Development and validation of a risk score predicting substantial weight gain over 5 years in middle-aged European men and women.

BACKGROUND Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population. METHODS We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥ 10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample). RESULTS Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥ 200 points were 9% and 96%, respectively. CONCLUSION The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

Development of a new tool for assessing health-related quality of life in patients with primary hyperparathyroidism.

BACKGROUND Several studies in recent years have evaluated Health Related Quality of Life (HRQoL) of patients with primary hyperparathyroidism (PHPT). No disease specific questionnaires are available to assess the impact of the disease. The aim of this research is to describe the development of a new disease specific Quality of Life (QoL) questionnaire for use specifically with PHPT patients. METHODS A conceptual model was developed describing the impact of the disease and its symptoms on QoL domains. A literature review was conducted to identify the most relevant domains. A focus group with experts was used to validate the domains; 24 patients were also interviewed to complement the information from the patient's perspective. A content analysis of the interviews was performed to identify items related with the impact of the disease, leading to PHPQoL-V.1 which was presented to a sample of 67 patients. Reliability was assessed by Cronbach's coefficient alpha and item-total score correlations. Validity was assessed by a factor analysis performed to determine the number of domains. Rasch analysis was carried out in order to refine the questionnaire items. RESULTS 259 items were extracted from the interviews that were subsequently reduced to 34 items. Cronbach's coefficient alpha was 0.92. The factor analysis extracted two domains (physical and emotional). After Rasch analysis the questionnaire PHPQoL-V.2 kept 16 items (9 physical and 7 emotional). The questionnaire was developed in a Spanish population and the final version was translated to English through translation and back-translation. CONCLUSION The first disease specific HRQoL questionnaire for PHPT patients (PHPQoL-16) has been developed. Validation studies designed to assess measurement properties of this tool are currently underway.

Automatic landmarks detection in breast reconstruction aesthetic assessment.

This paper addresses a fully automatic landmarks detection method for breast reconstruction aesthetic assessment. The set of landmarks detected are the supraesternal notch (SSN), armpits, nipples, and inframammary fold (IMF). These landmarks are commonly used in order to perform anthropometric measurements for aesthetic assessment. The methodological approach is based on both illumination and morphological analysis. The proposed method has been tested with 21 images. A good overall performance is observed, although several improvements must be achieved in order to refine the detection of nipples and SSNs.