Psychometric Properties of the Sexual Event Diary in a Sample of Dutch Women With Female Sexual Interest/Arousal Disorder

A multilevel structural equation model for assessing a drug effect on a patient-reported outcome measure in on-demand medication data

We analyze data from a clinical trial investigating the effect of an on-demand drug for women with low sexual desire. These data consist of a varying number of measurements/events across patients of when the drug was taken, including data on a patient-reported outcome consisting of five items measuring an unobserved construct (latent variable). Traditionally, these data are aggregated prior to analysis by composing one sum score per event and averaging this sum score over all observed events. In this paper, we explain the drawbacks of this aggregating approach. One drawback is that these averages have different standard errors because the variance of the underlying events differs between patients and because the number of events per patient differs. Another drawback is the implicit assumption that all items have equal weight in relation to the latent variable being measured. We propose a multilevel structural equation model, treating the events (level 1) as nested observations within patients (level 2), as alternative analysis method to overcome these drawbacks. The model we apply includes a factor model measuring a latent variable at the level of the event and at the level of the patient. Then, in the same model, the latent variables are regressed on covariates to assess the drug effect. We discuss the inferences obtained about the efficacy of the on-demand drug using our proposed model. We further illustrate how to test for measurement invariance across grouping covariates and levels using the same model.

A Systematic Literature Review of Health-related Quality of Life Measures for Women with Hypoactive Sexual Desire Disorder and Female Sexual Interest/Arousal Disorder

INTRODUCTION

Hypoactive Sexual Desire Disorder (HSDD) / Female Sexual Interest/Arousal Disorder (FSIAD) impacts health-related quality of life (HRQoL) of women and their partners, yet existing measures fail to adequately capture relevant concepts (ie, what is essential to measure including symptoms/impacts) important to women with HSDD/FSIAD.

OBJECTIVES

To identify HRQoL tools used to assess women with HSDD/FSIAD, and to evaluate their psychometric properties (ie, reliability, validity, and responsiveness).

METHODS

We conducted searches in PubMed, Embase and PsychINFO from June 5, 1989 to September 30, 2020 for studies in women with HSDD/FSIAD and psychometric analyses (English only). Principles of the Preferred Reporting Items for Systematic reviews and Meta-Analyses, the COnsensus-based Standards for the selection of health Measurement INstruments Risk of Bias Checklist and other psychometric criteria were applied. Based on this search, 56 papers were evaluated including 15 randomized-controlled trials, 11 observational/single arm/open label studies, and 30 psychometric studies.

RESULTS

Of the 18 measures identified, the Female Sexual Function Index (FSFI) and Female Sexual Distress Scale-Revised (FSDS-R) were included in most studies (> 50%). General HRQoL instruments were not used in any of the clinical trials; the SF-12, SF-36 and EQ-5D-5L were reported in two observational studies. No instruments achieved positive quality ratings across all psychometric criteria. The FSFI, FSDS-R, Sexual Event Diary (SED) and the Sexual Desire Relationship Distress Scale (SDRDS), were the only measures to receive a positive rating for content validity.

CONCLUSION

Reliable and valid HRQoL measures that include sexual desire and distress are needed to provide a more systematic and comprehensive assessment of HRQoL and treatment benefits in women with HSDD/FSIAD. While inferences about HRQoL are limited due to the lack of uniformity in concepts assessed and limited psychometric evaluation of these measures in women with HSDD/FSIAD, opportunities exist for the development of reliable and validated tools that comprehensively measure the most relevant and important concepts in women with HSDD/FSIAD. Lim-Watson MZ, Hays RD, Kingsberg S, et al. A systematic literature review of health-related quality of life measures for women with Hypoactive Sexual Desire Disorder and Female Sexual Interest/Arousal Disorder. Sex Med Rev 2021;XX:XXX-XXX.

A survival of the fittest strategy for the selection of genotypes by which drug responders and non-responders can be predicted in small groups

Phenotype Prediction Scores (PPS) might be powerful tools to predict traits or the efficacy of treatments based on combinations of Single-Nucleotide Polymorphism (SNPs) in large samples. We developed a novel method to produce PPS models for small samples sizes. The set of SNPs is first filtered on those known to be relevant in biological pathways involved in a clinical condition, and then further filtered repeatedly in a survival strategy to select stabile positive/negative risk alleles. This method is applied on Female Sexual Interest/Arousal Disorder (FSIAD), for which two subtypes has been proposed: 1) a relatively insensitive excitatory system in the brain for sexual cues, and 2) a dysfunctional activation of brain mechanisms for sexual inhibition. A double-blind, randomized, placebo-controlled cross-over experiment was conducted on 129 women with FSIAD. The women received three different on-demand drug-combination treatments during 3 two-week periods: testosterone (0.5 mg) + sildenafil (50 mg), testosterone (0.5 mg) + buspirone (10 mg), or matching placebos. The resulted PPS were independently validated on patient-level and group-level. The AUC scores for T+S of the derivation set was 0.867 (95% CI = 0.796-0.939; p<0.001) and was 0.890 (95% CI = 0.778-1.000; p<0.001) on the validation set. For T+B the AUC of the derivation set was 0.957 (95% CI = 0.921-0.992; p<0.001) and 0.869 (95% CI = 0.746-0.992; p<0.001) for the validation set. Both formulas could reliably predict for each drug who benefit from the on-demand drugs and could therefore be useful in clinical practice.

Genotype scores predict drug efficacy in subtypes of female sexual interest/arousal disorder: A double-blind, randomized, placebo-controlled cross-over trial

Attempts to develop a drug treatment for female sexual interest/arousal disorder have so far been guided by the principle of ‘one size fits all’, and have failed to acknowledge the complexity of female sexuality. Guided by personalized medicine, we designed two on-demand drugs targeting two distinct hypothesized causal mechanisms for this sexual disorder. The objective of this study was to design and test a novel procedure, based on genotyping, that predicts which of the two on-demand drugs will yield a positive treatment response. In a double-blind, randomized, placebo-controlled cross-over experiment, 139 women with female sexual interest/arousal disorder received three different on-demand drug-combination treatments during three 2-week periods: testosterone 0.5 mg + sildenafil 50 mg, testosterone 0.5 mg + buspirone 10 mg, and matching placebo. The primary endpoint was change in satisfactory sexual events. Subjects’ genetic profile was assessed using a microarray chip that measures 300,000 single-nucleotide polymorphisms. A preselection of single-nucleotide polymorphisms associated with genes that are shown to be involved in sexual behaviour were combined into a Phenotype Prediction Score. The Phenotype Prediction Score demarcation formula was developed and subsequently validated on separate data sets. Prediction of drug-responders with the Phenotype Prediction Score demarcation formula gave large effect sizes (d = 0.66 through 1.06) in the true drug-responders, and medium effect sizes (d = 0.51 and d = 0.47) in all patients (including identified double, and non-responders). Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the Phenotype Prediction Score demarcation formula were all between 0.78 and 0.79, and thus sufficient. The resulting Phenotype Prediction Score was validated and shown to effectively and reliably predict which women would benefit from which on-demand drug, and could therefore also be useful in clinical practice, as a companion diagnostic establishing the way to a true personalized medicine approach.