Minimal residual disease in cancer therapy - Small things make all the difference

Minimal residual disease (MRD) is a major hurdle in the eradication of malignant tumors. Despite the high sensitivity of various cancers to treatment, some residual cancer cells persist and lead to tumor recurrence and treatment failure. Obvious reasons for residual disease include mechanisms of secondary therapy resistance, such as the presence of mutant cells that are insensitive to the drugs, or the presence of cells that become drug resistant due to activation of survival pathways. In addition to such unambiguous resistance modalities, several patients with relapsing tumors do not show refractory disease and respond again when the initial therapy is repeated. These cases cannot be explained by the selection of mutant tumor cells, and the precise mechanisms underlying this clinical drug resistance are ill-defined. In the current review, we put special emphasis on cell-intrinsic and -extrinsic mechanisms that may explain mechanisms of MRD that are independent of secondary therapy resistance. In particular, we show that studying genetically engineered mouse models (GEMMs), which highly resemble the disease in humans, provides a complementary approach to understand MRD. In these animal models, specific mechanisms of secondary resistance can be excluded by targeted genetic modifications. This allows a clear distinction between the selection of cells with stable secondary resistance and mechanisms that result in the survival of residual cells but do not provoke secondary drug resistance. Mechanisms that may explain the latter feature include special biochemical defense properties of cancer stem cells, metabolic peculiarities such as the dependence on autophagy, drug-tolerant persisting cells, intratumoral heterogeneity, secreted factors from the microenvironment, tumor vascularization patterns and immunosurveillance-related factors. We propose in the current review that a common feature of these various mechanisms is cancer cell dormancy. Therefore, dormant cancer cells appear to be an important target in the attempt to eradicate residual cancer cells, and eventually cure patients who repeatedly respond to anticancer therapy but lack complete tumor eradication.

Age-specific and sex-specific weight gain norms to monitor antiretroviral therapy in children in low-income and middle-income countries.

BACKGROUND Viral load and CD4% are often not available in resource-limited settings for monitoring children's responses to antiretroviral therapy (ART). We aimed to construct normative curves for weight gain at 6, 12, 18, and 24 months following initiation of ART in children, and to assess the association between poor weight gain and subsequent responses to ART. DESIGN Analysis of data from HIV-infected children younger than 10 years old from African and Asian clinics participating in the International epidemiologic Databases to Evaluate AIDS. METHODS The generalized additive model for location, scale, and shape was used to construct normative percentile curves for weight gain at 6, 12, 18, and 24 months following ART initiation. Cox proportional models were used to assess the association between lower percentiles (< 50th) of weight gain distribution at the different time points and subsequent death, virological suppression, and virological failure. RESULTS Among 7173 children from five regions of the world, 45% were underweight at baseline. Weight gain below the 50th percentile at 6, 12, 18, and 24 months of ART was associated with increased risk of death, independent of baseline characteristics. Poor weight gain was not associated with increased hazards of virological suppression or virological failure. CONCLUSION Monitoring weight gain on ART using age-specific and sex-specific normative curves specifically developed for HIV-infected children on ART is a simple, rapid, sustainable tool that can aid in the identification of children who are at increased risk of death in the first year of ART.

A sorrow shared is a sorrow halved? Internet-based group therapy versus individual therapy for social anxiety disorder: A randomized controlled trial

Purpose: Social anxiety disorder is one of the most researched conditions in the field of Internet-based self-help. Various studies have shown that cognitive-behavioral treatments can be efficacious to reduce social phobic symptoms. Most of the interventions tested include some form of support, whereas the efficacy of a web-based group format has yet to be investigated. The present study aims at investigating the possible added value of therapist-guided group support in an Internet-based guided self-help treatment for SAD. Methods: A total of 150 adults with a diagnosis of SAD are randomly assigned to either a wait-list control group or one of two active treatment conditions. Participants in the two active conditions use the same Internet-based self-help program, either with individual guidance by a therapist or with the support of a therapist-guided group of 6 individuals. In the group condition, participants communicate with each other via an integrated, protected discussion forum. The primary outcome variables are symptoms of SAD and diagnostic status immediately after the intervention (12 weeks) and at 6-month follow-up. Secondary endpoints are general symptomatology, depression, quality of life and adherence to treatment. Furthermore, process variables such as group processes and the working alliance are studied. Results: Results are currently being analyzed. Results at post-treatment will be presented and discussed. Potential moderating and mediating variables of treatment success will be addressed. Conclusion: The results of this study should indicate whether therapist-guided group support could enhance the efficacy of an internet based self-help treatment for SAD. This novel treatment format, if shown efficacious, could represent a cost-effective option and could be further modified to treat other conditions.

Outcomes of tuberculosis positive non-injection drug users in Harris County from October 1995 through September 2004

Background. The population-based Houston Tuberculosis Initiative (HTI) study has enrolled and gathered demographic, social, behavioral, and disease related data on more than 80% of all reported Mycobacterium Tuberculosis (MTB) cases and 90% of all culture positive patients in Houston/Harris County over a 9 year period (from October 1995-September 2004). During this time period 33% (n=1210) of HTI MTB cases have reported a history of drug use. Of those MTB cases reporting a history of drug use, a majority of them (73.6%), are non-injection drug users (NIDUs). ^ Other than HIV, drug use is the single most important risk factor for progression from latent to infectious tuberculosis (TB). In addition, drug use is associated with increased transmission of active TB, as seen by the increased number of clonally related strains or clusters (see definition on page 30) found in this population. The deregulatory effects of drug use on immune function are well documented. Associations between drug use and increased morbidity have been reported since the late 1970's. However, limited research focused on the immunological consequence of non-injection drug use and its relation to tuberculosis infection among TB patients is available. ^ Methods. TB transmission patterns, symptoms, and prevalence of co-morbidities were a focus of this project. Smoking is known to suppress Nitric Oxide (NO) production and interfere with immune function. In order to limit any possible confounding due to smoking two separate analyses were done. Non-injection drug user smokers (NIDU-S) were compared to non-drug user smokers (NDU-S) and non-injection drug user non-smokers (NIDU-NS) were compared to non-drug user non-smokers (NDU-NS) individually. Specifically proportions, chi-square p-values, and (where appropriate) odds ratios with 95% confidence intervals were calculated to assess characteristics and potential associations of co-morbidities and symptoms of TB among NIDUs HTI TB cases. ^ Results. Significant differences in demographic characteristics and risk factors were found. In addition drug users were found to have a decreased risk for cancer, diabetes mellitus, and chronic pulmonary disease. They were at increased risk of having HIV/AIDS diagnosis, liver disease, and trauma related morbidities. Drug users were more likely to have pulmonary TB disease, and a significantly increased amount of clonally related strains of TB or "clusters" were seen in both smokers and non-smoker drug users when compared to their non-drug user counterparts. Drug users are more likely to belong to print groups (clonally related TB strains with matching spoligotypes) including print one and print three and the Beijing family group, s1. Drug users were found to be no more likely to experience drug resistance to TB therapy and were likely to be cured of disease upon completion of therapy. ^ Conclusion. Drug users demographic and behavioral risk factors put them at an increased risk contracting and spreading TB disease throughout the community. Their increased levels of clustering are evidence of recent transmission and the significance of certain print groups among this population indicate the transmission is from within the social family. For these reasons a focus on this "at risk population" is critical to the success of future public health interventions. Successful completion of directly observed therapy (DOT), the tracking of TB outbreaks and incidence through molecular characterization, and increased diagnostic strategies have led to the stabilization of TB incidence in Houston, Harris County over the past 9 years and proven that the Houston Tuberculosis Initiative has played a critical role in the control and prevention of TB transmission. ^

Application of cell line based genomic predictors to predict response to targeted therapies in breast cancer

Cancer cell lines can be treated with a drug and the molecular comparison of responders and non-responders may yield potential predictors that could be tested in the clinic. It is a bioinformatics challenge to apply the cell line-derived multivariable response predictors to patients who respond to therapy. Using the gene expression data from 23 breast cancer cell lines, I developed three predictors of dasatinib sensitivity by selecting differentially expressed genes and applying different classification algorithms. The performance of these predictors on independent cell lines with known dasatinib response was tested. The predictor based on weighted voting method has the best overall performance. It correctly predicted dasatinib sensitivity in 11 out of 12 (92%) breast and 17 out of 23 (74%) lung cancer cell lines. These predictors were then applied to the gene expression data from 133 breast cancer patients in an attempt to predict how the patients might respond to dasatinib therapy. Two predictors identified 13 patients in common to be dasatinib sensitive. Sixty two percent of these cases are triple negative (ER-negative, HER2-negative and PR-negative) and 76% are double negative. The result is consistent with the findings from other studies, which identified a target population for dasatinib treatment to be triple negative or basal breast cancer subtype. In conclusion, we think that the cell line-derived dasatinib classifiers can be applied to the human patients. ^

Hepatitis C and human immunodeficiency virus infections in injecting drug users in drug treatment centers in Vietnam

Background. Injecting drug users (IDUs) are at risk of infection with Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV). Independently, each of these viruses is a serious threat to health, with HIV ravaging the body’s immune system, and HCV causing cirrhosis, liver cancer and liver failure. Co-infection with HIV/HCV weakens the response to antiretroviral therapy in HIV patients. IDUs with HIV/HCV co-infection are at a 20 times higher risk of having liver-related morbidity and mortality than IDUs with HIV alone. In Vietnam, studies to ascertain the prevalence of HIV have found high rates, but little is known about their HCV status. ^ Purpose. To measure the prevalence of HCV and HIV infection and identify factors associated with these viruses among IDUs at drug treatment centers in northern Vietnam. ^ Methods. A cross-sectional study was conducted from November 2007 to February 2008 with 455 injecting drug users aged 18 to 39 years, admitted no more than two months earlier to one of four treatment centers in Northern Vietnam (Hatay Province) (response rate=95%). Participants, all of whom had completed detoxification and provided informed consent, completed a risk assessment questionnaire and had their blood drawn to test for the presence of antibody-HCV and antibody-HIV with enzyme immuno assays. Univariate and multivariable logistic regression models were utilized to explore the strength of association using HIV, HCV infections and HIV/HCV co-infection as outcomes and demographic characteristics, drug use and sexual behaviors as factors associated with these outcomes. Unadjusted and adjusted odds ratios and 95% confidence intervals were calculated. ^ Results. Among all IDU study participants, the prevalence of HCV alone was 76.9%, HIV alone was 19.8%. The prevalence of HIV/HCV co-infection was 92.2% of HIV-positive and 23.7% of HCV-positive respondents. No sexual risk behaviors for lifetime, six months or 30 days prior to admission were significantly associated with HCV or HIV infection among these IDUs. Only duration of injection drug use was independently associated with HCV and HIV infection, respectively. Longer duration was associated with higher prevalence. Nevertheless, while HCV infection among IDUs who reported being in their first year of injecting drugs were lower than longer time injectors, their rates were still substantial, 67.5%. ^ Compared with either HCV mono-infection or HIV/HCV non-infection, HIV/HCV co-infection was associated with the length of drug injection history but was not associated with sexual behaviors. Higher education was associated with a lower prevalence of HIV/HCV co-infection. When compared with HIV/HCV non-infection, current marriage was associated with a lower prevalence of HIV/HCV co-infection. ^ Conclusions. HCV was prevalent among IDUs from 18 to 39 years old at four drug treatment centers in northern Vietnam. Co-infection with HCV was predominant among HIV-positive IDUs. HCV and HIV co-infection were closely associated with the length of injection drug history. Further research regarding HCV/HIV co-infection should include non-injecting drug users to assess the magnitude of sexual risk behaviors on HIV and HCV infection. (At these treatment centers non-IDUs constituted 10-20% of the population.) High prevalence of HCV prevalence among IDUs, especially among HIV-infected IDUs, suggests that drug treatment centers serving IDUs should include not only HIV prevention education but they should also include the prevention of viral hepatitis. In addition, IDUs who are HIV-positive need to be tested for HCV to receive the best course of therapy and achieve the best response to HIV treatment. These data also suggest that because many IDUs get infected with HCV in the first year of their injection drug career, and because they also engaged in high risk sexual behaviors, outreach programs should focus on harm reduction, safer drug use and sexual practices to prevent infection among drug users who have not yet begun injecting drugs and to prevent further spread of HCV, HIV and co-infection. ^

CHEMOSENSITIZATION OF HEPATOCELLULAR CARCINOMA TO GEMCITABINE BY NON-INVASIVE RADIOFREQUENCY FIELD-INDUCED HYPERTHERMIA

Gemcitabine is a potent nucleoside analogue against solid tumors however drug resistance rapidly emerges. Removal of gemcitabine incorporated in the DNA by repair mechanisms could potentially contribute to resistance in chemo-refractory solid tumors. In this study, we evaluated homologous recombination repair of gemcitabine-stalled replication forks as a potential mechanism contributing to resistance. We also studied the effect of hyperthermia on homologous recombination pathway to explain the previously reported synergy between gemcitabine and hyperthermia. We found that hyperthermia degrades and inhibits localization of Mre11 to gemcitabine-stalled replication forks. Furthermore, gemcitabine-treated cells that were also treated with hyperthermia demonstrate a prolonged passage through late S/ G2 phase of cell cycle in comparison to cells treated with gemcitabine alone. This coincides with inhibition of resolution of γH2AX foci. Our findings also demonstrate that thermal sensitization of human hepatocellular carcinoma cell lines to gemcitabine is mediated through an Mre11-dependent homologous recombination repair pathway. Combination of non-invasive radiofrequency field-induced hyperthermia and gemcitabine was superior to either therapy alone (p

A comparison of adherence with minocycline treatment in Parkinson's disease and rheumatoid arthritis clinical trials

Background: Little is known about the effects on patient adherence when the same study drug is administered in the same dose in two populations with two different diseases in two different clinical trials. The Minocycline in Rheumatoid Arthritis (MIRA) trial and the NIH Exploratory Trials in Parkinson's disease (NET-PD) Futility Study I provide a unique opportunity to do the above and to compare methods measuring adherence. This study may increase understanding of the influence of disease and adverse events on patient adherence and will provide insights to investigators selecting adherence assessment methods in clinical trials of minocycline and other drugs in future.^ Methods: Minocycline adherence by pill count and the effect of adverse events was compared in the MIRA and NET-PD FS1 trials using multivariable linear regression. Within the MIRA trial, agreement between assay and pill count was compared. The association of adverse events with assay adherence was examined using multivariable logistic regression.^ Results: Adherence derived from pill count in the MIRA and NET-PD FS1 trials did not differ significantly. Adverse events potentially related to minocycline did not appear useful to predict minocycline adherence. In the MIRA trial, adherence measured by pill count appears higher than adherence measured by assay. Agreement between pill count and assay was poor (kappa statistic = 0.25).^ Limitations: Trial and disease are completely confounded and hence the independent effect of disease on adherence to minocycline treatment cannot be studied.^ Conclusion: Simple pill count may be preferred over assay in the minocycline clinical trials to measure adherence. Assays may be less sensitive in a clinical setting where appointments are not scheduled in relation to medication administration time, given assays depend on many pharmacokinetic and instrument-related factors. However, pill count can be manipulated by the patient. Another study suggested that self-report method is more sensitive than pill count method in differentiating adherence from non-adherence. An effect of medication-related adverse events on adherence could not be detected.^

A machine learning approach to identify clinical trials involving nanodrugs and nanodevices from ClinicalTrials.gov

BACKGROUND: Clinical Trials (CTs) are essential for bridging the gap between experimental research on new drugs and their clinical application. Just like CTs for traditional drugs and biologics have helped accelerate the translation of biomedical findings into medical practice, CTs for nanodrugs and nanodevices could advance novel nanomaterials as agents for diagnosis and therapy. Although there is publicly available information about nanomedicine-related CTs, the online archiving of this information is carried out without adhering to criteria that discriminate between studies involving nanomaterials or nanotechnology-based processes (nano), and CTs that do not involve nanotechnology (non-nano). Finding out whether nanodrugs and nanodevices were involved in a study from CT summaries alone is a challenging task. At the time of writing, CTs archived in the well-known online registry ClinicalTrials.gov are not easily told apart as to whether they are nano or non-nano CTs-even when performed by domain experts, due to the lack of both a common definition for nanotechnology and of standards for reporting nanomedical experiments and results. METHODS: We propose a supervised learning approach for classifying CT summaries from ClinicalTrials.gov according to whether they fall into the nano or the non-nano categories. Our method involves several stages: i) extraction and manual annotation of CTs as nano vs. non-nano, ii) pre-processing and automatic classification, and iii) performance evaluation using several state-of-the-art classifiers under different transformations of the original dataset. RESULTS AND CONCLUSIONS: The performance of the best automated classifier closely matches that of experts (AUC over 0.95), suggesting that it is feasible to automatically detect the presence of nanotechnology products in CT summaries with a high degree of accuracy. This can significantly speed up the process of finding whether reports on ClinicalTrials.gov might be relevant to a particular nanoparticle or nanodevice, which is essential to discover any precedents for nanotoxicity events or advantages for targeted drug therapy.

A technological framework based on automatic messaging for improving adherence of diabetic patients

En todo el mundo se ha observado un crecimiento exponencial en la incidencia de enfermedades crónicas como la hipertensión y enfermedades cardiovasculares y respiratorias, así como la diabetes mellitus, que causa un número de muertes cada vez mayor en todo el mundo (Beaglehole et al., 2008). En concreto, la prevalencia de diabetes mellitus (DM) está aumentando de manera considerable en todas las edades y representa un serio problema de salud mundial. La diabetes fue la responsable directa de 1,5 millones de muertes en 2012 y 89 millones de años de vida ajustados por discapacidad (AVAD) (OMS, 2014). Uno de los principales dilemas que suelen asociarse a la gestión de EC es la adherencia de los pacientes a los tratamientos, que representa un aspecto multifactorial que necesita asistencia en lo relativo a: educación, autogestión, interacción entre los pacientes y cuidadores y compromiso de los pacientes. Medir la adherencia del tratamiento es complicado y, aunque se ha hablado ampliamente de ello, aún no hay soluciones “de oro” (Reviews, 2002). El compromiso de los pacientes, a través de la participación, colaboración, negociación y a veces del compromiso firme, aumentan las oportunidades para una terapia óptima en la que los pacientes se responsabilizan de su parte en la ecuación de adherencia. Comprometer e involucrar a los pacientes diabéticos en las decisiones de su tratamiento, junto con expertos profesionales, puede ayudar a favorecer un enfoque centrado en el paciente hacia la atención a la diabetes (Martin et al., 2005). La motivación y atribución de poder de los pacientes son quizás los dos factores interventores más relevantes que afectan directamente a la autogestión de la atención a la diabetes. Se ha demostrado que estos dos factores desempeñan un papel fundamental en la adherencia a la prescripción, así como en el fomento exitoso de un estilo de vida sana y otros cambios de conducta (Heneghan et al., 2013). Un plan de educación personalizada es indispensable para proporcionarle al paciente las herramientas adecuadas que necesita para la autogestión efectiva de la enfermedad (El-Gayar et al. 2013). La comunicación efectiva es fundamental para proporcionar una atención centrada en el paciente puesto que influye en las conductas y actitudes hacia un problema de salud ((Frampton et al. 2008). En este sentido, la interactividad, la frecuencia, la temporalización y la adaptación de los mensajes de texto pueden promover la adherencia a un régimen de medicación. Como consecuencia, adaptar los mensajes de texto a los pacientes puede resultar ser una manera de hacer que las sugerencias y la información sean más relevantes y efectivas (Nundy et al. 2013). En este contexto, las tecnologías móviles en el ámbito de la salud (mHealth) están desempeñando un papel importante al conectar con pacientes para mejorar la adherencia a medicamentos recetados (Krishna et al., 2009). La adaptación de los mensajes de texto específicos de diabetes sigue siendo un área de oportunidad para mejorar la adherencia a la medicación y ofrecer motivación a adultos con diabetes. Sin embargo, se necesita más investigación para entender totalmente su eficacia. Los consejos de texto personalizados han demostrado causar un impacto positivo en la atribución de poder a los pacientes, su autogestión y su adherencia a la prescripción (Gatwood et al., 2014). mHealth se puede utilizar para ofrecer programas de asistencia de autogestión a los pacientes con diabetes y, al mismo tiempo, superar las dificultades técnicas y financieras que supone el tratamiento de la diabetes (Free at al., 2013). El objetivo principal de este trabajo de investigación es demostrar que un marco tecnológico basado en las teorías de cambios de conducta, aplicado al campo de la mHealth, permite una mejora de la adherencia al tratamiento en pacientes diabéticos. Como método de definición de una solución tecnológica, se han adoptado un conjunto de diferentes técnicas de conducta validadas denominado marco de compromiso de retroacción conductual (EBF, por sus siglas en inglés) para formular los mensajes, guiar el contenido y evaluar los resultados. Los estudios incorporan elementos del modelo transteórico (TTM, por sus siglas en inglés), la teoría de la fijación de objetivos (GST, por sus siglas en inglés) y los principios de comunicación sanitaria persuasiva y eficaz. Como concepto general, el modelo TTM ayuda a los pacientes a progresar a su próxima fase de conducta a través de mensajes de texto motivados específicos y permite que el médico identifique la fase actual y adapte sus estrategias individualmente. Además, se adoptan las directrices del TTM para fijar objetivos personalizados a un nivel apropiado a la fase de cambio del paciente. La GST encierra normas que van a ponerse en práctica para promover la intervención educativa y objetivos de pérdida de peso. Finalmente, los principios de comunicación sanitaria persuasiva y eficaz aplicados a la aparición de los mensajes se han puesto en marcha para aumentar la efectividad. El EBF tiene como objetivo ayudar a los pacientes a mejorar su adherencia a la prescripción y encaminarlos a una mejora general en la autogestión de la diabetes mediante mensajes de texto personalizados denominados mensajes de retroacción automáticos (AFM, por sus siglas en inglés). Después de una primera revisión del perfil, consistente en identificar características significativas del paciente basadas en las necesidades de tratamiento, actitudes y conductas de atención sanitaria, el sistema elige los AFM personalizados, los aprueba el médico y al final se transfieren a la interfaz del paciente. Durante el tratamiento, el usuario recopila los datos en dispositivos de monitorización de pacientes (PMD, por sus siglas en inglés) de una serie de dispositivos médicos y registros manuales. Los registros consisten en la toma de medicación, dieta y actividad física y tareas de aprendizaje y control de la medida del metabolismo. El compromiso general del paciente se comprueba al estimar el uso del sistema y la adherencia del tratamiento y el estado de los objetivos del paciente a corto y largo plazo. El módulo de análisis conductual, que consiste en una serie de reglas y ecuaciones, calcula la conducta del paciente. Tras lograr el análisis conductual, el módulo de gestión de AFM actualiza la lista de AFM y la configuración de los envíos. Las actualizaciones incluyen el número, el tipo y la frecuencia de mensajes. Los AFM los revisa periódicamente el médico que también participa en el perfeccionamiento del tratamiento, adaptado a la fase transteórica actual. Los AFM se segmentan en distintas categorías y niveles y los pacientes pueden ajustar la entrega del mensaje de acuerdo con sus necesidades personales. El EBF se ha puesto en marcha integrado dentro del sistema METABO, diseñado para facilitar al paciente diabético que controle sus condiciones relevantes de una manera menos intrusiva. El dispositivo del paciente se vincula en una plataforma móvil, mientras que una interfaz de panel médico permite que los profesionales controlen la evolución del tratamiento. Herramientas específicas posibilitan que los profesionales comprueben la adherencia del paciente y actualicen la gestión de envíos de AFM. El EBF fue probado en un proyecto piloto controlado de manera aleatoria. El principal objetivo era examinar la viabilidad y aceptación del sistema. Los objetivos secundarios eran también la evaluación de la eficacia del sistema en lo referente a la mejora de la adherencia, el control glucémico y la calidad de vida. Se reclutaron participantes de cuatro centros clínicos distintos en Europa. La evaluación del punto de referencia incluía datos demográficos, estado de la diabetes, información del perfil, conocimiento de la diabetes en general, uso de las plataformas TIC, opinión y experiencia con dispositivos electrónicos y adopción de buenas prácticas con la diabetes. La aceptación y eficacia de los criterios de evaluación se aplicaron para valorar el funcionamiento del marco tecnológico. El principal objetivo era la valoración de la eficacia del sistema en lo referente a la mejora de la adherencia. En las pruebas participaron 54 pacientes. 26 fueron asignados al grupo de intervención y equipados con tecnología móvil donde estaba instalado el EBF: 14 pacientes tenían T1DM y 12 tenían T2DM. El grupo de control estaba compuesto por 25 pa cientes que fueron tratados con atención estándar, sin el empleo del EBF. La intervención profesional tanto de los grupos de control como de intervención corrió a cargo de 24 cuidadores, entre los que incluían diabetólogos, nutricionistas y enfermeras. Para evaluar la aceptabilidad del sistema y analizar la satisfacción de los usuarios, a través de LimeSurvey, se creó una encuesta multilingüe tanto para los pacientes como para los profesionales. Los resultados también se recopilaron de los archivos de registro generados en los PMD, el panel médico profesional y las entradas de la base de datos. Los mensajes enviados hacia y desde el EBF y los archivos de registro del sistema y los servicios de comunicación se grabaron durante las cinco semanas del estudio. Se entregaron un total de 2795 mensajes, lo que supuso una media de 107,50 mensajes por paciente. Como se muestra, los mensajes disminuyen con el tiempo, indicando una mejora global de la adherencia al plan de tratamiento. Como se esperaba, los pacientes con T1DM recibieron más consejos a corto plazo, en relación a su estado. Del mismo modo, al ser el centro de T2DM en cambios de estilo de vida sostenible a largo plazo, los pacientes con T2DM recibieron más consejos de recomendación, en cuanto a dietas y actividad física. También se ha llevado a cabo una comparación de la adherencia e índices de uso para pacientes con T1DM y T2DM, entre la primera y la segunda mitad de la prueba. Se han observado resultados favorables para el uso. En lo relativo a la adherencia, los resultados denotaron una mejora general en cada dimensión del plan de tratamiento, como la nutrición y las mediciones de inserción de glucosa en la sangre. Se han llevado a cabo más estudios acerca del cambio a nivel educativo antes y después de la prueba, medidos tanto para grupos de control como de intervención. Los resultados indicaron que el grupo de intervención había mejorado su nivel de conocimientos mientras que el grupo de control mostró una leve disminución. El análisis de correlación entre el nivel de adherencia y las AFM ha mostrado una mejora en la adherencia de uso para los pacientes que recibieron los mensajes de tipo alertas, y unos resultados no significativos aunque positivos relacionados con la adherencia tanto al tratamiento que al uso correlacionado con los recordatorios. Por otra parte, los AFM parecían ayudar a los pacientes que no tomaban suficientemente en serio su tratamiento en el principio y que sí estaban dispuestos a responder a los mensajes recibidos. Aun así, los pacientes que recibieron demasiadas advertencias, comenzaron a considerar el envío de mensajes un poco estresante. El trabajo de investigación llevado a cabo al desarrollar este proyecto ofrece respuestas a las cuatro hipótesis de investigación que fueron la motivación para el trabajo. • Hipótesis 1 : es posible definir una serie de criterios para medir la adherencia en pacientes diabéticos. • Hipótesis 2: es posible diseñar un marco tecnológico basado en los criterios y teorías de cambio de conducta mencionados con anterioridad para hacer que los pacientes diabéticos se comprometan a controlar su enfermedad y adherirse a planes de atención. • Hipótesis 3: es posible poner en marcha el marco tecnológico en el sector de la salud móvil. • Hipótesis 4: es posible utilizar el marco tecnológico como solución de salud móvil en un contexto real y tener efectos positivos en lo referente a indicadores de control de diabetes. La verificación de cada hipótesis permite ofrecer respuesta a la hipótesis principal: La hipótesis principal es: es posible mejorar la adherencia diabética a través de un marco tecnológico mHealth basado en teorías de cambio de conducta. El trabajo llevado a cabo para responder estas preguntas se explica en este trabajo de investigación. El marco fue desarrollado y puesto en práctica en el Proyecto METABO. METABO es un Proyecto I+D, cofinanciado por la Comisión Europea (METABO 2008) que integra infraestructura móvil para ayudar al control, gestión y tratamiento de los pacientes con diabetes mellitus de tipo 1 (T1DM) y los que padecen diabetes mellitus de tipo 2 (T2DM). ABSTRACT Worldwide there is an exponential growth in the incidence of Chronic Diseases (CDs), such as: hypertension, cardiovascular and respiratory diseases, as well as diabetes mellitus, leading to rising numbers of deaths worldwide (Beaglehole et al. 2008). In particular, the prevalence of diabetes mellitus (DM) is largely increasing among all ages and constitutes a major worldwide health problem. Diabetes was directly responsible for 1,5 million deaths in 2012 and 89 million Disability-adjusted life year (DALYs) (WHO 2014). One of the key dilemmas often associated to CD management is the patients’ adherence to treatments, representing a multi-factorial aspect that requires support in terms of: education, self-management, interaction between patients and caregivers, and patients’ engagement. Measuring adherence is complex and, even if widely discussed, there are still no “gold” standards ((Giardini et al. 2015), (Costa et al. 2015). Patient’s engagement, through participation, collaboration, negotiation, and sometimes compromise, enhance opportunities for optimal therapy in which patients take responsibility for their part of the adherence equation. Engaging and involving diabetic patients in treatment decisions, along with professional expertise, can help foster a patient-centered approach to diabetes care (Martin et al. 2005). Patients’ motivation and empowerment are perhaps the two most relevant intervening factors that directly affect self-management of diabetes care. It has been demonstrated that these two factors play an essential role in prescription adherence, as well as for the successful encouragement of a healthy life-style and other behavioural changes (Heneghan et al. 2013). A personalised education plan is indispensable in order to provide the patient with the appropriate tools needed for the effective self-management of the disease (El-Gayar et al. 2013). Effective communication is at the core of providing patient-centred care since it influences behaviours and attitudes towards a health problem (Frampton et al. 2008). In this regard, interactivity, frequency, timing, and tailoring of text messages may promote adherence to a medication regimen. As a consequence, tailoring text messages to patients can constitute a way of making suggestions and information more relevant and effective (Nundy et al. 2013). In this context, mobile health technologies (mHealth) are playing significant roles in improving adherence to prescribed medications (Krishna et al. 2009). The tailoring of diabetes-specific text messages remains an area of opportunity to improve medication adherence and provide motivation to adults with diabetes but further research is needed to fully understand their effectiveness. Personalized text advices have proven to produce a positive impact on patients’ empowerment, self-management, and adherence to prescriptions (Gatwood et al. 2014). mHealth can be used for offering self-management support programs to diabetes patients and at the same time surmounting the technical and financial difficulties involved in diabetes treatment (Free et al. 2013). The main objective of this research work is to demonstrate that a technological framework, based on behavioural change theories, applied to mHealth domain, allows improving adherence treatment in diabetic patients. The framework, named Engagement Behavioural Feedback Framework (EBF), is built on top of validated behavioural techniques to frame messages, guide the definition of contents and assess outcomes: elements from the Transtheoretical Model (TTM), the Goal-Setting Theory (GST), Effective Health Communication (EHC) guidelines and Principles of Persuasive Technology (PPT) were incorporated. The TTM helps patients to progress to a next behavioural stage, through specific motivated text messages, and allow clinician’s identifying the current stage and tailor its strategies individually. Moreover, TTM guidelines are adopted to set customised goals at a level appropriate to the patient’s stage of change. The GST was used to build rules to be applied for enhancing educational intervention and weight loss objectives. Finally, the EHC guidelines and the PPT were applied to increase the effectiveness of messages. The EBF aims to support patients on improving their prescription adherence and persuade them towards a general improvement in diabetes self-management, by means of personalised text messages, named Automatic Feedback Messages (AFM). After a first profile screening, consisting in identifying meaningful patient characteristics based on treatment needs, attitudes and health care behaviours, customised AFMs are selected by the system, approved by the professional, and finally transferred into the patient interface. During the treatment, the user collects the data into a Patient Monitoring Device (PMD) from a set of medical devices and from manual inputs. Inputs consist in medication intake, diet and physical activity, metabolic measurement monitoring and learning tasks. Patient general engagement is checked by estimating the usage of the system and the adherence of treatment and patient goals status in the short and the long term period. The Behavioural Analysis Module, consisting in a set of rules and equations, calculates the patient’s behaviour. After behavioural analysis is accomplished, the AFM library and the dispatch setting are updated by the AFM Manager module. Updates include the number, the type and the frequency of messages. The AFMs are periodically supervised by the professional who also participates to the refinement of the treatment, adapted to the current transtheoretical stage. The AFMs are segmented in different categories and levels and patients can adjust message delivery in accordance with their personal needs. The EBF was integrated to the METABO system, designed to facilitate diabetic patients in managing their disease in a less intrusive approach. Patient device corresponds in a mobile platform, while a medical panel interface allows professionals to monitoring the treatment evolution. Specific tools allow professional to check patient adherence and to update the AFMs dispatch management. The EBF was tested in a randomised controlled pilot. The main objective was to examine the feasibility and acceptance of the system. Secondary objectives were also the assessment of the effectiveness of system in terms of adherence improvement, glycaemic control, and quality of life. Participants were recruited from four different clinical centres in Europe. The baseline assessment included demographics, diabetes status, profile information, knowledge about diabetes in general, usage of ICT platforms, opinion and experience about electronic devices and adoption of good practices with diabetes. Acceptance and the effectiveness evaluation criteria were applied to evaluate the performance of the technological framework. The main objective was the assessment of the effectiveness of system in terms of adherence improvement. Fifty-four patients participated on the trials. Twenty-six patients were assigned in the intervention group and equipped with mobile where the EBF was installed: 14 patients were T1DM and 12 were T2DM. The control group was composed of 25 patients that were treated through a standard care, without the usage of the EBF. Professional’s intervention for both intervention and control groups was carried out by 24 care providers, including endocrinologists, nutritionists, and nurses. In order to evaluate the system acceptability and analyse the users’ satisfaction, an online multi-language survey, using LimeSurvey, was produced for both patients and professionals. Results were also collected from the log-files generated in the PMDs, the professional medical panel and the entries of the data base. The messages sent to and from the EBF and the log-files of the system and communication services were recorded over 5 weeks of the study. A total of 2795 messages were submitted, representing an average of 107,50 messages per patient. As demonstrated, messages decrease over time indicating an overall improvement of the care plan’s adherence. As expected, T1DM patients were more loaded with short-term advices, in accordance with their condition. Similarly, being the focus of T2DM on long-term sustainable lifestyle changes, T2DM received more reminders advices, as for diet and physical activity. Favourable outcomes were observed for treatment and usage adherences of the intervention group: for both the adherence indices, results denoted a general improvement on each care plan’s dimension, such as on nutrition and blood glucose input measurements. Further studies were conducted on the change on educational level before and after the trial, measured for both control and intervention groups. The outcomes indicated the intervention group has improved its level of knowledge, while the control group denoted a low decrease. The correlation analysis between the level of adherences and the AFMs showed an improvement in usage adherence for patients who received warnings message, while non-significantly yet even positive indicators related to both treatment and usage adherence correlated with the Reminders. Moreover, the AFMs seemed to help those patients who did not take their treatment seriously enough in the beginning and who were willing to respond to the messages they received. Even though, patients who received too many Warnings, started to consider the message dispatch to be a bit stressful. The research work carried out in developing this research work provides responses to the four research hypothesis that were the motivation for the work: •Hypothesis 1: It is possible to define a set of criteria to measure adherence in diabetic patients. •Hypothesis 2: It is possible to design a technological framework, based on the aforementioned criteria and behavioural change theories, to engage diabetic patients in managing their disease and adhere to care plans. •Hypothesis 3: It is possible to implement the technological framework in the mobile health domain. •Hypothesis 4: It is possible to use the technological framework as a mobile health solution in a real context and have positive effects in terms of diabetes management indicators. The verification of each hypothesis allowed us to provide a response to the main hypothesis: The Main Hypothesis is: It is possible to improve diabetic adherence through a mHealth technological framework based on behavioural change theories. The work carried out to answer these questions is explained in this research work. The framework was developed and applied in the METABO project. METABO is an R&D project, co-funded by the European Commission (METABO 2008) that integrates mobile infrastructure for supporting the monitoring, management, and treatment of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients.

HIV-1 and T cell dynamics after interruption of highly active antiretroviral therapy (HAART) in patients with a history of sustained viral suppression

Identifying the immunologic and virologic consequences of discontinuing antiretroviral therapy in HIV-infected patients is of major importance in developing long-term treatment strategies for patients with HIV-1 infection. We designed a trial to characterize these parameters after interruption of highly active antiretroviral therapy (HAART) in patients who had maintained prolonged viral suppression on antiretroviral drugs. Eighteen patients with CD4+ T cell counts ≥ 350 cells/μl and viral load below the limits of detection for ≥1 year while on HAART were enrolled prospectively in a trial in which HAART was discontinued. Twelve of these patients had received prior IL-2 therapy and had low frequencies of resting, latently infected CD4 cells. Viral load relapse to >50 copies/ml occurred in all 18 patients independent of prior IL-2 treatment, beginning most commonly during weeks 2–3 after cessation of HAART. The mean relapse rate constant was 0.45 (0.20 log10 copies) day−1, which was very similar to the mean viral clearance rate constant after drug resumption of 0.35 (0.15 log10 copies) day−1 (P = 0.28). One patient experienced a relapse delay to week 7. All patients except one experienced a relapse burden to >5,000 RNA copies/ml. Ex vivo labeling with BrdUrd showed that CD4 and CD8 cell turnover increased after withdrawal of HAART and correlated with viral load whereas lymphocyte turnover decreased after reinitiation of drug treatment. Virologic relapse occurs rapidly in patients who discontinue suppressive drug therapy, even in patients with a markedly diminished pool of resting, latently infected CD4+ T cells.

Documents pertaining to the medicinal supplies within the North American colonies from 1643 to 1780,

Contains a reissue of four numbers (April 1937, June-Dec. 1938, Feb. 1939 and Dec. 1940) of the author's journal, the Badger pharmacist. Each number includes a reprint of the document discussed.

Can primaquine therapy for vivax malaria be improved?

The incidence and range of endemic malaria caused by Plasmodium vivax has expanded during the past 30 years. This parasite forms hypnozoites in the liver, creating a persistent reservoir of infection. Primaquine (PQ), introduced 50 years ago, is the only drug available to eliminate hypnozoites. However, lengthy treatment courses and follow-up periods are not conducive to assessing the effectiveness of this drug in preventing relapses. Resistance to standard therapy could be widespread. Studies are urgently needed to gauge this problem and to determine the safety, tolerability and efficacy of shorter courses and higher doses of PQ.

Audit of consultant physicians' reply letters for referrals to clinics in a tertiary teaching hospital

Background: Doctors referring patients to consultant physicians seek reply letters which both educate and assist in ongoing patient management. Highly desirable attributes in specialist letters include clearly stated and justified: (i) diagnostic formulations, (ii) management regimens, (iii) use of clinical investigations, (iv) prog-nostic statements, (v) contingency plans and (vi) follow-up arrangements. Aim: To explicitly evaluate the quality of reply letters for new patients referred to clinics at a tertiary teaching hospital. Methods: Letters were sampled from outpatient clinics of 10 different medical specialties at Princess Alexandra Hospital in Brisbane, Australia. Reply letters for new patient referrals between 1 August 2000 and 31 October 2000 were retrieved, from which data were abstracted to calculate the proportion of letters satisfying prespecified quality attributes. Results: Of 297 new patient referrals, reply letters were retrieved for 204 (69%). Of these, 147 (72%) referrals were accompanied by a referral letter, mostly (113/147; 77%) from general practitioners. For 120 referrals involving diagnostic issues, 69 (56%) letters stated a diagnostic formulation. Of 114 letters recommending further clinical investigations, 61 (53%) described a rationale for such testing. In 125 cases where therapy was a key issue, 83 (66%) letters recommended changes to current treatment for which reasons were specified in 46 (55%) cases, and contingency plans provided in 13 (16%). Prognosis was mentioned in only 18 (9%) cases. Follow-up arrangements were detailed in 123 (60%) letters. Assessments of patient understanding and likely adherence to therapy were stated in less than 15% of -letters. Conclusions: Opportunities exist for improving quality of consultant physicians' reply letters in terms of greater use of problem lists, contingency plans, prognostic statements and patient-centred assessments, as well as more frequent enunciation of consultants' reasoning behind requests for further tests and changes to current management. Use of structured letter templates may facilitate more consistent inclusion of key information to referring doctors.

What is the best size descriptor to use for pharmacokinetic studies in the obese?

The prevalence of obesity in the western world is dramatically rising, with many of these individuals requiring therapeutic intervention for a variety of disease states. Despite the growing prevalence of obesity there is a paucity of information describing how doses should be adjusted, or indeed whether they need to be adjusted, in the clinical setting. This review is aimed at identifying which descriptors of body size provide the most information about the relationship between dose and concentration in the obese. The size descriptors, weight, lean body weight, ideal body weight, body surface area, body mass index, fat-free mass, percent ideal body weight, adjusted body weight and predicted normal body weight were considered as potential size descriptors. We conducted an extensive review of the literature to identify studies that have assessed the quantitative relationship between the parameters clearance (CL) and volume of distribution (V) and these descriptors of body size. Surprisingly few studies have addressed the relationship between obesity and CL or V in a quantitative manner. Despite the lack of studies there were consistent findings: (i) most studies found total body weight to be the best descriptor of V. A further analysis of the studies that have addressed V found that total body weight or another descriptor that incorporated fat mass was the preferred descriptor for drugs that have high lipophilicity; (ii) in contrast, CL was best described by lean body mass and no apparent relationship between lipophilicity or clearance mechanism and preference for body size descriptor was found. In conclusion, no single descriptor described the influence of body size on both CL and V equally well. For drugs that are dosed chronically, and therefore CL is of primary concern, dosing for obese patients should not be based on their total weight. If a weight-based dose individualization is required then we would suggest that chronic drug dosing in the obese subject should be based on lean body weight, at least until a more robust size descriptor becomes available.