According to a study published online in the Journal of the National Cancer Institute, research indicates that including specific discrepancies in cost-effectiveness analysis would allow policy makers to set strategies that would reduce overall cancer risk, reduce disparities between racial ethnic subgroups, and be cost-effective.

Strategies of identifying effective and cost-efficient reductions in overall cancer incidence and mortality are often carried out by using disease simulation models, however, these models do not take the distribution of benefits within the population into consideration and are therefore sometimes criticized. Those details, accounting for inequalities between different population subgroups, can now be included due to advances in computer-based modeling in conjunction with the availability of better data.

Sue J. Goldie, MD, MPH, and Norman Daniels, Ph.D., of the Harvard School of Public Health, organized a typology of cancer disparities among U.S.’s black, white and Hispanic populations, separating differences resulting from various factors such as access, treatment quality and prevention in order to provide a framework for how health inequities could be more accurately considered in model-based cost-effectiveness analysis. Goldie and Daniels used this typology as orientation for evaluating different cervical cancer screenings and vaccination strategies that calculated the health and economic results for the average population as well as for calculating the three racial subgroups separately.

They discovered approaches that reduced the overall risk of cervical cancer from 74.5% to 60%, and improved cancer outcomes in all racial subgroups. In addition they also revealed an unequal distribution of benefits; for example, whilst current screening patterns would have resulted in a 60% reduction in overall cancer incidence, the actual reductions ranged from 54.8% for Hispanic women to 62.5% for white women.

The researchers discovered that screening strategies that directly targeted racial subgroups bearing the greatest inequalities provided a more equitable distribution of benefits, when combined with vaccination; for example, reduction in cervical cancer incidence was 69.7% in white women compared with 70.1% in Hispanic women, proving that these strategies were also more effective and more economic than current screening patterns.

The authors conclude that modeling different approaches in cancer prevention can identify strategies for the improvement of overall population health, fair distribution of health benefits, and utilize health care resources efficiently.

They conclude:

“These points of convergence are ‘win-win’ in the sense that they have the biggest positive impact in worst-off groups as well as on population health overall. Our claim is that such win-win strategies are most desirable from the perspective of both goals of health policy, population health improvement, and health equity.”

Kevin A. Ault, M.D., of the Department of Gynecology and Obstetrics at the Emory University School of Medicine writes in an accompanying editorial, that introducing HPV vaccines into the world of medicine has made cervical cancer prevention a reality. He supports the study’s conclusions on using models and agrees that, “modeling of racial and ethnic subgroups at increased risk identifies strategies that can reduce cancer burden among these groups.”

Ault recommends that these strategies should be made available to all women, based on recent research identifying HPV vaccination and diagnostic testing as potential improvements to the Pap smear in cervical cancer prevention.

Written by Petra Rattue