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Purpose\ud Using radiobiological modelling to estimate normal tissue toxicity, this study investigates the effects of dose escalation for concurrent chemoradiation therapy (CRT) in lower third oesophageal tumours on the stomach.\ud \ud Methods and materials\ud 10 patients with lower third oesophageal cancer were selected from the SCOPE 1 database (ISCRT47718479) with a mean planning target volume (PTV) of 348 cm3. The original 3D conformal plans (50Gy3D) were compared to newly created RapidArc plans of 50GyRA and 60GyRA, the latter using a simultaneous integrated boost (SIB) technique using a boost volume, PTV2. Dose-volume metrics and estimates of normal tissue complication probability (NTCP) were compared.\ud \ud Results\ud There was a significant increase in NTCP of the stomach wall when moving from the 50GyRA to the 60GyRA plans (11–17 %, Wilcoxon signed rank test, p = 0.01). There was a strong correlation between the NTCP values of the stomach wall and the volume of the stomach wall/PTV 1 and stomach wall/PTV2 overlap structures (R = 0.80 and R = 0.82 respectively) for the 60GyRA plans.\ud \ud Conclusion\ud Radiobiological modelling suggests that increasing the prescribed dose to 60Gy may be associated with a significantly increased risk of toxicity to the stomach. It is recommended that stomach toxicity be closely monitored when treating patients with lower third oesophageal tumours with 60Gy.

Background In order to improve lung cancer survival in the UK, a greater proportion of resectable cancers must be diagnosed. It is likely that resectability rates would be increased by more timely diagnosis. Aside from screening, the only way of achieving this is to reduce the time to diagnosis in symptomatic cancers. Currently, lung cancers are mainly diagnosed by general practitioners (GPs) using the National Institute for Health and Clinical Excellence (NICE) guidelines for urgent referral for chest X-ray, which recommend urgent imaging or referral for patients who have one of a number of chest symptoms for more than 3 weeks. We are proposing to expand this recommendation to include one of a number of chest symptoms of any duration in higher-risk patients. Methods/Design We intend to conduct a trial of imaging in these higher-risk patients and compare it with NICE guidelines to see if imaging improves stage at diagnosis and resection rates. This trial would have to be large (and consequently resource-intensive) because most of these patients will not have lung cancer, making optimal design crucial. We are therefore conducting a pilot trial that will ascertain the feasibility of running a full trial and provide key information that will be required in order to design the full trial. Discussion This trial will assess the feasibility and inform the design of a large, UK-wide, clinical trial of a change to the NICE guidelines for urgent referral for chest X-ray for suspected lung cancer. It utilizes a combination of workshop, health economic, quality of life, qualitative, and quantitative methods in order to fully assess feasibility. Trial registration Clinicaltrials.gov NCT01344005

Background In a non-inferiority (NI) trial, analysis based on the intention-to-treat (ITT) principle is anti-conservative, so current guidelines recommend analysing on a per-protocol (PP) population in addition. However, PP analysis relies on the often implausible assumption of no confounders. Randomisation-based efficacy estimators (RBEEs) allow for treatment non-adherence while maintaining a comparison of randomised groups. Fischer et al. have developed an approach for estimating RBEEs in randomised trials with two active treatments, a common feature of NI trials. The aim of this paper was to demonstrate the use of RBEEs in NI trials using this approach, and to appraise the feasibility of these estimators as the primary analysis in NI trials. Methods Two NI trials were used. One comparing two different dosing regimens for the maintenance of remission in people with ulcerative colitis (CODA), and the other comparing an orally administered treatment to an intravenously administered treatment in preventing skeletal-related events in patients with bone metastases from breast cancer (ZICE). Variables that predicted adherence in each of the trial arms, and were also independent of outcome, were sought in each of the studies. Structural mean models (SMMs) were fitted that conditioned on these variables, and the point estimates and confidence intervals compared to that found in the corresponding ITT and PP analyses. Results In the CODA study, no variables were found that differentially predicted treatment adherence while remaining independent of outcome. The SMM, using standard methodology, moved the point estimate closer to 0 (no difference between arms) compared to the ITT and PP analyses, but the confidence interval was still within the NI margin, indicating that the conclusions drawn would remain the same. In the ZICE study, cognitive functioning as measured by the corresponding domain of the QLQ-C30, and use of chemotherapy at baseline were both differentially associated with adherence while remaining independent of outcome. However, while the SMM again moved the point estimate closer to 0, the confidence interval was wide, overlapping with any NI margin that could be justified. Conclusion Deriving RBEEs in NI trials with two active treatments can provide a randomisation-respecting estimate of treatment efficacy that accounts for treatment adherence, is straightforward to implement, but requires thorough planning during the design stage of the study to ensure that strong baseline predictors of treatment are captured. Extension of the approach to handle nonlinear outcome variables is also required. Trial registration The CODA study: ClinicalTrials.gov, identifier: NCT00708656. Registered on 8 April 2008. The ZICE study trial: ClinicalTrials.gov, identifier: NCT00326820. Registered on 16 May 2006. Electronic supplementary material The online version of this article (doi:10.1186/s13063-017-1837-3) contains supplementary material, which is available to authorized users.