Combining Survival and Toxicity Effect Sizes from Clinical Trials: NCCTG 89-20-52 (Alliance)

Background: How can a clinician and patient incorporate survival and toxicity information into a single expression of comparative treatment benefit? Sloan et al. recently extended the ½ standard deviation concept for judging the clinical importance of findings from clinical trials to survival and tumor response endpoints. A new method using this approach to combine survival and toxicity effect sizes from clinical trials into a quality-adjusted effect size is presented.Methods: The quality-adjusted survival effect size (QASES) is calculated as survival effect size (ESS) minus the calibrated toxicity effect sizes (EST) (QASES=ESS-EST). This combined effect size can be weighted to adjust for the relative emphasis placed by the patient on survival and toxicity effects.Results: As an example, consider clinical trial NCCTG 89-20-52 which randomized patients to once-daily thoracic radiotherapy (ODTRT) versus twice-daily treatment of thoracic radiotherapy (TDRT) for the treatment of lung cancer. The ODTRT vs. TDRT arms had median survival time of 22 vs. 20 months (p=0.49) and toxicity rate of 39% vs. 54%, (p<0.05). The QASES of 0.18 standard deviations translates to a quality-adjusted survival difference of 5.7 months advantage for the ODRT arm over the TDRT treatment arm (22(16.3) months), p<0.05). Similar results are presented for the four possible case combinations of significant/non-significant survival and toxicity benefits using completed clinical trials.Conclusions: We used a novel approach to re-analyze clinical trial data to produce a single estimate for each treatment that combines survival and toxicity data. The QASES approach is an intuitive and mathematically simple yet robust approach

Combining Survival and Toxicity Effect Sizes from Clinical Trials: NCCTG 89-20-52 (Alliance)

Background: How can a clinician and patient incorporate survival and toxicity information into a single expression of comparative treatment benefit? Sloan et al. recently extended the ½ standard deviation concept for judging the clinical importance of findings from clinical trials to survival and tumor response endpoints. A new method using this approach to combine survival and toxicity effect sizes from clinical trials into a quality-adjusted effect size is presented. Methods: The quality-adjusted survival effect size (QASES) is calculated as survival effect size (ESS) minus the calibrated toxicity effect sizes (EST) (QASES=ESS-EST). This combined effect size can be weighted to adjust for the relative emphasis placed by the patient on survival and toxicity effects. Results: As an example, consider clinical trial NCCTG 89-20-52 which randomized patients to once-daily thoracic radiotherapy (ODTRT) versus twice-daily treatment of thoracic radiotherapy (TDRT) for the treatment of lung cancer. The ODTRT vs. TDRT arms had median survival time of 22 vs. 20 months (p=0.49) and toxicity rate of 39% vs. 54%, (p<0.05). The QASES of 0.18 standard deviations translates to a quality-adjusted survival difference of 5.7 months advantage for the ODRT arm over the TDRT treatment arm (22(16.3) months), p<0.05). Similar results are presented for the four possible case combinations of significant/non-significant survival and toxicity benefits using completed clinical trials. Conclusions: We used a novel approach to re-analyze clinical trial data to produce a single estimate for each treatment that combines survival and toxicity data. The QASES approach is an intuitive and mathematically simple yet robust approach

Using Garden Cafés to engage community stakeholders in health research.

Science Cafés, informal venues to promote bidirectional dialog, inquiry and learning about science between community members, scientists, healthcare and service providers, hold promise as an innovative tool for healthcare researchers and community members to improve health outcomes, especially among populations with health disparities. However, the process of optimizing science cafés is under-studied. We describe the pilot evaluation of a series of Science Cafés, called Garden Cafés (n = 9), conducted from September 2015 through April 2016 in Olmsted County, MN and Duval County, FL to connect Mayo Clinic researchers and local service providers with the community. Selection of discussion topics was guided by a county health needs assessment, which identified community priorities. Before leaving the events, community participants completed a brief anonymous survey assessing sociodemographics and their knowledge of research benefits, readiness to participate as a partner in health research, and health and science literacy confidence. Of the 112 attendees who responded, 51% were female and 51% were Black. Respondents reported that participating in the event significantly improved (all at p<0.001) their understanding on all three measures. Preliminary findings suggest that Garden Cafés are an effective forum to increase community understanding and disposition to collaborate in health research, especially in members from diverse backgrounds