Citations

OBJECTIVE Stereotactic radiosurgery (SRS) is an effective treatment for intracranial metastatic disease, but its role in triple-negative breast cancer requires further study. Herein, the authors report overall survival (OS) and local tumor control in a multiinstitutional cohort with triple-negative breast cancer metastases treated with SRS. METHODS Patients treated from 2010 to 2019 at 9 institutions were included in this retrospective study if they had biopsy-proven triple-negative breast cancer with intracranial metastatic lesions treated with SRS. Patients were excluded if they had undergone prior SRS, whole-brain radiation therapy, or resection of the metastatic lesions. A retrospective chart review was conducted to determine OS, local control, and treatment efficacy. RESULTS Sixty-eight patients with 315 treated lesions were assessed. Patients had a median Karnofsky Performance Status of 80 (IQR 70–90) and age of 57 years (IQR 48–67 years). Most treated patients had 5 or fewer intracranial lesions, with 34% of patients having a single lesion. Treated lesions were small, having a median volume owf 0.11 cm3 (IQR 0.03–0.60 cm3). Patients were treated with a median margin dose of 18 Gy (IQR 18–20 Gy) to the median 71% isodose line (IQR 50%–84%). Overall, patients had a 1-year OS of 43% and 2-year OS of 20%. Most patients (88%) were followed until death, by which time local tumor progression had occurred in only 7% of cases. Furthermore, 76% of the lesions demonstrated regression. Tumor volume was correlated with local tumor progression (p = 0.012). SRS was very well tolerated, and only 3 patients (5%) developed symptomatic radiation necrosis. CONCLUSIONS SRS is a safe and efficacious treatment for well-selected patients with triple-negative breast cancer, especially for those with a favorable performance status and small- to moderate-volume metastatic lesions.

Abstract INTRODUCTION Glioblastomas (GBMs) are highly aggressive tumors. A common clinical challenge after standard of care treatment is differentiating tumor progression from treatment-related changes, also known as pseudoprogression (PsP). Usually, PsP resolves or stabilizes without further treatment or a course of steroids, whereas true progression (TP) requires more aggressive management. Differentiating PsP from TP will affect the patient's outcome. This study investigated using deep learning to distinguish PsP MRI features from progressive disease. METHOD We included newly diagnosed GBM patients who met the inclusion criteria, including a new or increasing enhancing lesion size within the original radiation field and who had clinical, medication, and any histopathology available. The interpretation of the MR images at the image inclusion time point had to be indeterminate. We labeled those who subsequently were stable or improved on imaging and clinically as PSP and those with clinical and imaging deterioration as TP. A subset of subjects underwent a second resection. We labeled these subjects as PSP or TP based on the histological diagnosis. We performed skull stripping, coregistered contrast-enhanced T1 MRIs with T2-weighted images for each patient and used them as input to a 3-D Densenet121 model. We used several augmentation techniques and five-fold cross-validation to achieve more robust predictions. RESULT We included 124 patients who met the criteria, and of those, 63 were PsP and 61 were TP. We trained a deep learning model that achieved 76.4% (ranged 70%-84%, SD 5.122) mean accuracy over the 5 folds, 0.7560(ranged 0.6553-0.8535, SD 0.069) mean AUROCC, 88.72% (SD 6.86) mean sensitivity, and 62.05%(SD 9.11) mean specificity. CONCLUSION We report the development of a deep learning model that distinguishes PsP from TP in GBM patients treated per the Stupp protocol. Further refinement and external validation are required prior to widespread adoption in clinical practice.

Abstract PURPOSE Though patients with glioblastoma generally have poor overall survival (OS), OS estimates range significantly. We sought to develop a radiomics-based model predictive of OS in glioblastoma using preoperative MRI scans to identify these differences and guide clinical care. METHODS The primary endpoint was OS, determined from the date of surgery to death or last follow-up. T1, FLAIR, T2, and post-contrast T1 (T1c) MRI sequences were obtained for all patients. Using HD-GLIO-AUTO, lesion segmentation yielded three masks corresponding to the regions of contrast enhancement, non-enhancement, and total volume. Radiomics features were extracted from each region from the T2 and T1c sequences independently (i.e. either from T2 or T1c) and in combination. Age at surgery and gender were also considered. The data was split into training (75%) and test (25%) sets, stratifying for age at surgery. Kaplan-Meier analysis and the Coxnet model were used. For Coxnet, Elastic Net was used as the penalty, with optimization of the L1 coefficient using 5-fold cross-validation and evaluation via the concordance index (C-index). RESULTS From 3 institutions, 383 patients were included. Median OS was 395 days: 346 patients died, and 37 were right-censored. Age > 65 years was predictive of decreased OS (p < 0.005), but gender was not (p=0.16). For the Coxnet model, the C-index was 0.67 (standard deviation: 0.01) considering T2 and T1c sequences for the total lesion volume, with a C-index of 0.65 for the test set. For the enhancing volume, the model had a C-index of 0.71 for the test set using T1c sequences. Overall, C-indices ranged from 0.62-0.71. CONCLUSIONS We present a novel radiomics-based model predictive of OS in glioblastoma across a multi-institutional dataset. Ongoing efforts will incorporate immediate postoperative imaging and IDH and MGMT status into the proposed model to further improve prognostic ability and help guide clinical decision-making.

ImportanceCytokine storm due to COVID-19 can cause high morbidity and mortality and may be more common in patients with cancer treated with immunotherapy (IO) due to immune system activation.ObjectiveTo determine the association of baseline immunosuppression and/or IO-based therapies with COVID-19 severity and cytokine storm in patients with cancer.Design, Setting, and ParticipantsThis registry-based retrospective cohort study included 12 046 patients reported to the COVID-19 and Cancer Consortium (CCC19) registry from March 2020 to May 2022. The CCC19 registry is a centralized international multi-institutional registry of patients with COVID-19 with a current or past diagnosis of cancer. Records analyzed included patients with active or previous cancer who had a laboratory-confirmed infection with SARS-CoV-2 by polymerase chain reaction and/or serologic findings.ExposuresImmunosuppression due to therapy; systemic anticancer therapy (IO or non-IO).Main Outcomes and MeasuresThe primary outcome was a 5-level ordinal scale of COVID-19 severity: no complications; hospitalized without requiring oxygen; hospitalized and required oxygen; intensive care unit admission and/or mechanical ventilation; death. The secondary outcome was the occurrence of cytokine storm.ResultsThe median age of the entire cohort was 65 years (interquartile range [IQR], 54-74) years and 6359 patients were female (52.8%) and 6598 (54.8%) were non-Hispanic White. A total of 599 (5.0%) patients received IO, whereas 4327 (35.9%) received non-IO systemic anticancer therapies, and 7120 (59.1%) did not receive any antineoplastic regimen within 3 months prior to COVID-19 diagnosis. Although no difference in COVID-19 severity and cytokine storm was found in the IO group compared with the untreated group in the total cohort (adjusted odds ratio [aOR], 0.80; 95% CI, 0.56-1.13, and aOR, 0.89; 95% CI, 0.41-1.93, respectively), patients with baseline immunosuppression treated with IO (vs untreated) had worse COVID-19 severity and cytokine storm (aOR, 3.33; 95% CI, 1.38-8.01, and aOR, 4.41; 95% CI, 1.71-11.38, respectively). Patients with immunosuppression receiving non-IO therapies (vs untreated) also had worse COVID-19 severity (aOR, 1.79; 95% CI, 1.36-2.35) and cytokine storm (aOR, 2.32; 95% CI, 1.42-3.79).Conclusions and RelevanceThis cohort study found that in patients with cancer and COVID-19, administration of systemic anticancer therapies, especially IO, in the context of baseline immunosuppression was associated with severe clinical outcomes and the development of cytokine storm.Trial RegistrationClinicalTrials.gov Identifier: NCT04354701

Abstract Atherosclerotic renal artery stenosis (ARAS) is associated with irreversible parenchymal renal disease and regenerative stem cell therapies may improve renal outcomes. Hypoxia preconditioning (HPC) may improve the regenerative functions of adipose tissue-derived mesenchymal stem cells (AMSC) by affecting DNA 5-hydroxymethylcytosine (5hmC) marks in angiogenic genes. Here, we investigated using a porcine ARAS model, whether growth of ARAS AMSCs in hypoxia (Hx) versus normoxia (Nx) would enhance renal tissue repair, and comprehensively analyze how HPC modifies DNA hydroxymethylation compared to untreated ARAS and healthy/normal pigs (n=5 each). ARAS pigs exhibited elevated serum cholesterol, serum creatinine and renal artery stenosis, with a concomitant decrease in renal blood flow (RBF) and increased blood pressure (BP) compared to healthy pigs. Renal artery injection of either autologous Nx or Hx AMSCs improved diastolic BP, reduced kidney tissue fibrosis, and inflammation (CD3+ T-cells) in ARAS pigs. In addition, renal medullary hypoxia significantly lowered with Nx but not Hx AMSC treatment. Mechanistically, levels of epigenetic 5hmC marks (which reflect gene activation) estimated using DNA immunoprecipitation technique were elevated in profibrotic and inflammatory genes in ARAS compared with normal AMSCs. HPC significantly reduced 5hmC levels in cholesterol biosynthesis and oxidative stress response pathways in ARAS AMSCs. Thus, autologous AMSCs improve key renovascular parameters and inflammation in ARAS pigs, with HPC mitigating pathological molecular effects on inflammatory and profibrotic genes which may play a role in augmenting regenerative capacity of AMSCs.

BackgroundPatients with high‐risk prostate cancer (HRPC) have multiple accepted treatment options. Because there is no overall survival benefit of one option over another, appropriate treatment must consider patient life expectancy, quality of life, and cost.MethodsThe authors compared quality‐adjusted life years (QALYs) and cost effectiveness among treatment options for HRPC using a Markov model with three treatment arms: (1) external‐beam radiotherapy (EBRT) delivered with 20 fractions, (2) EBRT with 23 fractions followed by low‐dose‐rate (LDR) brachytherapy boost, or (3) radical prostatectomy alone. An exploratory analysis considered a simultaneous integrated boost according to the FLAME trial (ClinicalTrials.gov identifier NCT01168479).ResultsTreatment strategies were compared using the incremental cost‐effectiveness ratio (ICER). EBRT with LDR brachytherapy boost was a cost‐effective strategy (ICER, $20,929 per QALY gained). These results were most sensitive to variations in the biochemical failure rate. However, the results still demonstrated cost effectiveness for the brachytherapy boost paradigm, regardless of any tested parameter ranges. Probabilistic sensitivity analysis demonstrated that EBRT with LDR brachytherapy was favored in 52% of 100,000 Monte Carlo iterations. In an exploratory analysis, EBRT with a simultaneous integrated boost was also a cost‐effective strategy, resulting in an ICER of $62,607 per QALY gained; however, it was not cost effective compared with EBRT plus LDR brachytherapy boost.ConclusionsEBRT with LDR brachytherapy boost may be a cost‐effective treatment strategy compared with EBRT alone and radical prostatectomy for HRPC, demonstrating high‐value care. The current analysis suggests that a reduction in biochemical failure alone can result in cost‐effective care, despite no change in overall survival.

AbstractTRIT1 defect is a rare, autosomal‐recessive disorder of transcription, initially described as a condition with developmental delay, myoclonic seizures, and abnormal mitochondrial function. Currently, only 13 patients have been reported. We reviewed the genetic, clinical, and metabolic aspects of the disease in all known patients, including two novel, unrelated TRIT1 cases with abnormalities in oxidative phosphorylation complexes I and IV in fibroblasts. Taken together the features of all 15 patients, TRIT1 defect could be identified as a potentially recognizable syndrome including myoclonic epilepsy, speech delay, strabismus, progressive spasticity, and variable microcephaly, with normal lactate levels. Half of the patients had oxidative phosphorylation complex measurements and had multiple complex abnormalities.