Using clinical classification trees to identify individuals at risk of STDs during pregnancy.

Young pregnant women are a group at particularly high risk of STDs.1,2 In a systematic literature review of sexual risk and STDs among pregnant teenagers and those who have given birth, STD incidence was 19−39% during pregnancy, and 14−39% between six and 10 months postpartum. In addition, adolescent mothers were twice as likely as their nulliparous peers to acquire an STD during a 12-month period. Furthermore, 78−88% of pregnant women engaged in sex without condoms during pregnancy, and pregnant women were only about one-fifth as likely as nonpregnant women to use condoms.3 Current guidelines from the Centers for Disease Control and Prevention (CDC) recommend STD screening for all high-risk women-usually defined as those younger than 25 and those with multiple or new partners.4 Frequently, screening for all high-risk pregnant women occurs only during initial prenatal care visits, so an infection that is acquired later in pregnancy may go undetected. Some clinics retest women who are deemed high-risk (e.g., those testing STD-positive at their initial visit) or exhibit symptoms; however, testing procedures differ from clinic to clinic, and screening behavior can vary by provider.5 In addition, because an STD diagnosis and treatment are not enough to have long-term effects on risky behavior,6 an emphasis on prevention is necessary to achieve long-term risk reduction. Prevention programs integrated with prenatal care can capitalize on women's motivation to have a healthy pregnancy and child. HIV and other STD prevention programs have been successfully integrated in psychiatric care, drug treatment and palliative medicine settings.7–9 This model for prevention could be extended to include prenatal care. For interventions to be most effective in clinical settings, they should be easy to implement and tailored to meet the needs and risks of particular patients. Thus, it may be beneficial to identify subgroups of women at varying risk of STDs during pregnancy, and implement treatment, care and prevention programs that best meet the needs of those individuals. To successfully do this, providers need to go beyond the typical characteristics obtained during prenatal care assessments. A 2002 Institute of Medicine report and more recent research syntheses suggest that ecological approaches to health, and to STD prevention, are particularly useful and needed.3,10,11 Ecological systems theory emphasizes that factors from many levels (e.g., individual, dyad, family and community) can influence health.3,10–12 The few studies on young people's sexual activity that have included factors from many levels have shown that dyad, family and community factors independently contribute to risk behavior above and beyond individual factors.13–15 In addition to using primarily individual-level predictors, most studies that have tried to estimate STD risk have used standard analytic techniques (e.g., logistic regression). However, these methods are limited because they assume primarily linear relationships between the predictors and outcomes that may not be realistic in applied settings. Furthermore, results from these techniques (e.g., odds ratios in logistic regression) are difficult to translate into clinical practice and policy.16 Classification tree analysis, also called recursive partitioning, avoids the limitations associated with logistic regression and other standard methods. The technique uses a set of predictors to create subgroups of individuals that vary in risk for the main outcome of interest, ultimately producing a user-friendly classification tree that can be employed to guide care, treatment and prevention efforts in clinical settings. For example, in a study of young adults at an STD clinic, several subgroups were classified as having a high STD risk because of particular behavioral and emotional factors (e.g., one group felt bad about themselves after having sex and had sex to relieve tension; one group fell bad about themselves after having sex and had sex to get back at someone).17 Use of classification tree analysis has been documented in the health care and managed care literature,18 and has been used in many clinical and medical settings to identify high-risk patients and to help create clinical guidelines.19–23 Clinicians often use informal decision trees when making clinical decisions. On the basis of a complex interaction of medical, demographic and behavioral factors, clinicians determine the likelihood of disease outcomes and often use these patient characteristics to guide care and treatment decisions (e.g., if a woman is having risky sex and is younger than 25, the clinician may screen for STDs because past experience suggests that the patient is at risk). The purpose of this study is to use individual, dyad, and family- and community-level characteristics to develop a clinically relevant classification tree that will help identify women who are at risk of acquiring an STD during pregnancy and will provide a formal decision-making structure for STD prevention, treatment and care.