From the University of California, San Francisco, Department of Obstetrics, Gynecology, and Reproductive Sciences San Francisco, CA
Conflicts of interest: No conflicts of interest to report.
Correspondence: Joan M. Chow, MPH, DrPH, Epidemiology Unit, Surveillance and Epidemiology Section, Sexually Transmitted Disease Control Branch, Division of Communicable Disease Control, Center for Infectious Diseases, California Department of Public Health, 850 Marina Bay Parkway, Bldg P, 2nd Floor, Richmond, CA 94804. E-mail: email@example.com.
Received for publication November 1, 2012, and accepted November 6, 2012.
The public health field stands to gain much in the coming years by the passage of a number of groundbreaking pieces of legislation in the United States, including, most notably, the 2010 Affordable Care Act (ACA) with creation of the Prevention and Public Health Fund1 and the American Recovery and Reinvestment Act of 2009 with funding of the Health Information Technology (HI-Tech) Act to promote electronic health records.2 With the emphasis on increasing access to evidence-based clinical preventive services that are cost-effective and demonstrated impact on reducing adverse outcomes, public health goals can be more fully integrated into clinical practice on an individual level and realized on a population level. On the one hand, this improvement can specifically extend the reach of sexually transmitted disease (STD) control strategies more broadly to cover public and private sector health care populations; on the other hand, programs will be challenged to prioritize resources for the most effective strategies, monitor their implementation, and demonstrate their effectiveness. In the face of diminished local and national public health budgets, accountability is demanded at each of these stages across all programs.
If STD programs must prioritize evidence-based STD program interventions, they must invest in the scale-up of those interventions shown to have maximum impact on reducing STD acquisition and transmission in the short term and reduction of adverse outcomes such as infertility and neonatal morbidity in the long term. However, when there are multiple interventions competing for funding without clear evidence for effectiveness, programs are faced with a situation known as clinical equipoise, a situation that clinicians are ethically bound to resolve so as to offer the best option for a patient.3 Some authors have suggested that clinical equipoise exists with respect to the implementation of population-level chlamydia screening programs and that randomized controlled trials are needed for resolution.4 Is this indeed the case, although given the body of animal model and retrospective epidemiologic data supporting the association between chlamydia and adverse reproductive outcomes? Although a small number of randomized controlled trials of chlamydia screening demonstrating reduced incidence of pelvic inflammatory disease (PID) have been conducted since the late 1990s in a variety of populations, the expected impact has been less than compelling and results have been challenged.5–7 Gottlieb and colleagues8,9 in this issue have revisited the equipoise question by critically reviewing methodological issues in the earlier trials and discussed 2 more recent trials that attempted to address those issues. The methodological issues were numerous, ranging from potential selection bias in screening groups, incomplete capture of PID outcomes, and insufficient power to detect a protective effect of screening on PID risk. Based on this comprehensive review, Gottlieb and colleagues conclude that although the impact of chlamydia screening on PID incidence was evident across trials, the effect may have been overestimated. What impact might these new findings and interpretations have on designing our chlamydia control strategies going forward?
Gottlieb and colleagues identified numerous gaps in our understanding of pathogenesis of the multiple organisms associated with PID and the many challenges in designing and conducting yet another randomized controlled trial. Lack of compelling evidence stymies STD program ability to prioritize program resources, Instead, we should be applying principles being developed in. Unfortunately, the program science area to identify what combinations of interventions are effective and can be scaled up to synergistically reduce STD and their sequelae. With these principles in mind, we could use a comprehensive approach to evaluating chlamydia control programs and consider all critical components: risk reduction counseling, access to and correct use of condoms, screening, treatment, partner management, and repeat screening. Kretzschmar and colleagues10 have demonstrated significant impact based on modeling such a comprehensive program with these elements; for example, a 23% reduction in chlamydia positivity was achieved by either increasing screening by 3-fold or partner notification by 2-fold. However, modeling a comprehensive program and actually implementing one 2 present very different perspectives as demonstrated from provider practice data on various program components.
Gottlieb and colleagues noted that program factors can have a profound impact in translating anticipated impact of chlamydia screening on PID incidence in the real world. Sexually transmitted disease programs still face numerous challenges for effective implementation of chlamydia control strategies. In particular, chlamydia screening levels are not at the levels proposed in models (>50% according to Kretzschmar and colleagues10) to lower chlamydia positivity; for example, the annual chlamydia testing rate for sexually active US women aged 15 to 25 years, data from the 2006 to 2008 National Survey of Family Growth, was 37.9%.11 There are no comparable screening guidelines or significant screening levels for asymptomatic males. Partner management practices still depend on self-referral, and there is relatively low uptake of alternative expedited partner therapy options.12 Retesting levels for cases at 3 months remain well below 50% despite CDC national guidelines.13 That any measureable declines in PID have been noted in the face of these control strategy challenges is remarkable (assuming a true causal relationship) and suggests a potentially greater effect in the future if program control strategies can be more effectively implemented. Such a future might be more likely given the health care restructuring, provision of essential health benefits without co-payment, and integrated health information technology landscape with the ACA.
If randomized controlled trial data are not sufficient on their own to support expansion of chlamydia screening and related control strategies, fortunately, there are other data sources available for program evaluation that are potentially compelling. Recent long-term data on chlamydia and PID outcomes based on stable health care populations with established chlamydia screening and treatment programs have indicated population-level declines in PID.14,15 These findings provide a consistent picture of the positive impact of chlamydia control within these populations and could potentially be replicated in health care programs as ACA and HI-Tech legislation rolls out. Specifically, the ongoing proliferation of electronic health records will enable documentation and retrieval of STD clinical care and prevention service use, as well as reproductive health outcomes16,17; ongoing data collection of this magnitude will undoubtedly be a cost-efficient approach for demonstrating program effectiveness not heretofore possible.
These recent real-world examples of impact that can be attributed to the implementation of chlamydia screening and coordinated control strategies are encouraging and should be the data used to support expansion of chlamydia control strategies to a broader segment of the population. Randomized clinical trials are imperfect for resolving the clinical equipoise posed by chlamydia screening as some authors suggest; a suitable alternative may well be the observational data on chlamydia screening and outcomes based on electronic health record repositories to remove any clinical equipoise associated with our chlamydia control program efforts.
1. Koh HK, Sebelius KG. Promoting prevention through the Affordable Care Act. N Engl J Med 2010; 363: 1296–1299.
2. Office of the National Coordinator for Health Information Technology (ONC), Department of Health and Human Services. Health information technology: Standards, implementation specifications, and certification criteria for electronic health record technology, 2014 edition; revisions to the permanent certification program for health information technology. Final rule. Fed Regist 2012; 77: 54163–54292.
3. Mann H, Djulbegovic B. Choosing a control intervention for a randomized clinical trial. BMC Med Res Methodol 2003; 3: 7.
4. Low N, Bender N, Nartey L, et al.. Effectiveness of chlamydia screening: Systematic review. Int J Epidemiol 2009; 38: 435–448.
5. Scholes D, Stergachis A, Heidrich FE, et al.. Prevention of pelvic inflammatory disease by screening for cervical chlamydial infection. N Engl J Med 1996; 334: 1362–1366.
6. Ostergaard L, Andersen B, Moller JK, et al.. Home sampling versus conventional swab sampling for screening of Chlamydia trachomatis
in women: A cluster-randomized 1-year follow-up study. Clin Infect Dis 2000; 31: 951–957.
7. Morré SA, van den Brule AJ, Rozendaal L, et al.. The natural course of asymptomatic Chlamydia trachomatis
infections: 45% clearance and no development of clinical PID after one-year follow-up. Int STD AIDS 2002; 13 (suppl 2): 12–18.
8. Gottlieb SL, Xu F, Brunham R. Screening and treating Chlamydia trachomatis
genital infection to prevent pelvic inflammatory disease: Interpretation of findings from randomized controlled trials. Sex Transm Dis 2012. In press.
9. Andersen B, van Valkengoed I, Sokolowski I, et al.. Impact of intensified testing for urogenital Chlamydia trachomatis
infections: A randomised study with 9-year follow-up. Sex Transm Infect 2011; 87: 156–161.
10. Kretzschmar M, Satterwhite C, Leichliter J, et al.. Effects of screening and partner notification on chlamydia positivity in the United States: A modeling study. Sex Transm Dis 2012; 39: 325–331.
11. Tao G, Hoover KW, Leichliter JS, et al.. Self-reported chlamydia testing rates of sexually active women aged 15–25 years in the United States, 2006–2008. Sex Transm Dis 2012; 39: 605–607.
12. Jotblad S, Park IU, Bauer HM, et al.. Patient-delivered partner therapy for chlamydial infections: Practices, attitudes, and knowledge of California family planning providers. Sex Transm Dis 2012; 39: 122–127.
13. Hoover KW, Tao G, Nye MB, et al.. Suboptimal adherence to repeat testing recommendations for men and women with positive chlamydia tests in the United States, 2008–2010. Clin Infect Dis 2012. [Epub ahead of print].
14. Scholes D, Satterwhite CL, Yu O, et al.. Long-term trends in Chlamydia trachomatis
and related outcomes in a US managed care population. Sex Transm Dis 2012; 39: 81–88.
15. Rekart ML, Gilbert M, Meza R, et al.. Chlamydia public health programs and the epidemiology of pelvic inflammatory disease and ectopic pregnancy. J Infect Dis 2012. [Epub ahead of print].
16. Anschuetz GL, Asbel L, Spain CV, et al.. Association between enhanced screening for Chlamydia trachomatis
and Neisseria gonorrhoeae
and reductions in sequelae among women. J Adolesc Health 2012; 51: 80–85.
17. Satterwhite CL, Yu O, Raebel MA, et al.. Detection of pelvic inflammatory disease: Development of an automated case-finding algorithm using administrative data. Infect Dis Obstet Gynecol 2011; 2011: 428351.