Oral cancer prediction by noninvasive genetic screening

Oral squamous cell carcinomas (OSCCs) develop in genetically altered epithelium in the mucosal lining, also coined as fields, which are mostly not visible but occasionally present as white oral leukoplakia (OL) lesions. We developed a noninvasive genetic assay using next-generation sequencing (NGS) on brushed cells to detect the presence of genetically altered fields, including those that are not macroscopically visible. The assay demonstrated high accuracy in OL patients when brush samples were compared with biopsies as gold standard. In a cohort of Fanconi anemia patients, detection of mutations in prospectively collected oral brushes predicted oral cancer also when visible abnormalities were absent. We further provide insight in the molecular landscape of OL with frequent changes of TP53, FAT1 and NOTCH1. NGS analysis of noninvasively collected samples offers a highly accurate method to detect genetically altered fields in the oral cavity, and predicts development of OSCC in high-risk individuals. Noninvasive genetic screening can be employed to screen high-risk populations for cancer and precancer, map the extension of OL lesions beyond what is visible, map the oral cavity for precancerous changes even when visible abnormalities are absent, test accuracy of promising imaging modalities, monitor interventions and determine genetic progression as well as the natural history of the disease in the human patient.     

Existing fixation modalities for Jones type fifth metatarsal fracture fixation pose high rates of complications and nonunion

Jones type fifth metatarsal fractures pose a challenge to the foot and ankle surgeon, given documented high nonunion rates as well as high complication rates including hardware prominence, nerve injury, and screw breakage for existing treatment modalities including screw and plantar plate fixation. We call for the design of innovative Jones-fracture specific implants which contour to the natural curve of the fifth metatarsal. Future research should aim to expand upon existing literature for Jones fracture fixation and evaluate efficacy of novel implants which are designed to address unacceptably high complication rates for existing treatment modalities.     

Autonomic function testing in multiple system atrophy: a prognostic biomarker? and other updates on recent autonomic research

Clinical Autonomic Research -     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

Peri-operative tobacco cessation interventions: a systematic review and meta-analysis

Tobacco smoking is associated with a substantially increased risk of postoperative complications. The peri-operative period offers a unique opportunity to support patients to stop tobacco smoking, avoid complications and improve long-term health. This systematic review provides an up-to-date summary of the evidence for tobacco cessation interventions in surgical patients. We conducted a systematic search of randomised controlled trials of tobacco cessation interventions in the peri-operative period. Quantitative synthesis of the abstinence outcomes data was by random-effects meta-analysis. The primary outcome of the meta-analysis was abstinence at the time of surgery, and the secondary outcome was abstinence at 12 months. Thirty-eight studies are included in the review (7310 randomised participants) and 26 studies are included in the meta-analysis (5969 randomised participants). Studies were pooled for subgroup analysis in two ways: by the timing of intervention delivery within the peri-operative period and by the intensity of the intervention protocol. We judged the quality of evidence as moderate, reflecting the degree of heterogeneity and the high risk of bias. Overall, peri-operative tobacco cessation interventions increased successful abstinence both at the time of surgery, risk ratio (95%CI) 1.48 (1.20–1.83), number needed to treat 7; and 12 months after surgery, risk ratio (95%CI) 1.62 (1.29–2.03), number needed to treat 9. More work is needed to inform the design and optimal delivery of interventions that are acceptable to patients and that can be incorporated into contemporary elective and urgent surgical pathways. Future trials should use standardised outcome measures.