Users of any method of pregnancy prevention need reliable evidence on perfect and typical use effectiveness to support informed choice. Different study designs for effectiveness estimation have different advantages and disadvantages. Because participants in prospective studies may be highly selected and less representative of typical users than participants in population-based surveys, estimates from clinical studies likely represent “best-case scenarios.”4 Retrospective surveys depend on patients accurately recalling details about reproductive behavior over several years and cannot be used to calculate perfect use estimates. Importantly, low use of fertility awareness–based methods has necessitated lumping users of disparate fertility awareness–based methods together to calculate an overall typical use estimate in retrospective surveys.5,6 However, this may obscure the effectiveness of individual methods. We conducted a comprehensive search to identify prospective studies estimating typical and perfect use effectiveness of individual fertility awareness–based methods and systematically evaluated their quality.
We registered the study protocol in PROSPERO (CRD42015017760). Our comprehensive search strategy (Appendix 1, available online at http://links.lww.com/AOG/B132) identified studies published in English, Spanish, French, or German (languages spoken by the reviewers) from database inception through June 6, 2017, in MEDLINE, EMBASE, CINAHL, or Web of Science. We manually searched reference lists of included studies and pertinent review articles. We also searched clinicaltrials.gov with key words for ongoing trials published through June 27, 2017. We used Covidence available at www.covidence.org for title–abstract and full-text screening.
We assembled a multidisciplinary team, including experts in clinical reproductive health care (R.P.U. and J.B.S.), epidemiology (C.B.P. and E.T.J.), demography (M.E.G.), fertility awareness–based method instruction (R.P.U. and E.K.), systematic reviews (C.B.P. and R.P.U.), and conduct of fertility awareness–based method effectiveness studies (J.B.S.). We included studies that prospectively collected information on pregnancy intentions and outcomes and which followed at least 50 participants using a specific fertility awareness–based method to avoid pregnancy. Fertility awareness–based methods were defined as any method using specific rules to approximate the fertile window based on tracking one or more of the following biomarkers: menstrual dates, basal body temperature, cervical mucus, cervical position or consistency, or urinary hormones. Appendix 2, available online at http://links.lww.com/AOG/B132, provides more detailed study inclusion criteria.
Trained investigator dyads independently screened titles and abstracts for inclusion and then screened relevant full-text articles. We reconciled conflicts through discussion. We included studies that did not calculate a pregnancy rate if enough data were provided for the review team to calculate a 12-month or 13-cycle Pearl rate.7
Starting with the key questions outlined in our protocol, we drafted an abstraction form and each investigator piloted the form on several studies. We met in person to discuss and finalize the form (Appendix 3, available online at http://links.lww.com/AOG/B132). Investigator dyads independently extracted data for included studies in the Systematic Review Data Repository (https://srdr.ahrq.gov). We extracted data on study design, exclusion and inclusion criteria, sample size, demographics, type of fertility awareness–based method, attrition, pregnancy rate or probabilities, and methodologic approach. We attempted to contact authors of included studies as necessary to obtain clarification on statistical approaches, overlap of published reports, or other aspects of study design, but we did not include any unpublished effectiveness data.
To develop quality evaluation criteria, we reviewed established quality frameworks including the U.S. Preventive Services Task Force and Cochrane.8–10 Given specific quality issues unique to our topic,11–16 we modified the Task Force framework to enhance relevance to our specific question of interest. The final quality assessment framework contained 13 items, explained in detail in Appendix 4, available online at http://links.lww.com/AOG/B132. To be considered a “high-quality” study for our research question (effectiveness for prevention of unintended pregnancy), a study had to be ranked a “1” on all 13 criteria. Any study with a “3” ranking on any of 13 quality criteria was considered “low quality” for our primary question of interest. We considered all other studies “moderate quality.” We rated overall study quality using all peer-reviewed manuscripts pertaining to that study.
We briefly describe all studies meeting our inclusion criteria (Table 2). Next, we describe studies ranked moderate or high quality in greater detail along with the number of criteria (out of 13) that received the highest rating (see Appendix 5, available online at http://links.lww.com/AOG/B132, for full details on effectiveness estimates and populations for the moderate-quality studies). In summarizing effectiveness estimates, we excluded information from studies ranked low quality as a result of concerns about the validity of their estimates. In reporting the results, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance.17
We extracted first-year life table probabilities where possible. If these were not reported, we included 12-month (or 13-cycle) Pearl rates. Because Pearl rate estimates can be significantly affected by use duration, we limited our reporting to include Pearl rates of approximately 1-year duration, thus enhancing cross-study comparability.4,14,16 We required that perfect use pregnancy rates or probabilities be calculated using a denominator of only perfect use cycles to avoid reporting of underestimated effectiveness estimates.4,15
From 8,755 unique records, we excluded 8,312 in title–abstract review and 369 in full-text review (Fig. 1). We included 74 published articles11,16,18–58 , 59–88 in English (n=67), German (n=2), French (n=3), and Spanish (n=2). We identified 53 unique studies that describe 65 cohorts of specific fertility awareness–based method users (Table 2). The studies were conducted in a variety of geographic locations, languages, and settings in North and South America, Europe, Africa, and Asia. We ranked 0 as “high quality,” 21 as “moderate quality,” and 32 as “low quality” for our primary review question. Detailed quality ranking tables for each included study are provided in Appendix 6, available online at http://links.lww.com/AOG/B132, which also provides details on any recalculated specific effectiveness estimates (if multiple estimates were presented in the article). Appendix 5 (available online at http://links.lww.com/AOG/B132) provides detailed information about the population and effectiveness estimates at various time points for each study rated moderate or higher quality. Figures 2 and 3 present the 12-month or 13-cycle typical and perfect use pregnancy rates (ie, Pearl Index) and probabilities (ie, life table, Kaplan-Meier) for new users. Given the small number of moderate or higher quality studies for each method and the heterogeneity of study populations, we determined meta-analysis to be inappropriate.
Six studies assessed the calendar-based method with the Standard Days Method or variants. Of these, two were low quality28,65 and four were moderate quality.18,26,53,77 All were conducted in low- to middle-income countries (largely South America) among populations with lower literacy and socioeconomic status. In moderate-quality studies, first-year typical use pregnancy probabilities were 11.2 (95% CI 7.6–14.9), 12.9 (95% CI 8.5–15.3), and 14.1 (95% CI 11.8–16.4).18,26,53 One moderate-quality study reported a first-year perfect use pregnancy probability of 4.8 (95% CI 2.3–7.1).18 Two calendar-based rhythm method studies and one meta-analysis were classified as low quality.55,61,80
We identified three mucus-based Creighton Model studies32,37,41,57 and one meta-analysis,56 all conducted in the United States and Canada. Two studies and the meta-analysis did not provide standard typical use pregnancy estimates. Instead, in these three analyses, pregnancies occurring as a result of intercourse on a day identified by the woman or the couple as fertile were classified by investigators as caused by “achieving [pregnancy]-related behavior.” Achieving-related pregnancies thus included both intended or planned and unintended or unplanned pregnancies, and all these pregnancies were excluded from the effectiveness estimates. By excluding most unintended or unplanned pregnancies from effectiveness calculations, these studies underestimate pregnancy probabilities relative to standard typical use calculations, potentially quite substantially.89 We considered this type of calculation low-quality evidence related to the question of typical use effectiveness. One additional Creighton study provided a standard typical use pregnancy estimate in addition to the described approach but was ranked low for other reasons.37,41 In addition, perfect use pregnancy probabilities were incorrectly calculated in these studies (eg, using all cycles in the denominator rather than only perfect use cycles).
Two studies provided pregnancy probabilities for the mucus-based TwoDay method19,58 and we ranked both moderate quality. These studies were conducted in Guatemala, Peru, and the Philippines among populations characterized by lower literacy and socioeconomic status. One study reported first-year typical use (13.7, 95% CI 9.9–17.3) and perfect use (3.5, 95% CI 1.4–5.5) pregnancy probabilities.19
Fourteen studies evaluated the mucus-based Billings Ovulation Method or variants. We ranked nine low quality20,54,59,62,64,72,84,87,90 and five moderate quality.11,23,70,79,81 Among the moderate-quality studies, one was conducted in the United States, three in low- or middle-income countries, and one was multicountry (New Zealand, India, Ireland, Philippines, El Salvador). The typical use pregnancy probabilities for new users in the first year of use were 10.5 (95% CI 9.1–11.9), 22.4, 22.8, and 33.6.11,23,70,81 Another moderate study reported a pregnancy probability of 2.5 (95% CI 0.9–4.1)79 among experienced users. First-year perfect use pregnancy probabilities included 1.1 (95% CI 0.5–1.7)23 and 3.4.11 A study providing a reanalysis of the multicountry study data (typical use pregnancy probability 22.8 and perfect use probability 3.4) had the most high-quality indicators of any study in our review (11/13).11
We ranked three studies of the mucus-based Modified Mucus Method or variants low quality.29,30,60,79 We ranked one moderate quality; in this study, both the Modified Mucus Method and a simplified local variant of the Modified Mucus Method were assessed,79 but pregnancy probabilities among new users were not provided. Among experienced users, the pregnancy probabilities were 10.3 (95% CI 6.0–14.6) for the Modified Mucus Method and 11.5 (95% CI 5.8–17.2) for the users of the simplified variant. Correctly calculated perfect use estimates were not available.
Women who learn the Marquette Method have the option of using only a cervical mucus monitoring component. We ranked three studies on the Marquette Mucus-only Method, all in the United States, as moderate quality.38,39,44 First-year typical use pregnancy probabilities were 8 and 18.5 for all users39,44 and 4 in a perimenopausal-aged population.38 The first-year perfect use pregnancy probability was 2.7.39
We ranked five basal body temperature–based method studies low quality21,31,46,55,67 and two moderate quality.22,35 A small, moderate-quality study of the Bioself method (a handheld monitor with an internal computer algorithm) reported a first-year pregnancy probability of 9.0 for new users.35 A large, moderate-quality study of an algorithm-based internet application called Natural Cycles generated a first-year typical use pregnancy rate of 9.8 among all new users of the application.22 This estimate was obtained by assuming that the subset of women for whom pregnancy could not be ascertained from prospectively collected pregnancy test data all became pregnant, thus generating a conservative pregnancy rate estimate. Correctly calculated perfect use pregnancy rates were unavailable at the time of our literature search.
Among seven studies investigating single-check symptothermal methods, we ranked four low quality43,59,68,74 and three moderate quality.36,51,83 Only one study reported a first-year typical use pregnancy probability of 13.2.83 Among experienced users in Europe, typical use effectiveness estimates were 17.6 and 8.5 (95% CI 3.6–13.4).36,51 Correctly calculated perfect use pregnancy probabilities were unavailable.
Four studies evaluated double-check symptothermal methods (Thyma and Sensiplan); we ranked all four moderate quality.47,51,70,81 Two evaluated the Thyma method70,81 and reported typical use pregnancy probabilities of 11.2 and 33. Two studies evaluated Sensiplan: one conducted in Germany47 and one multicountry European study51; these two studies had some participant overlap (less than 50%). The pregnancy probability among new users of this method in Germany was 1.8 (95% CI 1.0–2.6).47 In the European multicenter study, the first-year pregnancy probability in new and experienced (40%) users combined was 2.6 (95% CI 1.4–3.8).51 Perfect use pregnancy rates among new users were 0.4 (95% CI 0.1–1.6) among those who used abstinence and 0.6 (95% CI 0.1–2.6) among those who consistently used barrier methods during the fertile time.
One moderate-quality study assessed the symptohormonal Persona urinary hormone monitor method25 and reported a typical use pregnancy probability of 25.6 and a perfect use probability of 12.1 among new users.25 Four studies assessed the symptohormonal Marquette Monitor-only Method (Clearblue Fertility Monitor): we ranked three moderate38,39,44 and one low quality.41 For new users of the Marquette Monitor-only Method, the typical use pregnancy probabilities in moderate-quality studies were 2 and 6.8.39,44 One study reported a perfect use pregnancy probability of 0.39
Four studies (two ranked moderate38,44 and two ranked low quality40,43) assessed users who chose to use the Monitor Plus Mucus form of the symptohormonal Marquette Method. In the moderate-quality studies, the typical use pregnancy probability for new users was 6 in a group of women 40–54 years old38 and 7 in a larger group of women whose mean age was 30 years.44 Correctly calculated perfect use pregnancy probabilities for the Marquette Monitor and Mucus Method were unavailable. The two moderate-quality studies reported perfect use pregnancy probabilities of 1.5–1.6 for users of all three Marquette Methods combined. These were not reported in the table as a result of the combination of methods but are in a similar range of the 0 and 2.7 probabilities reported in the randomized controlled trial for Marquette Monitor Only and Marquette Mucus Only.
Five studies in our review systematically assessed whether participants reported effectiveness estimates for users of barrier methods separately from users of periodic abstinence only. Among these studies, the percent of cycles in which other methods were used ranged from 3% to 55% and the percent of women who ever used barriers ranged from 30% to 46%; however, there were generally no substantive differences in pregnancy estimates for typical and perfect use.18,19,47,51,83 One exception was from a single-check symptothermal method in Europe, in which the typical use pregnancy rate for abstinence users was higher (19.2) than for barrier method users (3.9).51
Seven moderate-quality studies compared users of different fertility awareness–based methods with each other.38,39,44,51,70,79,81 The Marquette Monitor-only method had lower pregnancy rates than the Marquette Mucus-only method in a randomized trial (6.8 vs 18.5), and the Thyma method had lower pregnancy rates than the Billings Ovulation Method in one randomized control trial in the United States (11.2 vs 22.4, multiple decrement life tables, P<.01) but no differently in a second randomized trial in Colombia (33.6 vs 33). Given space limitations, a full description of comparative studies is provided in Appendix 7, available online at http://links.lww.com/AOG/B132.
In clinicaltrials.gov, we identified two ongoing (unpublished) studies; one assessing typical and perfect use effectiveness estimates for Creighton Model users and another assessing effectiveness of a new calendar-based method called Dynamic Optimal Timing.91–93
Our comprehensive systematic review of the effectiveness of fertility awareness–based methods for avoiding pregnancy reveals that the current evidence base for each method is small and of low to moderate quality. Typical use pregnancy probabilities varied between and among methods; correctly calculated perfect use estimates were less common.
One prior review of fertility awareness–based methods (2005) assessed only randomized controlled trials (n=2).13 Randomized trials are ideal for minimizing threats to internal validity; however, randomizing women to various contraceptive methods can raise logistic and, sometimes, ethical concerns.94 A 2011 review included nonrandomized prospective studies but did not comprehensively describe the evidence base.12
We identified several important limitations of the existing literature. No study achieved a high-quality rating across all 13 criteria (Table 2). Key limitations included failure to prospectively and regularly collect pregnancy intentions and inappropriate inclusion or exclusion of pregnancies in effectiveness estimates. An overall limitation of the evidence base is the heterogeneity of populations and settings among the studies. This obscures whether differences in effectiveness estimates are attributable to differences in the methods or in the populations studied. Many studies had high attrition. We were unable to interpret the potential effect of discontinuation on effectiveness estimates as a result of a lack of life table discontinuation rates stratified by discontinuation reasons.
Many people believe they are using a fertility awareness–based method to avoid pregnancy when in fact the method they are using has not undergone a standard prospective effectiveness assessment. Several methods shown in italics in Table 1 (including many increasingly popular internet applications) have no prospective trial data available to support their effectiveness yet are nonetheless being marketed as effective ways to avoid pregnancy.95 We strongly encourage investigation of the effectiveness of any new adaptation of existing fertility awareness–based methods, including internet-based versions. Likewise, users who make their own modifications should be counseled that effectiveness estimates from a specific fertility awareness–based method may not apply to their use of the method.
Strengths of our approach include a comprehensive search strategy in several languages, dyadic screening and abstraction, and careful assessment of quality. The study was further strengthened by assembling multidisciplinary team encompassing a variety of viewpoints. This fostered an environment of “oppositional collaboration,” which enhanced quality and transparency.96 Our approach excluded retrospective population-based surveys, which limits the generalizability of reported effectiveness estimates in our review. However, it provided the advantages of using prospectively collected information and assessing effectiveness estimations for individual fertility awareness–based methods. Systematic assessment of the risk of bias in individual observational studies is necessarily subjective17,97,98; we used an individual component process17 in which quality criteria were modified to be specific to our topic of study. Other investigators might have chosen different criteria or ranked studies differently for specific quality criteria. However, of the studies ranked low quality, all but four24,40,41,57 received more than one “low” ranking (out of 13). Of those ranked moderate, all had more than one reason for not achieving the highest quality ranking. Thus, we think it unlikely that the overall rank of the study would have changed with different reviewer teams. We encourage continued discussion of our quality framework (Appendix 4, http://links.lww.com/AOG/B132).
Clinicians advising patients interested in fertility awareness–based methods can share the effectiveness estimates identified in this review. However, they should note that these estimates are not necessarily applicable to all women or populations nor can they be used to definitively compare effectiveness between methods. Fertility awareness–based methods will continue to be relevant and important for many people for a variety of reasons; obtaining the best possible data, and documenting use in varying populations, is critical.
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