Time from first presentation in primary care to treatment of symptomatic colorectal cancer:effect on disease stage and survival

BACKGROUND: British 5-year survival from colorectal cancer (CRC) is below the European average, but the reasons are unclear. This study explored if longer provider delays (time from presentation to treatment) were associated with more advanced stage disease at diagnosis and poorer survival. METHODS: Data on 958 people with CRC were linked with the Scottish Cancer Registry, the Scottish Death Registry and the acute hospital discharge (SMR01) dataset. Time from first presentation in primary care to first treatment, disease stage at diagnosis and survival time from date of first presentation in primary care were determined. Logistic regression and Cox survival analyses, both with a restricted cubic spline, were used to model stage and survival, respectively, following sequential adjustment of patient and tumour factors. RESULTS: On univariate analysis, those with <4 weeks from first presentation in primary care to treatment had more advanced disease at diagnosis and the poorest prognosis. Treatment delays between 4 and 34 weeks were associated with earlier stage (with the lowest odds ratio occurring at 20 weeks) and better survival (with the lowest hazard ratio occurring at 16 weeks). Provider delays beyond 34 weeks were associated with more advanced disease at diagnosis, but not increased mortality. Following adjustment for patient, tumour factors, emergency admissions and symptoms and signs, no significant relationship between provider delay and stage at diagnosis or survival from CRC was found. CONCLUSIONS: Although allowing for a nonlinear relationship and important confounders, moderately long provider delays did not impact adversely on cancer outcomes. Delays are undesirable because they cause anxiety; this may be fuelled by government targets and health campaigns stressing the importance of very prompt cancer diagnosis. Our findings should reassure patients. They suggest that a health service's primary emphasis should be on quality and outcomes rather than on time to treatment

Ultrafast and high-throughput mass spectrometric assay for therapeutic drug monitoring of antiretroviral drugs in pediatric HIV-1 infection applying dried blood spots

Kaletra® (Abott Laboratories) is a co-formulated medication used in the treatment of HIV-1-infected children, and it contains the two antiretroviral protease inhibitor drugs lopinavir and ritonavir. We validated two new ultrafast and high-throughput mass spectrometric assays to be used for therapeutic drug monitoring of lopinavir and ritonavir concentrations in whole blood and in plasma from HIV-1-infected children. Whole blood was blotted onto dried blood spot (DBS) collecting cards, and plasma was collected simultaneously. DBS collecting cards were extracted by an acetonitrile/water mixture while plasma samples were deproteinized with acetone. Drug concentrations were determined by matrix-assisted laser desorption/ionization-triple quadrupole tandem mass spectrometry (MALDI-QqQ-MS/MS). The application of DBS made it possible to measure lopinavir and ritonavir in whole blood in therapeutically relevant concentrations. The MALDI-QqQ-MS/MS plasma assay was successfully cross-validated with a commonly used high-performance liquid chromatography (HPLC)–ultraviolet (UV) assay for the therapeutic drug monitoring (TDM) of HIV-1-infected patients, and it showed comparable performance characteristics. Observed DBS concentrations showed as well, a good correlation between plasma concentrations obtained by MALDI-QqQ-MS/MS and those obtained by the HPLC-UV assay. Application of DBS for TDM proved to be a good alternative to the normally used plasma screening. Moreover, collection of DBS requires small amounts of whole blood which can be easily performed especially in (very) young children where collection of large whole blood amounts is often not possible. DBS is perfectly suited for TDM of HIV-1-infected children; but nevertheless, DBS can also easily be applied for TDM of patients in areas with limited or no laboratory facilities

Single-solution Simulated Kalman Filter algorithm for global optimisation problems

This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. In comparison, the proposed ssSKF algorithm supersedes the original population-based Simulated Kalman Filter (SKF) algorithm by operating with only a single agent, and having less parameters to be tuned. In the proposed ssSKF algorithm, the initialisation parameters are not constants, but they are produced by random numbers taken from a normal distribution in the range of [0, 1], thus excluding them from tuning requirement. In order to balance between the exploration and exploitation in ssSKF, the proposed algorithm uses an adaptive neighbourhood mechanism during its prediction step. The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). The results show that the proposed ssSKF algorithm is a promising approach and able to outperform GWO and GA algorithms, significantly