and summarise studies that applied deep learning to radiotherapy dose data, in particular studies that utilised full three-dimensional dose distributions. Ten papers have reported on deep learning models for outcome prediction utilising spatial dose information, whereas four studies used reduced dimensionality (dose volume histogram) information for prediction. Many of these studies suffer from the same issues that plagued early normal tissue complication probability modelling, including small, single-institutional patient cohorts, lack of external validation, poor data and model reporting, use of late toxicity data without taking time-to-event into account, and nearly exclusive focus on clinician-reported complications. They demonstrate, however, how radiation dose, imaging and clinical data may be technically integrated in convolutional neural networks-based models; and some studies explore how deep learning may help better understand spatial variation in radiosensitivity. In general, there are a number of issues specific to the intersection of radiotherapy outcome modelling and deep learning, for example translation of model developments into treatment plan optimisation, which will require further combined effort from the radiation oncology and artificial intelligence communities. • The use of deep learning for radiotherapy outcome prediction is reviewed. • Ten studies used convolutional neural networks and spatial dose for prediction. • Studies were generally small and single institutional, with lack of external validation. • Deep learning may explore spatial variation in radiosensitivity, but methodology underdeveloped. [ABSTRACT FROM AUTHOR]

Electronic patient-reported outcome (ePRO) measures have the potential to improve patient care, both at an individual level by detecting symptoms and at an organisational level to rationalise follow-up. The introduction of ePROs has many challenges, including funding, institutional rigidity and acceptability for both patients and clinicians. There are multiple examples of successful ePRO programmes but no specific feasibility studies in those who are less digitally engaged. Prostate cancer is predominantly a disease of older men and digital exclusion is associated with increased age. We assessed the feasibility of ePRO completion in older men receiving treatment for advanced prostate cancer both within the clinic and from home. Men receiving palliative systemic treatment were asked to complete ePROs on a tablet computer in the outpatient department at 0 and 3 months. Participants were also offered optional completion from home. Feasibility was assessed via a mixed methods approach. On-site ePRO completion was acceptable to most patients, with 90% finding it easy or straightforward and 80% preferring electronic over paper. Remote completion was more challenging, even for those who accessed e-mail daily and owned a tablet, with only 20% of participants successfully completing ePROs. Barriers to electronic completion can be categorised as technical, attitudinal and medical. Quality of life and symptom ePRO results were comparable with published data. On-site completion is achievable in this population with limited staff support. However, remote completion requires further work to improve systems and acceptability for patients. Remote completion is critical to add significantly to current clinical care by detecting symptoms or stratifying follow-up. • Electronic patient-reported outcome measures can potentially improve patient care and streamline services. • Digital access and familiarity are lower in older groups. • Electronic patient-reported outcome measures are feasible in clinic but more challenging from home. • Strategies to support remote completion are summarised. [ABSTRACT FROM AUTHOR]