Laser augmented by brachytherapy versus laser alone in the palliation of adenocarcinoma of the oesophagus and cardia: a randomised study

Background: Many patients with advanced malignant dysphagia are not suitable for definitive treatment. The best option for palliation of dysphagia varies between patients. This paper looks at a simple technique for enhancing laser recanalisation. Aim: To assess the value of adjunctive brachytherapy in prolonging palliation of malignant dysphagia by endoscopic laser therapy. Patients: Twenty two patients with advanced malignant dysphagia due to adenocarcinoma of the oesophagus or gastric cardia, unsuitable for surgery or radical chemoradiotherapy. Methods: Patients able to eat a soft diet after laser recanalisation were randomised to no further therapy or a single treatment with brachytherapy (10 Gy). Results were judged on the quality and duration of dysphagia palliation, need for subsequent intervention, complications, and survival. Results: The median dysphagia score for all patients two weeks after initial treatment was 1 (some solids). The median dysphagia palliated interval from the end of initial treatment to recurrent dysphagia or death increased from five weeks (control group) to 19 weeks (brachytherapy group). Three patients had some odynophagia for up to six weeks after brachytherapy. There was no other treatment related morbidity or mortality. Further intervention was required in 10 of 11 control patients (median five further procedures) compared with 7/11 brachytherapy patients (median two further procedures). There was no difference in survival (median 20 weeks (control), 26 weeks (brachytherapy)). Conclusions: Laser therapy followed by brachytherapy is a safe, straightforward, and effective option for palliating advanced malignant dysphagia, which is complementary to stent insertion

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use, and pave the way to further large scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multistakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two round, modified Delphi process to collect and analyse expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 predefined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. 123 experts participated in the first round of Delphi, 138 in the second, 16 in the consensus meeting, and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI specific reporting items (made of 28 subitems) and 10 generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we have developed a guideline comprising key items that should be reported in early stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings

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Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation; analyses timings and patterns of tumour evolution; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity; and evaluates a range of more-specialized features of cancer genomes