A self-assessment efficacy tool for spermicide contraceptive users

Abstract

Easily accessible contraceptive methods, such as chemical and barrier methods, are used currently by approximately 1 in 6 women who use contraception in the United States. Even in the face of suboptimal effectiveness, coitally dependent methods likely will always have a role in fertility management. Because most contraceptive efficacy stratifications use population-based data, for women to make informed decisions about the individual fit of a contraceptive method, better evidence-based, user-friendly tools are needed. Spermicides are a readily available, over-the counter, woman-controlled contraceptive method, but their effectiveness is user-dependent. Patient-decision aids for spermicides and other barrier methods are not well-developed, and overall failure rates could be improved by aids that account for individual characteristics. We sought to derive a prediction rule for successful use of spermicides for pregnancy prevention and to convert those data to a point-of-care instrument that women can use when they are considering spermicide use during contraceptive decision-making. We pooled local data from 3 randomized clinical trials that were published in 2004, 2007, and 2010 that tested spermicide efficacy. We constructed a prediction rule for unintended pregnancy using bootstrap validation and developed a scoring system. Data from 621 women showed a mean age of 29 years; 49% of the women were African American, and 43% were white. The overall pregnancy rate was 10.3% (95% confidence interval, 7.9-12.7) over 6months. In adjusted logistic regression, age >35 years was protective against pregnancy (odds ratio, 0.19; 95% confidence interval, 0.06-0.58; P= .003), and multigravidity was associated with high failure rates (odds ratio, 7.24; 95% confidence interval, 3.04-17.3; P < .001). These risk factors (together with frequency of unprotected sex) were used in a model that maximized sensitivity for pregnancy prediction to compute the predicted probability of unintended pregnancy for each woman. This model was 97% accurate in predicting women who had a <5% pregnancy risk while using spermicides. Using prospectively collected data, we built a simple risk calculator for contraceptive failure that women can consult when considering spermicide use. This instrument could support patient-centered contraceptive decision-making.