Telehealth system (e-CUIDATE) to improve quality of life in breast cancer survivors: rationale and study protocol for a randomized clinical trial.

BACKGROUND Breast cancer survivors suffer physical impairment after oncology treatment. This impairment reduces quality of life (QoL) and increase the prevalence of handicaps associated to unhealthy lifestyle (for example, decreased aerobic capacity and strength, weight gain, and fatigue). Recent work has shown that exercise adapted to individual characteristics of patients is related to improved overall and disease-free survival. Nowadays, technological support using telerehabilitation systems is a promising strategy with great advantage of a quick and efficient contact with the health professional. It is not known the role of telerehabilitation through therapeutic exercise as a support tool to implement an active lifestyle which has been shown as an effective resource to improve fitness and reduce musculoskeletal disorders of these women. METHODS / DESIGN This study will use a two-arm, assessor blinded, parallel randomized controlled trial design. People will be eligible if: their diagnosis is of stages I, II, or IIIA breast cancer; they are without chronic disease or orthopedic issues that would interfere with ability to participate in a physical activity program; they had access to the Internet and basic knowledge of computer use or living with a relative who has this knowledge; they had completed adjuvant therapy except for hormone therapy and not have a history of cancer recurrence; and they have an interest in improving lifestyle. Participants will be randomized into e-CUIDATE or usual care groups. E-CUIDATE give participants access to a range of contents: planning exercise arranged in series with breathing exercises, mobility, strength, and stretching. All of these exercises will be assigned to women in the telerehabilitation group according to perceived needs. The control group will be asked to maintain their usual routine. Study endpoints will be assessed after 8 weeks (immediate effects) and after 6 months. The primary outcome will be QoL measured by The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 version 3.0 and breast module called The European Organization for Research and Treatment of Cancer Breast Cancer-Specific Quality of Life questionnaire. The secondary outcomes: pain (algometry, Visual Analogue Scale, Brief Pain Inventory short form); body composition; physical measurement (abdominal test, handgrip strength, back muscle strength, and multiple sit-to-stand test); cardiorespiratory fitness (International Fitness Scale, 6-minute walk test, International Physical Activity Questionnaire-Short Form); fatigue (Piper Fatigue Scale and Borg Fatigue Scale); anxiety and depression (Hospital Anxiety and Depression Scale); cognitive function (Trail Making Test and Auditory Consonant Trigram); accelerometry; lymphedema; and anthropometric perimeters. DISCUSSION This study investigates the feasibility and effectiveness of a telerehabilitation system during adjuvant treatment of patients with breast cancer. If this treatment option is effective, telehealth systems could offer a choice of supportive care to cancer patients during the survivorship phase. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01801527.

Expert study: A bolus calculator improves glycemic control and quality of life of type 1 diabetic patients (T1DM) (preliminary results)

Aims: To evaluate the impact on glycemic control and quality of life of a bolus calculator. Methods: Multicentre randomized prospective crosssectional study. Patients were randomized to control phase (3 months; calculation of prandial insulin according to insulinto-carbohydrate ratio and insulin sensitivity factor using a single strip meter) or intervention phase (3 months; calculation of prandial insulin with a bolus advisor), with a washout period (3 months). Patients wore a continuous glucosensor (7 days) and answered a quality of life questionnaire at the beginning and at the end of each phase. A questionnaire of satisfaction was obtained at the end of both phases. Inclusion criteria: Adults; T1DM> 1 year, HbA1c > 7.5%, basal-bolus therapy with insulin analogs, experience with carbohydrate Results: Data from the first 32 subjects with at least 1 ended phase (27 females, age 38 – 11 years, diabetes duration 16.8 – 7.5 years). Basal characteristics were comparable independently of the starting phase. No differences were found between phases in terms of mean blood glucose, standard deviation (from meter neither from sensor) and satisfaction. Conclusions: The use of a bolus calculator improves glycemic control and quality of life of T1DM subjects.

Evaluation of quality improvement for cesarean sections caesarean section programmes through mixed methods.

BACKGROUND The rate of avoidable caesarean sections (CS) could be reduced through multifaceted strategies focusing on the involvement of health professionals and compliance with clinical practice guidelines (CPGs). Quality improvements for CS (QICS) programmes (QICS) based on this approach, have been implemented in Canada and Spain. OBJECTIVES Their objectives are as follows: 1) Toto identify clusters in each setting with similar results in terms of cost-consequences, 2) Toto investigate whether demographic, clinical or context characteristics can distinguish these clusters, and 3) Toto explore the implementation of QICS in the 2 regions, in order to identify factors that have been facilitators in changing practices and reducing the use of obstetric intervention, as well as the challenges faced by hospitals in implementing the recommendations. METHODS Descriptive study with a quantitative and qualitative approach. 1) Cluster analysis at patient level with data from 16 hospitals in Quebec (Canada) (n = 105,348) and 15 hospitals in Andalusia (Spain) (n = 64,760). The outcome measures are CS and costs. For the cost, we will consider the intervention, delivery and complications in mother and baby, from the hospital perspective. Cluster analysis will be used to identify participants with similar patterns of CS and costs based, and t tests will be used to evaluate if the clusters differed in terms of characteristics: Hospital level (academic status of hospital, level of care, supply and demand factors), patient level (mother age, parity, gestational age, previous CS, previous pathology, presentation of the baby, baby birth weight). 2) Analysis of in-depth interviews with obstetricians and midwives in hospitals where the QICS were implemented, to explore the differences in delivery-related practices, and the importance of the different constructs for positive or negative adherence to CPGs. Dimensions: political/management level, hospital level, health professionals, mothers and their birth partner. DISCUSSION This work sets out a new approach for programme evaluation, using different techniques to make it possible to take into account the specific context where the programmes were implemented.

Circulating prolactin and in situ breast cancer risk in the European EPIC cohort: a case-control study.

INTRODUCTION The relationship between circulating prolactin and invasive breast cancer has been investigated previously, but the association between prolactin levels and in situ breast cancer risk has received less attention. METHODS We analysed the relationship between pre-diagnostic prolactin levels and the risk of in situ breast cancer overall, and by menopausal status and use of postmenopausal hormone therapy (HT) at blood donation. Conditional logistic regression was used to assess this association in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, including 307 in situ breast cancer cases and their matched control subjects. RESULTS We found a significant positive association between higher circulating prolactin levels and risk of in situ breast cancer among all women [pre-and postmenopausal combined, ORlog2 = 1.35 (95%CI 1.04-1.76), Ptrend = 0.03]. No statistically significant heterogeneity was found between prolactin levels and in situ cancer risk by menopausal status (Phet = 0.98) or baseline HT use (Phet = 0.20), although the observed association was more pronounced among postmenopausal women using HT compared to non-users (Ptrend = 0.06 vs Ptrend = 0.35). In subgroup analyses, the observed positive association was strongest in women diagnosed with in situ breast tumors <4 years compared to ≥4 years after blood donation (Ptrend = 0.01 vs Ptrend = 0.63; Phet = 0.04) and among nulliparous women compared to parous women (Ptrend = 0.03 vs Ptrend = 0.15; Phet = 0.07). CONCLUSIONS Our data extends prior research linking prolactin and invasive breast cancer to the outcome of in situ breast tumours and shows that higher circulating prolactin is associated with increased risk of in situ breast cancer.

Oral and general health-related quality of life in patients treated for oral cancer compared to control group.

BACKGROUND Health-related quality of life (HRQoL) is gaining importance as a valuable outcome measure in oral cancer area. The aim of this study was to assess the general and oral HRQoL of oral and oropharyngeal cancer patients 6 or more months after treatment and compare them with a population free from this disease. METHODS A cross-sectional study was carried out with patients treated for oral cancer at least 6 months post-treatment and a gender and age group matched control group. HRQoL was measured with the 12-Item Short Form Health Survey (SF-12); oral HRQoL (OHRQoL) was evaluated using the Oral Health Impact Profile (OHIP-14) and the Oral Impacts on Daily Performances (OIDP). Multivariable regression models assessed the association between the outcomes (SF-12, OHIP-14 and OIDP) and the exposure (patients versus controls), adjusting for sex, age, social class, functional tooth units and presence of illness. RESULTS For patients (n = 142) and controls (n = 142), 64.1% were males. The mean age was 65.2 (standard deviation (sd): 12.9) years in patients and 67.5 (sd: 13.7) years in controls. Patients had worse SF-12 Physical Component Summary scores than controls even in fully the adjusted model [β-coefficient = -0.11 (95% CI: -5.12-(-0.16)]. The differences in SF-12 Mental Component Summary were not statistically significant. Regarding OHRQoL patients had 11.63 (95% CI: 6.77-20.01) higher odds for the OHIP-14 and 21.26 (95% CI: 11.54-39.13) higher odds for OIDP of being in a worse category of OHRQoL compared to controls in the fully adjusted model. CONCLUSION At least 6 months after treatment, oral cancer patients had worse OHRQoL, worse physical HRQoL and similar psychological HRQoL than the general population.

Lack of correlation between the optimal glycaemic control and coronary micro vascular dysfunction in patients with diabetes mellitus: a cross sectional study.

Background Coronary microvascular dysfunction (CMD) is associated with cardiovascular events in type 2 diabetes mellitus (T2DM). Optimal glycaemic control does not always preclude future events. We sought to assess the effect of the current target of HBA1c level on the coronary microcirculatory function and identify predictive factors for CMD in T2DM patients. Methods We studied 100 patients with T2DM and 214 patients without T2DM. All of them with a history of chest pain, non-obstructive angiograms and a direct assessment of coronary blood flow increase in response to adenosine and acetylcholine coronary infusion, for evaluation of endothelial independent and dependent CMD. Patients with T2DM were categorized as having optimal (HbA1c < 7 %) vs. suboptimal (HbA1c ≥ 7 %) glycaemic control at the time of catheterization. Results Baseline characteristics and coronary endothelial function parameters differed significantly between T2DM patients and control group. The prevalence of endothelial independent CMD (29.8 vs. 39.6 %, p = 0.40) and dependent CMD (61.7 vs. 62.2 %, p = 1.00) were similar in patients with optimal vs. suboptimal glycaemic control. Age (OR 1.10; CI 95 % 1.04–1.18; p < 0.001) and female gender (OR 3.87; CI 95 % 1.45–11.4; p < 0.01) were significantly associated with endothelial independent CMD whereas glomerular filtrate (OR 0.97; CI 95 % 0.95–0.99; p < 0.05) was significantly associated with endothelial dependent CMD. The optimal glycaemic control was not associated with endothelial independent (OR 0.60, CI 95 % 0.23–1.46; p 0.26) or dependent CMD (OR 0.99, CI 95 % 0.43–2.24; p = 0.98). Conclusions The current target of HBA1c level does not predict a better coronary microcirculatory function in T2DM patients. The appropriate strategy for prevention of CMD in T2DM patients remains to be addressed. Keywords: Endothelial dysfunction; Diabetes mellitus; Coronary microcirculation

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.