Caleb J P Economou

Jiao Xie

Gregory Comadira

Brent Richards

Mandy Tallott

Steven C Wallis

Jenny Ordoñez

Jeffrey Lipman

Jason A Roberts
email: j.roberts2@uq.edu.au

Population pharmacokinetics of ticarcillin in critically ill patients receiving extended daily diafiltration

Keywords: antibiotics, dosing, pharmacokinetics, pharmacodynamics, renal replacement therapy, extended daily diafiltration dosing, pharmacodynamics, dialysis, antibiotics, intensive care unit

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Ticarcillin-clavulanate is an injectable ß-lactam-ß-lactamase inhibitor combination. This drug combination belongs to the group of extended-spectrum penicillins with a spectrum of activity against gram-positive, gram-negative (including activity against Pseudomonas spp) and anaerobic bacteria. As with other time-dependent antibiotics, the therapeutic success of ticarcillin-clavulanate is reliant on the amount of time free drug remains above the MIC of the infective pathogen (fT>MIC) at the site of infection. Ticarcillin-clavulanate are 79% and 41% renally excreted respectively [START_REF] Jackson | Augmentin: absorption, excretion and pharmacokinetic studies in man[END_REF] and undergo a similar rate of clearance from the body. Ticarcillin is 45-65% protein bound with a low volume of distribution 0.17 L/kg while clavulanate is about 30% protein bound with a volume of distribution around 0.25 L/kg [START_REF] Navarro | New formulations of amoxicillin/clavulanic acid[END_REF]. Although this drug combination is not currently subject to active marketing or wide use, it is likely to still be used in challenging clinical scenarios and so knowledge of how to dose this product, and in particular ticarcillin, remains important.

Extended daily diafiltration (EDDf) is the haemodiafiltration setting of prolonged intermittent renal replacement therapy (PIRRT). PIRRT is a modality of renal replacement therapy (RRT) that combines the advantages of using high blood and dialysate flow rates and short treatment times seen in intermittent haemodialysis (IHD) with the haemodynamic stability demonstrated in continuous renal replacement therapies (CRRT). At present, dosage regimens have been defined for ticarcillinclavulanate during continuous veno-venous haemofiltration (CVVH), continuous venovenous haemodialysis (CVVHD), continuous veno-venous haemodiafiltration (CVVHDF) and IHD [START_REF] Heintz | Antimicrobial dosing concepts and recommendations for critically ill adult patients receiving continuous renal replacement therapy or intermittent hemodialysis[END_REF]. To date however, the pharmacokinetics of ticarcillin during EDDf have not been established. Although some pharmacokinetic data in critically ill patients exists for clavulanate by virtue of studies with the amoxicillin-clavulanate product in non-RRT patients [START_REF] Carlier | Population pharmacokinetics and dosing simulations of amoxicillin/clavulanic acid in critically ill patients[END_REF], little data for ticarcillin exists.

The aim of this study is to describe the population pharmacokinetics of ticarcillin during EDDf in critically ill patients with AKI.

Methods

Setting

This was an observational pharmacokinetic study conducted at the Gold Coast Hospital, Department of Intensive Care Medicine, Gold Coast, Australia. Ethical approval was obtained from the local institutional Human Research Ethics Committee to conduct the study. Written informed consent was obtained from all participants or from their substitute decision-makers.

Study population

The inclusion criteria for this study were: (i) age ≥ 18 years; (ii) admission to an intensive care unit; (iii) clinical indication for ticarcillin-clavulanate (only the combination formulation was available in Australia at the time of study); and (iv) receiving EDDf. The exclusion criteria were: (i) pregnant women; (ii) patients with active bleeding; or (iii) patients with HIV or hepatitis.

Study protocol

Ticarcillin-clavulanate was administered at the direction of the treating physician with patients receiving their first dose within 24 hours of initiating EDDf. Ticarcillinclavulanate dosing is based on the ticarcillin component of the combination therapy, in our patient population requiring EDDf due to AKI, in the absence of published guidelines, patients were dosed at 3 grams of ticarcillin every 8 hours, extrapolated from dosing regimens adopted in patients undergoing CRRT [START_REF]Lexi-Comp: Drug Information Handbook: A Clinically Relevant Resource for All Healthcare Professionals[END_REF][START_REF] Trotman | Antibiotic dosing in critically ill adult patients receiving continuous renal replacement therapy[END_REF]. Prior to the first EDDf session, blood samples (3 mL) were taken from each participant to determine plasma ticarcillin concentrations. Blood sampling occurred from the haemodiafilter pre-filter port line.

Blood sampling occurred when EDDf was commenced (T0) and at 30 minutes (T30), T60, T120, T180, T300, T480 and at T600 on the first and third EDDf session. EDDf was commenced at the discretion of the clinician and did not uniformly correspond with timing of ticarcillin dosing. EDDf was performed in all patients using a 5008s online haemodiafiltration machine (Fresenius Medical Care, Bad Homburg, Germany) with Fresenius polysulfone AV600S 1.4 m 2 high flux haemodiafilters (Fresenius Medical Care).

The standardised EDDf prescription included a blood flow rate (Qb) 300 mL/min, dialysate flow rate (Qd) 200 mL/min and 50 mL/min predilution with a targeted treatment duration of at least 8 hours.

Other clinical and demographic data were collected on the day of plasma sampling, including: age, sex, total body weight (TBW), and body mass index (BMI). Clinical data included Acute Physiology and Chronic Health Evaluation (APACHE) II scores, as well as serum albumin and serum creatinine concentrations (Scr).

Sample handling, storage and assay

Blood samples were centrifuged at 3000 rpm for 10 minutes in a temperature controlled centrifuge. Plasma samples were stored at -80°C until bio-analysis. Ticarcillin was measured using a Shimadzu Nexera X2 UHPLC system coupled to a Shimadzu 8030+ triple quadrupole mass spectrometer (Shimadzu Corporation, Kyoto, Japan).

The linear range when assaying ticarcillin was 1 to 200 mg/L with a precision of 2.6, 10.6 and 0.9% at 3, 30 and 150 mg/L respectively, and accuracy of 1.4 and 2.3 % at 1 and 5 mg/L respectively.

Population pharmacokinetic modelling

To describe total ticarcillin concentrations, one and two-compartment models were developed with the Nonparametric Adaptive Grid (NPAG) algorithm within the Pmetrics software package for R (Los Angeles, CA, version 1.5.1). Elimination from the central compartment and intercompartmental distribution into the peripheral compartment (two compartment model) were modeled as first-order processes.

Population pharmacokinetic covariate screening

Age, gender, body weight and presence of RRT were evaluated as clinically relevant and physiologically plausible covariates. Covariates selection were performed using a stepwise linear regression from R on all covariates and Bayesian posterior parameters.

Potential covariates were separately entered into the model and statistically tested by use of the -2 log-likelihood values. If inclusion of the covariate resulted in a statistically significant improvement in the -2 log-likelihood values (p<0.05) and/or improved the goodness-of-fit plots, then the covariate was retained in the final model.

Model Diagnostics

Goodness of fit was assessed by linear regression, with an observed-predicted (both population-and individual-predicted concentrations) plot, coefficients of determination, and log-likelihood values. Predictive performance was based on mean prediction error (bias) and the mean bias-adjusted squared prediction error (imprecision) of the population and individual prediction models. The internal validity of the population pharmacokinetic model was assessed by the bootstrap resampling method (n=1000) and normalised prediction distribution errors (NPDE). Using the visual predictive check (VPC) method, parameters obtained from the bootstrap method were plotted with the observed concentrations. NPDE plots were checked for normal distribution characteristics and trends in the data errors.

Results

Demographic and clinical data

In total 53 blood samples were obtained from the six critically ill patients (3 male) that were enrolled in the study. The demographic characteristics of the patients are shown in Table 1.

Population pharmacokinetic model building

Ticarcillin pharmacokinetics was best described using a two-compartment linear model. 2. The diagnostic plots confirm the appropriateness of the final covariate model as shown in Figure 1.

Discussion

Key findings

In this descriptive pharmacokinetic study of ticarcillin (co-formulated with clavulanate) in critically ill patients undergoing EDDf, we found that the median ticarcillin clearance was 6.41 L/h during EDDf and 4.97 L/h when off EDDf. The high clearance we describe highlights the importance of further investigation of antibiotic pharmacokinetics in patients undergoing this increasingly utilised RRT modality [START_REF] Santre | Pharmacokinetics of vancomycin during continuous hemodiafiltration[END_REF][START_REF] Deldot | Vancomycin pharmacokinetics in critically ill patients receiving continuous venovenous haemodiafiltration[END_REF]. We also observed high variability in all pharmacokinetic parameter estimates of ticarcillin (Table 2) which further emphasises the challenges of using a fixed dosing approach for drugs that display 'silent' pharmacodynamic profiles such as antibiotics. Therapeutic drug monitoring may contribute in further optimising the dosing of β-lactam antibiotics in individual patient's undergoing EDDf.

An important consideration when dosing antibiotics in patients undergoing RRT is the presence of residual renal function and the quantification of removal of renally excreted antibiotics via this process. Factors such as the serum creatinine concentration and patient age are used to generate the glomerular filtration rate (GFR), as ticarcillin is predominantly excreted by the GFR, it follows that patients of more advanced age and patient's demonstrating higher serum creatinine concentrations are likely to correlate to a reduction in the renal removal of ticarcillin. The presence of vasopressors may also increase cardiac output and the filtration capacity of the kidney also affecting ticarcillin removal. Of the six participants consented to the study, 5 were receiving vasopressors as part of their treatment. Optimal dosing of ticarcillin in the critically ill patient requires the accurate assessment of endogenous renal function and the determination of the contribution of non-EDDf ticarcillin removal to CL.

Relationship with previous papers

Despite the widespread use of ticarcillin-clavulanate when it was more readily available globally, information on the use of this drug in critically ill patients undergoing different forms of RRT are relatively scarce. No previous data has been presented on the pharmacokinetics of ticarcillin in critically ill patients undergoing EDDf. A consequence of the dearth of information on the dosing of β-lactam/β-lactamase combinations such as ticarcillin-clavulanate has resulted in dosing estimates based on extrapolations of more widely used formulations such as piperacillin-tazobactam or theoretical applications of dosing equations [START_REF] Trotman | Antibiotic dosing in critically ill adult patients receiving continuous renal replacement therapy[END_REF][START_REF] Kempke | Antimicrobial doses in continuous renal replacement therapy: a comparison of dosing strategies. Critical care research and practice[END_REF]. Information on antibiotic dosing may even be extrapolated from similar RRT modalities, for example using antibiotic pharmacokinetic data during CVVHDF to guide dosing in EDDf. Whilst these approaches are acceptable with the limited data available, the optimal solution is to guide dosing based on pharmacokinetic studies of the relevant RRT modality and where available, through clinical use of TDM [START_REF] Honore | Applying pharmacokinetic/pharmacodynamic principles for optimizing antimicrobial therapy during continuous renal replacement therapy[END_REF] .

Typically, in non-critically ill patients with normal renal function, ticarcillin dosing guidelines vary between 12 to 18 g daily in divided doses based on indication and severity of infection. In critically ill patients undergoing CVVH, CVVHDF and CVVHD a loading dose of 3 g has been suggested in some drug dosing reference guidelines to establish therapeutic levels of ticarcillin followed by 2 g 6-8 hourly, 3 g 6-8 hourly and 3 g 6 hourly respectively [START_REF]Lexi-Comp: Drug Information Handbook: A Clinically Relevant Resource for All Healthcare Professionals[END_REF]. These dosing regimens reflect the ability of the different forms of RRT to remove ticarcillin to varying extents. Interestingly, the dosage guidelines described in patients undergoing CRRT generally expose the patient to less ticarcillin than would be administered in patients with normal renal function demonstrating the superiority of a functioning kidney in removing ticarcillin compared with CRRT.

Subsequent to commencing this pharmacokinetic study, ticarcillin-clavulanate has been withdrawn from active marketing, due to the availability of alternative antibiotics and declining global demand. There is a strong likelihood that ticarcillin-clavulanate will continue to be used in niche clinical scenarios of patients with difficult multi-drug resistant infections with unique susceptibility profiles. This study provides information on the interindividual variability of ticarcillin in a small cohort of patients in the critical care setting. The effective removal during renal replacement therapy of low molecular weight drugs with low distribution volumes such as β-lactam antibiotics like ticarcillin warrants the need for further pharmacokinetic studies during these therapies. This study provided an example of the variability that may be encountered in the clinical setting and potentially the manner in which similar β-lactam antibiotics may demonstrate pharmacokinetic variability during EDDf.

Implications of study findings

There is an ongoing need for pharmacokinetic studies to be performed that optimise drug therapy with evolving renal replacement therapies around the world. The lack of available data to guide decision limits patient dosing based on extrapolations of data from other pharmacokinetic studies performed using different RRT modalities which may have far different correlative pharmacokinetic effects. Some intensive care units (ICU) may receive supplementary guidance by the use of TDM to optimise the dosing, however most do not have access to such supplemental tests. The concentrations of ticarcillin observed in this trial demonstrated current dosing of 3.1 grams of ticarcillin-clavulanate every 8 hours irrespective of timing of EDDf achieves drug exposures associated with maximal antibacterial effect, although may risk some patients manifesting high concentrations.

Study limitations

Although this study is the first descriptive pharmacokinetic study of ticarcillin in critically ill patients undergoing EDDf, it has some limitations we would like to declare. Firstly, the sample size is small, therefore, describing all possible correlations between pharmacokinetic parameters and covariates may not have been possible due to the sample size. Secondly, we measured ticarcillin plasma concentrations and not concentrations at the site of infection which may provide better mechanistic data regarding the effectiveness of dosing. Finally, this study was not designed nor powered to examine the effect of ticarcillin exposure on patient outcome and larger studies are needed to explore this question further.

Conclusion

Like other β-lactam antibiotics ticarcillin demonstrates highly variable pharmacokinetics in EDDf. Importantly, we observed a strong effect of the patient's endogenous renal function, described using serum creatinine concentration and age, on non-EDDf clearance confirming that this must be accounted for when choosing drug dosing regimens during PIRRT. We conclude that ticarcillin is cleared to a much greater extent during EDDf than by CRRT and that more studies are needed for all drugs during this increasingly used form of PIRRT to ensure optimal therapy in a patient population at risk of therapeutic failure.

  The goodness of fit of the model was improved by inclusion of separate clearance parameters for clearance in the presence of EDDf (CLEDDf) and the absence of EDDf (CLnon-EDDf). The model was also improved by inclusion of age normalised to the study sample mean value of 45-years and the inverse of serum creatinine concentration (in units μmol/L) normalised to the median value observed before first EDDf (216 μmol/L).Addition of these covariates, but not others, each individually resulted in statistically significant improvements in the -2 log-likelihood from the previous model (P <0.05). The addition of each covariate improved the agreement between the observed and population-predicted concentrations as well as distribution of observed data within the visual predictive check and so was retained in the final model. The final covariate model was as follows: CL=CLEDDf*(EDDf)+CLnon-EDDf*(212/secr)*(45/age) where CL is the typical value of ticarcillin CL, CLnon-EDDf is the population parameter estimate of ticarcillin CL without EDDf; CLEDDf is the population parameter estimate of ticarcillin CL with EDDf; and secr is serum creatinine concentration. The term EDDf becomes one when EDDf is on, whereas it is zero when EDDf is off. The mean ± SD population pharmacokinetic parameter estimates from the final covariate model are shown in Table

Figure 1 .

 1 Figure 1. Diagnostic plots for the final population pharmacokinetic covariate model A.

Table 1 :

 1 Demographic characteristics of included patients

	Patient	Age	Height	Sex	Weight	BMI	APACHE II	Serum
		(years)	(cm)		(kg)	(kg/m 2 )		creatinine
								concentrations
								(µmol/L)*
	1	19	165	F	65	23.9		165
	2	29	170	F	80	27.7		78
	3	52	165	F	100	36.7		381
	4	24	175	M	85	27.8		117
	5	61	165	M	100	36.7		355
	6	75	175	M	98	32.0		315
	Median	40.5	167.5	-	91.5	29.9		240
	Quartile 1	25.3	165.0	-	81.3	27.7		129
	Quartile 3	58.8	173.8	-	99.5	35.5		345

Key: BMI -Body Mass Index; APACHE II -Acute Physiological and Chronic Health Evaluation II; M -male; F -female.

*Serum creatinine concentration values before institution of EDD-f

Table 2 :

 2 Population pharmacokinetic parameter estimates for ticarcillin during EDDf in the final two compartment covariate model CLEDDf, population clearance of ticarcillin during EDDf; CLnon-EDDf, population clearance of ticarcillin off EDDf; Vc, population volume of distribution in the central compartment; kCP, rate constant for ticarcillin distribution from the central to the peripheral compartment; kPC, rate constant for ticarcillin distribution from the peripheral to the central compartment

		Mean	SD	CV%	Median
	CLEDDf (L/h)	20.27	9.69	104.46	6.41
	CLnon-EDDf (L/h)	11.19	9.49	86.53	4.97
	Vc (L)	56.18	24.43	43.50	56.46
	kPC (L/h)	22.62	2.46	14.43	21.93
	kCP (L/h)	14.31	3.26	17.15	13.54

a

Declarations


Sonia Dollfus
email: dollfus-s@chu-caen.fr

Camille Delouche

Cécile Hervochon

Cyril Mach

Valérie Bourgeois

Maud Rotharmel

Maxime Tréhout

Anaïs Vandevelde

Olivier Guillin

Rémy Morello

Prof Sonia Dollfus

Specificity and sensitivity of the Self-assessment of Negative Symptoms (SNS) in patients with schizophrenia

Keywords: Schizophrenia, Self-assessment, negative symptoms, SNS, sensitivity, specificity

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Negative symptoms are found in patients with schizophrenia at any stage. They can be the first symptoms during the prodromal phase [START_REF] Piskulic | Negative symptoms in individuals at clinical high risk of psychosis[END_REF], they can be observed during a first episode of schizophrenia [START_REF] Galderisi | Persistent negative symptoms in first episode patients with schizophrenia: results from the European First Episode Schizophrenia Trial[END_REF] or during the late stage of illness, they can persist despite the improvement of positive symptoms, and they are often responsible for impaired social functioning and quality of life [START_REF] Moller | Long-term course of schizophrenic, affective and schizoaffective psychosis: focus on negative symptoms and their impact on global indicators of outcome[END_REF][START_REF] Delamillieure | The subjective quality of life in deficit and nondeficit schizophrenic patients[END_REF]. The detection and evaluation of negative symptoms remains challenging despite their frequency, at all stages of illness. Recent tools including the Brief Negative Symptoms Scale (BNSS) [START_REF] Kirkpatrick | The brief negative symptom scale : psychometric properties[END_REF]) and the Clinical Assessment Interview for Negative Symptoms (CAINS) [START_REF] Kring | The Clinical Assessment Interview for Negative Symptoms (CAINS): final development and validation[END_REF]) have improved the evaluation of negative symptoms. However these scales are based on observer ratings and aim to quantify the severity of negative symptoms thanks to a semistructured interview with prompts and queries. Therefore, these scales do not allow patients self-assessing their feelings and experiences even if ratings of internal experiences regarding asociality and avolition are however considered. Analysis of the scales highlights the predominance of hetero-assessments over self-assessments and a consensus supports five negative symptom dimensions (affective flattening, alogia, anhedonia, social withdrawal and avolition) [START_REF] Lincoln | Current developments and challenges in the assessment of negative symptoms[END_REF][START_REF] Kirkpatrick | The NIMH-MATRICS consensus statement on negative symptoms[END_REF][START_REF] Strauss | Network analysis reveals the latent structure of negative symptoms in schizophrenia[END_REF]. Recently, two scales have been developed to specifically evaluate negative symptoms by self-rating. One is the Motivation and Pleasure Scale-Self-Report (MAPSR), an 18-item selfreport version of the CAINS Motivation and Pleasure subscale [START_REF] Llerena | The Motivation and Pleasure Scale-Self-Report (MAP-SR): reliability and validity of a self-report measure of negative symptoms[END_REF]. Another one is the Self-assessment of Negative Symptoms (SNS) for which patients with schizophrenia have demonstrated the ability to complete its reliably and consistently [START_REF] Dollfus | Self-Evaluation of Negative Symptoms: A Novel Tool to Assess Negative Symptoms[END_REF][START_REF] Hervochon | Validation of the French version of the self-evaluation of negative symptoms (SNS)][END_REF]. The SNS has several advantages. It is a short 20 item scale with short and easily understandable sentences, and the three response choices allow a fast selfevaluation in under five minutes. The five negative symptom dimensions are self-evaluated and one strength of the scale is that patients are able to express their deficits in motivation and pleasure as well as their loss of emotion independently of depressed mood [START_REF] Dollfus | Self-Evaluation of Negative Symptoms: A Novel Tool to Assess Negative Symptoms[END_REF]. Moreover, the first validation study for the SNS revealed a good test-retest reliability, good internal consistency, tight convergent and divergent validities. A factor analysis on the 5 sub-scores revealed 2 factors, 'motivation' and 'emotion' ones in accordance with the literature [START_REF] Dollfus | Self-Evaluation of Negative Symptoms: A Novel Tool to Assess Negative Symptoms[END_REF] although the hierarchical model reported by [START_REF] Strauss | The Latent Structure of Negative Symptoms in Schizophrenia[END_REF] with the five subscales representing separate dimensions influenced by two higher-order factors (motivation and emotion) was not tested. A second study in another French population confirmed these good psychometric properties [START_REF] Hervochon | Validation of the French version of the self-evaluation of negative symptoms (SNS)][END_REF].

The purpose of this study was to evaluate the sensitivity and specificity of the SNS in order to determine the suitability of SNS as a screening measure. We hypothesize that some negative symptoms can be revealed by the SNS in healthy subjects and so their comparison with patients can allow us to determine the threshold beyond which the symptoms are considered as pathological in patients with schizophrenia. Consequently, we used the SNS to conduct a comparative study between patients with schizophrenia and healthy subjects.

Materiel and Methods:

Population:

Ninety nine healthy controls (HC) with no history of psychiatric disorders or substance abuse and with a Beck Depression Inventory (BDI) score [START_REF] Beck | Comparison of Beck depression inventories -IA and -II in psychiatric outpatients[END_REF] under 4 were included along with 109 patients diagnosed with schizophrenia or schizoaffective disorders (SZ) based on the DSM-5 (Diagnostic and Statistical of Manual Disorder 5th edition) with no history of substance abuse. Forty-nine patients were recruited from the university hospital (Caen, France) and 60 came from the clinic affiliated with the University of Medicine of Rouen (France), both groups participated in previous validation studies of the SNS after providing informed consent [START_REF] Dollfus | Self-Evaluation of Negative Symptoms: A Novel Tool to Assess Negative Symptoms[END_REF][START_REF] Hervochon | Validation of the French version of the self-evaluation of negative symptoms (SNS)][END_REF]. So, both data from both studies were gathered and reanalyzed in the present study.

Symptom assessments:

The Brief Psychiatric Rating Scale (BPRS) [START_REF] Overall | The Brief Psychiatric Rating-Scale[END_REF]) is a 18-item clinician-rated measure that assesses clinical psychiatric symptoms. Items are rated on a 7-point Likert scale, ranging from 1 (not present) to 7 (extremely severe). The total score reflects symptom severity, while the subscores reflect the positive (conceptual disorganization, hallucinations, unusual thought content) and negative components (emotional withdrawal, motor retardation, and blunted affect).

The Scale of Assessment of Negative Symptoms (SANS) [START_REF] Andreasen | The scale for the assessment of negative symptoms (SANS): conceptual and theoretical foundations[END_REF]) had 25 items divided into five subscales (Affective Flattening or Blunting, Alogia, Avolition-Apathy, Anhedonia-Asociality, and Attention) for which global severity is rated from 0 to 5, with higher scores for the more severe dimension.

The SNS is a self-assessment of 20 items, allowing patients to evaluate themselves on the five dimensions of negative symptoms [START_REF] Dollfus | Self-Evaluation of Negative Symptoms: A Novel Tool to Assess Negative Symptoms[END_REF]. Each item is scored as either 2 (strongly agree), 1 (somewhat agree), or 0 (strongly disagree). The number of responses was voluntarily limited to 3 in order to simplify completion and to avoid random responses when score ranges are too broad. The total score is the sum of the 20 items, ranging from 0 (no negative symptoms) to 40 (severe negative symptoms). Five subscores can also be computed, corresponding to the 5 negative dimensions (social withdrawal, emotional range, alogia, avolition, and anhedonia).

The Calgary Depression Scale for Schizophrenia (CDSS) [START_REF] Addington | Assessing Depression in Schizophrenia : The Calgary Depression Scale[END_REF]) is a 9 item semi-structured interview that assesses depressive symptoms in schizophrenia. Each item is rated on a 4-point scale ranging from 0 (absent) to 3 (severe). The CDSS was used to take into account potential depression in the patients since overlap of negative and depressive symptoms has been observed [START_REF] Dollfus | Self-Evaluation of Negative Symptoms: A Novel Tool to Assess Negative Symptoms[END_REF].

Data analyses:

Continuous data were expressed as mean ± standard deviation (mean ± SD). HC and SZ groups were compared by Student's t-test following verification of homoscedasticity with Levene's test. Categorical variables were presented as percentages and compared using Chi-square or Fisher's exact tests as appropriate.

Receiver Operating Characteristic (ROC) curves were established for discriminating SZ and HC participants by assigning the best threshold as determined by sensitivity (Se) and specificity (Sp). The threshold corresponds to the point lies at the intersection of the ROC curve and the line perpendicular to the diagonal of no discrimination. This threshold is optimal since it minimizes the difference between sensitivity (Se) and specificity (Sp). The area under the ROC curve (AUROC) and the diagnostic odds ratio were used to evaluate the diagnostic performance of the SNS scale. Diagnostic parameters are given with their 95% confidence intervals (95% CI).

Positive and negative predictive values (PPV and NPV) were also calculated. Since these values depend on the rate of illness (RoI) in the sample studied (here RoI = 52%), these values were also computed at a lower rate (RoI = 10%) with the pretest odds (pretOdds = RoI/1-RoI), the positive and negative posttest odds (Pos_posttOdds = pretOdds X LR+ and Neg_posttOdds = ptOdds x LR-; LR+ and LR-being the positive and negative Likelihood Ratio (LR+ = sensitivity/(1specificity) and LR-= (1-sensitivity)/specificity)). PPV is equal to

Pos_posttOdds/1+Pos_posttOdds and NPV to 1 -(Neg_posttOdds/1+Neg_posttOdds).

In order to make sure that depression or severity of negative symptoms did not influence the results, the number of patients with a CDSS score above 8 or with a negative sub-score BPRS above 1 DS of the mean were identified and two analyses were done without these patients.

The diagnostic odds ratio (DOR) is a measure of the effectiveness of a diagnostic test and is defined as the ratio of the likelihoods ratios (LR+/LR-). The rationale for the diagnostic odds ratio is that it is a single indicator of test performance and independent of prevalence (unlike accuracy), and is presented as an odds ratio [START_REF] Glas | The diagnostic odds ratio : a single indicator of test performance[END_REF].

All p-values were two sided and p < 0.05 was considered statistically significant. All statistical analyses were conducting using IBM ® -SPSS® 22.0 software.

Results:

Descriptive statistics

The characteristics of the 109 patients with schizophrenia and 99 controls are summarized in Table 1. The patients with SZ were significantly older (p < 0.001) than healthy subjects but no correlation was found between age and total SNS scores in patients (r= 0.16, P=0.08). As expected SNS scores and subscores were significantly higher in SZ patients than in HC (Table 1).

Patients had a significant lower level of school education than that in healthy subjects but SNS total scores did not differ (P = 0.5) in subgroups of patients characterized by higher level (N=55;

15.92 ± 7.54) or lower level than bacchalaureate (N=54; 16.85 ± 8.22).

The DOR was equal to 72.8, 95% CI = [29. 1-181.8].

The PPV and NPV were 87.8 % and 91.4 % respectively (Table 2) meaning that 87.8 % is the probability to present the disease in a subject with SNS score above 7 and 91.4% is the probability to be healthy with SNS score under 7. When the rate of illness in the sample was lowered at 10%, the PPV and NPV were 42.1 % and 99.0% respectively.

ROC Curve

An AUROC analysis was performed in order to assess the discriminant performance of the SNS scale for screening (figure 1). The SNS (AUROC = 0.942 ± 0.046; p < 0.001) appears to be an appropriate screening tool for distinguishing SZ and HC at a threshold value of 7 (< 7 vs ≥ 7).

The sensitivity and specificity were 92.7% (95% CI = [86.1-96.8]) and 85.9% (95CI = [77.4-92.1])

respectively. Various thresholds according to the sensitivity and specificity are displayed on Table 3.

AUROC analyses in the population after removing the patients with a CDSS score > 8 (N= 18;

16.5%) or a negative BPRS subscore >14 (N=16; 14.7%) showed similar results with the same thresholds at 7 with AUC at 0.933 ± 0.018 (p < 0.001) and 0.934 ± 0.018 (P < 0.001) respectively.

Discussion:

This is the first study highlighting a scale threshold for the identification of the negative dimension of schizophrenia with good sensitivity and specificity.

The results demonstrate that healthy subjects can report negative symptoms without any relationship with schizophrenia. Moreover, the SNS allows thresholding the intensity of negative symptoms beyond which it can be related to the negative dimension of schizophrenia.

The sensitivity and specificity were 92.7% (95% CI = [86.1-96.8] %) and 85.9% (95% CI = [77.4-92.1] %) respectively at the optimal threshold, classifying subjects with SNS scores ≥ 7 as patients with schizophrenia. The positive and negative likelihood ratios (LR+ and LR-) were independent of illness prevalence. The DOR was equal to 72.8, 95% CI = [29. 1-181.8]. This value is much greater than one, indicating that the test is correctly discriminant. The DOR is a measure of test performance. It combines the strengths of sensitivity and specificity, as prevalence independent indicators, with the advantage of accuracy as a single indicator. The DOR at 72.8 means that the probability of having negative symptoms beyond 7 in patients is 71 times higher than that in healthy subjects.

Contrarily to the DOR, the PPV and NPV depend on the rate of illness. This rate is high in the present sample (52%) that could explain the high PPV (87.8%) and NPV (91.4%). However, PPV and NPV were still high (42.1 % and 99.0 % respectively) when the rate was artificially lowered at 10% underlining the interest of using SNS in psychiatric population.

As SNS can be used for screening negative symptoms in clinical practice and research in schizophrenia, the important point is to avoid missing true positives and so a highly sensitive test is required to respond to this [START_REF] Rothman | Modern Epidemiology[END_REF].

The good discriminant properties of the SNS including high values for sensitivity, specificity, and DOR might support its use for the identification of negative symptoms as pathological. Indeed, a total SNS score equal to or greater than 7 is associated with an 87.8% probability that negative symptoms are related to the negative dimension of schizophrenia. In contrast, a total SNS score less than 7 is associated with a 91.4% probability that the symptoms are not pathological negative symptoms related to schizophrenia. This result suggests that under the SNS threshold of 7, the level of severity of symptoms reported with SNS might be considered as no pathological in healthy subjects or as very mild in patients with schizophrenia. In the same vein, we could consider that 7 is an SNS minimal score for a patient to be included in a trial targeting negative symptoms. After excluding the 16 patients with high level of negative symptoms, same results were obtained with the same threshold at 7 supporting the fact that the severity of negative symptoms did not impact on the threshold observed. However, further studies would be necessary in a larger group of patients with and without negative symptoms to confirm that this SNS threshold can discriminate both groups of patients with schizophrenia.

In the present study, SNS was used in patients with an advanced stage of illness. Consequently, we cannot extrapolate the pathological threshold found here in a younger population and particularly in patients at an early stage of illness. Further studies are needed in this specific population. Indeed, primary negative symptoms are observed in up to a quarter of patients with first episode schizophrenia [START_REF] Galderisi | Persistent negative symptoms in first episode patients with schizophrenia: results from the European First Episode Schizophrenia Trial[END_REF][START_REF] Chang | Persistent negative symptoms in first-episode schizophrenia: a prospective three-year follow-up study[END_REF]. Negative symptoms are often the first to appear at the beginning of illness prior to the emergence of positive symptoms and are often retrospectively related to the prodromal stage [START_REF] Häfner | Onset and early course as determinants of the further course of schizophrenia[END_REF]. Eighty two percent of subjects with a high risk of psychosis scored at moderate or above on at least one negative symptom, and negative symptoms significantly predicted the likelihood of conversion to psychosis [START_REF] Piskulic | Negative symptoms in individuals at clinical high risk of psychosis[END_REF]). However, negative symptoms are difficult to evaluate and recent standardized scales like the BNSS [START_REF] Kirkpatrick | The brief negative symptom scale : psychometric properties[END_REF] or CAINS [START_REF] Kring | The Clinical Assessment Interview for Negative Symptoms (CAINS): final development and validation[END_REF]) are based essentially on observer ratings. If internal experiences for avolition and asociality are also rated in these scales, they are based on semistructured interview and cannot be considered as self-assessments of subjective experiences. However, a self-assessment from CAINS was developed. In a first version, poor reliability and validity of the expression items were reported [START_REF] Park | Screening for negative symptoms: preliminary results from the self-report version of the Clinical Assessment Interview for Negative Symptoms[END_REF]) leading to a revised version, the Motivation And Pleasure Scale Self-report (MAPSR) [START_REF] Llerena | The Motivation and Pleasure Scale-Self-Report (MAP-SR): reliability and validity of a self-report measure of negative symptoms[END_REF]) that focused exclusively on self-reported deficits in motivation and pleasure. Consequently, MAPSR only covers 2 negative dimensions instead of the 5 ones recommended [START_REF] Kirkpatrick | The NIMH-MATRICS consensus statement on negative symptoms[END_REF]) [START_REF] Strauss | Network analysis reveals the latent structure of negative symptoms in schizophrenia[END_REF][START_REF] Ahmed | Cross-cultural validation of the 5-factor structure of negative symptoms in schizophrenia[END_REF]). Compared to hetero-evaluations, self-evaluation like SNS provides clinical information not necessarily detected by caregivers or medical staff in a standard interview and can provide information on the symptoms as recognized by the patients themselves [START_REF] Lindstrom | Patient-rated versus clinician-rated side effects of drug treatment in schizophrenia. Clinical validation of a self-rating version of the UKU Side Effect Rating Scale (UKU-SERS-Pat)[END_REF].

Consequently, the SNS might be a valuable tool to help clinicians who guide the cognitive or social therapy based on the patient's answers. Whether self-reports have previously been developed to evaluate psychotic symptoms in schizophrenia [START_REF] Niv | The validity of using patient self-report to assess psychotic symptoms in schizophrenia[END_REF]) and prodromal psychotic symptoms [START_REF] Kobayashi | A self-reported instrument for prodromal symptoms of psychosis: testing the clinical validity of the PRIME Screen-Revised (PS-R) in a Japanese population[END_REF][START_REF] Kelleher | Are screening instruments valid for psychoticlike experiences? A validation study of screening questions for psychotic-like experiences using in-depth clinical interview[END_REF], they do not allow screening negative symptoms. The recent scales, BNSS and CAINS were adapted for assessing negative symptoms in clinical high-risk population but are still based on interviews [START_REF] Strauss | Preliminary psychometric properties of the brief negative symptom scale in youth at clinical High-risk for psychosis[END_REF][START_REF] Gur | Negative symptoms in youths with psychosis spectrum features : complementary scales in relation to neurocognitive performance and function[END_REF]. Consequently, the SNS based on self-assessment might be a valuable and complementary tool for detecting negative symptoms at an early stage of illness.

Despite the excellent sensitivity and specificity shown by SNS in the identification of negative symptoms, the study has some limitations. The absence of a cross validation in other samples prevent us to confirm the efficiency of the identified cutting score and to demonstrate its stability and generalization in other populations.

The fact that patients presented a low level of depressive symptoms assessed with CDSS and the exclusion of healthy subjects with depressive symptoms did not allow to evaluate the overlap of depressive and negative symptoms or to address the discrimination of primary and negative symptoms secondary to depression. However, after removing the 18 patients with high scores of depression, same results were obtained with the same thresholds supporting the fact that the severity of depressive symptoms did not impact on the threshold observed. Other limitations are that assessments of insight, clinical functioning and cognitive functions were not included. Regarding insight, the previous study did not reveal any relationship between the severity of insight and the level of negative symptoms assessed by SNS [START_REF] Dollfus | Self-Evaluation of Negative Symptoms: A Novel Tool to Assess Negative Symptoms[END_REF]. However, further studies are needed to explore the relationship between the level of negative symptoms and the level of functioning and cognitive deficit since several studies have reported some relationships [START_REF] Gur | Negative symptoms in youths with psychosis spectrum features : complementary scales in relation to neurocognitive performance and function[END_REF]. Another limitation regards the demographic characteristics since healthy subjects were younger and with better school levels than patients, that might contribute to varying the threshold of SNS. However, we did not find any correlation between age and total SNS scores and any difference of total SNS scores according the level of education in patients.

In conclusion, the excellent sensitivity and specificity of the SNS makes it a valuable tool for the screening of negative symptoms in clinical practice. Further studies on the detection of negative symptoms with the SNS in subjects at high risk for psychosis or with a first psychotic episode would be of great interest. The threshold corresponds to the point lies at the intersection of the ROC curve and the line perpendicular (discontinuous line) to the diagonal of no discrimination (continuous line).

Figure 1 .

 1 Figure 1. Screening performances of SNS scale -Area Under Receiver Operating Characteristic curve (AUROC).

Table 1 .

 1 Participant characteristics Self-assessment of Negative symptoms; BPRS: Brief Psychiatric Rating Scale; BDI: Beck Depression Inventory; CDSS: Calgary Depression Syndrome Scale; SANS: Scale for the Assessment of Negative Symptoms Table 2. Accuracy of SNS scale's screening parameters for the schizophrenic and control subjects detection -SNS 's threshold value = 7 (Schizophrenic patient : ≥ 7 -Control subject :

	Variables	Patients with schizophrenia (N=109)	Healthy controls (N=99)	p
	Age	38.9 ± 11.3	28.8 ± 13.2	<0.001
	Bacchalaureate or more (%)	50.5	98.1	<0.001
	SNS Social withdrawal	3.13 ± 2.52	0.48 ± 0.80	<0.001
	Diminished emotional range	3.52 ± 1.95	1.10 ± 1.37	<0.001
	Alogia	3.56 ± 2.27	0.84 ± 1.35	<0.001
	Avolition	3.74 ± 2.39	0.86 ± 1.10	<0.001
	Anhedonia	2.62 ± 2.25	0.19 ± 0.67	<0.001
	Total score	16.39 ± 7.87	3.47 ± 3.58	<0.001
	SANS global total score	15.05 ± 4.41
	BPRS
	Positive symptoms	8.36 ± 4.55	-	-
	Negative symptoms	10.67 ± 3.79	-	-
	Total score	43.80 ± 12.35	-	-
	Patients with
	negative symptoms	14.7
	> 14 (%)
	BDI Total score		1.85 ± 1.85	-
	CDSS Total score	4.02 ± 4.76	-	-
	Patients with CDSS score >8 (%)	16.5
	SNS:

Table 3 :

 3 Sensitivity and specificity of SNS for different threshold values

	Threshold	Sensitivity	Specificity
	5,0	0,963	0,707
	6,0	0,936	0,808
	7,0	0,927	0,859
	8,0	0,853	0,889
	9,0	0,817	0,909
	10,0	0,771	0,919
	11,0	0,743	0,939

Acknowledgements:

We thank Gaelle Quarck and Grégory Simon for their help in the recruitment of healthy participants.

Conflicts of interest