Efficacy and Safety of On-Demand Use of 2 Treatments Designed for Different Etiologies of Female Sexual Interest/Arousal Disorder: 3 Randomized Clinical Trials

Personalizing medicine in Africa: current state, progress and challenges

Personalized medicine has been identified as a powerful tool for addressing the myriad of health issues facing different health systems globally. Although recent studies have expanded our understanding of how different factors such as genetics and the environment play significant roles in affecting the health of individuals, there are still several other issues affecting their translation into personalizing health interventions globally. Since African populations have demonstrated huge genetic diversity, there is a significant need to apply the concepts of personalized medicine to overcome various African-specific health challenges. Thus, we review the current state, progress, and challenges facing the adoption of personalized medicine in Africa with a view to providing insights to critical stakeholders on the right approach to deploy.

A comparison of the multilevel MIMIC model to the multilevel regression and mixed ANOVA model for the estimation and testing of a cross-level interaction effect: A simulation study

When observing data on a patient-reported outcome measure in, for example, clinical trials, the variables observed are often correlated and intended to measure a latent variable. In addition, such data are also often characterized by a hierarchical structure, meaning that the outcome is repeatedly measured within patients. To analyze such data, it is important to use an appropriate statistical model, such as structural equation modeling (SEM). However, researchers may rely on simpler statistical models that are applied to an aggregated data structure. For example, correlated variables are combined into one sum score that approximates a latent variable. This may have implications when, for example, the sum score consists of indicators that relate differently to the latent variable being measured. This study compares three models that can be applied to analyze such data: the multilevel multiple indicators multiple causes (ML-MIMIC) model, a univariate multilevel model, and a mixed analysis of variance (ANOVA) model. The focus is on the estimation of a cross-level interaction effect that presents the difference over time on the patient-reported outcome between two treatment groups. The ML-MIMIC model is an SEM-type model that considers the relationship between the indicators and the latent variable in a multilevel setting, whereas the univariate multilevel and mixed ANOVA model rely on sum scores to approximate the latent variable. In addition, the mixed ANOVA model uses aggregated second-level means as outcome. This study showed that the ML-MIMIC model produced unbiased cross-level interaction effect estimates when the relationships between the indicators and the latent variable being measured varied across indicators. In contrast, under similar conditions, the univariate multilevel and mixed ANOVA model underestimated the cross-level interaction effect.

Female sexual dysfunctions: an overview on the available therapeutic interventions

INTRODUCTION

There are different types of female sexual dysfunctions (FSDs), and FSD in general has a high prevalence worldwide. Studies of FSD should consider it as a multifactorial disorder that has biological, psychological, environmental, and relational aspects. In this review we discuss the available therapeutic interventions for FSD.

EVIDENCE ACQUISITION

For the current narrative review the PubMed database was searched to identify all publications up to 30 March 2021 that were systematic reviews and meta-analyses which examined therapeutic interventions for FSDs based on the diagnostic classifications of ICD-10 and ICD-11.

EVIDENCE SYNTHESIS

Thirty systematic reviews and meta-analyses were included in this review. Hormone therapy (HT) and testosterone are effective to improve sexual desire in menopausal women. In these women HT and ospemiphene may improve pain during intercourse. Flibanserin may improve sexual desire and may reduce desire-related distress in premenopausal women. Bremelanotide is effective to improve desire, arousal, and orgasm scores. Evidence are still limited on the efficacy of psychoactive drugs, phosphodiesterase type 5 (PDE5), oxytocin, herbal drugs, and tibolone to treat FSDs. Psychological interventions such as cognitive-behavior therapy, mindfulness training, sensate focus, bibliotherapy are effective for the management of several different FSDs.

CONCLUSIONS

The management of FSDs may require multidisciplinary and interdisciplinary approaches. Pharmacological and nonpharmacological interventions appears to have potential as a treatment for FSDs, but there are currently no gold standards regarding recommended treatment modalities, and the duration, frequency, and intensity of therapy sessions.

Bremelanotide for Treatment of Female Hypoactive Sexual Desire

Hypoactive sexual desire disorder (HSDD) is a persistent deficiency or absence of sexual fantasies and desire resulting in significant distress or interpersonal difficulty. Women with this disorder may display a lack of motivation for sexual activity, reduced responsiveness to erotic cues, a loss of interest during sexual activity, and avoidance of situations that could lead to sexual activity. The pathophysiology of HSDD is thought to be centered around inhibitory and excitatory hormones, neurotransmitters, and specific brain anatomy. Due to the multifactorial nature of HSDD, treatment can be complex and must attempt to target the biological and psychosocial aspects of the disorder. Bremelanotide is a melanocortin receptor agonist and has been recently approved by the FDA to treat HSDD. Bremelanotide is administered intranasally or as a subcutaneous injection. The recommended dosage of bremelanotide is 1.75 mg injected subcutaneously in the abdomen or thigh at least 45 min before sexual activity. Studies showed improvements in desire, arousal, and orgasm scores when 1.75 mg of bremelanotide was administered before sexual activity compared to a placebo. Bremelanotide is a promising way to treat HSDD.

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 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.

Testosterone therapy and other treatment modalities for female sexual dysfunction

PURPOSE OF REVIEW

Recently in October 2019 a Global Consensus Position on the use of Testosterone Therapy for Women was published. The use of testosterone and other agents for female sexual dysfunction (FSD) is an important topic for the urologist focusing on sexual health. This review describes the known causes for FSD, and discusses the role of androgens in this disorder, the evidence for using testosterone treatment, and other current and emerging therapies.

RECENT FINDINGS

A recent meta-analysis, published in The Lancet Diabetes & Endocrinology evaluated a total of 36 randomized control trials spanning 1990-2018 and includes a total of 8480 patients. The primary findings were that testosterone therapy (TTh) increased sexual function including satisfactory sexual event frequency, sexual desire, pleasure, arousal, orgasm, responsiveness, and self-image when compared with either a placebo or drug-control (e.g., estrogen ± progestogen). In addition, TTh reduced sexual concerns and distress in postmenopausal women. Side effects included an increase in weight, acne, and hair growth, but there was no increase in serious adverse events. Importantly, TTh duration was greater than 12 weeks in all randomized control trials included in this meta-analysis.

SUMMARY

TTh is effective to treat FSD in postmenopausal women. More data is required to evaluate the long-term safety data on the effects of TTh on cardiovascular health, breast health, cognitive function, and the musculoskeletal system in women.

Multilevel analyses of on-demand medication data, with an application to the treatment of Female Sexual Interest/Arousal Disorder

Data from clinical trials investigating on-demand medication often consist of an intentionally varying number of measurements per patient. These measurements are often observations of discrete events of when the medication was taken, including for example data on symptom severity. In addition to the varying number of observations between patients, the data have another important feature: they are characterized by a hierarchical structure in which the events are nested within patients. Traditionally, the observed events of patients are aggregated into means and subsequently analyzed using, for example, a repeated measures ANOVA. This procedure has drawbacks. One drawback is that these patient means have different standard errors, first, because the variance of the underlying events differs between patients and second, because the number of events per patient differs. In this paper, we argue that such data should be analyzed by applying a multilevel analysis using the individual observed events as separate nested observations. Such a multilevel approach handles this drawback and it also enables the examination of varying drug effects across patients by estimating random effects. We show how multilevel analyses can be applied to on-demand medication data from a clinical trial investigating the efficacy of a drug for women with low sexual desire. We also explore linear and quadratic time effects that can only be performed when the individual events are considered as separate observations and we discuss several important statistical topics relevant for multilevel modeling. Taken together, the use of a multilevel approach considering events as nested observations in these types of data is advocated as it is more valid and provides more information than other (traditional) methods.

Testosterone therapy for women with low sexual desire: a position statement from the Brazilian Society of Endocrinology and Metabolism

OBJECTIVE

To summarize current evidence regarding testosterone treatment for women with low sexual desire.

MATERIALS AND METHODS

The Female Endocrinology and Andrology Department of the Brazilian Society of Endocrinology and Metabolism invited nine experts to review the physiology of testosterone secretion and the use, misuse, and side effects of exogenous testosterone therapy in women, based on the available literature and guidelines and statements from international societies.

RESULTS

Low sexual desire is a common complaint in clinical practice, especially in postmenopausal women, and may negatively interfere with quality of life. Testosterone seems to exert a positive effect on sexual desire in women with sexual dysfunction, despite a small magnitude of effect, a lack of long-term safety data, and insufficient evidence to make a broad recommendation for testosterone therapy. Furthermore, there are currently no testosterone formulations approved for women by the relevant regulatory agencies in the United States, Brazil, and most other countries, and testosterone formulations approved for men are not recommended for use by women.

CONCLUSION

Therefore, testosterone therapy might be considered if other strategies fail, but the risks and benefits must be discussed with the patient before prescription. Arch Endocrinol Metab. 2019;63(3):190-8.

Expert opinion on existing and developing drugs to treat female sexual dysfunction

INTRODUCTION

Female sexual dysfunction (FSD) is a highly prevalent, yet commonly underdiagnosed and undertreated condition. This paper reviews the diagnostic terminology for FSD, and basic sexual physiology in women. The Food and Drug Administration (FDA) approved drugs for FSD are discussed, followed by investigational drugs for FSD currently in phase 2 or 3 clinical trials, reasons for failure of drug development, and potential future drug targets. Areas covered: A literature review was conducted for available treatments for FSD: flibanserin, estrogen, ospemifene and prasterone. Potential treatments are assessed, as was the Pharmaprojects database which includes clinical trial information. Testosterone, bremelanotide, bupropion-trazodone, PDE-5 inhibitors, prostaglandins, tibolone and combination therapies, and the theoretical basis of potential drug targets are discussed. Expert opinion: The lack of established endpoints for phase 3 studies of FSD has impeded approval of new treatments, and required additional studies for validation, resulting in proposed changes to the FDA draft guidance for FSD clinical trials in October 2016. Current DSM-5 diagnostic nosology also fails to capture the full range of symptomology. Several promising compounds have shown no movement for several years limiting women's options. Overcoming socio-cultural bias against women's sexual and reproductive health will be critical in the approval of new treatments for FSD.

Effects of testosterone administration on threat and escape anticipation in the orbitofrontal cortex

Recent evidence suggests that the steroid hormone testosterone can decrease the functional coupling between orbitofrontal cortex (OFC) and amygdala. Theoretically this decoupling has been linked to a testosterone-driven increase of goal-directed behaviour in case of threat, but this has never been studied directly. Therefore, we placed twenty-two women in dynamically changing situations of escapable and inescapable threat after a within-subject placebo controlled testosterone administration. Using functional magnetic resonance imaging (fMRI) we provide evidence that testosterone activates the left lateral OFC (LOFC) in preparation of active goal-directed escape and decouples this OFC area from a subcortical threat system including the central-medial amygdala, hypothalamus and periaqueductal gray. This LOFC decoupling was specific to threatening situations, a point that was further emphasized by an absence of such decoupling in a second experiment focused on resting-state connectivity. These results not only confirm that testosterone administration decouples the LOFC from the subcortical threat system, but also show that this is specifically the case in response to acute threat, and ultimately leads to an increase in LOFC activity when the participant prepares a goal-directed action to escape. Together these results for the first time provide a detailed understanding of functional brain alterations induced by testosterone under threat conditions, and corroborate and extend the view that testosterone prepares the brain for goal-directed action in case of threat.

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.