Cachexia in cancer: what is in the definition?

OBJECTIVE: This study aimed to provide evidence-based results on differences in overall survival (OS) rate to guide the diagnosis of cancer cachexia. DESIGN: Data collection and clinical assessment was performed every 3 months (5 visits): baseline data, muscle strength, nutritional and psychosocial status. 2 definitions on cachexia using different diagnostic criteria were applied for the same patient population. Fearon et al's definition is based on weight loss, body mass index (BMI) and sarcopenia. Evans et al nuances the contribution of sarcopenia and attaches additional attention to abnormal biochemistry parameters, fatigue and anorexia. The mean OS rates were compared between patients with and without cachexia for both definitions. RESULTS: Based on the population of 167 patients who enrolled, 70% developed cachexia according to Fearon et al's definition and 40% according to Evans et al's definition. The OS in the cachectic population is 0.97 and 0.55 years, respectively. The difference in OS between patients with and without cachexia is more significant using the diagnostic criteria of Evans et al. The focus of Fearon et al on weight loss and sarcopenia over-rates the assignment of patients to the cachectic group and OS rates have less prognostic value. CONCLUSION: This study presents a correlation with prognosis in favour of Evans et al' definition as a tool for cachexia diagnosis. This means that weight loss and BMI decline are both key factors in patients with cancer leading to cachexia but less decisive as stated by Fearon et al. Instead, extra factors gain importance in order to predict survival, such as chronic inflammation, anaemia, protein depletion, reduced food intake, fatigue, decreased muscle strength and lean tissue depletion. TRIAL REGISTRATION NUMBER: B300201112334.

Ningaloo reef: shallow marine habitats mapped using a hyperspectral sensor.

Research, monitoring and management of large marine protected areas require detailed and up-to-date habitat maps. Ningaloo Marine Park (including the Muiron Islands) in north-western Australia (stretching across three degrees of latitude) was mapped to 20 m depth using HyMap airborne hyperspectral imagery (125 bands) at 3.5 m resolution across the 762 km(2) of reef environment between the shoreline and reef slope. The imagery was corrected for atmospheric, air-water interface and water column influences to retrieve bottom reflectance and bathymetry using the physics-based Modular Inversion and Processing System. Using field-validated, image-derived spectra from a representative range of cover types, the classification combined a semi-automated, pixel-based approach with fuzzy logic and derivative techniques. Five thematic classification levels for benthic cover (with probability maps) were generated with varying degrees of detail, ranging from a basic one with three classes (biotic, abiotic and mixed) to the most detailed with 46 classes. The latter consisted of all abiotic and biotic seabed components and hard coral growth forms in dominant or mixed states. The overall accuracy of mapping for the most detailed maps was 70% for the highest classification level. Macro-algal communities formed most of the benthic cover, while hard and soft corals represented only about 7% of the mapped area (58.6 km(2)). Dense tabulate coral was the largest coral mosaic type (37% of all corals) and the rest of the corals were a mix of tabulate, digitate, massive and soft corals. Our results show that for this shallow, fringing reef environment situated in the arid tropics, hyperspectral remote sensing techniques can offer an efficient and cost-effective approach to mapping and monitoring reef habitats over large, remote and inaccessible areas.