Use of routinely available clinical, nutritional, and functional criteria to classify cachexia in advanced cancer patients.

BACKGROUND: Cachexia is a highly prevalent syndrome in cancer and chronic diseases. However, due to the heterogeneous features of cancer cachexia, its identification and classification challenge clinical practitioners. OBJECTIVE: To determine the clinical relevance of a cancer cachexia classification system in advanced cancer patients. DESIGN: Beginning with the four-stage classification system proposed for cachexia [non-cachexia (NCa), pre-cachexia (PCa), cachexia (Ca) and refractory cachexia (RCa)], we assigned patients to these cachexia stages according to five classification criteria available in clinical practice: 1) biochemistry (high C-reactive protein or leukocytes, or hypoalbuminemia, or anemia), 2) food intake (normal/decreased), weight loss: 3) moderate (≤5%) or 4) significant (>5%/past six months) and 5) performance status (Eastern Cooperative Oncology Group Performance Status ≥ 3). We then determined if symptom severity, body composition changes, functional levels, hospitalizations and survival rates varied significantly across cachexia stages. RESULTS: Two-hundred and ninety-seven advanced cancer patients with primary gastrointestinal and lung tumors were included. Patients were classified into Ca (36%), PCa and RCa (21%, respectively) and NCa (15%). Significant (p < 0.05) differences were observed among cachexia stages for most of the outcome measures (symptoms, body composition, handgrip strength, emergency room visits and length of hospital stays) according to cachexia severity. Survival also differed between cachexia stages (except between PCa and Ca). CONCLUSION: Five clinical criteria can be used to stage cancer cachexia patients and predict important clinical, nutritional and functional outcomes. The lack of statistical difference between PCa and Ca in almost all clinical outcomes examined suggests either that the PCa group includes patients already affected by early cachexia or that more precise criteria are needed to differentiate PCa from Ca patients. More studies are required to validate these findings.

Average sunrise time predicts depression prevalence.

OBJECTIVE: Folk wisdom has it that early rising is associated with being "healthy, wealthy and wise." A physiologic explanation may be Wiegand's "Depressiogenic Theory of Sleep," which posits that excessive REM sleep causes depression. Sleeping late increases REM sleep, and thus may increase depression risk. Published depression prevalence research does not use arising time, but average sunrise time (AST) for cities might serve as an analogue for arising time. Two studies of depression prevalence in urban populations, the EURODEP Programme, which measured geriatric depression in nine European cities, and the Epidemiologic Catchment Area (ECA) study of five US centres, have so far lacked satisfactory explanations for the striking differences in depression prevalence between cities. It was hypothesized that differences in rising times between cities, as determined by AST, could explain the variability in depression prevalences. METHODS: Correlations were calculated for published depression prevalences from the EURODEP and ECA studies, and AST for each site. RESULTS: For both studies, depression prevalences are significantly correlated with AST, with later sunrise (corresponding to earlier arising times in relation to sunrise) associated with lower depression prevalence. CONCLUSIONS: The hypothesis that later rising from sleep is associated with increased depression was supported. The findings also suggest that a city's depression prevalence could be reduced by simple public health measures to manipulate AST, such as going to Daylight Saving Time (DST) year-round or shifting time-zone boundaries. For individuals, getting up earlier from sleep may be helpful in depression.