Advantages of determining the fertile window with the individualised Natural Cycles algorithm over calendar-based methods

Abstract Purpose: This study aims to compare the accuracy of fertile window identification with the contraceptive app Natural Cycles against the Rhythm Method and Standard Days Method (SDM). Materials and methods: Menstruation dates, basal body temperature (BBT), and luteinising hormone (LH) test results were collected anonymously from Natural Cycles app users. The fraction of green days (GDs) and wrong green days (WGDs) allocated by the various algorithms was determined over 12 cycles. For comparison of Natural Cycles and the Rhythm Method, 26,626 cycles were analysed. Results: Natural Cycles’ algorithms allocated 59% GDs (LH, BBT) in cycle 12, while the fraction of WGDs averaged 0.08%. The Rhythm Method requires monitoring of six cycles, resulting in no GDs or WGDs in cycle 1–6. In cycle 7, 49% GDs and 0.26% WGDs were allocated. GDs and WGDs decreased to 43% and 0.08% in cycle 12. The probabilities of WGDs on the day before ovulation with Natural Cycles were 0.31% (BBT) and 0% (LH, BBT), and 0.80% with the Rhythm Method. The probability of WGDs on the day before ovulation was 6.90% with the SDM. Conclusions: This study highlights that individualised algorithms are advantageous for accurate determination of the fertile window and that static algorithms are more likely to fail during the most fertile days