Evaluation of the Clinical Utility of the Bone Metastases Ensemble Trees for Survival Decision Support Platform (BMETS-DSP): A Case-Based Pilot Assessment.

PURPOSE: The Bone Metastases Ensemble Trees for Survival Decision Support Platform (BMETS-DSP) provides patient-specific survival predictions and evidence-based recommendations to guide multidisciplinary management for symptomatic bone metastases. We assessed the clinical utility of the BMETS-DSP through a pilot prepost design in a simulated clinical environment. METHODS: Ten Radiation Oncology physicians reviewed 55 patient cases at two time points: without and then with the use of BMETS-DSP. Assessment included 12-month survival estimate, confidence in and likelihood of sharing estimates with patients, and recommendations for open surgery, systemic therapy, hospice referral, and radiotherapy (RT) regimen. Paired statistics compared pre- versus post-DSP outcomes. Reported statistical significance is P < .05. RESULTS: Pre- versus post-DSP, overestimation of true minus estimated survival time was significantly reduced (mean difference -2.1 [standard deviation 4.1] v -1 month [standard deviation 3.5]). Prediction accuracy was significantly improved at cut points of < 3 (72 v 79%), ≤ 6 (64 v 71%), and ≥ 12 months (70 v 81%). Median ratings of confidence in and likelihood of sharing prognosis significantly increased. Significantly greater concordance was seen in matching use of 1-fraction RT with the true survival < 3 months (70 v 76%) and < 10-fraction RT with the true survival < 12 months (55 v 62%) and appropriate use of open surgery (47% v 53%), without significant changes in selection of hospice referral or systemic therapy. CONCLUSION: This pilot study demonstrates that BMETS-DSP significantly improved physician survival estimation accuracy, prognostic confidence, likelihood of sharing prognosis, and use of prognosis-appropriate RT regimens in the care of symptomatic bone metastases, supporting future multi-institutional validation of the platform.

Improving providers' survival estimates and selection of prognosis- and guidelines-appropriate treatment for patients with symptomatic bone metastases: Development of the Bone Metastases Ensemble Trees for Survival Decision Support Platform.

RATIONALE, AIMS AND OBJECTIVES: In the management of symptomatic bone metastases, current practice guidelines do not provide clear methodology for selecting palliative radiotherapy (RT) regimens based on specific patient and disease features. Decision support aids may offer an effective means for translating the complex data needed to render individualised treatment decisions, yet no such tools are available for use in this setting. Thus, we describe the development of the Bone Metastases Ensemble Trees for Survival-Decision Support Platform (BMETS-DSP), which aims to optimise selection of evidence-based, individualised palliative RT regimens. METHOD: The Ottawa Decision Support Framework was used as the theoretical basis for development of BMETS-DSP. First, we utilised stakeholder input and review of the literature to assess determinants underlying the provider decision. Based on this assessment and iterative stakeholder feedback, we developed the web-based, provider-facing BMETS-DSP. Consistent with the underlying theoretical framework, our design also included assessment of decision quality using the International Patient Decision Aids Standards (IPDAS) certification checklist. RESULTS: Stakeholder input and review of 54 evidence-based publications identified the following determinants of the provider decision: estimated prognosis, characteristics of the target symptomatic lesion and the primary cancer type, consideration of alternative interventions, access to patient-specific recommendations, and patient preferences. Based on these determinants, we developed the BMETS-DSP that (1) collects patient-specific data, (2) displays an individualised predicted survival curve, and (3) provides case-specific, evidence-based recommendations regarding RT, open surgery, systemic therapy, and hospice referral to aid in the decision-making process. The finalised tool met IPDAS quality requirements. Preliminary results of a pilot assessment suggest impact of clinical outcomes. CONCLUSIONS: We describe the successful development of a provider-facing decision support platform to aid in the provision of palliative RT in better alignment with patient and disease features. Impact of the BMETS-DSP on decision outcomes will be further assessed in a randomised, controlled study.

External Validation of the Bone Metastases Ensemble Trees for Survival (BMETS) Machine Learning Model to Predict Survival in Patients With Symptomatic Bone Metastases.

PURPOSE: The Bone Metastases Ensemble Trees for Survival (BMETS) model uses a machine learning algorithm to estimate survival time following consultation for palliative radiation therapy for symptomatic bone metastases (SBM). BMETS was developed at a tertiary-care, academic medical center, but its validity and stability when applied to external data sets are unknown. PATIENTS AND METHODS: Patients treated with palliative radiation therapy for SBM from May 2013 to May 2016 at two hospital-based community radiation oncology clinics were included, and medical records were retrospectively reviewed to collect model covariates and survival time. The Kaplan-Meier method was used to estimate overall survival from consultation to death or last follow-up. Model discrimination was estimated using time-dependent area under the curve (tAUC), which was calculated using survival predictions from BMETS based on the initial training data set. RESULTS: A total of 216 sites of SBM were treated in 182 patients. Most common histologies were breast (27%), lung (23%), and prostate (23%). Compared with the BMETS training set, the external validation population was older (mean age, 67 v 62 years; P < .001), had more primary breast (27% v 19%; P = .03) and prostate cancer (20% v 12%; P = .01), and survived longer (median, 10.7 v 6.4 months). When the BMETS model was applied to the external data set, tAUC values at 3, 6, and 12 months were 0.82, 0.77, and 0.77, respectively. When refit with data from the combined training and external validation sets, tAUC remained > 0.79. CONCLUSION: BMETS maintained high discriminative ability when applied to an external validation set and when refit with new data, supporting its generalizability, stability, and the feasibility of dynamic modeling.

A multi-institutional phase 2 trial of stereotactic body radiotherapy in the treatment of bone metastases in pediatric and young adult patients with sarcoma.

BACKGROUND: Metastasectomy is standard of care for pediatric patients with metastatic sarcoma with limited disease. For patients with unresectable disease, stereotactic body radiotherapy (SBRT) may serve as an alternative. Herein, the authors report the results of a prospective, multi-institutional phase 2 trial of SBRT in children and young adults with metastatic sarcoma. METHODS: Patients aged >3 years and ≤40 years with unresected, osseous metastatic nonrhabdomyosarcoma sarcomas of soft tissue and bone were eligible. Patients received SBRT to a dose of 40 Gray (Gy) in 5 fractions. Local control (LC), progression-free survival (PFS), and overall survival (OS) were calculated using the Kaplan-Meier method. RESULTS: Fourteen patients with a median age of 17 years (range, 4-25 years) were treated to 37 distinct metastatic lesions. With a median follow-up of 6.8 months (30.5 months in surviving patients), the Kaplan-Meier patient-specific and lesion-specific LC rates at 6 months were 89% and 95%, respectively. The median PFS was 6 months and the median OS was 24 months. In a post hoc analysis, PFS (median, 9.3 months vs 3.7 months; log-rank P = .03) and OS (median not reached vs 12.7 months; log-rank P = .02) were improved when all known sites of metastatic disease were consolidated with SBRT compared with partial consolidation. SBRT was well tolerated, with 2 patients experiencing grade 3 toxicities. CONCLUSIONS: SBRT achieved high rates of LC in pediatric patients with inoperable metastatic nonrhabdomyosarcoma sarcomas of soft tissue and bone. These results suggest that the ability to achieve total consolidation of metastatic disease with SBRT is associated with improved PFS and OS.

Aiming for 100% Local Control in Locally Advanced Cervical Cancer: The Role of Complex Brachytherapy Applicators and Intraprocedural Imaging.

The use of brachytherapy for the treatment of gynecologic malignancies, particularly cervical cancer, has a long and rich history that is nearly as long as the history of radiation oncology itself. From the first gynecologic brachytherapy treatments in the early 20th century to the modern era, significant transformation has occurred driven largely by advancements in technology. The development of high-dose rate sources, remote afterloaders, novel applicators, and 3-dimensional image guidance has led to improved local control, and thus improved survival, solidifying the role of brachytherapy as an integral component in the treatment of locally advanced cervical cancer. Current research efforts examining novel magnetic resonance imaging sequences, active magnetic resonance tracking, and the application of hydrogel aim to further improve local control and reduce treatment toxicity.

Radiation therapy for gynecologic malignancies during the COVID-19 pandemic: International expert consensus recommendations.

OBJECTIVE: To develop expert consensus recommendations regarding radiation therapy for gynecologic malignancies during the COVID-19 pandemic. METHODS: An international committee of ten experts in gynecologic radiation oncology convened to provide consensus recommendations for patients with gynecologic malignancies referred for radiation therapy. Treatment priority groups were established. A review of the relevant literature was performed and different clinical scenarios were categorized into three priority groups. For each stage and clinical scenario in cervical, endometrial, vulvar, vaginal and ovarian cancer, specific recommendations regarding dose, technique, and timing were provided by the panel. RESULTS: Expert review and discussion generated consensus recommendations to guide radiation oncologists treating gynecologic malignancies during the COVID-19 pandemic. Priority scales for cervical, endometrial, vulvar, vaginal, and ovarian cancers are presented. Both radical and palliative treatments are discussed. Management of COVID-19 positive patients is considered. Hypofractionated radiation therapy should be used when feasible and recommendations regarding radiation dose, timing, and technique have been provided for external beam and brachytherapy treatments. Concurrent chemotherapy may be limited in some countries, and consideration of radiation alone is recommended. CONCLUSIONS: The expert consensus recommendations provide guidance for delivering radiation therapy during the COVID-19 pandemic. Specific recommendations have been provided for common clinical scenarios encountered in gynecologic radiation oncology with a focus on strategies to reduce patient and staff exposure to COVID-19.

Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic covariates. To establish its relative clinical utility, we compared BMETS with 2 simpler Cox regression models used in this setting. METHODS AND MATERIALS: For 492 bone sites in 397 patients evaluated for palliative radiation therapy (RT) for SBM from January 2007 to January 2013, data for 27 clinical variables were collected. These covariates and the primary outcome of time from consultation to death were used to build BMETS using random survival forests. We then performed Cox regressions as per 2 validated models: Chow's 3-item (C-3) and Westhoff's 2-item (W-2) tools. Model performance was assessed using cross-validation procedures and measured by time-dependent area under the curve (tAUC) for all 3 models. For temporal validation, a separate data set comprised of 104 bone sites treated in 85 patients in 2018 was used to estimate tAUC from BMETS. RESULTS: Median survival was 6.4 months. Variable importance was greatest for performance status, blood cell counts, recent systemic therapy type, and receipt of concurrent nonbone palliative RT. tAUC at 3, 6, and 12 months was 0.83, 0.81, and 0.81, respectively, suggesting excellent discrimination of BMETS across postconsultation time points. BMETS outperformed simpler models at each time, with respective tAUC at each time of 0.78, 0.76, and 0.74 for the C-3 model and 0.80, 0.78, and 0.77 for the W-2 model. For the temporal validation set, respective tAUC was similarly high at 0.86, 0.82, and 0.78. CONCLUSIONS: For patients with SBM, BMETS improved survival predictions versus simpler traditional models. Model performance was maintained when applied to a temporal validation set. To facilitate clinical use, we developed a web platform for data entry and display of BMETS-predicted survival probabilities.

Frequency of Complicated Symptomatic Bone Metastasis Over a Breadth of Operational Definitions.

PURPOSE: Numerous randomized trials have demonstrated noninferiority of single- versus multiple-fraction palliative radiation therapy (RT) in the management of uncomplicated bone metastases; yet there is neither a clear definition of what constitutes a complicated lesion, nor substantial data regarding the prevalence of such complicating features in clinical practice. Thus, we identify a range of evidence-based operational definitions of complicated symptomatic bone metastases and characterize the frequency of such complicating features at a high-volume, tertiary care center. METHODS AND MATERIALS: A retrospective review of patients seen in consultation for symptomatic bone metastases between March 1, 2007, and July 31, 2013, at Johns Hopkins Hospital identified patient and disease characteristics. Descriptive statistics characterized the frequency of the following complicating features: prior RT, prior surgery, neuraxis compromise, pathologic fracture, and soft tissue component at the symptomatic site. A range of definitions for complicated bone metastases was evaluated based on combinations of these features. Uni- and multivariable logistic regressions evaluated the odds of complicated bone metastases as a function of site of primary cancer and of the symptomatic target lesion. RESULTS: A total of 686 symptomatic bone metastases in 401 patients were evaluated. Percent of target sites complicated by prior RT was 4.4%, prior surgery was 8.9%, pathologic fracture was 20.6%, neuraxis compromise was 52.0% among spine and medial pelvis sites, and soft tissue component was 38.6%. More than 96 possible definitions of complicated bone metastases were identified. The presence of such complicated lesions ranged from 2.3% to 67.3%, depending on the operational definition used. Odds of a complicated lesion were significantly higher for spine sites and select nonbreast histologies. CONCLUSIONS: In this retrospective study, we found complicated symptomatic bone metastases may be present in up to two-thirds of patients. Literature review also demonstrates no clear standard definition of complicated bone metastases, potentially explaining underutilization of single-fraction palliative RT in this setting.

Widely metastatic IDH1-mutant glioblastoma with oligodendroglial features and atypical molecular findings: a case report and review of current challenges in molecular diagnostics.

BACKGROUND: Gliomas with 1p/19q-codeletion as well as mutation of isocitrate dehydrogenase (IDH) 1 are typically characterized as oligodendrogliomas with comparatively good response to treatment with radiation and chemotherapy. CASE PRESENTATION: We present the case of a 28-year-old man with an IDH1 and TP53 mutant high grade glioma with abnormalities in chromosomes 1 and 19 suggestive of anaplastic oligodendroglioma that rapidly progressed to widespread metastatic disease. Biopsy of a liver lesion confirmed metastasis of the patient's known brain primary and chemotherapy with temozolomide was initiated. The patient's rapidly growing tumor burden with fulminant liver failure and tumor lysis led to multisystem failure of which the patient died. Further molecular testing illustrated features more consistent with glioblastoma: multiple large chromosomal aberrations including loss of whole chromosome 1 and 2q; gain/amplification of MYCN, MET, and CDK4; loss of CDKN2A/B; and an ATRX mutation. CONCLUSION: This case illustrates the importance of higher level molecular diagnostic testing for patients with particularly aggressive disease progression that is not concordant with standard prognoses. Additional data on cases with atypical alterations of 1p and 19q are needed to better understand the distinct biology of these cancers so that appropriate therapies can be developed.