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BACKGROUND:Prostate cancer (PC) primarily affects elderly men. However, the specific features of cases diagnosed at younger ages (

BACKGROUND:Tools to aid in the prognosis assessment of colon cancer patients in terms of risk of mortality are needed. Goals of this study are to develop and validate clinical prediction rules for 1- and 2-year mortality in these patients. METHODS:This is a prospective cohort study of patients diagnosed with colon cancer who underwent surgery at 22 hospitals. The main outcomes were mortality at 1 and 2 years after surgery. Background, clinical parameters, and diagnostic tests findings were evaluated as possible predictors. Multivariable multilevel logistic regression and survival models were used in the analyses to create the clinical prediction rules. Models developed in the derivation sample were validated in another sample of the study. RESULTS:American Society of Anesthesiologists Physical Status Classification System (ASA), Charlson comorbidity index (> = 4), age (>75 years), residual tumor (R2), TNM stage IV and log of lymph nodes ratio (> = -0.53) were predictors of 1-year mortality (C-index (95% CI): 0.865 (0.792-0.938)). Adjuvant chemotherapy was an additional predictor. Again ASA, Charlson Index (> = 4), age (>75 years), log of lymph nodes ratio (> = -0.53), TNM, and residual tumor were predictors of 2-year mortality (C-index:0.821 (0.766-0.876). Chemotherapy was also an additional predictor. CONCLUSIONS:These clinical prediction rules show very good predictive abilities of one and two years survival and provide clinicians and patients with an easy and quick-to-use decision tool for use in the clinical decision process while the patient is still in the index admission.

Sex hormones play a role in gastric cancer and colorectal cancer etiology, however, epidemiological evidence is inconsistent. This study examines the influence of menstrual and reproductive factors over the risk of both tumors.In this case-control study 128 women with gastric cancer and 1293 controls, as well as 562 female and colorectal cancer cases and 1605 controls were recruited in 9 and 11 Spanish provinces, respectively. Population controls were frequency matched to cases by age and province. Demographic and reproductive data were directly surveyed by trained staff. The association with gastric, colon and rectal cancer was assessed using logistic and multinomial mixed regression models.Our results show an inverse association of age at first birth with gastric cancer risk (five-year trend: OR = 0.69; p-value = 0.006). Ever users of hormonal contraception presented a decreased risk of gastric (OR = 0.42; 95%CI = 0.26-0.69), colon (OR = 0.64; 95%CI = 0.48-0.86) and rectal cancer (OR = 0.61; 95%CI = 0.43-0.88). Postmenopausal women who used hormone replacement therapy showed a decreased risk of colon and rectal tumors. A significant interaction of educational level with parity and months of first child lactation was also observed.These findings suggest a protective role of exogenous hormones in gastric and colorectal cancer risk. The role of endogenous hormones remains unclear.

Application of illness-severity scores in Intermediate Care Units (ImCU) shows conflicting results. The aim of the study is to design a severity-of-illness score for patients admitted to an ImCU.We performed a retrospective observational study in a single academic medical centre in Pamplona, Spain. Demographics, past medical history, reasons for admission, physiological parameters at admission and during the first 24 hours of ImCU stay, laboratory variables and survival to hospital discharge were recorded. Logistic regression analysis was performed to identify variables for mortality prediction.A total of 743 patients were included. The final multivariable model (derivation cohort = 554 patients) contained only 9 variables obtained at admission to the ImCU: previous length of stay 7 days (6 points), health-care related infection (11), metastatic cancer (9), immunosuppressive therapy (6), Glasgow comma scale 12 (10), need of non-invasive ventilation (14), platelets 50000/mcL (9), urea 0.6 g/L (10) and bilirubin 4 mg/dL (9). The ImCU severity score (ImCUSS) is generated by summing the individual point values, and the formula for determining the expected in-hospital mortality risk is: e(ImCUSS points*0.099 - 4,111)/(1 + e(ImCUSS points*0.099 - 4,11)1). The model showed adequate calibration and discrimination. Performance of ImCUSS (validation cohort = 189 patients) was comparable to that of SAPS II and 3. Hosmer-Lemeshow goodness-of-fit C test was χ2 8.078 (p=0.326) and the area under receiver operating curve 0.802.ImCUSS, specially designed for intermediate care, is based on easy to obtain variables at admission to ImCU. Additionally, it shows a notable performance in terms of calibration and mortality discrimination.

Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous condition characterized by occasional exacerbations. Identifying clinical subtypes among patients experiencing COPD exacerbations (ECOPD) could help better understand the pathophysiologic mechanisms involved in exacerbations, establish different strategies of treatment, and improve the process of care and patient prognosis. The objective of this study was to identify subtypes of ECOPD patients attending emergency departments using clinical variables and to validate the results using several outcomes. We evaluated data collected as part of the IRYSS-COPD prospective cohort study conducted in 16 hospitals in Spain. Variables collected from ECOPD patients attending one of the emergency departments included arterial blood gases, presence of comorbidities, previous COPD treatment, baseline severity of COPD, and previous hospitalizations for ECOPD. Patient subtypes were identified by combining results from multiple correspondence analysis and cluster analysis. Results were validated using key outcomes of ECOPD evolution. Four ECOPD subtypes were identified based on the severity of the current exacerbation and general health status (largely a function of comorbidities): subtype A (n = 934), neither high comorbidity nor severe exacerbation; subtype B (n = 682), moderate comorbidities; subtype C (n = 562), severe comorbidities related to mortality; and subtype D (n = 309), very severe process of exacerbation, significantly related to mortality and admission to an intensive care unit. Subtype D experienced the highest rate of mortality, admission to an intensive care unit and need for noninvasive mechanical ventilation, followed by subtype C. Subtypes A and B were primarily related to other serious complications. Hospitalization rate was more than 50% for all the subtypes, although significantly higher for subtypes C and D than for subtypes A and B. These results could help identify characteristics to categorize ECOPD patients for more appropriate care, and help test interventions and treatments in subgroups with poor evolution and outcomes.

Intermediate Care Units (ImCU) have become an alternative scenario to perform Non-Invasive Ventilation (NIV). The limited number of prognostic studies in this population support the need of mortality prediction evaluation in this context.The objective of this study is to analyze the performance of Simplified Acute Physiology Score (SAPS) II and 3 in patients undergoing NIV in an ImCU. Additionally, we searched for new variables that could be useful to customize these scores, in order to improve mortality prediction.Cohort study with prospectively collected data from all patients admitted to a single center ImCU who received NIV. The SAPS II and 3 scores with their respective predicted mortality rates were calculated. Discrimination and calibration were evaluated by calculating the area under the receiver operating characteristic curve (AUC) and with the Hosmer-Lemeshow goodness of fit test for the models, respectively. Binary logistic regression was used to identify new variables to customize the scores for mortality prediction in this setting.The study included 241 patients consecutively admitted to an ImCU staffed by hospitalists from April 2006 to December 2013.The observed in-hospital mortality was 32.4% resulting in a Standardized Mortality Ratio (SMR) of 1.35 for SAPS II and 0.68 for SAPS 3. Mortality discrimination based on the AUC was 0.73 for SAPS II and 0.69 for SAPS 3. Customized models including immunosuppression, chronic obstructive pulmonary disease (COPD), acute pulmonary edema (APE), lactic acid, pCO2 and haemoglobin levels showed better discrimination than old scores with similar calibration power.These results suggest that SAPS II and 3 should be customized with additional patient-risk factors to improve mortality prediction in patients undergoing NIV in intermediate care.