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Studies examining ctDNA, a blood-based marker of tumor burden, have largely focused on its use as a prognostic and predictive biomarker. While patient reported outcomes are most often associated with treatment-related toxicities, tumor burden may also contribute to these symptoms, including pain. Approximately one third of patients (pts) who receive radiation (RT) to painful bone metastases (mets) do not experience pain relief, but few studies have identified predictors of response to palliative RT. We hypothesize that ctDNA will predict persistent pain in pts with metastatic breast cancer and could be used to predict response to palliative RT. Plasma was collected before and 3 months (mos) after RT in pts with stage IV HR+, HER2- breast cancer in the context of a multi-institutional Phase II study of palbociclib, hormone therapy (HT), and palliative RT [30 Gy in 10 fractions (fxns) or 20 Gy in 5 fxns] for bone mets. ctDNA was detected using Snapshot, an anchored multiplex assay that detects 28 clinically significant cancer genes. Pts were eligible if treated with HT and palbociclib for at least one cycle and had either painful bone mets or asymptomatic bone mets at risk for a clinical event. Response, the primary endpoint, was prespecified as either a 2-point decrease in maximum pain score on the Brief Pain Inventory in the irradiated site(s) 3 mos post RT or prevention of a clinical event (e.g., cord compression) among pts with asymptomatic disease. The relationship between ctDNA and response to palliative RT was examined. 35 pts completed baseline and 3-month post RT assessments. 27 were treated for painful bone mets. With concurrent palbociclib, 61% and 37% of pts received aromatase inhibitors and fulvestrant, respectively. Median age was 60 years (31-83). 25% of pts were non-Hispanic Black. 72% of pts received 5 fxn RT and 69% received RT to one bone region. 29 pts (83%) were responders [95% CI: 66%-93%, p=.003]. Median progression free survival (PFS) was 30.4 mos (1.3 - 44.0). Three-year PFS and overall survival were 45.6% and 67.2%, respectively. 41% and 39% of pts had detectable ctDNA prior to and 3 mos post RT, respectively. 39% of pts had stable or increased ctDNA proportions 3 mos post RT relative to baseline. Six pts, all of whom presented with painful bone mets, did not respond to palliative RT. 100% of pts (n=15) without detectable ctDNA before and after RT responded to palliative RT, while 39% of pts with stable or increased ctDNA 3 mos post RT had no pain relief to RT (p=0.005). Four pts with ctDNA at baseline had no detectable ctDNA after RT, and all responded to RT. Our multi-institutional Phase II trial is the first to demonstrate high rates of response to concurrent RT with palbociclib and HT and to evaluate ctDNA as a biomarker of pain and response to palliative RT in pts with metastatic breast cancer. Our novel findings indicate that ctDNA detection correlates with persistent pain, a patient reported symptom, and predicts the efficacy of palliative RT. [ABSTRACT FROM AUTHOR]

To introduce an ultrasound-based method for evaluating long-term radiation-induced parotid gland toxicity in head and neck cancer (HNC) patients. The method integrates ultrasound radiomics analysis of the parotid gland with machine learning techniques. A cohort of 56 patients who had previously undergone radiotherapy for HNC was enrolled during routine follow-up visits (median: 25 months, range: 12 -87 months) when each participant underwent a sagittal ultrasound scan of the parotid glands, using a conventional scanner equipped with a linear probe (10 MHz). The scan duration is less than 5 minutes. Manual contours of the parotid glands were delineated on the B-mode images, and subsequently, radiomic features, were extracted. These features encompassed first-order histogram, second-order gray level and gray tone features. Patient self-assessment questionnaires rated saliva consistency and mouth dryness on a 0-3 scale. Correlations between extracted radiomic features, mean radiation dose, and toxicity outcomes were analyzed. Six machine learning models classified toxicity into none/mild versus moderate/severe, evaluated via area under the curve of the receiver operating characteristic curve (AUC-ROC), accuracy, precision, and sensitivity with three-fold cross-validation. Significant correlations (p < 0.05) were found between 34 radiomic features and mean dose (6.4 – 61.8 Gy). Notable features included Difference Variance of the gray-level co-occurrence matrix (Pearson correlation coefficient: 0.54, p < 0.01). For saliva consistency toxicity, 53 significant features were identified, with Root Mean Squared (Spearman correlation coefficient: 0.50, p < 0.01) being prominent. Mouth dryness showed 18 significant features, with Large Area Emphasis being notable (Spearman correlation coefficient: 0.30, p = 0.01). Table 1 presents the performance of the top machine learning models in classifying none/mild versus moderate/severe toxicities. Ultrasound radiomics combined with machine learning effectively assesses long-term radiation-induced parotid toxicity in HNC radiotherapy, highlighting clear associations between radiomic features, radiation dose, and toxicity outcomes. This imaging method offers potential for improved patient care through enhanced monitoring and management of radiation-induced parotid toxicity. [ABSTRACT FROM AUTHOR]

Primary Parotid Carcinomas (PPC) comprise a wide array of histologies, each with varying propensity for local invasion and cervical nodal involvement. Upfront surgical excision of the primary tumor constitutes the standard of care for PPC, but there exists little consensus regarding management of the clinically negative neck (cN0). We conducted a clinicopathologic correlative analysis of the National Cancer Database (NCDB) to identify predictors of occult nodal involvement in PPC to guide elective neck management. The NCDB was queried for adults diagnosed from 2010-2020 with cN0M0 PPC who underwent adequate surgical resection (defined as subtotal to radical parotidectomy with >/=18 nodes examined) without pre-surgical treatment. Pathologic T-classification, tumor size, histology, grade, lymphovascular space invasion (LVSI), gender, and age at diagnosis were specified a priori as variables of interest. The primary outcome, occult nodal positivity (i.e. cN0 but pN+), was assessed by univariable (UVA) and multivariable (MVA) logistic regression, depicted as odds ratios (OR) and corresponding 95% confidence intervals (95%CI) with a prespecified threshold for statistical significance of p< 0.05. Recursive partitioning analysis (RPA) was then performed to hierarchically categorize patients according to occult nodal disease risk. From an initial 51,663 patients with PPC 1,899 met inclusion criteria and were included for analysis, of whom 1,047 (55.1%) had occult nodal involvement. By UVA, the incidence of occult nodal positivity was significantly higher with male sex; age 51 and older; high grade; pT2 status or greater; histology of adenocarcinoma, salivary duct carcinoma, or carcinoma ex-PA; tumor size >2cm; and LVSI. On MVA, tumor size, age, and gender were no longer significantly associated with occult nodal involvement; however, LVSI (OR 8.3, 95%CI 6.3-10.8), carcinoma ex-pleomorphic adenoma (OR 3.6, 95%CI 1.7-7.7), adenocarcinoma (OR 3.5, 95%CI 2.2-5.5), salivary duct carcinoma (OR 3.62, 95%CI 2.2-6.1), pT3 (OR 1.9, 95%CI 1.1-3.3), pT4 (OR 3.1, 95%CI 1.8-5.4), and high grade (OR 2.7, 95%CI 2.0-3.5) remained significant. On RPA evaluating LVSI, histology, pT, and grade, LVSI was the strongest predictor of occult nodal involvement (87% if LVSI+ vs 32% if LVSI–). LVSI appears to supersede tumor histology, grade, size, and pT status as the strongest risk factor for occult nodal involvement in PPC. To our knowledge, this is the largest series to evaluate this pathologic feature. Further research into this heretofore underappreciated risk factor and its implications for management of the cN0 neck is warranted. [ABSTRACT FROM AUTHOR]