Prospective randomized clinical studies involving reirradiation: update of a systematic review

Background Reirradiation is a potentially useful option for many patients with recurrent cancer, aiming at cure or symptom palliation, depending on disease/recurrence type and stage. The purpose of this follow-up study to a previous review from 2016 was to summarize all recently published randomized trials. Points of interest again included identifcation of methodological strengths and weaknesses, practice-changing results, and open questions. Material and methods Systematic review of trials published between 2015 and February 2023. Results We reviewed 7 additional trials, most of which addressed reirradiation of head and neck or brain tumours. The median number of patients was 60. Mirroring the previous review, trial design, primary endpoints and statistical hypotheses varied widely. The updated results only impact on decision making for reirradiation of nasopharynx cancer and glioma. Patients with one of these diseases, as well as other head and neck cancers, may benefit from reirradiation-induced local control, e.g. in terms of progression-free survival. For the first time, hyperfractionated radiotherapy emerged as preferred option for recurrent, inoperable nasopharynx cancer. Despite better therapeutic ratio with hyperfractionation, serious toxicity remains a concern after high cumulative total doses. Randomized trials are still lacking for prostate cancer and other sites. Conclusion Multicentric randomized trials on reirradiation are feasible and continue to refine the current standard of care for recurrent disease after previous radiotherapy. Ongoing prospective studies such as the European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer (ESTRO-EORTC) observational cohort ReCare (NCT: NCT03818503) will further shape the clinical practice of reirradiation

Oncological Outcomes, Long-Term Toxicities, Quality of Life and Sexual Health after Pencil-Beam Scanning Proton Therapy in Patients with Low-Grade Glioma.

PURPOSE To assess oncological outcomes, toxicities, quality of life (QoL) and sexual health (SH) of low-grade glioma (LGG) patients treated with pencil-beam scanning proton therapy (PBS-PT). MATERIAL AND METHODS We retrospectively analyzed 89 patients with LGG (Neurofibromatosis type 1; n = 4 (4.5%) patients) treated with PBS-PT (median dose 54 Gy (RBE)) from 1999 to 2022 at our institution. QoL was prospectively assessed during PBS-PT and yearly during follow-up from 2015 to 2023, while a cross-sectional exploration of SH was conducted in 2023. RESULTS Most LGGs (n = 58; 65.2%) were CNS WHO grade 2 and approximately half (n = 43; 48.3%) were located in the vicinity of the visual apparatus/thalamus. After a median follow-up of 50.2 months, 24 (27%) patients presented with treatment failures and most of these (n = 17/24; 70.8%) were salvaged. The 4-year overall survival was 89.1%. Only 2 (2.2%) and 1 (1.1%) patients presented with CTCAE grade 4 and 3 late radiation-induced toxicity, respectively. No grade 5 late adverse event was observed. The global health as a domain of QoL remained stable and comparable to the reference values during PBS-PT and for six years thereafter. Sexual satisfaction was comparable to the normative population. CONCLUSIONS LGG patients treated with PBS-PT achieved excellent long-term survival and tumor control, with exceptionally low rates of high-grade late toxicity, and favorable QoL and SH

Prospective randomized clinical studies involving reirradiation: update of a systematic review

BACKGROUND Reirradiation is a potentially useful option for many patients with recurrent cancer, aiming at cure or symptom palliation, depending on disease/recurrence type and stage. The purpose of this follow-up study to a previous review from 2016 was to summarize all recently published randomized trials. Points of interest again included identifcation of methodological strengths and weaknesses, practice-changing results, and open questions. MATERIAL AND METHODS Systematic review of trials published between 2015 and February 2023. RESULTS We reviewed 7 additional trials, most of which addressed reirradiation of head and neck or brain tumours. The median number of patients was 60. Mirroring the previous review, trial design, primary endpoints and statistical hypotheses varied widely. The updated results only impact on decision making for reirradiation of nasopharynx cancer and glioma. Patients with one of these diseases, as well as other head and neck cancers, may benefit from reirradiation-induced local control, e.g. in terms of progression-free survival. For the first time, hyperfractionated radiotherapy emerged as preferred option for recurrent, inoperable nasopharynx cancer. Despite better therapeutic ratio with hyperfractionation, serious toxicity remains a concern after high cumulative total doses. Randomized trials are still lacking for prostate cancer and other sites. CONCLUSION Multicentric randomized trials on reirradiation are feasible and continue to refine the current standard of care for recurrent disease after previous radiotherapy. Ongoing prospective studies such as the European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer (ESTRO-EORTC) observational cohort ReCare (NCT: NCT03818503) will further shape the clinical practice of reirradiation

JulianA: An automatic treatment planning platform for intensity-modulated proton therapy and its application to intra- and extracerebral neoplasms

Creating high quality treatment plans is crucial for a successful radiotherapy treatment. However, it demands substantial effort and special training for dosimetrists. Existing automated treatment planning systems typically require either an explicit prioritization of planning objectives, human-assigned objective weights, large amounts of historic plans to train an artificial intelligence or long planning times. Many of the existing auto-planning tools are difficult to extend to new planning goals. A new spot weight optimisation algorithm, called JulianA, was developed. The algorithm minimises a scalar loss function that is built only based on the prescribed dose to the tumour and organs at risk (OARs), but does not rely on historic plans. The objective weights in the loss function have default values that do not need to be changed for the patients in our dataset. The system is a versatile tool for researchers and clinicians without specialised programming skills. Extending it is as easy as adding an additional term to the loss function. JulianA was validated on a dataset of 19 patients with intra- and extracerebral neoplasms within the cranial region that had been treated at our institute. For each patient, a reference plan which was delivered to the cancer patient, was exported from our treatment database. Then JulianA created the auto plan using the same beam arrangement. The reference and auto plans were given to a blinded independent reviewer who assessed the acceptability of each plan, ranked the plans and assigned the human-/machine-made labels. The auto plans were considered acceptable in 16 out of 19 patients and at least as good as the reference plan for 11 patients. Whether a plan was crafted by a dosimetrist or JulianA was only recognised for 9 cases. The median time for the spot weight optimisation is approx. 2 min (range: 0.5 min - 7 min)

Quality-of-life and toxicity in cancer patients treated with multiple courses of radiation therapy

Background Treatment of metastatic cancer patients with multiple repeat courses of radiotherapy has become more frequent due to their improved overall survival. However, very little is known about their long-term outcome. This analysis reports on the quality-of-life, hematologic toxicity, patient-reported experiences and satisfaction, and psychological distress of cancer patients treated with multiple repeat radiotherapy. Methods All patients treated with ≥5 courses of radiotherapy between 2011 and 2019 at the Department of Radiation Oncology, University Hospital Zurich (USZ) were screened for this study. A course of radiotherapy was defined as all treatment sessions to one anatomical site under one medical indication. All patients completed two questionnaires: EORTC QLQ-C30 questionnaire for quality-of-life and a questionnaire evaluating psychological distress and patient-reported experiences. Hematologic toxicities were assessed via a recent blood sample. Results Of n = 33 patients treated with ≥5 radiotherapy courses and being alive, 20 (60.6%) participated in this study. The most common primary tumor was non-small cell lung cancer (n = 14, 42.4%). The most common sites of irradiation were brain (n = 78, 37.1%) and bone metastases (n = 59, 28.1%). All participating patients reported that they had experienced a subjective benefit from multiple repeat radiotherapy and denied increased side effects in later radiotherapy courses. Yet, 45% (n = 9) of the patients reported an increase of psychological distress with increasing numbers of radiotherapy treatments. While global health status was stable, patients having received multiple repeat radiotherapy reported increased fatigue (p = <0.006). Blood analysis showed significantly reduced hemoglobin and lymphocyte levels compared to the healthy population (p = <0.03). Discussion and conclusion Patient-reported experiences and satisfaction of long-term cancer patients treated with multiple repeat radiotherapy are positive. However, increased levels of fatigue and significantly reduced hemoglobin and lymphocyte levels were observed. These data indicate the need to further investigate the effects of multiple courses of radiotherapy in chronic cancer patients

Deep-Learning-Based Dose Predictor for Glioblastoma–Assessing the Sensitivity and Robustness for Dose Awareness in Contouring

External beam radiation therapy requires a sophisticated and laborious planning procedure. To improve the efficiency and quality of this procedure, machine-learning models that predict these dose distributions were introduced. The most recent dose prediction models are based on deep-learning architectures called 3D U-Nets that give good approximations of the dose in 3D almost instantly. Our purpose was to train such a 3D dose prediction model for glioblastoma VMAT treatment and test its robustness and sensitivity for the purpose of quality assurance of automatic contouring. From a cohort of 125 glioblastoma (GBM) patients, VMAT plans were created according to a clinical protocol. The initial model was trained on a cascaded 3D U-Net. A total of 60 cases were used for training, 15 for validation and 20 for testing. The prediction model was tested for sensitivity to dose changes when subject to realistic contour variations. Additionally, the model was tested for robustness by exposing it to a worst-case test set containing out-of-distribution cases. The initially trained prediction model had a dose score of 0.94 Gy and a mean DVH (dose volume histograms) score for all structures of 1.95 Gy. In terms of sensitivity, the model was able to predict the dose changes that occurred due to the contour variations with a mean error of 1.38 Gy. We obtained a 3D VMAT dose prediction model for GBM with limited data, providing good sensitivity to realistic contour variations. We tested and improved the model’s robustness by targeted updates to the training set, making it a useful technique for introducing dose awareness in the contouring evaluation and quality assurance process

Deep-Learning-Based Dose Predictor for Glioblastoma-Assessing the Sensitivity and Robustness for Dose Awareness in Contouring

External beam radiation therapy requires a sophisticated and laborious planning procedure. To improve the efficiency and quality of this procedure, machine-learning models that predict these dose distributions were introduced. The most recent dose prediction models are based on deep-learning architectures called 3D U-Nets that give good approximations of the dose in 3D almost instantly. Our purpose was to train such a 3D dose prediction model for glioblastoma VMAT treatment and test its robustness and sensitivity for the purpose of quality assurance of automatic contouring. From a cohort of 125 glioblastoma (GBM) patients, VMAT plans were created according to a clinical protocol. The initial model was trained on a cascaded 3D U-Net. A total of 60 cases were used for training, 15 for validation and 20 for testing. The prediction model was tested for sensitivity to dose changes when subject to realistic contour variations. Additionally, the model was tested for robustness by exposing it to a worst-case test set containing out-of-distribution cases. The initially trained prediction model had a dose score of 0.94 Gy and a mean DVH (dose volume histograms) score for all structures of 1.95 Gy. In terms of sensitivity, the model was able to predict the dose changes that occurred due to the contour variations with a mean error of 1.38 Gy. We obtained a 3D VMAT dose prediction model for GBM with limited data, providing good sensitivity to realistic contour variations. We tested and improved the model's robustness by targeted updates to the training set, making it a useful technique for introducing dose awareness in the contouring evaluation and quality assurance process

Validation and extension of the METSSS score in a metastatic cancer patient cohort after palliative radiotherapy within the last phase of life

Introduction and background Choosing the right treatment for the right patient in a setting of metastatic cancer disease remains a challenge. To facilitate clinical decision-making, predictive tools have been developed to personalize treatment. Here, we aim to assess the use of the recently proposed "METSSS score" as a prognostic tool for overall survival of cancer patients after palliative radiotherapy in the last phase of life. Methods All patients treated with palliative radiotherapy at the end-of-life at the Department of Radiation Oncology of the University Hospital Zurich between January 2010 and December 2019 were included in this study. Data on demographics, diagnosis, treatment and comorbidities was extracted from the treatment planning and the electronical medical records system. To statistically assess the validity of the "METSSS score", the mortality risk score was calculated, followed by stratification of all patients to prognostic risk groups. The prediction of the 1-year overall survival estimates was subsequently calculated. Results Over the past decade, 274 patients have received palliative radiotherapy during the end-of-life period. One third of patients was female (34%, n = 93). The most frequent primary tumor was lung cancer (n = 121, 44%), and 55% of patients (n = 152) had no comorbidities according to the Charlson-Deyo comorbidity index. The most common radiotherapy site was the brain and eye region (42%, n = 115). The median actual overall survival of all patients was 40 days from the start of radiotherapy. The "METSSS score" survival model predicted that 269 patients (98.1%) belong into the high-risk, four patients (1.5%) into the medium-risk, and one patient (0.4%) into the low-risk group. The predicted median 1-year overall survival was 10%. Discussion The METSSS score correctly predicted the survival of our end-of-life patient cohort by assigning them into the highest risk category, and it can therefore serve as a decision-making tool when assigning patient to symptomatic radiotherapy

Stereotactic body radiotherapy to defer systemic therapy in patients with oligorecurrent disease

Background Patients who develop oligorecurrent disease may be treated with metastasis-directed stereotactic body radiotherapy (SBRT) to defer the start of systemic therapy and delay its potential side effects. We report oncological outcomes and patterns of failure in patients with oligorecurrent disease treated with SBRT and determine which factors impact the interval to initiation of systemic therapy. Material/Methods This retrospective study included patients with oligorecurrent disease (≤5 lesions) from any solid organ malignancy, treated with SBRT to all metastases and no systemic therapy for a minimum one month after SBRT between 01/2014 and 12/2019. The Kaplan-Meier method was used to analyze overall survival (OS) and progression-free survival (PFS), and the cumulative incidence of initiation of systemic therapy was analyzed assuming death without systemic therapy as a competing risk. Univariable and multivariable analyses are used to assess predictors of the systemic therapy-free interval. Results Among 545 patients treated with SBRT for oligometastatic disease, 142 patients were treated with SBRT only for oligorecurrent disease. The most common primary tumors were lung and gastrointestinal cancer in 47 (33.1 %) and 28 (19.7 %) patients, respectively. After a median follow-up of 25 months, the median PFS and OS was 6.1 months and 48.9 months, respectively. Distant metastases were the most common first failure, and oligometastatic distant failure occured in 86 patients (60.6 %). New metastases were treated with repeat SBRT in 48 patients (33.8 %). The 1- and 2-year cumulative incidence of initiation of systemic therapy was 24.6 % and 36.8 %, respectively. In multivariable analysis, the number of previous lines of systemic therapy and the cumulative volume of metastases were significantly associated with the interval to initiation of systemic therapy. Conclusion Selected patients with oligorecurrence achieved favorable OS and low cumulative incidence of initiation of systemic therapy. Prospective studies are warranted to determine how the deferral of systemic therapy impacts OS compared with immediate systemic therapy in combination with SBRT