How does sex influence multimorbidity? Secondary analysis of a large nationally representative dataset

Multimorbidity increases with age and is generally more common in women, but little is known about sex effects on the “typology” of multimorbidity. We have characterized multimorbidity in a large nationally representative primary care dataset in terms of sex in ten year age groups from 25 years to 75 years and over, in a cross-sectional analysis of multimorbidity type (physical-only, mental-only, mixed physical and mental; and commonest conditions) for 1,272,685 adults in Scotland. Our results show that women had more multimorbidity overall in every age group, which was most pronounced in the 45–54 years age group (women 26.5% vs. men 19.6%; difference 6.9 (95% CI 6.5 to 7.2). From the age of 45, physical-only multimorbidity was consistently more common in men, and physical-mental multimorbidity more common in women. The biggest difference in physical-mental multimorbidity was found in the 75 years and over group (women 30.9% vs. men 21.2%; difference 9.7 (95% CI 9.1 to 10.2). The commonest condition in women was depression until the age of 55 years, thereafter hypertension. In men, drugs misuse had the highest prevalence in those aged 25–34 years, depression for those aged 35–44 years, and hypertension for 45 years and over. Depression, pain, irritable bowel syndrome and thyroid disorders were more common in women than men across all age groups. We conclude that the higher overall prevalence of multimorbidity in women is mainly due to more mixed physical and mental health problems. The marked difference between the sexes over 75 years especially warrants further investigation. © 2016 by the authors; licensee MDPI, Basel, Switzerland

Chronic obstructive pulmonary disease and comorbidities:a large cross-sectional study in primary care

Background: Chronic obstructive pulmonary disease (COPD) is common, and a major cause of morbidity and mortality worldwide. Recent studies suggest that comorbidities of COPD increase the risk of hospitalisation, polypharmacy, and mortality, but their estimated prevalence varies widely in the literature. Aim: To evaluate the prevalence of 38 physical and mental health comorbidities in people with COPD, and compare findings with those for people without COPD in a large nationally representative dataset. Design and setting: A cross-sectional data analysis on 1 272 685 adults in Scotland from 314 primary care practices. Method Data: on COPD, along with 31 physical and seven mental health comorbidities, were extracted. The prevalence of comorbidities was compared between people who did, and did not, have COPD, standardised by age, sex, and socioeconomic deprivation. Results: From the total sample, 51 928 patients had COPD (4.1%). Of these, 86.0% had at least one comorbidity, compared with 48.9% of people without COPD. Of those with COPD, 22.3% had ≥5 comorbid conditions compared with 4.9% of those who did not have COPD (adjusted odds ratio 2.63, 95% confidence interval = 2.56 to 2.70). In total, 29 of the 31 physical conditions and six of the seven mental health conditions were statistically significantly more prevalent in people who had COPD than those who did not. Conclusion: Patients with COPD have extensive associated comorbidities. There is a real need for guidelines and health care to reflect this complexity, including how to detect those common comorbidities that relate to both physical and mental health, and how best to manage them. Primary care, which is unique in terms of offering expert generalist care, is best placed to provide this integrated approach

The Local Optima Level in Chemotherapy Schedule Optimisation

In this paper a multi-drug Chemotherapy Schedule Optimisation Problem (CSOP) is subject to Local Optima Network (LON) analysis. LONs capture global patterns in fitness landscapes. CSOPs have not previously been subject to fitness landscape analysis. We fill this gap: LONs are constructed and studied for meaningful structure. The CSOP formulation presents novel challenges and questions for the LON model because there are infeasible regions in the fitness landscape and an unknown global optimum; it also brings a topic from healthcare to LON analysis. Two LON Construction algorithms are proposed for sampling CSOP fitness landscapes: a Markov-Chain Construction Algorithm and a Hybrid Construction Algorithm. The results provide new insight into LONs of highly-constrained spaces, and into the proficiency of search operators on the CSOP. Iterated Local Search and Memetic Search, which are the foundations for the LON algorithms, are found to markedly out-perform a Genetic Algorithm from the literature

Theoretical and practical development of the TOPSY self-management intervention for women who use a vaginal pessary for pelvic organ prolapse

Background: Pelvic organ prolapse (POP) is a common condition in women, where the downward descent of pelvic organs into the vagina causes symptoms which impacts quality of life. Vaginal pessaries offer an effective alternative to surgery for the management of POP. However, the need for regular follow-up can be burdensome for women and requires significant healthcare resources. The TOPSY study is a randomised controlled trial which aims to determine the clinical and cost-effectiveness of self-management of vaginal pessaries. This paper describes the theoretical and practical development of the self-management intervention. Methods: The intervention was developed using the MRC complex intervention framework, normalisation process theory (NPT) and self-management theory. The intervention aims to boost perceived self-efficacy in accordance with Bandura’s social cognitive theory and is guided by the tasks and skills Lorig and Hollman describe as necessary to self-manage a health condition. Results: The TOPSY intervention was designed to support women to undertake the medical management, role management and emotional management of their pessary. The six self-management skills described by Lorig and Hollman: problem-solving, decision-making, resource utilisation, formation of a patient-provider partnership role, action planning and self-tailoring, are discussed in detail, including how women were supported to achieve each task within the context of pessary self-management. The TOPSY intervention includes a self-management support session with a pessary practitioner trained in intervention delivery, a follow-up phone call 2 weeks later and ongoing telephone or face-to-face support as required by the woman initiated by contacting a member of the research team. Conclusions: The TOPSY study intervention was developed utilising the findings from a prior service development project, intervention development and self-efficacy theory, relevant literature, clinician experience and feedback from pessary using women and members of the public. In 2022, the findings of the TOPSY study will provide further evidence to inform this important aspect of pessary management. Trial registration: ISRCTN Registry ISRCTN62510577. Registered on June 10, 2017

From regional pulse vaccination to global disease eradication: insights from a mathematical model of Poliomyelitis

Mass-vaccination campaigns are an important strategy in the global fight against poliomyelitis and measles. The large-scale logistics required for these mass immunisation campaigns magnifies the need for research into the effectiveness and optimal deployment of pulse vaccination. In order to better understand this control strategy, we propose a mathematical model accounting for the disease dynamics in connected regions, incorporating seasonality, environmental reservoirs and independent periodic pulse vaccination schedules in each region. The effective reproduction number, $R_e$, is defined and proved to be a global threshold for persistence of the disease. Analytical and numerical calculations show the importance of synchronising the pulse vaccinations in connected regions and the timing of the pulses with respect to the pathogen circulation seasonality. Our results indicate that it may be crucial for mass-vaccination programs, such as national immunisation days, to be synchronised across different regions. In addition, simulations show that a migration imbalance can increase $R_e$ and alter how pulse vaccination should be optimally distributed among the patches, similar to results found with constant-rate vaccination. Furthermore, contrary to the case of constant-rate vaccination, the fraction of environmental transmission affects the value of $R_e$ when pulse vaccination is present.Comment: Added section 6.1, made other revisions, changed titl

The TOPSY pessary self-management intervention for pelvic organ prolapse: a study protocol for the process evaluation.

BACKGROUND: Process evaluations have become a valued component, alongside clinical trials, of the wider evaluation of complex health interventions. They support understanding of implementation, and fidelity, related to the intervention and provide valuable insights into what is effective in a practical setting by examining the context in which interventions are implemented. The TOPSY study consists of a large multi-centre randomised controlled trial comparing the effectiveness of pessary self-management with clinic-based care in improving women's condition-specific quality of life, and a nested process evaluation. The process evaluation aims to examine and maximise recruitment to the trial, describe intervention fidelity and explore participants' and healthcare professionals' experiences. METHODS: The trial will recruit 330 women from approximately 17 UK centres. The process evaluation uses a mixed-methods approach. Semi-structured interviews will be conducted with randomised women (18 per randomised group/n = 36), women who declined trial participation but agreed to interview (non-randomised women) (n = 20) and healthcare professionals recruiting to the trial (n ~ 17) and delivering self-management and clinic-based care (n ~ 17). The six internal pilot centres will be asked to record two to three recruitment discussions each (total n = 12-18). All participating centres will be asked to record one or two self-management teaching appointments (n = 30) and self-management 2-week follow-up telephone calls (n = 30). Process data (quantitative and qualitative) will be gathered in participant completed trial questionnaires. Interviews will be analysed thematically and recordings using an analytic grid to identify fidelity to the intervention. Quantitative analysis will be predefined within the process evaluation analysis plan. DISCUSSION: The wide variety of pessary care delivered across the UK for women with pelvic organ prolapse presents specific localised contexts in which the TOPSY interventions will be implemented. Understanding this contextual variance is central to understanding how and in what circumstances pessary self-management can be implemented (should it be effective). The inclusion of non-randomised women provides an innovative way of collecting indispensable information about eligible women who decline trial participation, allowing broader contextualisation and considerations of generalisability of trial findings. Methodological insights from examination of recruitment processes and mechanisms have the potential to inform recruitment mechanisms and future recruitment strategies and study designs. TRIAL REGISTRATION: ISRCTN62510577 . Registered on 6 October 2017

A General Model for Multilocus Epistatic Interactions in Case-Control Studies

Background: Epistasis, i.e., the interaction of alleles at different loci, is thought to play a central role in the formation and progression of complex diseases. The complexity of disease expression should arise from a complex network of epistatic interactions involving multiple genes. Methodology: We develop a general model for testing high-order epistatic interactions for a complex disease in a casecontrol study. We incorporate the quantitative genetic theory of high-order epistasis into the setting of cases and controls sampled from a natural population. The new model allows the identification and testing of epistasis and its various genetic components. Conclusions: Simulation studies were used to examine the power and false positive rates of the model under different sampling strategies. The model was used to detect epistasis in a case-control study of inflammatory bowel disease, in which five SNPs at a candidate gene were typed, leading to the identification of a significant three-locus epistasis

Evolution of Resistance to Targeted Anti-Cancer Therapies during Continuous and Pulsed Administration Strategies

The discovery of small molecules targeted to specific oncogenic pathways has revolutionized anti-cancer therapy. However, such therapy often fails due to the evolution of acquired resistance. One long-standing question in clinical cancer research is the identification of optimum therapeutic administration strategies so that the risk of resistance is minimized. In this paper, we investigate optimal drug dosing schedules to prevent, or at least delay, the emergence of resistance. We design and analyze a stochastic mathematical model describing the evolutionary dynamics of a tumor cell population during therapy. We consider drug resistance emerging due to a single (epi)genetic alteration and calculate the probability of resistance arising during specific dosing strategies. We then optimize treatment protocols such that the risk of resistance is minimal while considering drug toxicity and side effects as constraints. Our methodology can be used to identify optimum drug administration schedules to avoid resistance conferred by one (epi)genetic alteration for any cancer and treatment type

Targeted Drug Delivery by Gemtuzumab Ozogamicin: Mechanism-Based Mathematical Model for Treatment Strategy Improvement and Therapy Individualization

Gemtuzumab ozogamicin (GO) is a chemotherapy-conjugated anti-CD33 monoclonal antibody effective in some patients with acute myeloid leukemia (AML). The optimal treatment schedule and optimal timing of GO administration relative to other agents remains unknown. Conventional pharmacokinetic analysis has been of limited insight for the schedule optimization. We developed a mechanism-based mathematical model and employed it to analyze the time-course of free and GO-bound CD33 molecules on the lekemic blasts in individual AML patients treated with GO. We calculated expected intravascular drug exposure (I-AUC) as a surrogate marker for the response to the drug. A high CD33 production rate and low drug efflux were the most important determinants of high I-AUC, characterizing patients with favorable pharmacokinetic profile and, hence, improved response. I-AUC was insensitive to other studied parameters within biologically relevant ranges, including internalization rate and dissociation constant. Our computations suggested that even moderate blast burden reduction prior to drug administration enables lowering of GO doses without significantly compromising intracellular drug exposure. These findings indicate that GO may optimally be used after cyto-reductive chemotherapy, rather than before, or concomitantly with it, and that GO efficacy can be maintained by dose reduction to 6 mg/m2 and a dosing interval of 7 days. Model predictions are validated by comparison with the results of EORTC-GIMEMA AML19 clinical trial, where two different GO schedules were administered. We suggest that incorporation of our results in clinical practice can serve identification of the subpopulation of elderly patients who can benefit most of the GO treatment and enable return of the currently suspended drug to clinic

Mathematical modeling of solid cancer growth with angiogenesis

<p>Abstract</p> <p>Background</p> <p>Cancer arises when within a single cell multiple malfunctions of control systems occur, which are, broadly, the system that promote cell growth and the system that protect against erratic growth. Additional systems within the cell must be corrupted so that a cancer cell, to form a mass of any real size, produces substances that promote the growth of new blood vessels. Multiple mutations are required before a normal cell can become a cancer cell by corruption of multiple growth-promoting systems.</p> <p>Methods</p> <p>We develop a simple mathematical model to describe the solid cancer growth dynamics inducing angiogenesis in the absence of cancer controlling mechanisms.</p> <p>Results</p> <p>The initial conditions supplied to the dynamical system consist of a perturbation in form of pulse: The origin of cancer cells from normal cells of an organ of human body. Thresholds of interacting parameters were obtained from the steady states analysis. The existence of two equilibrium points determine the strong dependency of dynamical trajectories on the initial conditions. The thresholds can be used to control cancer.</p> <p>Conclusions</p> <p>Cancer can be settled in an organ if the following combination matches: better fitness of cancer cells, decrease in the efficiency of the repairing systems, increase in the capacity of sprouting from existing vascularization, and higher capacity of mounting up new vascularization. However, we show that cancer is rarely induced in organs (or tissues) displaying an efficient (numerically and functionally) reparative or regenerative mechanism.</p