Chest computed tomography for staging renal tumours: validation and simplification of a risk prediction model from a large contemporary retrospective cohort.

OBJECTIVES: To externally validate a nomogram recently proposed by Larcher et al. (BJU Int. 2017; 120: 490) and to develop a simplified model with comparable accuracy to guide on the need for staging chest computed tomography (CT) for patients with new renal masses. PATIENTS AND METHODS: We analysed the data of 1082 consecutive patients with unilateral enhancing renal masses referred to urology multidisciplinary team meetings at two centres between 2011 and 2017. All patients underwent a staging chest CT at diagnosis. We fitted multivariable logistic regression models and tested the Larcher model performance using area under the receiver-operating curve (AUC), calibration and decision curve analysis. RESULTS: Forty-two patients (3.9%) had a positive chest CT. The Larcher nomogram had an AUC of 83.8% (95% confidence interval [CI] 77.1-90.6), but was only moderately well calibrated (calibration-in-the-large = -0.61, slope = 0.82). Specifically, the nomogram overestimated the risk of positive chest CT, and the magnitude of miscalibration increased with increasing predicted risks. Using a stepwise backward approach, a new model was developed including tumour size, nodal stage and systemic symptoms. Compared with the Larcher model, the new model had a similar AUC (82.7% [95% CI 75.5-90.0]), but improved calibration and clinical net benefit. The predicted risk of positive chest CT was <1% in the low-risk group and 1.9-79.9% in the high-risk group. CONCLUSION: The Larcher nomogram is an accurate prediction tool that was moderately well calibrated with our dataset. However, our simplified model has similar accuracy and uses more objective variables available from referral, so may be easier to incorporate into clinical practice. The low-risk group from our model (tumour size ≤4 cm and no systemic symptoms) had a risk of positive chest CT <1%, suggesting these patients may forego chest CT.

D-methionine interferes with non-typeable Haemophilus influenzae peptidoglycan synthesis during growth and biofilm formation.

Non-typeable Haemophilus influenzae (NTHi) is an opportunistic pathogen that plays a major role in a number of respiratory tract infections, including otitis media, cystic fibrosis and chronic obstructive pulmonary disease. Biofilm formation has been implicated in both NTHi colonization and disease, and is responsible for the increased tolerance of this pathogen towards antibiotic treatment. Targeting metabolic pathways that are important in NTHi biofilm formation represents a potential strategy to combat this antibiotic recalcitrance. A previous investigation demonstrated increased expression of a putative d-methionine uptake protein following exposure of NTHi biofilms to the ubiquitous signalling molecule, nitric oxide. We therefore hypothesized that treatment with exogenous d-methionine would impact on NTHi biofilm formation and increase antibiotic sensitivity. Treatment of NTHi during the process of biofilm formation resulted in a reduction in biofilm viability, increased biomass, changes in the overall biofilm architecture and the adoption of an amorphous cellular morphology. Quantitative proteomic analyses identified 124 proteins that were differentially expressed following d-methionine treatment, of which 51 (41 %) were involved in metabolic and transport processes. Nine proteins involved in peptidoglycan synthesis and cell division showed significantly increased expression. Furthermore, d-methionine treatment augmented the efficacy of azithromycin treatment and highlighted the potential of d-methionine as an adjunctive therapeutic approach for NTHi biofilm-associated infections.