The “case-control” study: Valid selection of subjects

1985 ◽  
Vol 38 (7) ◽  
pp. 543-548 ◽  
Author(s):  
Olli S. Miettinen
Blood ◽  
2004 ◽  
Vol 104 (7) ◽  
pp. 2003-2006 ◽  
Author(s):  
Frank P. Mockenhaupt ◽  
Stephan Ehrhardt ◽  
Sabine Gellert ◽  
Rowland N. Otchwemah ◽  
Ekkehart Dietz ◽  
...  

Abstract The high frequency of α+-thalassemia in malaria-endemic regions may reflect natural selection due to protection from potentially fatal severe malaria. In Africa, bearing 90% of global malaria morbidity and mortality, this has not yet been observed. We tested this hypothesis in an unmatched case-control study among 301 Ghanaian children with severe malaria and 2107 controls (62% parasitemic). In control children, α+-thalassemia affected neither prevalence nor density of Plasmodium falciparum. However, heterozygous α+-thalassemia was observed in 32.6% of controls but in only 26.2% of cases (odds ratio [OR], 0.74; 95% confidence interval [CI], 0.56-0.98). Protection against severe malaria was found to be pronounced comparing severe malaria patients with parasitemic controls (adjusted OR in children < 5 years of age, 0.52; 95% CI, 0.34-0.78) and to wane with age. No protective effect was discernible for homozygous children. Our findings provide evidence for natural selection of α+-thalassemia in Africa due to protection from severe malaria.


2008 ◽  
Vol 124 (3) ◽  
pp. 362-363
Author(s):  
Demosthenes B. Panagiotakos ◽  
Loukianos Rallidis ◽  
Christos Pitsavos ◽  
Christodoulos Stefanadis ◽  
Dimitrios Kremastinos

1988 ◽  
Vol 74 (6) ◽  
pp. 675-679 ◽  
Author(s):  
Eugenio Pari ◽  
Marco Rosselli Del Turco ◽  
Domenico Palli ◽  
Eva Buiatti ◽  
Paolo Bruzzi ◽  
...  

In recent years techniques for the selection of risk groups for high priority breast screening have been evaluated (7, 11). We used data from a large multicentric case control study in Italy, recently published (12), to fit a reduced logistic model for predictive purposes, using variables which are easily collected. The predicted probability of being a case obtained through the logistic analysis was then used to classify the same set of data by calculating values of sensitivity and specificity at different cutoff points of the predicted probability. The results showed the low predictive power of the model. The selection of higher risk groups in a screening population program is discussed.


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