4 research outputs found
Methodology for the assessment of new dichotomous diagnostic tests
No full textThe correct evaluation of a new diagnostic test requires the knowledge of the true status of the patient. Practically, such a favorable situation is rarely encountered and the status is most usually determined through one or several imperfect reference tests. In this case, a bias is introduced in assessing new diagnostic procedures and prevalence becomes a variable of prominent importance when calculating predictive values as well as sensitivity and specificity. Prevalence also affects the statistical parameters of the new tests in two-stage designs, and corrective procedures are necessary in these instances. This paper focuses an adjustment to be made to allow a correct assessment of new diagnostic procedures in specific situations. © 1981.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
The delta and epsilon errors in the assessment of cancer clinical trials
No full textThe error probabilities α and β are widely used to compute sample sizes and to analyze results of clinical trials. These errors are, however, not the only probablities to consider when assessing results of clinical studies. The rate of false positive (δ) and false negative (ε) results allows one to determine if an experimental finding is likely to reflect the true situation in the population of interest. The δ error is generally high in randomized phase III and in early phase II clinical trials in cancer patients, whereas the ε error is relatively low in these settings. This is essentially due to the small probability of detecting a more effective treatment or a new chemotherapeutic agent active in cancer. The δ error could be considerably reduced by increasing the sample sizes and by restricting the allowance made for the α error, which should be set at a 1% level as a minimum requirement.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
Long-term survivors with small cell carcinoma of the lung
No full textSCOPUS: ar.jinfo:eu-repo/semantics/publishe
