MAR With Artificial Gametes: Treatment Characteristics and Their Trade-offs Determining Treatment Preference

Ovarian Failure Clinical Trial

Official title: Medical Assisted Reproduction With Artificial Gametes in Women With Ovarian Failure: Treatment Characteristics and Their Trade-offs Determining Treatment Preference of Patients and Clinicians

Status Not yet recruiting

Clinical Trial Summary

To gain insight by means of a discrete choice experiment questionnaire into characteristics of medically assisted reproduction (MAR) with artificial gametes (AGs) valued by couples confronted with ovarian failure and their physicians and the trade-offs they make between these treatment characteristics.

Clinical Trial Description

Introduction 3-17% of heterosexual couples trying to conceive will be faced with fertility problems (Boivin et al, 2007). Of these couples 50% will be confronted with a female factor, which includes amongst others ovarian failure (WHO, 2000). Ovarian failure can occur pre-maturely (i.e. before the age of 40 years old, in 1% of women; Coulam, 1982; Coulam et al., 1986) or at a physiologically natural age of after 40 years but before reaching the limit of 44 years old at which modern women that still want children can rely on reimbursed medical assisted reproduction (MAR) in European countries, such as Belgium and the Netherlands.

Although some couples with ovarian failure will have attempted MAR without success, they will be left with IVF with donor ooyctes or embryo reception as only treatment option. These treatment options will not result in genetic parenthood for one or both of the partners.

Researchers are currently developing new forms of MAR that do not require patients to have functional gametes but rely on artificial gametes (AGs) developed by means of different techniques (Hendriks et al, submitted).

Reproductive medicine experts are starting to reflect on the need for minimal thresholds of effectiveness and safety to introduce these and other new forms of MAR into clinical practice (Harper et al, 2012; Schatten, 2002; Winston & Hardy, 2002). Research, however, showed that specific subgroups of infertile patients value other treatment characteristics besides safety and effectiveness, such as, for example, naturalness (Hendriks et al, 2014; De Groot et al, submitted; Lankreijer et al, in preparation). The perspectives of couples with ovarian failure on MAR with AGs has yet to be explored. Clinicians' perspectives on MAR with AGs - valuable because of their expertise and their direct involvement in possible future decision-making - has not been studied. A previous study showed that clinicians differ from patients in their evaluation of the importance of characteristics of fertility clinics (van Empel et al, 2011) and would be interesting to compare the perspective of patients and clinicians on MAR with AGs

Objective The aim is to gain insight into characteristics of MAR with AGs valued by couples confronted with ovarian failure and their physicians and the trade-offs they make between these treatment characteristics.

Methodology The treatment characteristics valued by patients are identified by literature review. Treatment characteristics valued by clinicians will be identified by preparatory qualitative research. The (relative) importance of these treatment characteristics will be examined with a discrete choice experiments analysed with multinomial logistic regression.

The study population will be heterosexual couples confronted with infertility due to ovarian failure between the age of 18 and 44 years old treated in the K.U.Leuven and clinicians who indicated an interest in reproductive medicine in their membership of the Belgian Society for Reproductive Medicine (BSRM).

Both the preparatory qualitative study and discrete choice experiment questionnaire will be preceded by giving written information supported by figures on MAR with AGs (i.e. referred to in the rest of the protocol as 'preceding information on MAR with AGs') which will be pilot tested. This preceding information on MAR with AGs will define MAR with AG and will be exemplified by explaining the possible techniques to create AG and conceive a child (appendix 3).

The preparatory qualitative study Physicians treating heterosexual couples confronted with infertility due to ovarian failure will be selected from the professional network of the authors, resulting in a convenience sample. Clinicians will be interviewed at their clinic.

All interviews will be conducted by a female interviewer (SH) who is familiar with all aspects of the treatment options but not involved in patient care. The interview will start with the preceding information on MAR with AGs'. The in-depth interviews will take 30-60 min and will be guided by a semi-structured interview guide and a topic list developed based on the literature on the biology of AG (Hendriks et al, submitted), on the consequences of the clinical application of AGs (Hendriks et al, submitted), and previous qualitative and quantitative research on the importance of treatment characteristics for patients (Hendriks et al., 2013; Lankrijker et al, in preperation; Hendriks et al, in preperation).

Interviews will be recorded, transcribed verbatim and analyzed with content analysis by two researchers independently.

As appropriate for qualitative research, the number of interviews per group (i.e. couples and physicians) will be defined by the achievement of data saturation per group (i.e. when a sense of closure is achieved because no new themes answering the research question emerged in three successive interviews; Francis et al., 2010; Pope et al., 2000; Tong et al., 2007).

Part 2: Discrete choice experiment (DCE) A discrete choice experiment questionnaire (DCE-Q) will be designed based on the results of the preparatory qualitative study, incorporating all identified valued treatment characteristics. A DCE aims to identify attributes (in this case treatment characteristics) significantly affecting choice and trade-offs of all attributes with one attribute generally considered the most important (in this case, either pregnancy rate or safety (Dancet et al., 2013), depending on the insights gathered by the qualitative study.

A discrete choice experiment (DCE) is the best available method to investigate the relative importance of characteristics of multi-dimensional concepts (e.g. quality of care, characteristics of fertility treatments) and allows the calculation of respondents trade-offs between characteristics (Ryan and Farrar, 2000; Bryan and Parry, 2001; Sculpher et al., 2004; Telser and Zweifel, 2007; Albada and Triemstra, 2009). In a DCE, respondents have to choose repeatedly between choice sets, each described by characteristics with varying levels.

In this DCE-Q respondents will be asked to choose between choice sets developed to represent the hypothetical but realistic fertility treatments based on AGs. The fertility treatments will be described by a number attributes that can each vary across a number of levels (e.g. pregnancy rate varying between 20% and 35%). The attributes will be the valued treatment characteristics identified by the preparatory qualitative study in couples and physicians. The levels over which the attributes can vary in the description of the hypothetical fertility treatments will reflect a range realistic for current MAR and future MAR with AGs (Hendriks et al, submitted).

A mathematical model (i.e. a fractional factorial design, which is both orthogonal and balanced, created according to published principles; Street and Burgess, 2007) will define how many of all combinations of attributes and levels will be questioned. To realize 'choice sets' (i.e. define to which hypothetical fertility treatment to compare each selected combination) with maximum differentiation between the compared hypothetical fertility treatments, a fold-over technique will be applied to result in 'mirror' scenarios. We will make sure that the efficiency of the final design, calculated according to Street and Burgess (2010b), will ensure 100% informative value.

We will make sure that maximal 17 choice sets (Sculpher et al., 2004; Christofides et al., 2006; Bech et al., 2010) are presented in each questionnaire, if necessary choice sets will be divided over different questionnaires.

Four DCE-Q questionnaire addenda will be developed in addition to the preceding information on MAR with AGs. First, to clarify the DCE method, the DCE-Q will be preceded by detailed instructions. Couples and physicians will be explained that from each choice set they need to select the hypothetical fertility treatment which they prefer. An example choice set, where respondents have to select their preferred airline ticket for a holiday will be exemplifying. Second, a form to collect demographic characteristics and professional characteristics or medical characteristics, for physicians or couples, respectively will be developed. Third, to test the face-validity of the modelled treatment characteristics, respondents will be asked for any additional treatment characteristics on which they would have liked to be informed to choose between fertility treatments. Fourth and only applicable to couples, not to physicians, couples' actual past choice behaviour will be examined by asking them which fertility treatments they have opted for, and for which reasons they decided for or against the offered treatment options.

The DCE-Q and its addenda will be distributed by post. With regards to couples, all couples of which the woman was diagnosed with ovarian failure between October 2009 and October 2014 at the K.U.Leuven will be addressed. With regards to physicians, all physicians who indicated an interest in reproductive medicine in their membership of the Belgian Society for Reproductive Medicine (BSRM) will be addressed. Couples will be requested to fill out the questionnaire addenda together and to each fill out the DCE-Q separately. Physicians will be requested to fill out the questionnaire individually. The questionnaire will be coded, so that respondents who do not reply either by filling out the questionnaire or the statement of non-participation, can be send a maximum of two reminders. Prior to filling out the questionnaire respondents will be informed on the purpose of the study and provided with contact information. This way participation results in giving informed consent.

Data of incoming questionnaires will be entered in the Statistical Package for the Social Sciences (SPSS; version 21.0 for Mac, Chicago, IL, USA). For analysis of the DCE-Q the data will be exported to the STATA Software (version 11.1.). Data from couples and physicians will be analysed separately. P-values of <0.05 will be considered statistically significant.

The data gathered from the DCE-Q addenda will be described with descriptive analyses (e.g. demographic characteristics) or content analysis (e.g. question on missed treatment characteristics).

The data gathered with the DCE-Q will be analyzed with multinomial logistic regression. For each treatment characteristic, analyses will examine whether it contributes significantly to respondents preference. Trade-offs that respondents are willing to make between pregnancy rate and any other attribute (i.e. the willingness to trade-off pregnancy rate; WTpreg) will be calculated as pregnancy rate is considered the 'gold standard' to benchmark the other fertility treatment characteristics (van Empel et al, 2011). Confidence intervals (95%) for the WTpreg were computed using a non-parametric bootstrap approach (2000 replications).

To investigate heterogeneity in preferences between subgroups of couples or physicians, we will included interaction terms in the model (i.e. confounders' tests). Furthermore, the results of the analysis of the data of the couples will be compared with the results of the analysis of the data of the physicians. ;

Study Design

Observational Model: Cohort, Time Perspective: Cross-Sectional

Related Conditions & MeSH terms

• Ovarian Failure

• NCT number: NCT02280681
• Study type: Observational [Patient Registry]
• Source: Universitaire Ziekenhuizen Leuven
• Status: Not yet recruiting
• Phase: N/A
• Start date: October 2014
• Completion date: October 2015