Journal of Multiple Sclerosis

Is Gender Associated to Extended Cardiac Monitoring after First Dose of Fingolimod and Level of Satisfaction with the Monitoring Experience in Relapsing-Remitting Multiple Sclerosis Patients? A Post-hoc Analysis of the BEAT Study

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Introduction

Sphingosine 1-phosphate (S1P) is a soluble signalling molecule deriving from the phosphorylation of sphingosine by sphingosine kinases that are ubiquitously expressed [1,2]. Through its interaction with the sphingosine 1-phosphate receptor (S1PR), S1P is involved in immunological, cardiovascular, and neurological processes. There are five S1PR subtypes (S1PR1-5), expressed in various cell types, such as lymphocytes, neurons, endothelial cells, myocytes and implicated in several immune-mediated disorders, such as rheumatoid arthritis, inflammatory bowel diseases, and multiple sclerosis (MS) [3-6]. Animal and human studies have suggested the presence of a disturbance in sphingolipid metabolism in MS patients [7,8].

Fingolimod has been the first S1PR modulator to receive regulatory approval as second-line treatment for the treatment of relapsingremitting multiple sclerosis (RRMS). Fingolimod is a sphingosine 1-phosphate receptor modulator that inhibits the infiltration of potentially autoreactive lymphocytes from lymph nodes to the central nervous system (CNS). Fingolimod exerts its action by functionally antagonizing S1P-receptors (S1PRs) expressed on lymphocytes and reducing infiltration of autoreactive lymphocytes into the CNS, where they can induce inflammation and tissue damage [8,9]. These As these receptors are expressed in various tissues, including cardiac tissues, possibly causing transitory effects on heart rate (HR) and atrioventricular (AV) conduction, sometimes accompanied by a decrease in blood pressure (BP) [10,11]. These effects may result in bradycardia and AV blocks [12-16] and occur mainly following the first administration, as the fingolimod agonistic activity on S1P1 produces then a rapid receptor internalization and degradation. Therefore, it is recommended that all patients have an ECG and blood pressure measurement performed before and 6 hours after the first administration of the drug and that, in case of bradycardia, monitoring is extended until abnormal ECG signs and related symptoms are resolved (Gilenya, Summary of Product Characteristics).

New agents selectively targeting subtype 1 of the S1PR, aimed at achieving better efficacy and reducing safety concerns, are currently in different stages of development, including ponesimod, siponimod, ozanimod, ceralifimod, and amiselimod, with promising phase IIIII clinical trials results [17]. However, at the moment, no secondgeneration S1PR modulators have yet been approved.

The BEAT observational study [18] was aimed at characterizing the patients with RRMS for whom an extension of monitoring was required after routine first fingolimod dosing (FFD), in order to understand whether autonomic factors contribute to the heart rate (HR) effects. The study showed that the baseline autonomic profile, in particular the dominance of cardiac vagal modulation, does not represent a risk factor for rate or rhythm complications but can help identifying patients with higher probability to require monitoring beyond the first 6 hours after FFD.

It has been shown since several years that male and female patients exhibit differences regarding the pharmacology and toxicity of medications, and may differ in their response to drug treatment, not only as a result of physiological differences, such as body weight, surface area, extracellular and intracellular water, but also in terms of differences in pharmacokinetics and pharmacodynamics [19-22]. Sex and gender differences in the efficacy and tolerability of several types of pharmacological treatments have been extensively reported [23-30], however, this topic continues to draw limited attention. Since some years, Novartis has undertaken a wide gender-medicine project, called MetaGeM, with the purpose to evaluate gender differences that occur in therapeutic approaches, clinical outcomes, and safety parameters, by means of post-hoc analyses and meta-analyses of previously conducted observational trials. The MetaGeM project includes 12 Italian observational studies in different clinical areas, including immune-mediate disorders, organ transplants, and infectious, CNS, cardiovascular and respiratory diseases, performed between 2002 and 2016. Within the MetaGeM project, a post-hoc analysis of the BEAT study results has been performed with the following objectives: (i) assessing the association between gender and need of extension of the ECG monitoring, taking into consideration the effect of other variables having a statistically or clinically relevant impact on ECG monitoring prolongation; (ii) describing the gender-related differences in the degree of patients’ satisfaction with FFD and monitoring experience, and assessing the association between gender and degree of satisfaction.

Methods

BEAT was an observational, prospective, multicentre study with duration limited to the observation period following FFD, i.e. 6 hours in the routine cases or up to 24 hours (or until resolution of the signs and symptoms) if an extension of the monitoring period was required. Before drug administration a continuous ECG recording of at least 15 minutes was performed, followed by clinical and ECG continuous monitoring over 6 hours after FFD. Adult outpatients of both sexes diagnosed with RRMS, for whom the decision to start treatment with fingolimod had already been taken, based on clinical judgment and regardless of the decision to recruit the patient into the study, were enrolled in the BEAT study. Early and permanent discontinuation of fingolimod in a previous fingolimod trial due to adverse event (AE) or serious adverse event (SAE) represented the main exclusion criterion. The study was performed in accordance with the Declaration of Helsinki and was approved by the local Ethic Committees of the centers involved in the study. All participants gave their written informed consent prior to their inclusion in the study. HR variability (HRV) data were obtained analyzing ECG registrations by means of dedicated software. Detailed study design, objectives, methods, and overall results have been reported elsewhere [18].

Patients’ satisfaction with the FFD monitoring experience was assessed by means of an ad-hoc 13-item questionnaire, administered to each patient at the end of the ECG monitoring. Only 10 items were suitable for the gender analysis (items 1-8, 10, and 11) (Table 1), since they have numerically coded answers evaluating some attributes of the monitoring experience (e.g. ease, satisfaction, inconvenience) or patient feelings (e.g. nervousness); items range between 0 (not at all, none) and 10 (extremely, all) and the score of items #1, 4, 5, 7, 8, 10, 11 increases with treatment satisfaction, while the score of items #2, 3, 6 decreases while treatment satisfaction increases. The remaining three items (# 9, 12, 13) require open answers (about patient advice to other patients to improve the use of time during monitoring, on the advantages of oral therapy in allowing to carry out daily activities, and 5 words to describe the monitoring experience, respectively) and were thus not suitable for the patients’ satisfaction total score calculation.

Table 1: Questionnaire on patients’ satisfaction with fingolimod first-dose monitoring experience (items involved in satisfaction score calculation)

Statistical methods

All patients evaluated in the statistical analysis of the BEAT study were considered in this gender analysis, i.e. all patients fulfilling the study inclusion/exclusion criteria, having received the FFD, and for whom data about the decision to stop or extend the ECG monitoring beyond 6 hours were available. Missing values were not replaced and did not contribute to the analysis of the variable. The continuous, normally distributed variables were expressed as a mean and standard deviation (SD); in case of not normally distributed parameters, median and interquartile range (IQR) were provided; for qualitative data, absolute and relative frequencies were calculated.

First of all, some exploratory analyses were performed comparing, by means of statistical tests, the baseline demographic and clinical characteristics of patients needing vs. not needing extended monitoring. The considered patients’ characteristics were: age, EDSS score, number of relapses in the year before enrolment, normalized spectral power in the LF band (RR LFnu), normalized spectral power in the HF band (RR HFnu), ratio between the absolute spectral power in LF and in HF band (RR LF/HF), assumption of drugs which can alter HR or AV conduction. These characteristics were also compared between male and female patients. The comparisons were performed with non-parametric Wilcoxon test, while differences between categorical variables were tested by Chi-square. The significance threshold was set at 0.05 (all p-values presented are exploratory, so no correction for multiple testing was applied) [31].

Then, in order to evaluate the association between gender and need of extension of the ECG monitoring, a multi-step approach was applied.

A univariate logistic regression model was applied where need of extension of the ECG monitoring (yes, no) and gender were the dependent and independent variables, respectively. Odds ratio (OR) and 95% Wald Confidence Intervals (CI) provided a raw measure of association, the effect of other covariates being not controlled.

Similarly, other seven logistic regression models were applied respectively considering as independent variables age (≤ 40, >40 years), EDSS score (<4, ≥ 4), N° of relapses in the last year (≥ 1, 0), use of drugs which can alter HR or AV conduction (yes, no), and RR LFnu, RR HFnu, RR LF/HF as continuous variables. These models provided raw measure of the association between extended monitoring and each independent variable.

Then, seven bivariate logistic regression models were run, where need of extension of the ECG monitoring (yes, no) was the dependent variable and gender was the independent one. In each model, another covariate was added in order to provide an estimate of association (OR and 95% CI) between the outcome and gender controlled by that covariate. As covariates, the same as in the previous step were chosen.

The last step involved the estimate of a multivariate logistic regression model; the dependent variable was the need of extension of the ECG monitoring and gender was the independent one. All previously mentioned covariates were added to the model and backward selection method was applied; the model provided a final estimate of the association between gender and need to prolong the ECG monitoring, keeping constant the effect of covariates.

The gender-related differences in the degree of patients’ satisfaction were evaluated comparing (by means of non-parametric Wilcoxon tests) the answers to the 10 items of the questionnaire by males and females. In order to evaluate the association between gender and degree of satisfaction a multi-step approach was adopted again. First, a patients’ satisfaction total score was created. The standardized Cronbach’s alpha coefficient was calculated considering the 10 items of the patients’ satisfaction questionnaire. Cronbach’s alpha is known as an estimate of reliability of test scores; some professionals, as a rule of thumb, require a reliability of 0.70 or higher, with 0.60 as the lowest acceptable threshold [32]. Then, different Cronbach’s alpha coefficients eliminating one at a time each item of the questionnaire were calculated, and the best solution was identified as the solution maximizing the number of items and the value of Cronbach’s alpha in the meantime. Then an exploratory factor analysis (EFA) was performed to find independent latent constructs (factors), not directly measurable and influencing responses to the observed variables. Orthogonal VARIMAX rotation was applied; factors having an eigenvalue >1.0 [33,34] and individual variables with higher-than-0.4 loadings on retained factors were considered [35]. In the end, in order to evaluate the solution found, Cronbach’s alpha coefficient was calculated considering the items retained after EFA. The patients’ satisfaction total score was then calculated for each patient summing the responses to items retained after EFA.

The patients’ satisfaction total score in males and females was compared by means of Wilcoxon test and a multivariate regression model was lastly estimated to evaluate the association between the patients’ satisfaction score (dependent variable) and gender (independent variable). The model was adjusted for the following covariates: need of extending monitoring (yes, no), number of relapses in the year before enrolment (0, ≥ 1), age (≤ 40, >40 years) and EDSS score (<4, ≥ 4).

Statistical analysis was performed using SAS v9.2 and Enterprise Guide v4.3. Project management including data banking, quality control and statistical analysis, was performed by Medineos Observational Research (Modena, Italy).

Results

Overall 625 patients were evaluable in the BEAT study, with mean (SD) age of 38.26 (9.68) years and mean duration of MS of 7.63 (6.36) years; 67% were women. Demographic and baseline clinical characteristics are summarized in Table 2. Among evaluable patients, 580 (92.8%; 95% CI: 90.5%; 94.7%) were discharged at the sixth hour after FFD and only 45 (7.2%; 95% CI: 5.3%; 9.5%) required an extended monitoring, 11 (5.3%) among males and 34 (8.1%) among females. The following reasons for extended monitoring were provided (multiple response were admitted): 22 (46.8% of the total number of reasons provided) for low or decreasing HR, 13 (27.7%) for ECG abnormalities, 2 (4.3%) for other AEs, and 8 (17.0%) for other reasons. Overall, 27 (4.3%) patients experienced at least one AE and 6 (1.0%) had a serious AE (5 AV blocks and 1 sinus bradycardia); 25 (4.0%) patients had AEs considered possibly causally related to fingolimod and 4 (0.6%) patients had AEs causing fingolimod discontinuation.

Table 2: Summary of study population demographic and baseline clinical characteristics

Gender and prolongation of the ECG monitoring

Gender and extended monitoring vs. patient clinical characteristics (statistical tests): Statistical tests comparing patients who needed to extend the continuous ECG monitoring vs. those who did not showed statistically significant differences in the number of relapses in the year before enrolment, in the RR LFnu, RR HFnu and in RR LF/HF (Table 3). Moreover, statistical tests by gender showed that females assumed significantly more frequently drugs which can alter HR or AV conduction compared to men (6.4% of females vs. 0.5% of males) and that RR LFnu and RR LF/HF were lower in women (median (IQR): 72.0 (51.2-83.8) and 3.3 (1.3-7.4) respectively) than in men (79.0 (65.0-89.9) and 4.5 (2.1-10.2)), whereas RR HFnu was higher in females than in males (median (IQR): 21.3 (11.3-38.2) vs. 16.4 (7.3- 28.2), respectively) (Table 3).

Table 3: Prolongation of the ECG monitoring and gender vs. patient clinical characteristics

Association between gender and prolongation of the ECG monitoring: The univariate logistic regression models revealed no association between gender and need of extension of the ECG monitoring (OR (95% CI): 0.639 (0.317-1.288)). However, statistically significant ORs were found for number of relapses in the year before enrolment (OR of having extending monitoring patients with ≥ 1 vs. 0 previous relapses (95% CI): 0.459 (0.223; 0.945)), RR LFnu (as continuous value): 0.987 (0.975; 0.999), RR HFnu (as continuous value): 1.017 (1.003; 1.031).

The absence of association between gender and prolongation of the ECG monitoring was confirmed also by the results of bivariate logistic regression models (Table 4). The models confirmed the association between prolongation of the monitoring and number of relapses in the year before enrolment and RR HFnu.

Table 4: Association between gender and prolongation of the ECG monitoring (bivariate logistic regression models)

The multivariate logistic regression model confirmed the absence of association between gender and need of extension of the ECG monitoring, and the association between number of relapses in the year before enrolment and prolongation of monitoring (Figure 1): keeping constant the effect of gender and of the other covariates included in the model, the patients with ≥ 1 relapse in the year before enrolment had about 60% less probability of needing extended monitoring compared to patients with no relapses (OR=0.366, 95% CI=0.166; 0.805). Moreover, patients assuming drugs which can alter HR/AV conduction had more than 3 times the probability of needing prolongation of ECG monitoring than patients not assuming them (OR=3.238, 95% CI=1.024; 10.239). Lastly, a one unit increase in RR HFnu increased of about 2% the probability of needing extended monitoring (OR=1.017, 95% CI=1.002; 1.032).

Figure 1: Association between gender and prolongation of ECG monitoring (multivariate logistic regression model).

Gender and patients’ satisfaction with FFD and monitoring experience

Gender vs. patients’ satisfaction (statistical tests): Regarding treatment satisfaction, between-gender statistically significant differences emerged for the items 2, 5, 8, 10, and 11 of the questionnaire (Table 1, Figure 2) showing a higher level of satisfaction in women than men.

Figure 2: Satisfaction questionnaire: descriptive statistics of numerical items by gender (median).

Association between gender and patients’ satisfaction:

Patients’ satisfaction total score: The standardized Cronbach’s alpha coefficient calculated considering all the 10 items of the questionnaire was 0.66 indicating a questionable internal consistency. Then, different Cronbach’s alpha coefficients eliminating one at a time each item of the questionnaire were calculated, and the best solution was the elimination of item 11 (How much do you think the new method of administration can affect your daily activities in terms of time?). The Cronbach’s alpha considering items 1, 2, 3, 4, 5, 6, 7, 8 and 10 was acceptable (0.70). As results of the EFA on the items 1, 2, 3, 4, 5, 6, 7, 8 and 10 (ranging between 0 and 10), one factor was retained; its components were the items 1, 4, 5, 7, 8, and 10 (items 2, 3 and 6 were erased having lower-than-0.4 loadings on retained factor). Cronbach’s alpha coefficient considering these 6 items increased to 0.75. Then, a patients’ satisfaction total score summing the value of these 6 items was calculated, ranging between 0 (not at all satisfied) and 60 (extremely satisfied).

Gender vs. patients’ satisfaction total score (statistical test): The patients’ satisfaction total score (calculated at the previous step) was higher in women (median (IQR)): 54.0 (49.0-58.0)) than in men (median (IQR): 53.0 (46.0-57.0); Wilcoxon test p-value=0.024).

Association between gender and patients’ satisfaction total score (multivariate regression model): Analyzing the association between satisfaction, gender, and other covariates in a multivariate model (Table 5), gender resulted significantly associated to treatment satisfaction: female patients had a score 1.7 points higher than man taking constant the effect of age, EDSS score, number of previous relapses and need of extended monitoring.

Table 5: Association between satisfaction, gender, and other covariates (multivariate model)

Discussion

For many years, clinical and drug therapy research has mainly focused on male sex, assuming that studying females would give similar results. However, several diseases - including MS - affect males and females differently and medications were shown to obtain different efficacy and safety outcomes in men and women [36-40]. In addition, optimal dosing of medications, in terms of efficacy and side effects, has been studied for long time in patient populations mainly composed of men, whereas they may significantly differ between the two sexes. In recent years, sex differences in disease susceptibility and response to pharmacological therapy have deserved greater attention, and it has been progressively accepted that medical research should increase women presence in clinical trials in order to be equal and correct [41]. Gender differences concerning fingolimod treatment have been previously reported in terms of treatment understanding - with women reporting significantly more knowledge on fingolimod therapy than men [42] – and of AEs – with women developing more infections and men more liver function test alterations during longterm fingolimod treatment [43]. Our post-hoc gender analysis of the multicenter observational BEAT study – focused on FFD and the requirement of prolonged ECG monitoring – while confirming in both sexes the reassuring cardiac safety profile of fingolimod, whose first administration had no significant cardiac consequences in both males and females, showed that gender was not associated with the occurrence of early ECG alterations requiring the extension of monitoring beyond the first 6 hours.

The mechanism of action of fingolimod on S1PRs is known to be responsible of its effects on HR and AV conduction at therapy initiation and for the mild but possibly persistent effects on blood pressure observed in some patients on long-term treatment, and it may be useful for physicians to know more about the epidemiology of the risk factors for such cardiac effects. The BEAT study has explored some factors potentially predicting ECG alterations following the first administration of the drug, highlighting that the background autonomic profile and specifically the dominance of cardiac vagal modulation could help identifying patients with higher probability to require ECG monitoring beyond the first 6 hours. We wanted to assess whether sex could be in some way associated to the need for extensive cardiac monitoring, but it seems from our results that there is no association between sex and early ECG abnormalities requiring a prolongation of the routine 6-hour post-FFD monitoring.

Statistically significant between-gender differences emerged in the assumption of drugs altering HR or AV conduction, and in the sympathovagal balance status (RRLFnu, RR HFnu, and relative ratio, Table 3) but, as confirmed by our stepwise analysis, taking constant the effect of these variables, gender was not associated to the probability of requiring an extended monitoring, while the use of drugs which can alter HR/AV conduction had the highest association with the need for prolonging ECG monitoring, having experienced relapses during the year preceding FFD was negatively associated to the probability of requiring extended ECG monitoring and RR HFnu was modestly positively associated to it.

There is a growing emphasis on patient satisfaction about pharmacologic treatments and medical or surgical procedures, in the attempt to improve patient’s adherence to the physician’s recommendations and also in the light of “paying for performance”. In the United States, for example, hospitals are financially rewarded or penalized based on the patient experience scores they obtain [44]. The Institute for Health Care Improvement defines the patient’s “experience of care” as composed by both the quality of care and the degree of patient’s satisfaction [45]. Few data are available about gender differences in satisfaction with medical treatments. Women rated their satisfaction with hospital stay significantly lower than men, requiring more gender-sensitive care [46]. Women were shown to be more prone than men to stop or switch statin treatment due to AEs [47]. On the other hand, women showed higher adherence to other medications in different settings [27,48]. To our knowledge, nothing has been reported about gender differences in satisfaction with fingolimod treatment. Though limited to FFD and its monitoring experience, our evaluation showed significantly higher overall satisfaction among women compared to men. In particular, women reported significantly less anticipatory nervousness about taking FFD and more easiness in taking the medication according to the given instructions. Furthermore, they were significantly more satisfied with the experience of care and perceived a greater favorable impact of the drug on their daily living (Figure 2). Considering that in addition to literature data [27,48], clinical experience have taught us that women generally have a greater attention to care and a more favorable compliance to treatments, we think these results can perhaps be better interpreted in this sense, than as a specific greater satisfaction with the fingolimod treatment and monitoring experience.

This study has the obvious limitation of being a post-hoc analysis of a study that had not originally been designed with the aim of detecting gender differences. Another limitation is that the number of patients undergone prolonged ECG monitoring was small, limiting the power of gender comparison. A variety of patient satisfaction survey instruments to measure patient experience/satisfaction in both the hospital and outpatient clinic settings have been developed for different clinical conditions [27,49-52]. It may be objected that our satisfaction questionnaire is not a known and validated one. However, it is recognized that patient satisfaction has a complex construct and is highly context dependent. Therefore, we made the effort to develop a specific satisfaction score, which showed to be satisfactory for the internal consistency assessment (Crohnbach alpha 0.75) and whose 6 considered items proved to address a single latent dimension.

Conclusion

Overall, this post-hoc gender analysis suggests that, even if gender differences emerged in the assumption of drugs altering heart rate or AV conduction and in the sympathovagal balance status, keeping constant the effect of these variables, there is no association between sex and early ECG response to FFD administration. Our specifically developed satisfaction score shows that women report a higher level of satisfaction with drug administration and monitoring procedures, adding another piece to the knowledge on gender differences in the response to drug therapies.

Acknowledgements

The authors meet the criteria of the International Committee of Medical Journal Editors (ICMJE) for authorship and were fully responsible for all aspects of manuscript development. We are grateful to Renata Perego and Sara Rizzoli for their help in drafting the manuscript. We are also grateful to the following participating centers, involved in data collection.

BEAT Study Centers

• Amato Maria Pia, A.O.U. Careggi - Florence

• Ardito Bonaventura, Ospedale Generale Regionale F.Miulli - Acquaviva delle Fonti

• Avolio Carlo, A.O.U. Ospedali Riuniti - Foggia

• Bandini Fabio, Ospedale San Paolo - Savona

• Bergamaschi Roberto, Istituto Neurologico Fondazione C. Mondino - Pavia

• Bonavita Simona, A.O.U. Seconda Università di Napoli - Naples

• Bosco Domenico, Ospedale S. Giovanni di Dio - Crotone

• Brescia Morra Vincenzo, A.O.U. Federico II – Naples

• Buccafusca Maria, AOU Policlinico G. Martino - Messina

• Cavalla Paola, A.O Città della Salute e della Scienza- Turin

• Centonze Diego, Fondazione Policlinico Tor Vergata - Rome

• Comi Giancarlo, Ospedale San Raffaele Srl - Milan

• Costantino Gianfranco, A.O.U. Ospedali Riuniti Foggia - Foggia

• Danni Maura Chiara, A.O. Ospedali Riuniti - Ancona

• De Robertis Francesca, Ospedale Vito Fazzi – Lecce

• Di Battista Giancarlo, ACO San Filippo Neri - Rome

• Dotta Michele, Ospedale San Lazzaro - Alba

• Florio Ciro, A.O.R.N. A.Cardarelli - Naples

• Francia Ada, Azienda Policlinico Umberto I - Rome

• Galgani Simonetta, A.O. San Camillo-Forlanini – Rome

• Ghezzi Angelo, A.O. Sant’Antonio Abate - Gallarate

• Grimaldi Luigi, Fondazione Istituto S. Raffaele “G.Giglio” - Cefalù

• Leoni Stefania, A.O.U. Sassari - Sassari

• Lugaresi Alessandra, Ospedale clinicizzato SS. Annunziata - Chieti

• Lus Giacomo, A.O.U. SUN Seconda Università di Napoli - Naples

• Maimone Davide, A.O. Garibaldi Centro – Catania

• Mancardi Gian Luigi, A.O.U. San Martino – Genova

• Marrosu Maria Giovanna, P. O. Binaghi - Cagliari

• Massacesi Luca, A.O.U. Careggi - Florence

• Melato Maurizio, Ospedale SS Antonio e Biagio - Alessandria

• Mirabella Massimiliano, Policlinico Universitario A. Gemelli - Rome

• Mondino Fiorella, Ospedale Santa Croce e Carle - Cuneo

• Montanari Enrico, Ospedale di Vaio – Fidenza

• Murialdo Alessandra, IRCCS A.O.U. San Martino IST - Genova

• Pasquali Livia, A.O.U. Pisana Ospedale Santa Chiara – Pisa

• Patti Francesco, A.O.U. Policlinico-Vittorio Emanuele – Catania

• Perini Paola, Azienda Ospedaliera Padova – Padova

• Perla Franco, Regina Montis Regalis – Mondovì

• Petrone Alfredo, Azienda Ospedaliera Cosenza – Cosenza

• Piscaglia Maria Grazia, Ospedale civile S.Maria delle Croci – Ravenna

• Rilla Maria Teresa, Ospedale di Imperia – Imperia

• Rottoli Maria Rosa, A.O. Papa Giovanni XXIII – Bergamo

• Ruggieri Stefano, Istituto Mediterraneo Neuromed – Pozzilli

• Salemi Giuseppe, A.O.U. Policlinico P. Giaccone – Palermo

• Sarchielli Paola, Clinica Neurologica S. Maria della Misericordia – Perugia

• Scarpini Elio, Ospedale Maggiore Policlinico IRCCS Cà Granda – Milan

• Sessa Edoardo, IRCCS Centro Neurolesi Bonino Pulejo – Messina

• Solaro Claudio, Ospedale Padre Micone – Genova

• Spitaleri Daniele, A.O.R.N. San Giuseppe Moscati – Avellino

• Tassinari Tiziana, Ospedale Santa Corona - Pietra Ligure

• Teatini Francesco, Ospedale Centrale di Bolzano – Bolzano

• Tezzon Frediano, Ospedale Tappeneiner – Merano

• Totaro Rocco, P.O. San Salvatore - L’Aquila

• Trojano Maria, A.O.U. Policlinico Consorziale – Bari

• Ulivelli Monica, A.O.U. Senese Policlinico S.M. alle Scotte – Siena

• Valentino Paola, A.O. Mater Domini – Catanzaro

• Venturi Simonetta, Eo Ospedali Galliera – Genova

• Zimatore Giovanni Bosco, Ospedale Mons. Raffaele Dimiccoli - Barletta

Declaration of Conflicting Interests

Colombo Delia is a part-time employee of Novartis Farma Italy and received grants from Allergan and Aventis.

Zagni Emanuela is an employee of Novartis Farma, Italy.

Alessandra Ori is an employee of Medineos Observational Research.

Nicola Montano received consulting fees from Novo Nordisk and Novartis.

Giuseppe De Angelis received consulting fees from Novartis.

Emilio Vanoli received consulting and advisory board fees from Novartis. He is consultant to LIVANOVA for vagal stimulation, Molteni, CVRx, Sanofi, STm.

Funding

The study was supported by a grant from Novartis Farma SpA, Origgio (VA), Italy.

References

1. Chun J, Hartung HP (2010) Mechanism of action of oral fingolimod (FTY720) in multiple sclerosis. Clin Neuropharmacol 33: 91-101.
2. Schmouder R, Hariry S, David OJ (2012) Placebo-controlled study of the effects of fingolimod on cardiac rate and rhythm and pulmonary function in healthy volunteers. Eur J Clin Pharmacol 68: 355-362.
3. Guo J, MacDonell KL, Giles WR (1999) Effects of sphingosine 1-phosphate on pacemaker activity in rabbit sino-atrial node cells. Pflugers Arch 438: 642-648.
4. Schmouder R, Serra D, Wang Y, Kovarik JM, DiMarco J, et al (2006) FTY720: Placebo-controlled study of the effect on cardiac rate and rhythm in healthy subjects. J Clin Pharmacol 46: 895-904.
5. Budde K, Schmouder RL, Nashan B, Brunkhorst R, Lücker PW et al (2003) Pharmacodynamics of single doses of the novel immunosuppressant FTY720 in stable renal transplant patients. Am J Transplant 3: 846-854.
6. Cohen JA, Barkhof F, Comi G, Hartung HP, Khatri BO, et al. (2010) Oral fingolimod or intramuscular interferon for relapsing multiple sclerosis. New Engl J Med 362: 402-415.
7. Kappos L, Cohen J, Collins W, de Vera A, Zhang-Auberson L, et al. (2014) Fingolimod in relapsing multiple sclerosis: An integrated analysis of safety findings. Mult Scler Relat Disord 3: 494–504.
8. Laroni A, Brogi D, Morra VB, Guidi L, Pozzilli C, et al. (2014) Safety of the first dose of fingolimod for multiple sclerosis: Results of an open-label clinical trial. BMC Neurology: 14: 65.
9. Paolicelli D, Manni A, Direnzo V, D'Onghia M, Tortorella C, et al. (2015) Long-term cardiac safety and tolerability of fingolimod in multiple sclerosis: A postmarketing study. J Clin Pharmacol 55: 1131-1136.
10. Vanoli E, Montano N, De Angelis G, Badilini F, Mirabella M, et al. (2019) Cardiovascular autonomic individual profile of relapsing-remitting multiple sclerosis patients and risk of extending cardiac monitoring after first dose fingolimod. J Neurol Sci 405:116423.
11. Baggio G, Corsini A, Floreani A, Giannini S, Zagonel V (2013) Gender medicine: A task for the third millennium. Clin Chem Lab Med 51:713-727.
12. Koren G, Nordeng H, MacLeod S (2013) Gender differences in drug bioequivalence: time to rethink practices. Clin Pharmacol Ther 93:260-262.
13. Ueno K, Sato H (2012) Sex-related differences in pharmacokinetics and pharmacodynamics of anti-hypertensive drugs. Hypertens Res 35:245-250.
14. Soldin OP, Mattison DR (2009) Sex differences in pharmacokinetics and pharmacodynamics. Clin Pharmacokinet 48: 143-157.
15. Pieretti S, Di Giannuario A, Di Giovannandrea R, Marzoli F, Piccaro G, et al. (2016) Gender differences in pain and its relief. Ann Ist Super Sanita 52: 184-189.
16. Di Giosia P, Passacquale G, Petrarca M, Giorgini P, Marra AM, et al. (2017) Gender differences in cardiovascular prophylaxis: Focus on antiplatelet treatment. Pharmacol Res 119:3 6-47.
17. Cangemi R, Romiti GF, Campolongo G, Ruscio E, Sciomer S, et al. (2017) Gender related differences in treatment and response to statins in primary and secondary cardiovascular prevention: The never-ending debate. Pharmacol Res 117: 148-155.
18. Canevelli M, Quarata F, Remiddi F, Lucchini F, Lacorte E, et al. (2017) Sex and gender differences in the treatment of Alzheimer's disease: A systematic review of randomized controlled trials. Pharmacol Res 115: 218-223.
19. Sramek JJ, Murphy MF, Cutler NR (2016) Sex differences in the psychopharmacological treatment of depression. Dialogues Clin Neurosci 18: 447-457.
20. Perucca E, Battino D, Tomson T (2014) Gender issues in antiepileptic drug treatment. Neurobiol Dis 72: 217-23.
21. Colombo D, Banfi G, Cassano N, Graziottin A, Vena GA, et al. (2017) The GENDER ATTENTION Observational Study: Gender and Hormonal Status Differences in the Incidence of Adverse Events During Cyclosporine Treatment in Psoriatic Patients. Adv Ther 34:1349-1363.
22. Rosano GM, Lewis B, Agewall S, Wassmann S, Vitale C et al (2015) Gender differences in the effect of cardiovascular drugs: A position document of the Working Group on Pharmacology and Drug Therapy of the ESC. Eur Heart J 36: 2677-2680.
23. Bender R, Lange S (2001) Adjusting for multiple testing - when and how? J Clin Epidemiol 54: 343-349.
24. Guttman L (1953) Image Theory for the Structure of Quantitative Variates, Psychometrica 18: 277-296.
25. Kaiser HF, Rice J (1974) Little Jiffy, Mark Iv. Educational and Psychological Measurement 34: 111-117.
26. Truong Y, McColl R (2011) Intrinsic motivations, self-esteem, and luxury goods consumption. Journal of Retailing and Consumer Services 18: 555–561.
27. Golden LC, Voskuhl R (2017) The importance of studying sex differences in disease: The example of multiple sclerosis. J Neurosci Res 95: 633-643.
28. Li R, Sun X, Shu Y, Mao Z, Xiao L, et al. (2017) Sex differences in outcomes of disease-modifying treatments for multiple sclerosis: A systematic review. Mult Scler Relat Disord 12: 23-28.
29. Ngo ST, Steyn FJ, McCombe PA (2014) Gender differences in autoimmune disease. Front Neuroendocrinol 35: 347-369.
30. Cobo G, Hecking M, Port FK, Exner I, Lindholm B, et al. (2016) Sex and gender differences in chronic kidney disease: progression to end-stage renal disease and haemodialysis. Clin Sci (Lond) 130: 1147-1163.
31. Regitz-Zagrosek V, Kararigas G (2017) Mechanistic pathways of sex differences in cardiovascular disease. Physiol Rev 97: 1-37.
32. Woosley RL, Anthony M, Peck CC (2000) Biological sex analysis in clinical research. J Women’s Health Gender Based Med 9: 933-934.
33. Zimmer A, Bläuer C, Coslovsky M, Kappos L, Derfuss T (2015) Optimizing treatment initiation: Effects of a patient education program about fingolimod treatment on knowledge, self-efficacy and patient satisfaction. Mult Scler Relat Disord 4: 444-450.
34. Manni A, Direnzo V, Iaffaldano A, Di Lecce V, Tortorella C, et al. (2017) Gender differences in safety issues during Fingolimod therapy: Evidence from a real-life relapsing multiple sclerosis cohort. Brain Behav 7: e00804.
35. Mehta SJ (2015) Patient satisfaction reporting and its implications for patient care. AMA J Ethics 17: 616-621.
36. Teunissen TAM, Rotink ME, Lagro-Janssen ALM (2016) Gender differences in quality of care experiences during hospital stay: A contribution to patient-centered healthcare for both men and women. Patient Educ Couns 99: 631-637.
37. Karalis DG, Wild RA, Maki KC, Gaskins R, Jacobson TA, et al. (2016) Gender differences in side effects and attitudes regarding statin use in the Understanding Statin Use in America and Gaps in Patient Education (USAGE) study. J Clin Lipidol 10: 833-841.
38. Lefort M, Neufcourt L, Pannier B, Vaïsse B, Bayat S, et al. (2018) Sex differences in adherence to antihypertensive treatment in patients aged above 55: The French League Against Hypertension Survey (FLAHS). J Clin Hypertens (Greenwich) 20: 1496-1503.
39. Atkinson MJ, Sinha A, Hass SL, Colman SS, Kumar RN, et al. (2004) Validation of a general measure of treatment satisfaction, the Treatment Satisfaction Questionnaire for Medication (TSQM), using a national panel study of chronic disease. Health Qual Life Outcomes 2: 12.
40. Moon J, Kolar C, Brummel A, Ekstrand M, Holtan H, et al. (2016) Development and validation of a patient satisfaction survey for comprehensive medication management. J Manag Care Spec Pharm 22: 81-86.
41. García-Aparicio J, Herrero-Herrero JI (2015) Development, validation, and administration of a treatment-satisfaction questionnaire for caregivers of dependent type 2 diabetic patients. Clin Interv Aging 10: 969-977.
42. Vermersch P, Hobart J, Dive-Pouletty C, Bozzi S, Hass S, et al. (2017) Measuring treatment satisfaction in MS: Is the Treatment Satisfaction Questionnaire for Medication fit for purpose? Mult Scler 23: 604-613.