Background: The evaluation of research output, such as an estimation of the proportion of treatments successes is of ethical, scientific, and public importance. How often experimental cancer treatments that undergo testing in randomized clinical trials (RCTs) result in discovery of successful new interventions has rarely been evaluated systematically. Methods: We evaluated treatment success in a consecutive cohort of RCTs performed by the National Cancer Institute cooperative groups over the past five decades. We investigated therapeutic success in 3 ways: assessing the proportion of statistically significant trials favoring new or standard treatments, determining the proportion of the trials in which new treatments were considered to be superior to standard treatments according to the original researchers, quantitatively synthesizing data for overall survival and event-free survival. Results: Data from 624 trials (781 randomized comparisons) involving 216,451 patients were analyzed. 30% of trials had statistically significant results. Among these, new interventions were superior to established treatments in 80% of trials. The original researchers judged that the risk-benefit profile favored new treatments in 41% trials. Hazard ratio for survival and event-free survival was 0.95 (99% CI 0.93–0.98) and 0.90 (99%CI 0.87– 0.93) respectively, slightly favoring the new treatments. Breakthrough interventions were discovered in 15% of trials. The main advances have occurred in the management of gastro-intestinal cancer and hematological malignancies Conclusions: When cancer treatments have been tested in RCTs by the NCI cooperatives groups, about one third of the trials lead to the discovery of successful new treatments. On average, the death rate in these trials has been reduced by 5% with the new treatments. Grant support: NIH/ORI (No 1R01NS044417–01; 5 R01 NS052956–02).
Deregulation of the LEA Careers Service followed by the establishment of the National Assembly for Wales in 1999 led, through consultation, to the establishment of a bi-lingual all-age career guidance service under the banner of Careers Wales. The article traces the history of career guidance in Wales from 1974, showing how it has taken a very different path to England, gaining a positive outcome from an independent review of Careers Wales in 2004 and an accolade from the OECD. Current strengths, especially the innovative use of technology, are explored, and challenges for the future are investigated, including the contributions of other guidance providers. Priority is currently being given to the development of common pan-Wales standards. The need for a stronger research culture is recognised. Most crucial of all, in the authors' opinion, is the maintenance of client entitlement in the face of financial restrictions.
For primary lung cancer, it is crucial to identify new predictors to guide the development of new strategies for predicting and improving survival. A multivariable study was conducted comparing patients who survived >5 years to whom died <2 years after diagnosis, matched on age, gender, TNM stage, tumor number and cell type. Patients were compared on other characteristics at diagnosis, follow-up information and genotypes on 5 critical enzymes in the glutathione metabolic pathway. Multiple logistic regression analysis evaluated all variables encompassing 4 dimensions. Included were 394 pairs of patients. Univariable analysis showed that smoking status and pack-years smoked, tumor grade, disease progression/recurrence, pulmonary resection and surgery type and selected comorbidities were significantly associated with survival. Patients who were physically active, reported a better quality of life after their diagnosis, or had positive GSTM1 genotype experienced longer survival. In multivariable analysis, disease progression/recurrence (OR: 3. Physicians often consider the characteristics of a diagnostic test as a discrete set of parameters generally falling into two categories of validity and reliability. Such interpretation of the test result is not an optimal way of harnessing all available information. A model is proposed to combine all measures of a test into a framework inspired from the Signal Detection Theory (SDT). By simulating subject and observer variation, the model is capable of transforming the measures of validity and reliability into the SDT parameters and vice versa. Two implications follow: First, the ideal performance of the test (when observer variation is eliminated) can be estimated. Second: quantitative interpretation of repeated tests, a common clinical scenario, is possible. Modeling results of a published study on interpretation of mammography for detecting breast cancer (Kerlikowske 1998) further clarifies such implications. The original study reported the sensitivity, specificity, intra-observer, and inter-observer disagreement of the test as 0.72, 0.83, 0.14, and 0.22, respectively. The model shows that by eliminating observer variation, the sensitivity and specificity will increase to 0.86 and 0.92, respectively. The combined sensitivity and specificity of two radiologists' reports the same mammogram (considering the test as positive when at least one radiologist reports a positive result) will be 0.87 and 0.72, respectively. A multivariate probabilistic sensitivity analysis was also performed and the model was found to be robust against minor changes in the inputs. Such an integrative approach can help obtain additional information beyond what is obtainable from the conventional interpretation of test results. The use of smoking cessation aids, such as nicotine replacement therapy, bupropion, and other substances designed to reduce cravings and withdrawal symptoms, is considered a promising approach, and thousands of articles report on such interventions. Roughly one fifth of those ar...
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