Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

BACKGROUND: Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. METHODS: The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. RESULTS: It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. CONCLUSION: The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources

Using Southern Oscillation index phases to forecast sugarcane yields: a case study for northeastern Australia

Climate is a key driver of sugarcane productivity. Advance knowledge of the likely climate and its impact on production could add value to production, harvest and marketing efforts. A climate forecast system that incorporates five patterns or phases of the southern oscillation index is used to assess whether an early indication of sugarcane yield anomalies in Australia can be produced. results indicate that, for certain sugarcane growing regions, the climate forecast systems offers better estimates of the direction of the anomaly when compared with no climate forecast system. Improved results of the direction of the yield anomaly can be obtained some 7 months prior to the commencement of harvest. This information can then be used by marketers to plan better the customer allocations, shipping schedules and storage requirements for the next season. Advance knowledge of the crop size can also assist industry decisons makers in scheduling when the harvest season should commence. Further research is required to determine if other climatic indices, such as sea-surface temperatures, can improve yield estimation. Consideration also needs to be given to determining whether the magnitude and direction of the yield anomaly can be more accurately forecasted with varying lead times

Familial aggregation of urothelial cell carcinoma.

Item does not contain fulltextUrothelial cell carcinoma (UCC) is not considered to be a familial disease. Familial clustering of UCC was described in several case reports, however, some with an extremely early age at onset suggesting a genetic component. Epidemiological studies yielded inconsistent evidence of familial UCC, possibly because of low power and the inability to adjust for strong confounding. In our study the existence of a familial subtype of UCC was evaluated, as well as familial clustering of UCC with other types of cancer. A population-based family case-control study was performed including patients newly diagnosed with UCC of the bladder, ureter, renal pelvis or urethra, between January 1995 and December 1997, in the southeastern part of the Netherlands. Information on the patients' first-degree relatives was collected by postal questionnaire and subsequent telephone calls. The patients' partners filled out a similar questionnaire on their relatives. All reported occurrences of UCC were verified using medical records. Disease occurrence among case-relatives and control-relatives was compared to obtain the familial risk. Random effect proportional hazards regression analyses were used to calculate this familial risk while adjusting for age, gender and smoking behavior. In 95 families of the 1,193 patients and in 36 families of the 853 partners at least 1 relative was diagnosed with UCC. This yielded an adjusted hazard ratio (HR) of 1.8 (95% CI: 1.3-2.7). An increased risk was also found for cancer of the hematolymphopoietic system (hazard ration = 1.9, 95% CI: 1.2-3.1) among case-relatives. These results indicate that UCC has a familial component with an almost 2-fold increased risk among first-degree relatives of patients with UCC, which cannot be explained by smoking. Future segregation analyses may indicate whether this clustering can be attributed to genetic susceptibility