Our group has previously published the Graded Prognostic Assessment (GPA), a prognostic index for patients with brain metastases. Updates have been published with refinements to create ...diagnosis-specific Graded Prognostic Assessment indices. The purpose of this report is to present the updated diagnosis-specific GPA indices in a single, unified, user-friendly report to allow ease of access and use by treating physicians.
A multi-institutional retrospective (1985 to 2007) database of 3,940 patients with newly diagnosed brain metastases underwent univariate and multivariate analyses of prognostic factors associated with outcomes by primary site and treatment. Significant prognostic factors were used to define the diagnosis-specific GPA prognostic indices. A GPA of 4.0 correlates with the best prognosis, whereas a GPA of 0.0 corresponds with the worst prognosis.
Significant prognostic factors varied by diagnosis. For lung cancer, prognostic factors were Karnofsky performance score, age, presence of extracranial metastases, and number of brain metastases, confirming the original Lung-GPA. For melanoma and renal cell cancer, prognostic factors were Karnofsky performance score and the number of brain metastases. For breast cancer, prognostic factors were tumor subtype, Karnofsky performance score, and age. For GI cancer, the only prognostic factor was the Karnofsky performance score. The median survival times by GPA score and diagnosis were determined.
Prognostic factors for patients with brain metastases vary by diagnosis, and for each diagnosis, a robust separation into different GPA scores was discerned, implying considerable heterogeneity in outcome, even within a single tumor type. In summary, these indices and related worksheet provide an accurate and facile diagnosis-specific tool to estimate survival, potentially select appropriate treatment, and stratify clinical trials for patients with brain metastases.
Brain metastases are a common sequelae of breast cancer. Survival varies widely based on diagnosis-specific prognostic factors (PF). We previously published a prognostic index (Graded Prognostic ...Assessment GPA) for patients with breast cancer with brain metastases (BCBM), based on cohort A (1985-2007, n = 642), then updated it, reporting the effect of tumor subtype in cohort B (1993-2010, n = 400). The purpose of this study is to update the Breast GPA with a larger contemporary cohort (C) and compare treatment and survival across the 3 cohorts.
A multi-institutional (19), multinational (3), retrospective database of 2473 patients with breast cancer with newly diagnosed brain metastases (BCBM) diagnosed from January 1, 2006, to December 31, 2017, was created and compared with prior cohorts. Associations of PF and treatment with survival were analyzed. Kaplan-Meier survival estimates were compared with log-rank tests. PF were weighted and the Breast GPA was updated such that a GPA of 0 and 4.0 correlate with the worst and best prognoses, respectively.
Median survival (MS) for cohorts A, B, and C improved over time (from 11, to 14 to 16 months, respectively; P < .01), despite the subtype distribution becoming less favorable. PF significant for survival were tumor subtype, Karnofsky Performance Status, age, number of BCBMs, and extracranial metastases (all P < .01). MS for GPA 0 to 1.0, 1.5-2.0, 2.5-3.0, and 3.5-4.0 was 6, 13, 24, and 36 months, respectively. Between cohorts B and C, the proportion of human epidermal receptor 2 + subtype decreased from 31% to 18% (P < .01) and MS in this subtype increased from 18 to 25 months (P < .01).
MS has improved modestly but varies widely by diagnosis-specific PF. New PF are identified and incorporated into an updated Breast GPA (free online calculator available at brainmetgpa.com). The Breast GPA facilitates clinical decision-making and will be useful for stratification of future clinical trials. Furthermore, these data suggest human epidermal receptor 2-targeted therapies improve clinical outcomes in some patients with BCBM.
Controversy endures regarding the optimal treatment of patients with brain metastases (BMs). Debate persists, despite many randomized trials, perhaps because BM patients are a heterogeneous ...population. The purpose of the present study was to identify significant diagnosis-specific prognostic factors and indexes (Diagnosis-Specific Graded Prognostic Assessment DS-GPA).
A retrospective database of 5,067 patients treated for BMs between 1985 and 2007 was generated from 11 institutions. After exclusion of the patients with recurrent BMs or incomplete data, 4,259 patients with newly diagnosed BMs remained eligible for analysis. Univariate and multivariate analyses of the prognostic factors and outcomes by primary site and treatment were performed. The significant prognostic factors were determined and used to define the DS-GPA prognostic indexes. The DS-GPA scores were calculated and correlated with the outcomes, stratified by diagnosis and treatment.
The significant prognostic factors varied by diagnosis. For non-small-cell lung cancer and small-cell lung cancer, the significant prognostic factors were Karnofsky performance status, age, presence of extracranial metastases, and number of BMs, confirming the original GPA for these diagnoses. For melanoma and renal cell cancer, the significant prognostic factors were Karnofsky performance status and the number of BMs. For breast and gastrointestinal cancer, the only significant prognostic factor was the Karnofsky performance status. Two new DS-GPA indexes were thus designed for breast/gastrointestinal cancer and melanoma/renal cell carcinoma. The median survival by GPA score, diagnosis, and treatment were determined.
The prognostic factors for BM patients varied by diagnosis. The original GPA was confirmed for non-small-cell lung cancer and small-cell lung cancer. New DS-GPA indexes were determined for other histologic types and correlated with the outcome, and statistical separation between the groups was confirmed. These data should be considered in the design of future randomized trials and in clinical decision-making.
To determine which parameters allow for CyberKnife fiducial-less tumor tracking in stereotactic body radiation therapy (SBRT) for early-stage non-small cell lung cancer.
A total of 133 lung SBRT ...patients were preselected for direct soft-tissue tracking based on manufacturer recommendations (peripherally located tumors ≥1.5 cm with a dense appearance) and staff experience. Patients underwent a tumor visualization test to verify adequate detection by the tracking system (orthogonal radiographs). An analysis of potential predictors of successful tumor tracking was conducted looking at: tumor stage, size, histology, tumor projection on the vertebral column or mediastinum, distance to the diaphragm, lung-to-soft tissue ratio, and patient body mass index.
Tumor visualization was satisfactory for 88 patients (66%) and unsatisfactory for 45 patients (34%). Median time to treatment start was 6 days in the success group (range, 2-18 days) and 15 days (range, 3-63 days) in the failure group. A stage T2 (P=.04), larger tumor size (volume of 15.3 cm(3) vs 6.5 cm(3) in success and failure group, respectively) (P<.0001), and higher tumor density (0.86 g/cm(3) vs 0.79 g/cm(3)) were predictive of adequate detection. There was a 63% decrease in failure risk with every 1-cm increase in maximum tumor dimension (relative risk for failure = 0.37, CI=0.23-0.60, P=.001). A diameter of 3.6 cm predicted a success probability of 80%. Histology, lung-to-soft tissue ratio, distance to diaphragm, patient's body mass index, and tumor projection on vertebral column and mediastinum were not found to be predictive of success.
Tumor size, volume, and density were the most predictive factors of a successful XSight Lung tumor tracking. Tumors >3.5 cm have ≥80% chance of being adequately visualized and therefore should all be considered for direct tumor tracking.
The novel coronavirus of 2019 has had a broad impact of the delivery of healthcare, including cancer care. We chose to quantify the impact in the radiation oncology department of the largest academic ...center in the hardest hit city in Canada. With the approval of our ethics review board, data on each patient treated from March 13, 2020 to August 10, 2020 were compared to patients treated during the same period in 2019. We compared the case mix, delay from treatment decision to treatment start, and number of fractions per patient. We reviewed prospectively collected information regarding deviations from our usual practice. During the pandemic the caseload was reduced by 12%; this was more pronounced in prostate and CNS tumors. The average number of fractions per patient was reduced from 12.3 to 10.9. This reduction was most marked in prostate, breast, gastro-intestinal, and palliative cases. When physicians were questioned, they reported that 17% of treatment plans deviated from their usual practice because of the pandemic. The most common deviations were related to changes in department policies (77%) vs. patient-specific deviations (20%) or changes requested by the patient (3%). Rare deviations were due to patients contracting COVID-19 (2 patients). At its worse, the wait list contained 27% of patients who had a delay to radiotherapy of more than 28 days. However, the average wait time increased little (19.6 days vs. 18.2 days) as more pressing cases were prioritized. In an unprecedented health crisis, our radiation oncology department was able to reduce resource utilization, notably by decreasing the number of fractions per patient. It will be important to follow these patients' health outcomes for insight into these practices. More quantitative tools to simulate and plan future practice changes in response to resource constraints will be implemented.
Introduction: Stereotactic radiosurgery (SRS) is a promising treatment option for patients with multiple brain metastases (BM). Recent technical advances have made LINAC based SRS a patient friendly ...technique, allowing for accurate patient positioning and a short treatment time. Since SRS is increasingly being used for patients with multiple BM, it remains essential that SRS be performed with the highest achievable quality in order to prevent unnecessary complications such as radionecrosis. The purpose of this article is to provide guidance for high-quality LINAC based SRS for patients with BM, with a focus on single isocenter non-coplanar volumetric modulated arc therapy (VMAT).
Methods: The article is based on a consensus statement by the study coordinators and medical physicists of four trials which investigated whether patients with multiple BM are better palliated with SRS instead of whole brain radiotherapy (WBRT): A European trial (NCT02353000), two American trials and a Canadian CCTG lead intergroup trial (CE.7). This manuscript summarizes the quality assurance measures concerning imaging, planning and delivery.
Results: To optimize the treatment, the interval between the planning-MRI (gadolinium contrast-enhanced, maximum slice thickness of 1.5 mm) and treatment should be kept as short as possible (< two weeks). The BM are contoured based on the planning-MRI, fused with the planning-CT. GTV-PTV margins are minimized or even avoided when possible. To maximize efficiency, the preferable technique is single isocenter (non-)coplanar VMAT, which delivers high doses to the target with maximal sparing of the organs at risk. The use of flattening filter free photon beams ensures a lower peripheral dose and shortens the treatment time. To bench mark SRS treatment plan quality, it is advisable to compare treatment plans between hospitals.
Conclusion: This paper provides guidance for quality assurance and optimization of treatment delivery for LINAC-based radiosurgery for patients with multiple BM.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
The diagnosis-specific Graded Prognostic Assessment (GPA) was published to clarify prognosis for patients with brain metastases. This study refines the existing Breast-GPA by analyzing a larger ...cohort and tumor subtype.
A multi-institutional retrospective database of 400 breast cancer patients treated for newly diagnosed brain metastases was generated. Prognostic factors significant for survival were analyzed by multivariate Cox regression and recursive partitioning analysis (RPA). Factors were weighted by the magnitude of their regression coefficients to define the GPA index.
Significant prognostic factors by multivariate Cox regression and RPA were Karnofsky performance status (KPS), HER2, ER/PR status, and the interaction between ER/PR and HER2. RPA showed age was significant for patients with KPS 60 to 80. The median survival time (MST) overall was 13.8 months, and for GPA scores of 0 to 1.0, 1.5 to 2.0, 2.5 to 3.0, and 3.5 to 4.0 were 3.4 (n = 23), 7.7 (n = 104), 15.1 (n = 140), and 25.3 (n = 133) months, respectively (p < 0.0001). Among HER2-negative patients, being ER/PR positive improved MST from 6.4 to 9.7 months, whereas in HER2-positive patients, being ER/PR positive improved MST from 17.9 to 20.7 months. The log-rank statistic (predictive power) was 110 for the Breast-GPA vs. 55 for tumor subtype.
The Breast-GPA documents wide variation in prognosis and shows clear separation between subgroups of patients with breast cancer and brain metastases. This tool will aid clinical decision making and stratification in clinical trials. These data confirm the effect of tumor subtype on survival and show the Breast-GPA offers significantly more predictive power than the tumor subtype alone.
In radiation oncology, predicting patient risk stratification allows specialization of therapy intensification as well as selecting between systemic and regional treatments, all of which helps to ...improve patient outcome and quality of life. Deep learning offers an advantage over traditional radiomics for medical image processing by learning salient features from training data originating from multiple datasets. However, while their large capacity allows to combine high-level medical imaging data for outcome prediction, they lack generalization to be used across institutions. In this work, a pseudo-volumetric convolutional neural network with a deep preprocessor module and self-attention (PreSANet) is proposed for the prediction of distant metastasis, locoregional recurrence, and overall survival occurrence probabilities within the 10 year follow-up time frame for head and neck cancer patients with squamous cell carcinoma. The model is capable of processing multi-modal inputs of variable scan length, as well as integrating patient data in the prediction model. These proposed architectural features and additional modalities all serve to extract additional information from the available data when availability to additional samples is limited. This model was trained on the public Cancer Imaging Archive Head-Neck-PET-CT dataset consisting of 298 patients undergoing curative radio/chemo-radiotherapy and acquired from 4 different institutions. The model was further validated on an internal retrospective dataset with 371 patients acquired from one of the institutions in the training dataset. An extensive set of ablation experiments were performed to test the utility of the proposed model characteristics, achieving an AUROC of Formula: see text, Formula: see text and Formula: see text for DM, LR and OS respectively on the public TCIA Head-Neck-PET-CT dataset. External validation was performed on a retrospective dataset with 371 patients, achieving Formula: see text AUROC in all outcomes. To test for model generalization across sites, a validation scheme consisting of single site-holdout and cross-validation combining both datasets was used. The mean accuracy across 4 institutions obtained was Formula: see text, Formula: see text and Formula: see text for DM, LR and OS respectively. The proposed model demonstrates an effective method for tumor outcome prediction for multi-site, multi-modal combining both volumetric data and structured patient clinical data.
Evidence for external beam radiation therapy (RT) as part of treatment for retroperitoneal sarcoma (RPS) is limited. Preoperative RT is the subject of a current randomized trial, but the results will ...not be available for many years. In the meantime, many practitioners use preoperative RT for RPS, and although this approach is used in practice, there are no radiation treatment guidelines. An international expert panel was convened to develop consensus treatment guidelines for preoperative RT for RPS.
An expert panel of 15 academic radiation oncologists who specialize in the treatment of sarcoma was assembled. A systematic review of reports related to RT for RPS, RT for extremity sarcoma, and RT-related toxicities for organs at risk was performed. Due to the paucity of high-quality published data on the subject of RT for RPS, consensus recommendations were based largely on expert opinion derived from clinical experience and extrapolation of relevant published reports. It is intended that these clinical practice guidelines be updated as pertinent data become available.
Treatment guidelines for preoperative RT for RPS are presented.
An international panel of radiation oncologists who specialize in sarcoma reached consensus guidelines for preoperative RT for RPS. Many of the recommendations are based on expert opinion because of the absence of higher level evidence and, thus, are best regarded as preliminary. We emphasize that the role of preoperative RT for RPS has not been proven, and we await data from the European Organization for Research and Treatment of Cancer (EORTC) study of preoperative radiotherapy plus surgery versus surgery alone for patients with RPS. Further data are also anticipated pertaining to normal tissue dose constraints, particularly for bowel tolerance. Nonetheless, as we await these data, the guidelines herein can be used to establish treatment uniformity to aid future assessments of efficacy and toxicity.
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