Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Kessels R

PROVIDER: S-EPMC6695215 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Kessels Rob R Bloemers Jos J Tuiten Adriaan A van der Heijden Peter G M PGM

PloS one 20190815 8

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. Traditiona ...[more]

PMID: 31415608

Similar Datasets

Project description: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.

Project description:BackgroundFor the treatment of female sexual dysfunction, the most relevant outcome measures are patient-reported treatment effects and changes in symptoms, underscoring the need for reliable, validated patient-reported outcome (PRO) instruments. The aim of this study was to evaluate the psychometric characteristics (validity and reliability) of the Female Sexual Distress Scale-Desire/Arousal/Orgasm (FSDS-DAO) PRO measure, which was adapted from the validated FSDS-Revised (FSDS-R) questionnaire and added 2 questions involving arousal and orgasm.MethodsPsychometric analyses were based on the data from a multicenter phase 2b dose-finding study that compared the safety and efficacy of bremelanotide versus placebo and were conducted in the evaluable modified intent-to-treat population (N = 325) from that study. Psychometric evaluation of the new items in the FSDS-DAO included confirmatory factor analyses, tests of internal consistency and test-retest reliability, examinations of convergent and discriminant validity, and determination of responsiveness. The validity of the FSDS-DAO was evaluated based on previously developed instruments, including the Female Sexual Function Index (FSFI), General Assessment Questionnaire (GAQ), Women's Inventory of Treatment Satisfaction (WITS-9), and Female Sexual Encounter Profile-Revised (FSEP-R).ResultsConfirmatory factor analyses demonstrated that the FSDS-DAO items fit very well (Bentler's comparative fit index of 0.929). Cronbach's α for the FSDS-DAO total score was ≥ 0.91 at Visits 1, 2, 5, and 12, demonstrating adequate internal consistency reliability. Test-retest reliability was acceptable with an intra-class coefficient of 0.61 and a Spearman's correlation coefficient score of 0.62 between Visits 1 and 2 (4 weeks). Acceptable construct validity was demonstrated by significant correlations with related PRO scales in the expected directions and magnitude. For example, participants reporting the worst levels of sexual function on the FSFI also showed the worst FSDS-DAO scores at Visits 5 and 12. The FSDS-DAO total score was responsive to change.ConclusionsEvidence supports the validity and reliability of the FSDS-DAO for assessing sexually related distress in women with female sexual arousal disorder and/or hypoactive sexual desire disorder; the addition of the arousal and orgasm items did not impact the validity and reliability of the measure. Clinical Trial Registration ClinicalTrials.gov NCT01382719.

Project description:Very little has been elucidated about sexual interest in female-to-male (FtM) transsexual persons.To investigate the sexual interest of FtM transsexual persons vs that of men using an eye-tracking system.The study included 15 men and 13 FtM transsexual subjects who viewed three sexual videos (clip 1: sexy clothed young woman kissing the region of the male genitals covered by underwear; clip 2: naked actor and actress kissing and touching each other; and clip 3: heterosexual intercourse between a naked actor and actress) in which several regions were designated for eye-gaze analysis in each frame. The designation of each region was not visible to the participants.Visual attention was measured across each designated region according to gaze duration.For clip 1, there was a statistically significant sex difference in the viewing pattern between men and FtM transsexual subjects. Longest gaze time was for the eyes of the actress in men, whereas it was for non-human regions in FtM transsexual subjects. For clip 2, there also was a statistically significant sex difference. Longest gaze time was for the face of the actress in men, whereas it was for non-human regions in FtM transsexual subjects, and there was a significant difference between regions with longest gaze time. The most apparent difference was in the gaze time for the body of the actor: the percentage of time spent gazing at the body of the actor was 8.35% in FtM transsexual subjects, whereas it was only 0.03% in men. For clip 3, there were no statistically significant differences in viewing patterns between men and FtM transsexual subjects, although longest gaze time was for the face of the actress in men, whereas it was for non-human regions in FtM transsexual subjects.We suggest that the characteristics of sexual interest of FtM transsexual persons are not the same as those of biological men. Tsujimura A, Kiuchi H, Soda T, et al. The Pattern of Sexual Interest of Female-to-Male Transsexual Persons With Gender Identity Disorder Does Not Resemble That of Biological Men: An Eye-Tracking Study. Sex Med 2017;5:e169-e174.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure