Inappropriate Use of Radioactive Iodine for Low-Risk Papillary Thyroid Cancer Is Most Common in Regions with Poor Access to Healthcare

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140266/1/thy.2015.0112.pd

HPV Status as Prognostic Biomarker in Head and Neck Cancer—Which Method Fits the Best for Outcome Prediction?

The incidence of human papillomavirus (HPV)-related head and neck cancer (HNSCC) is rising globally, presenting challenges for optimized clinical management. To date, it remains unclear which biomarker best reflects HPV-driven carcinogenesis, a process that is associated with better therapeutic response and outcome compared to tobacco/alcohol-induced cancers. Six potential HPV surrogate biomarkers were analyzed using FFPE tissue samples from 153 HNSCC patients (n = 78 oropharyngeal cancer (OPSCC), n = 35 laryngeal cancer, n = 23 hypopharyngeal cancer, n = 17 oral cavity cancer): p16, CyclinD1, pRb, dual immunohistochemical staining of p16 and Ki67, HPV-DNA-PCR, and HPV-DNA-in situ hybridization (ISH). Biomarkers were analyzed for correlation with one another, tumor subsite, and patient survival. P16-IHC alone showed the best performance for discriminating between good (high expression) vs poor outcome (low expression; p = 0.0030) in OPSCC patients. Additionally, HPV-DNA-ISH (p = 0.0039), HPV-DNA-PCR (p = 0.0113), and p16-Ki67 dual stain (p = 0.0047) were significantly associated with prognosis in uniand multivariable analysis for oropharyngeal cancer. In the non-OPSCC group, however, none of the aforementioned surrogate markers was prognostic. Taken together, P16-IHC as a single biomarker displays the best diagnostic accuracy for prognosis stratification in OPSCC patients with a direct detection of HPV-DNA by PCR or ISH as well as p16-Ki67 dual stain as potential alternatives

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Tumor mutational burden as a predictive biomarker for checkpoint inhibitor immunotherapy

Immune checkpoint inhibitor (ICI) therapies can achieve meaningful tumor responses in a subset of patients with most types of cancer that have been investigated. However, the majority of patients treated with these drugs do not experience any clinical benefit. Because not all patients benefit from ICIs, and some may experience more meaningful tumor response if treated with chemotherapy or other treatments, there is a compelling need for predictive biomarkers to facilitate more informed selection of therapy. Tumor mutational burden (TMB) is one feature of a tumor that has predictive value for ICI therapy across multiple cancer types. In a pan-cancer analysis of over 1,600 patients, higher TMB was associated with longer survival and higher response rates with ICI therapy. While this effect was seen in the majority of cancer types, indicating that TMB underlies fundamental aspects of immune-mediated tumor rejection, the optimal predictive cut-point varied widely by histology, suggesting that there is unlikely to be one tissue-agnostic definition of high TMB that is useful for predicting ICI response. More comprehensive predictive models integrating TMB with other factors – including genetic, immunologic, and clinicopathologic markers – will be needed to potentially achieve a tissue-agnostic predictor of benefit from ICIs