Predictive quantitative ultrasound radiomic markers associated with treatment response in head and neck cancer

Aim: We aimed to identify quantitative ultrasound (QUS)-radiomic markers to predict radiotherapy response in metastatic lymph nodes of head and neck cancer. Materials & methods: Node-positive head and neck cancer patients underwent pretreatment QUS imaging of their metastatic lymph nodes. Imaging features were extracted using the QUS spectral form, and second-order texture parameters. Machine-learning classifiers were used for predictive modeling, which included a logistic regression, naive Bayes, and k-nearest neighbor classifiers. Results: There was a statistically significant difference in the pretreatment QUS-radiomic parameters between radiological complete responders versus partial responders (p < 0.05). The univariable model that demonstrated the greatest classification accuracy included: spectral intercept (SI)-contrast (area under the curve = 0.741). Multivariable models were also computed and showed that the SI-contrast + SI-homogeneity demonstrated an area under the curve = 0.870. The three-feature model demonstrated that the spectral slope-correlation + SI-contrast + SI-homogeneity-predicted response with accuracy of 87.5%. Conclusion: Multivariable QUS-radiomic features of metastatic lymph nodes can predict treatment response a priori

Walking speed, cognitive function and dementia risk in the English Longitudinal Study

Background: Physical and cognitive function decline with age. Slow walking speed has been associated with negative health outcomes and dementia is often preceded by cognitive decline. This study investigated walking speed, cognitive function and the interaction between changes in these measures in relation to dementia risk. Method: Walking speed and cognition were assessed in 3,932 individuals aged ≥60 years at wave 1 (2002-03) and 2 (2004-05) of the English Longitudinal Study of Ageing. New dementia cases were assessed from wave 3 (2006-07) to wave 7 (2014-15). The associations were modelled using Cox proportional hazards regression. Results: Participants with faster baseline walking speeds (HR 0.36; 95% CI 0.22 - 0.60) had a decreased risk of dementia. Those who had a greater decline in walking speed (waves 1 - 2 (HR 1.23; 95% CI 1.03 - 1.47) had an increased dementia risk. Participants with greater baseline cognition (HR 0.42; 95% CI 0.34 - 0.54) had a reduced dementia risk. Those who had a greater decline in cognition (waves 1-2) had a greater risk of dementia (HR 1.78; 95% CI 36 1.53 - 2.06). Change in walking speed and change in cognition did not interact significantly in relation to dementia risk (HR 1.01; 95% CI 0.88 – 1.17). Conclusions: In this community-dwelling sample of English adults those with slower walking speeds and a greater decline in speed over time had an increased risk of developing dementia independent of changes in cognition. Further research is required to understand the mechanisms that may drive these associations

Alternative lengthening of telomeres, ATRX loss and H3â K27M mutations in histologically defined pilocytic astrocytoma with anaplasia

Anaplasia may be identified in a subset of tumors with a presumed pilocytic astrocytoma (PA) component or piloid features, which may be associated with aggressive behavior, but the biologic basis of this change remains unclear. Fiftyâ seven resections from 36 patients (23 M, 13 F, mean age 32 years, range 3â 75) were included. A clinical diagnosis of NF1 was present in 8 (22%). Alternative lengthening of telomeres (ALT) was assessed by telomereâ specific FISH and/or CISH. A combination of immunohistochemistry, DNA sequencing and FISH were used to study BRAF, ATRX, CDKN2A/p16, mutant IDH1 p.R132H and H3â K27M proteins. ALT was present in 25 (69%) cases and ATRX loss in 20 (57%), mostly in the expected association of ALT+/ATRXâ (20/24, 83%) or ALTâ /ATRX+ (11/11, 100%). BRAF duplication was present in 8 (of 26) (31%). H3â K27M was present in 5 of 32 (16%) cases, all with concurrent ATRX loss and ALT. ALT was also present in 9 (of 11) cases in the benign PA precursor, 7 of which also had ATRX loss in both the precursor and the anaplastic tumor. In a single pediatric case, ALT and ATRX loss developed in the anaplastic component only, and in another adult case, ALT was present in the PAâ A component only, but ATRX was not tested. Features associated with worse prognosis included subtotal resection, adult vs. pediatric, presence of a PA precursor preceding a diagnosis of anaplasia, necrosis, presence of ALT and ATRX expression loss. ALT and ATRX loss, as well as alterations involving the MAPK pathway, are frequent in PA with anaplasia at the time of development of anaplasia or in their precursors. Additionally, a small subset of PA with anaplasia have H3â K27M mutations. These findings further support the concept that PA with anaplasia is a neoplasm with heterogeneous genetic features and alterations typical of both PA and diffuse gliomas.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147190/1/bpa12646_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147190/2/bpa12646.pd

Quantitative thermal imaging biomarkers to detect acute skin toxicity from breast radiation therapy using supervised machine learning

Purpose Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes associated with radiation-induced dermatitis, such as inflammation, may also increase body-surface temperature, which can be detected by thermal imaging. Quantitative thermal imaging markers were identified and used in supervised machine learning to develop a predictive model for radiation dermatitis. Methods and Materials Ninety patients treated for adjuvant whole-breast RT (4250 cGy/fx = 16) were recruited for the study. Thermal images of the treated breast were taken at 4 intervals: before RT, then weekly at fx = 5, fx = 10, and fx = 15. Parametric thermograms were analyzed and yielded 26 thermal-based features that included surface temperature (°C) and texture parameters obtained from (1) gray-level co-occurrence matrix, (2) gray-level run-length matrix, and (3) neighborhood gray-tone difference matrix. Skin toxicity was evaluated at the end of RT using the Common Terminology Criteria for Adverse Events (CTCAE) guidelines (Ver.5). Binary group classes were labeled according to a CTCAE cut-off score of ≥2, and thermal features obtained at fx = 5 were used for supervised machine learning to predict skin toxicity. The data set was partitioned for model training, independent testing, and validation. Fifteen patients (∼17% of the whole data set) were randomly selected as an unseen test data set, and 75 patients (∼83% of the whole data set) were used for training and validation of the model. A random forest classifier with leave-1-patient-out cross-validation was employed for modeling single and hybrid parameters. The model performance was reported using receiver operating characteristic analysis on patients from an independent test set. Results Thirty-seven patients presented with adverse skin effects, denoted by a CTCAE score ≥2, and had significantly higher local increases in skin temperature, reaching 36.06°C at fx = 10 (P = .029). However, machine-learning models demonstrated early thermal signals associated with skin toxicity after the fifth RT fraction. The cross-validated model showed high prediction accuracy on the independent test data (test accuracy = 0.87) at fx = 5 for predicting skin toxicity at the end of RT. Conclusions Early thermal markers after 5 fractions of RT are predictive of radiation-induced skin toxicity in breast RT

Determinants of adult vaccination at inner-city health centers: A descriptive study

BACKGROUND: Pneumococcal polysaccharide vaccination rates among adults 65 years and older or less than 65 years with high risk medical conditions are still below Healthy People 2010 recommended levels of 90%. This study was designed to: 1) assess self-reported pneumococcal vaccination rates following health center level interventions to increase adult vaccination rates; and 2) determine factors associated with vaccination. METHODS: Tailored interventions to increase immunizations were implemented at two inner-city health centers. We surveyed 375 patients 50 years of age and older. Multivariate logistic regression examines the predictors of 1) self-reported pneumococcal vaccination and 2) combined self-reported influenza and pneumococcal vaccination. Both of these models were stratified by age group (50–64 years and 65 years and older). RESULTS: Pneumococcal vaccination rates were 45% by self-report, 55% by medical record review, 69% for patients 65 years old and older, 32% for patients 50–64 years; they did not differ by race. Receipt of the previous season's influenza vaccine was significantly related to pneumococcal vaccination among both younger and older patients. Receiving both the pneumococcal vaccine and the most recent influenza vaccine compared with receiving neither, among younger patients was related to unemployment, more frequent physician visits, and belief that those who do not receive the flu shot are more susceptible to the flu. For older patients, receipt of both vaccines was related to nonsmoking status, believing that friends/family think the patient should be vaccinated, seeing posters advertising flu shot clinics, and belief that those who do not receive the flu shot are more susceptible to the flu. CONCLUSION: Our findings suggest that improving overall pneumococcal vaccination rates among eligible adults, has the potential to eliminate racial disparities. Interventions delivering vaccination messages specific to older and younger adult groups may be the best strategy for improving adult vaccination rates

Impact of vaccine economic programs on physician referral of children to public vaccine clinics: a pre-post comparison

BACKGROUND: The Vaccines for Children (VFC) Program is a major vaccine entitlement program with limited long-term evaluation. The objectives of this study are to evaluate the effect of VFC on physician reported referral of children to public health clinics and on doses administered in the public sector. METHODS: Minnesota and Pennsylvania primary care physicians (n = 164), completed surveys before (e.g., 1993) and after (2003) VFC, rating their likelihood on a scale of 0 (very unlikely) to 10 (very likely) of referring a child to the health department for immunization. RESULTS: The percentage of respondents likely to refer was 60% for an uninsured child, 14% for a child with Medicaid, and 3% for a child with insurance that pays for immunization. Half (55%) of the physicians who did not participate in VFC were likely to refer a Medicaid-insured child, as compared with 6% of those who participated (P < 0.001). Physician likelihood to refer an uninsured child for vaccination, measured on a scale of 0 to 10 where 10 is very likely, decreased by a mean difference of 1.9 (P < 0.001) from pre- to post-VFC. The likelihood to refer a Medicaid-insured child decreased by a mean of 1.2 (P = 0.001). CONCLUSION: Reported out-referral to public clinics decreased over time. In light of increasing immunizations rates, this suggests that more vaccines were being administered in private provider offices

Predictors of colorectal cancer screening in diverse primary care practices

BACKGROUND: To explain why rates of colorectal cancer (CRC) screening including fecal occult blood testing (FOBT), flexible sigmoidoscopy (FS), colonoscopy (CS), and barium enema (BE), are low, this study assessed determinants of CRC screening from medical records. METHODS: Data were abstracted from patients aged ≥64 years selected from each clinician from 30 diverse primary care practices (n = 981). Measurements included the rates of annual FOBT, ever receiving FOBT, ever receiving FS/CS/BE under a combination variable, endoscopy/barium enema (EBE). RESULTS: Over five years, 8% had received annual FOBT, 53% had ever received FOBT and 22% had ever received EBE. Annual FOBT was negatively associated with female gender, odds ratio (OR) = .23; 95% confidence interval = .12–.44 and positively associated with routinely receiving influenza vaccine, OR = 2.55 (1.45–4.47); and more office visits: 3 to <5 visits/year, OR = 2.78 (1.41–5.51), and ≥5 visits/year, OR = 3.35 (1.52-7.42). Ever receiving EBE was negatively associated with age ≥75 years, OR = .66 (.46–.95); being widowed, OR = .59 (.38–.92); and positively associated with more office visits: 3 to <5 visits/year, OR = 1.83 (1.18–2.82) and ≥5 visits/year, OR = 2.01 (1.14–3.55). CONCLUSION: Overall CRC screening rates were low, but were related to the number of primary care office visits. FOBT was related to immunization status, suggesting the possible benefit of linking these preventive services

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting