Disparities and guideline adherence for HPV testing among patients with oropharyngeal squamous cell carcinoma, NCDB, and SEER

BACKGROUND: Human papilloma virus testing for oropharyngeal squamous-cell carcinoma has been recommended by the National Comprehensive Cancer Network since 2012. We examine disparities, reported rates of human papillomavirus (HPV) testing, and the impact on these findings of limitations with the variable in database registries. METHODS: The HPV variable was queried for patients with oropharyngeal squamous carcinoma (OPSCC) from 2013 to 2016 in National Cancer Data Base (NCDB) and Surveillance, Epidemiology, and End Results (SEER). Multivariable regression was used to identify disparities based on sociodemographic variables. Sensitivity analyses were used to investigate limitations of the variable. RESULTS: Despite limitations in the HPV variable in the databases, there was less than 100% adherence to recommended testing, and there were significant disparities in multiple sociodemographic variables. For example, in NCDB 70% of white versus 60.4% of black patients were tested (odds ratio [OR] 0.75, confidence interval [CI] 0.66-0.85, p ≤ 0.0001); in SEER 59.8% of white and 47.6% of black patients were tested (OR 0.73, CI 0.67-0.81; p ≤ 0.0001). CONCLUSIONS: Disparities exist among patients undergoing testing for HPV-associated OPSCC and adherence to guideline recommended HPV testing has been suboptimal. In addition, the HPV variable definition, especially as it relates to p16 positivity, and use in these two registries should be improved

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely

Interactive voice response technology for symptom monitoring and as an adjunct to the treatment of chronic pain

Chronic pain is a medical condition that severely decreases the quality of life for those who struggle to cope with it. Interactive voice response (IVR) technology has the ability to track symptoms and disease progression, to investigate the relationships between symptom patterns and clinical outcomes, to assess the efficacy of ongoing treatments, and to directly serve as an adjunct to therapeutic treatment for chronic pain. While many approaches exist toward the management of chronic pain, all have their pitfalls and none work universally. Cognitive behavioral therapy (CBT) is one approach that has been shown to be fairly effective, and therapeutic interactive voice response technology provides a convenient and easy-to-use means of extending the therapeutic gains of CBT long after patients have discontinued clinical visitations. This review summarizes the advantages and disadvantages of IVR technology, provides evidence for the efficacy of the method in monitoring and managing chronic pain, and addresses potential future directions that the technology may take as a therapeutic intervention in its own right

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

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring