Heterogeneity in multistage carcinogenesis and mixture modeling

Carcinogenesis is commonly described as a multistage process, in which stem cells are transformed into cancer cells via a series of mutations. In this article, we consider extensions of the multistage carcinogenesis model by mixture modeling. This approach allows us to describe population heterogeneity in a biologically meaningful way. We focus on finite mixture models, for which we prove identifiability. These models are applied to human lung cancer data from several birth cohorts. Maximum likelihood estimation does not perform well in this application due to the heavy censoring in our data. We thus use analytic graduation instead. Very good fits are achieved for models that combine a small high risk group with a large group that is quasi immune

Oral abstracts 1: SpondyloarthropathiesO1. Detecting axial spondyloarthritis amongst primary care back pain referrals

Background: Inflammatory back pain (IBP) is an early feature of ankylosing spondylitis (AS) and its detection offers the prospect of early diagnosis of AS. However, since back pain is very common but only a very small minority of back pain sufferers have ASpA or AS, screening of back pain sufferers for AS is problematic. In early disease radiographs are often normal so that fulfilment of diagnostic criteria for AS is impossible though a diagnosis of axial SpA can be made if MRI evidence of sacroiliitis is present. This pilot study was designed to indicate whether a cost-effective pick up rate for ASpA/early AS could be achieved by identifying adults with IBP stratified on the basis of age. Methods: Patients aged between 18 and 45 years who were referred to a hospital physiotherapy service with back pain of more than 3 months duration were assessed for IBP. All were asked to complete a questionnaire based on the Berlin IBP criteria. Those who fulfilled IBP criteria were also asked to complete a second short questionnaire enquiring about SpA comorbidities, to have a blood test for HLA-B27 and CRP level and to undergo an MRI scan of the sacroiliac joints. This was a limited scan, using STIR, diffusion-weighted, T1 and T2 sequences of the sacroiliac joints to minimize time in the scanner and cost. The study was funded by a research grant from Abbott Laboratories Ltd. Results: 50 sequential patients agreed to participate in the study and completed the IBP questionnaire. Of these 27 (54%) fulfilled criteria for IBP. Of these, 2 patients reported a history of an SpA comorbidity - 1 psoriasis; 1 ulcerative colitis - and 3 reported a family history of an SpA comorbidity - 2 psoriasis; 1 Crohn's disease. 4 were HLA-B27 positive, though results were not available for 7. Two patients had marginally raised CRP levels (6, 10 -NR ≤ 5). 19 agreed to undergo MRI scanning of the sacroiliac joints and lumbar spine; 4 scans were abnormal, showing evidence of bilateral sacroiliitis on STIR sequences. In all cases the changes met ASAS criteria but were limited. Of these 4 patients 3 were HLA-B27 positive but none gave a personal or family history of an SpA-associated comorbidity and all had normal CRP levels. Conclusions: This was a pilot study yielding only limited conclusions. However, it is clear that: Screening of patients referred for physiotherapy for IBP is straightforward, inexpensive and quick. It appears that IBP is more prevalent in young adults than overall population data suggest so that targeting this population may be efficient. IBP questionnaires could be administered routinely during a physiotherapy assessment. HLA-B27 testing in this group of patients with IBP is a suitable screening tool. The sacroiliac joint changes identified were mild and their prognostic significance is not yet clear so that the value of early screening needs further evaluation. Disclosure statement: C.H. received research funding for this study from Abbott. A.K. received research funding for this study, and speaker and consultancy fees, from Abbott. All other authors have declared no conflicts of interes

GetReal in mathematical modelling : a review of studies predicting drug effectiveness in the real world

The performance of a drug in a clinical trial setting often does not reflect its effect in daily clinical practice. In this third of three reviews, we examine the applications that have been used in the literature to predict real-world effectiveness from randomized controlled trial efficacy data. We searched MEDLINE, EMBASE from inception to March 2014, the Cochrane Methodology Register, and websites of key journals and organisations and reference lists. We extracted data on the type of model and predictions, data sources, validation and sensitivity analyses, disease area and software. We identified 12 articles in which four approaches were used: multi-state models, discrete event simulation models, physiology-based models and survival and generalized linear models. Studies predicted outcomes over longer time periods in different patient populations, including patients with lower levels of adherence or persistence to treatment or examined doses not tested in trials. Eight studies included individual patient data. Seven examined cardiovascular and metabolic diseases and three neurological conditions. Most studies included sensitivity analyses, but external validation was performed in only three studies. We conclude that mathematical modelling to predict real-world effectiveness of drug interventions is not widely used at present and not well validated. © 2016 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd

GetReal in mathematical modelling : a review of studies predicting drug effectiveness in the real world

The performance of a drug in a clinical trial setting often does not reflect its effect in daily clinical practice. In this third of three reviews, we examine the applications that have been used in the literature to predict real-world effectiveness from randomized controlled trial efficacy data. We searched MEDLINE, EMBASE from inception to March 2014, the Cochrane Methodology Register, and websites of key journals and organisations and reference lists. We extracted data on the type of model and predictions, data sources, validation and sensitivity analyses, disease area and software. We identified 12 articles in which four approaches were used: multi-state models, discrete event simulation models, physiology-based models and survival and generalized linear models. Studies predicted outcomes over longer time periods in different patient populations, including patients with lower levels of adherence or persistence to treatment or examined doses not tested in trials. Eight studies included individual patient data. Seven examined cardiovascular and metabolic diseases and three neurological conditions. Most studies included sensitivity analyses, but external validation was performed in only three studies. We conclude that mathematical modelling to predict real-world effectiveness of drug interventions is not widely used at present and not well validated. © 2016 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd

EFFECT OF SECUKINUMAB ON SIGNS AND SYMPTOMS OF PSORIATIC ARTHRITIS: RESULTS OF A 24-WEEK MULTICENTRE, DOUBLE-BLIND, RANDOMIZED, PLACEBO-CONTROLLED TRIAL

Pathophysiology and treatment of rheumatic disease

Anti-Interleukin 17A Monoclonal Antibody Secukinumab Reduces Signs and Symptoms of Psoriatic Arthritis in a 24-Week Multicenter, Double-Blind, Randomized, Placebo-Controlled Trial

Pathophysiology and treatment of rheumatic disease

Interleukin-17A Blockade with Secukinumab Reduces Spinal Inflammation in Patients with Ankylosing Spondylitis As Early As Week 6, As Detected by Magnetic Resonance Imaging

Pathophysiology and treatment of rheumatic disease

SECUKINUMAB REDUCES SPINAL INFLAMMATION AS EARLY AS WEEK 6, AS DETECTED BY MRI - RESULTS OF A DOUBLE-BLIND, PHASE II PROOF-OF-CONCEPT STUDY IN PATIENTS WITH ANKYLOSING SPONDYLITIS

Pathophysiology and treatment of rheumatic disease