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First, we would like to thank the author, Chelsea B. Polis [1], for her input to the discussion about possibilities and risks of fertility awareness based methods (FABMs) and taking her time to extensively reviewing our work [2]. We have gladly read the commentary by Chelsea B. Polis [1] and will try to answer all questions that address the content and the aim of the original study [2] as well as the data analysis. Within the study, more emphasis was placed on the Pearl-Index (PI) in the abstract and in the discussion compared to the Life-Table Analysis. The main question of the original study was to investigate whether the application of an additional app has an influence on the security and use of the fertility awareness-based method (Daysy). In order to have a baseline to which our hypothesis could be tested, reference was made to a previously published work by Freundl et al. Unfortunately, in this older work, only the PI is comparable. Since Daysy is based on the fertility algorithm of Babycomp and Ladycomp from Valley Electronics, it was claimed that Daysy has a similar PI to these products that are ultimately bounded by the fertility awareness-based method itself. We are aware of the weakness of the PI as a calculation of contraception safety and addressed it accordingly in our manuscript. We agree that a major problem of the PI is that it does not account for the duration of exposure; the PI is reasonably reflective of contraception failure if duration of use is short (i.e. 6 to 12months) and most users use the method for about this period of time. Therefore, we added (as already approached by the journals peer-reviewers) a life-table analysis. In a lifetable analysis (or, in the original study, the equivalent to the Kaplan-Meier approach), a separate failure rate is calculated for each month of use making varying durations of use less problematic. As already published, life-table analysis observed at cycle 13 can roughly be compared to the PI. The Kaplan-Meier approach was used to calculate the overall effectiveness rates. Polis suggests that at least 10 pregnancies occurred to women with fewer than 13 cycles. She does not comment that this subgroup consists of a total of 696 women. Polis further expresses concerns that the investigators did not prospectively collect information regarding perfect or imperfect use of the method for each cycle. We understand this concern, this is why we have already discussed it extensively in the publication itself as a limitation of the study. It is very difficult to carry out a large scale real-life study with a total of 4738 cycles and at the same time have full information about the users. Due to the retrospective nature of the study, it was not possible to determine when and how often users had sexual intercourse on the basis of each cycle. Thus, the calculation of the perfect-use pregnancy rate could only be calculated by analyzing all cycles in which the fertility monitor was correctly used. Thus, we concluded that this could lead to a possible downward bias. Polis further notes that a survey participation rate of 13% is low. Within the study, 6278 women were contacted, 1969 women (31%) followed the invitation, and 798 women (13%) completed the survey. Compared to similar studies, this response rate is quite high.

Clarifications concerning the commentary “Published analysis of contraceptive effectiveness of Daysy and DaysyView app is fatally flawed”