MD, MSc Florence Poizeau

MSc Sandrine Kerbrat

MSc Frédéric Balusson

MD, PhD Pierre Tattevin

MD, PhD Matthieu Revest

PharmD, PhD Vincent Cattoir

Damien Luque Paz

MD Thierry Lesimple

MD, MSc David Luque-Paz

MD Marc Pracht

MD Monica Dinulescu

MD David Russo

MD, PhD Emmanuel Oger

MD, PhD Alain Dupuy
email: alain.dupuy@chu-rennes.fr.

The Association Between Antibiotic Use and Outcome Among Metastatic Melanoma Patients Receiving Immunotherapy

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

Tumor immunotherapy using immune checkpoint inhibitors (ICI) has dramatically changed the prognosis of metastatic melanoma as well as several other cancers. [START_REF] Ribas | Cancer immunotherapy using checkpoint blockade[END_REF] However, only approximately 35% to 45% of patients benefit from immunotherapy. [START_REF] Hodi | Nivolumab plus ipilimumab or nivolumab alone versus ipilimumab alone in advanced melanoma (CheckMate 067): 4-year outcomes of a multicentre, randomised, phase 3 trial[END_REF][START_REF] Robert | Pembrolizumab versus ipilimumab in advanced melanoma (KEYNOTE-006): post-hoc 5-year results from an open-label, multicentre, randomised, controlled, phase 3 study[END_REF][START_REF] Larkin | Five-Year Survival with Combined Nivolumab and Ipilimumab in Advanced Melanoma[END_REF] Identification of factors that affect the efficacy of ICI has therefore become a new challenge. One of the most disturbing findings that has emerged in the past 3 years is the suspected detrimental effect of antibiotics: across several cancers, antibiotics administered before ICI have been associated with shorter progression-free and overall survival. [START_REF] Rossi | Concomitant medications during immune checkpoint blockage in cancer patients: Novel insights in this emerging clinical scenario[END_REF][START_REF] Yu | Effects of Antibiotic Use on Outcomes in Cancer Patients Treated Using Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis[END_REF][START_REF] Mohiuddin | Association of Antibiotic Exposure With Survival and Toxicity in Patients With Melanoma Receiving Immunotherapy[END_REF][START_REF] Petrelli | Survival of Patients Treated with Antibiotics and Immunotherapy for Cancer: A Systematic Review and Meta-Analysis[END_REF][START_REF] Wilson | The effect of antibiotics on clinical outcomes in immune-checkpoint blockade: a systematic review and meta-analysis of observational studies[END_REF][START_REF] Xu | The association between antibiotics use and outcome of cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis[END_REF][START_REF] Pinato | Association of Prior Antibiotic Treatment With Survival and Response to Immune Checkpoint Inhibitor Therapy in Patients With Cancer[END_REF] Because the role of the gut microbiota in response to ICI has been substantiated by experimental data in mice, [START_REF] Routy | Gut microbiome influences efficacy of PD-1based immunotherapy against epithelial tumors[END_REF] the hypothesis of an impairment of ICI efficacy consecutive to antibiotic-induced gut dysbiosis has been raised. [START_REF] Huang | Relating Gut Microbiome and Its Modulating Factors to Immunotherapy in Solid Tumors: A Systematic Review[END_REF] Among patients receiving ICI, dysbiosis could consecutively lead to cancer progression and death. Alongside this neat causal hypothesis, however, one alternative line of explanation, namely confounding by indication, has not been ruled out, nor even appropriately discussed in the vast majority of reports. Thus, more aggressive disease or a comorbid burden among patients receiving antibiotics could lead to the poorer prognosis observed, independently from any causal effect of antibiotic exposure. [START_REF] Hussain | Concomitant medications and immune checkpoint inhibitor therapy for cancer: causation or association?[END_REF][START_REF] Spakowicz | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications[END_REF] In other words, patients with more active or advanced metastatic cancer, with a poorer prognosis, are more likely to require medical care, including antibiotic courses. Because it is very challenging to control for, confounding by indication has been considered as the "most stubborn bias". [START_REF] Bosco | A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies[END_REF] We addressed the question of the impact of exposure to antibiotics on ICI efficacy and survival in a cohort of advanced melanoma patients using data prospectively collected in the French Health Insurance database. To ensure the best comparability between patients exposed and non-exposed to antibiotics, we used a propensity score weighting method, and included a large homogeneous single-cancer population. We defined two cohorts according to the first-line treatment used: anti-PD-1 antibody or targeted therapy. The hypothesis of a deleterious effect of antibiotic-induced gut dysbiosis has been raised for ICI, although no suspicion of such an effect literature has emerged in the literature on targeted therapy. Therefore, studying these two cohorts in parallel offered the opportunity to disentangle causal effect from bias.

Methods

Data source and study cohorts

This study was conducted using the French National Health Insurance database (SNDS, Système National des Données de Santé), [START_REF] Tuppin | Value of a national administrative database to guide public decisions: From the système national d'information interrégimes de l'Assurance Maladie (SNIIRAM) to the système national des données de santé (SNDS) in France[END_REF][START_REF] Bezin | The national healthcare system claims databases in France, SNIIRAM and EGB: Powerful tools for pharmacoepidemiology[END_REF] and followed the REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) guidelines. [START_REF] Benchimol | The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement[END_REF] The database covers 98.8% of the population living in France (around 66 million inhabitants), and contains exhaustive data on all reimbursements for health-related expenditures, including dispensed drugs with date of dispensation. Information about all hospitalizations in a public or private hospital is also provided, including diagnoses (using ICD-10 codes, International Classification of Diseases, 10 th revision) and expensive drugs prescribed during hospital stays. Long-term diseases (including cancers) are recorded, with diagnoses encoded according to ICD-10, because they give entitlement to 100% health insurance coverage.

We previously constructed a national cohort including every new patient receiving a systemic treatment for metastatic melanoma in France between June 2015 and December 2017 (N=4725). [START_REF] Poizeau | Patients with Metastatic Melanoma Receiving Anticancer Drugs: Changes in Overall Survival, 2010-2017[END_REF] The population selection process has been detailed previously. [START_REF] Poizeau | Patients with Metastatic Melanoma Receiving Anticancer Drugs: Changes in Overall Survival, 2010-2017[END_REF] We selected two cohorts of patients with metastatic melanoma, differentiated by the first-line treatment received: an anti-PD-1 antibody cohort including 2605 patients receiving pembrolizumab or nivolumab, and a targeted therapy cohort including1527 patients receiving BRAF inhibitors (vemurafenib, dabrafenib), alone or combined with MEK inhibitors (cobimetinib, trametinib).

Ethics approval

The study was approved by the French Data Protection Agency (CNIL, DR-2016-384).

Drug exposure

A timeframe for antibiotic courses received in the 3 months prior to the initiation of the first-line anti-melanoma treatment was chosen for the main analysis, so as to correspond to the previous literature regarding antibiotic exposure and ICI efficacy among patients with melanoma. [START_REF] Mohiuddin | Association of Antibiotic Exposure With Survival and Toxicity in Patients With Melanoma Receiving Immunotherapy[END_REF] Antibiotic exposure was ascertained from dispensations occurring outside the hospital and was assumed to last 7 days, except for certain packages of tetracyclines used for acne and rosacea (60 days), single-dose fosfomycin (1 day), and benzathine penicillin G (14 days).

Sensitivity analyses

In a first sensitivity analysis, we narrowed the timeframe for antibiotic exposure to 1 month prior to the first-line anti-melanoma treatment, as this timing appeared as more detrimental for ICI efficacy. [START_REF] Wilson | The effect of antibiotics on clinical outcomes in immune-checkpoint blockade: a systematic review and meta-analysis of observational studies[END_REF][START_REF] Pinato | Association of Prior Antibiotic Treatment With Survival and Response to Immune Checkpoint Inhibitor Therapy in Patients With Cancer[END_REF] In a second sensitivity analysis, antibiotic exposure was restricted to antibiotics having a higher impact on the gut microbiota, namely fluoroquinolones and broad-spectrum βlactams (including second-and third-generation cephalosporins, and penicillins associated with β-lactamase inhibitors). [START_REF] Zimmermann | The effect of antibiotics on the composition of the intestinal microbiota -a systematic review[END_REF][START_REF] Yang | The varying effects of antibiotics on gut microbiota[END_REF][START_REF] Sullivan | Effect of antimicrobial agents on the ecological balance of human microflora[END_REF][START_REF] Bhalodi | Impact of antimicrobial therapy on the gut microbiome[END_REF] These can be considered as the backbone for testing the hypothesis of impaired efficacy of ICI as a result of antibiotic-induced gut dysbiosis. Patients receiving highimpact antibiotics were compared to patients who did not receive antibiotics. A third sensitivity analysis was performed because administration of antibiotics is not recorded during hospital stays in the SNDS database. Patients with an infection identified in hospital discharge coding, who could have been misclassified in the "no antibiotics" group if they had received antibiotics only during their hospital stay, were excluded.

Outcomes

Two outcomes were used. Overall survival (OS) was estimated from the initiation of the first treatment line to the date of death or until censoring on December 31, 2017. The duration of the first treatment line, estimated from time-to-treatment discontinuation (TTD), was defined as the date of the start of the first treatment line to the date of treatment discontinuation. The date of the start of the first treatment line was the date of the first dispensation of targeted therapy or infusion of anti-PD-1 antibody. The treatment line was considered as discontinued when another treatment line was initiated, or 3 months after the last recorded dispensation if no subsequent treatment was initiated. TTD has been proposed as an efficacy end-point for real-world evidence trials. [START_REF] Blumenthal | Analysis of time-to-treatment discontinuation of targeted therapy, immunotherapy, and chemotherapy in clinical trials of patients with nonsmall-cell lung cancer[END_REF][START_REF] Demets | When Can Intermediate Outcomes Be Used as Surrogate Outcomes?[END_REF]

Covariates

Multiple covariates were used: age, sex, number and location of metastatic sites, previous surgery, stereotactic or external beam radiotherapy. In addition, numerous comorbidities were sought: cardiovascular or cerebrovascular disorders, diabetes, history of another cancer, chronic respiratory, renal, liver or pancreatic disease, inflammatory and systemic diseases requiring immunosuppressive or immunomodulating agents, neurological or psychiatric disorders, substance or alcohol abuse (Supplementary Table 1). The algorithm used to identify comorbidities in the SNDS database was based on the SNDS mapping tool, consisting in reference coding instructions developed to standardize the analysis of the morbidity burden from health-care utilization. [START_REF]Caisse Nationale d'Assurance Maladie. Méthodologie Médicale de La Cartographie Des Pathologies et Des Dépenses[END_REF][START_REF] Constantinou | Two morbidity indices developed in a nationwide population permitted performant outcome-specific severity adjustment[END_REF] Long-term disease diagnoses, hospitalization discharge diagnoses and medical procedures were sought in the 4 years prior to the anti-melanoma treatment initiation. In addition, medications were screened for in the 12 months before the anti-melanoma treatment initiation (4 years for certain immunosuppressive or immunomodulating agents).

Propensity score and pseudo-populations

Overlap weighting based on the propensity score was used to create pseudo-populations, in which characteristics measured were balanced between patients exposed and non-exposed to antibiotics. [START_REF] Thomas | Using Propensity Score Methods to Create Target Populations in Observational Clinical Research[END_REF][START_REF] Mlcoch | Propensity Score Weighting Using Overlap Weights: A New Method Applied to Regorafenib Clinical Data and a Cost-Effectiveness Analysis[END_REF] A multivariate logistic regression was performed to calculate the propensity score for antibiotic exposure using all the covariates with non-zero values collected before the antibiotic timeframe. Treated patients were weighted by the probability of not receiving antibiotics (1 -propensity score) and untreated patients were weighted by the probability of receiving antibiotics (propensity score). [START_REF] Thomas | Overlap Weighting[END_REF][START_REF] Li | Addressing Extreme Propensity Scores via the Overlap Weights[END_REF] Covariate balance was checked using standardized differences in pseudo-populations in the exposed versus non-exposed groups.

Statistical analysis

Kaplan-Meier curves and weighted log-rank tests were performed within pseudo-populations. To evaluate the impact of antibiotic exposure on OS and TTD, a propensity score-weighted Cox proportional hazards regression model was used to estimate weighted hazard ratios (wHRs) and 95% confidence intervals (CIs). Proportional hazards were assessed by plotting log(log(survival)) versus the log of survival time for categorical covariates, and scaled Schönfeld residuals versus survival time for continuous covariates. To study the prescription of antibiotics according to the progression of melanoma disease, the proportion of patients initiating an antibiotic course was plotted against time for patients receiving anti-PD-1 antibody or targeted therapy as a first treatment line. Because every individual living in France is included in the SNDS database until death, there was no loss to follow-up. Statistical significance was defined at an a priori value of 0.05. Statistical analyses were performed using R v3.6.0 software (R Inc, USA). All statistical tests were 2-sided.

Results

Patient characteristics

In the anti-PD-1 antibody cohort (n=2605), 749 (28.6%) patients received antibiotics in the 3 months prior to anti-PD-1 initiation. In the targeted therapy cohort (n=1527), 460 (30.1%) patients received antibiotics in the 3 months prior to targeted therapy initiation. Age, sex, metastatic sites, previous surgery or radiotherapy and comorbidities were reported for both the ICI and targeted therapy cohorts. After overlap weighting, standardized mean differences between patients receiving or not receiving antibiotics were close to zero for all covariates (Table 1, Supplementary Table 2). All the characteristics measured were thus well balanced across groups within the pseudo-populations.

Antibiotic exposure before first-line anti-melanoma treatment

In the anti-PD-1 antibody cohort, 749 patients received 954 antibiotic prescriptions in the 3 months prior to their first-line treatment. In the targeted therapy cohort, there were 583 antibiotic prescriptions for 460 patients. The main antibiotics prescribed were amoxicillin/clavulanate (28.9%), amoxicillin (19.8%), pristinamycin (10.3%) and ofloxacin (4.5%). Primary infections requiring hospitalization were urinary tract (26.3%), respiratory tract (22.6%), skin and skinassociated structures infections (22.9%) and fever of undetermined cause (16.7%). The proportion of patients receiving an antibiotic prescription each day was estimated in the 2 years before the initiation of the first-line anti-melanoma treatment. The incidence of antibiotic prescriptions rose steadily from 12 months before the first-line treatment in both cohorts (Figure 1).

Association between antibiotic use in the 3 months prior to anti-melanoma treatment and outcome

In the anti-PD-1 antibody cohort, 956 (36.7%) patients had died and 1602 (61.5%) had discontinued their first treatment line by December 31, 2017. Antibiotic exposure was not associated with shorter OS (wHR=1.01, 95% CI = 0.88-1.17) or TTD (wHR=1.00, 95% CI = 0.89-1.11). Kaplan-Meier curves were superimposed according to antibiotic receipt in the pseudo-populations (Figure 2, A andB).

In the targeted therapy cohort, 701 (45.9%) patients had died and 1074 (70.3%) had discontinued their first treatment line by December 31, 2017. Antibiotic exposure was not associated with OS (wHR=1.08, 95% CI = 0.92-1.27) or TTD (wHR=1.04, 95% CI = 0.91-1.18) (Figure 2, C andD).

Sensitivity analyses

As the impact of antibiotic treatment was suspected to be more detrimental in the month prior to ICI initiation, a first sensitivity analysis was performed narrowing the antibiotic timeframe to 1 month. No statistically significant association between antibiotic treatment and OS or TTD was evidenced in either cohort (Figure 3).

As high-impact antibiotics (fluoroquinolones, penicillins associated with β-lactamase inhibitors and second-and third-generation cephalosporins) induce more profound gut dysbiosis, [START_REF] Zimmermann | The effect of antibiotics on the composition of the intestinal microbiota -a systematic review[END_REF][START_REF] Yang | The varying effects of antibiotics on gut microbiota[END_REF][START_REF] Sullivan | Effect of antimicrobial agents on the ecological balance of human microflora[END_REF][START_REF] Bhalodi | Impact of antimicrobial therapy on the gut microbiome[END_REF] a second sensitivity analysis restricted the analysis to these antibiotics. In both the anti-PD-1 antibody and targeted therapy cohorts, no statistically significant association between high-impact antibiotics and OS or TTD was evidenced (Figure 3).

In a third sensitivity analysis, patients hospitalized with a diagnosis of infection were excluded, as antibiotics administered during hospital stays are not recorded in the SNDS database. OS and TTD were not associated with antibiotic treatment after exclusion of these patients in either the anti-PD-1 antibody or the targeted therapy cohorts (Figure 3).

Crude HRs (resulting from analyses in the initial non-weighted populations) and wHRs (obtained from pseudo-populations) for the main and sensitivity analyses are provided in Supplementary Table 3.

Discussion

In this population-based study including 749 patients exposed to antibiotics compared to 1856 non-exposed patients, using an overlap weighting method based on a propensity score to balance characteristics of patients between groups, we evidenced that antibiotic use prior to anti-PD-1 antibody for advanced melanoma was not associated with worse outcome, whether for OS or for TTD. Consistent results were observed when the timeframe of antibiotic exposure was reduced from 3 to 1 month prior to anti-PD-1 initiation, or when exposure was restricted to antibiotics leading to more profound gut dysbiosis.

Considerable interest has been devoted to the investigation of how concomitant therapies with a potential immunomodulatory effect might interact with ICI among cancer patients. In particular, gut microbes could enhance antitumor immunity through T-cell responses to microbial antigens and cross-reactions with cancer antigens. [START_REF] Fluckiger | Cross-reactivity between tumor MHC class Irestricted antigens and an enterococcal bacteriophage[END_REF][START_REF] Inamura | Roles of microbiota in response to cancer immunotherapy[END_REF] In keeping with this hypothesis, antibiotic treatment could decrease ICI efficacy by altering the composition and diversity of the gut microbiota. [START_REF] Routy | Gut microbiome influences efficacy of PD-1based immunotherapy against epithelial tumors[END_REF][START_REF] Huang | Relating Gut Microbiome and Its Modulating Factors to Immunotherapy in Solid Tumors: A Systematic Review[END_REF][START_REF] Matson | The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients[END_REF][START_REF] Gopalakrishnan | Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients[END_REF][START_REF] Wind | Gut microbial species and metabolic pathways associated with response to treatment with immune checkpoint inhibitors in metastatic melanoma[END_REF][START_REF] Pierrard | Impact of the gut microbiome on immune checkpoint inhibitor efficacy-a systematic review[END_REF][START_REF] Hakozaki | The Gut Microbiome Associates with Immune Checkpoint Inhibition Outcomes in Patients with Advanced Non-Small Cell Lung Cancer[END_REF][START_REF] Baruch | Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients[END_REF] However, there is no consensus on which bacterial species are associated with response to anti-PD-1 antibody. [START_REF] Huang | Relating Gut Microbiome and Its Modulating Factors to Immunotherapy in Solid Tumors: A Systematic Review[END_REF][START_REF] Wind | Gut microbial species and metabolic pathways associated with response to treatment with immune checkpoint inhibitors in metastatic melanoma[END_REF][START_REF] Pierrard | Impact of the gut microbiome on immune checkpoint inhibitor efficacy-a systematic review[END_REF] In addition, only a minority of the taxa forming the human gut microbiota are able to colonize mice, which makes extrapolating findings from rodent studies hazardous. [START_REF] Zhang | Environmental spread of microbes impacts the development of metabolic phenotypes in mice transplanted with microbial communities from humans[END_REF][START_REF] Walter | Establishing or Exaggerating Causality for the Gut Microbiome: Lessons from Human Microbiota-Associated Rodents[END_REF] Thus, the link between the gut microbiota and response to ICI still needs to be further understood, and to date we lack experimental evidence on the issue of whether, how and for how long induced gut dysbiosis can alter ICI efficacy. [START_REF] Walter | Establishing or Exaggerating Causality for the Gut Microbiome: Lessons from Human Microbiota-Associated Rodents[END_REF] In view of the immunological rationale, observational studies have investigated the effect of antibiotic exposure on ICI efficacy among cancer patients. The current body of knowledge derived from observational studies converges towards poorer prognosis among patients exposed to antibiotics in all cancers treated with ICI. [START_REF] Rossi | Concomitant medications during immune checkpoint blockage in cancer patients: Novel insights in this emerging clinical scenario[END_REF][START_REF] Petrelli | Survival of Patients Treated with Antibiotics and Immunotherapy for Cancer: A Systematic Review and Meta-Analysis[END_REF][START_REF] Wilson | The effect of antibiotics on clinical outcomes in immune-checkpoint blockade: a systematic review and meta-analysis of observational studies[END_REF][START_REF] Xu | The association between antibiotics use and outcome of cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis[END_REF][START_REF] Spakowicz | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications[END_REF][START_REF] Tsikala-Vafea | Use of antibiotics is associated with worse clinical outcomes in patients with cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis[END_REF][START_REF] Wu | The impact of antibiotics on efficacy of immune checkpoint inhibitors in malignancies: A study based on 44 cohorts[END_REF] The association was often strong but the data were heterogeneous, mixing different treatment lines, different ICIs or even different types of cancer within the same studies. Relevant confounders could not be appropriately taken into account in most studies, due to small sample sizes and heterogeneity. For example, patients with certain comorbidities or locations of metastases could be more likely to receive antibiotics, and these data were absent or incomplete. This could also explain why the association between antibiotic exposure and poor prognosis was not related to the spectrum of the antibiotics used, nor therefore to their impact on the gut microbiota. [START_REF] Mohiuddin | Association of Antibiotic Exposure With Survival and Toxicity in Patients With Melanoma Receiving Immunotherapy[END_REF][START_REF] Spakowicz | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications[END_REF] To disentangle the causal effect of antibiotic exposure from the confounding effect of patient characteristics, including patient fitness, comorbidities, and evolution of the metastatic disease, is a challenging issue. [START_REF] Hussain | Concomitant medications and immune checkpoint inhibitor therapy for cancer: causation or association?[END_REF][START_REF] Spakowicz | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications[END_REF] Confounding by indication is hard to fully capture with conventional methods, which inadequately control for prognostic variables. [START_REF] Bosco | A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies[END_REF][START_REF] Greenland | Control of Confounding in the Assessment of Medical Technology[END_REF] However, confounding by indication can have a major impact on results. This bias can suggest an association that does not exist, or even reverse the direction of an association. [START_REF] Bosco | A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies[END_REF] Regarding our population, we report in Figure 1 the proportion of patients receiving antibiotics, which increased with the approach of first-line anti-melanoma treatment. The steady increase in antibiotic use in the months preceding the initiation of the firstline treatment for metastatic melanoma could be in line with the intensification of care related to a symptomatic or complicated cancer. Antibiotic prescription could be associated with the discovery of the metastatic stage (e.g. pulmonary infections associated with lung metastases). In particular, a peak in antibiotic prescription was reached in the targeted therapy cohort in the month preceding the initiation of targeted therapy, which could suggest a strong confounding effect, and explain the statistically significantly increased crude HR for OS in the month prior to initiation in the targeted therapy cohort.

Our study has several strengths. First, while confounding is the alternative explanation for the shorter survival of patients receiving antibiotics in previous observational studies, the propensity score weighting method using overlap weights has been reported to show remarkable performance to avoid this bias. [START_REF] Mlcoch | Propensity Score Weighting Using Overlap Weights: A New Method Applied to Regorafenib Clinical Data and a Cost-Effectiveness Analysis[END_REF][START_REF] Austin | An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies[END_REF][START_REF] Hernán | A structural approach to selection bias[END_REF] Second, we identified a large number of comorbidities and provided precise information on metastatic locations using our database, which combines diagnosis-based and medication-based information with considerable historical depth. [START_REF] Tuppin | Value of a national administrative database to guide public decisions: From the système national d'information interrégimes de l'Assurance Maladie (SNIIRAM) to the système national des données de santé (SNDS) in France[END_REF][START_REF] Constantinou | Two morbidity indices developed in a nationwide population permitted performant outcome-specific severity adjustment[END_REF] These characteristics are relevant confounders in this context, and their identification enabled us to balance prognosis factors across groups. Third, the size of our nationwide database yielded a power of over 99% to demonstrate the previously suggested association among patients receiving anti-PD-1 antibody. [START_REF] Mohiuddin | Association of Antibiotic Exposure With Survival and Toxicity in Patients With Melanoma Receiving Immunotherapy[END_REF][START_REF] Wu | The impact of antibiotics on efficacy of immune checkpoint inhibitors in malignancies: A study based on 44 cohorts[END_REF] The number of antibiotic-exposed patients in our study was similar to the number in meta-analyses mixing studies on all cancer types, treatment lines and antibiotic timeframes. [START_REF] Yu | Effects of Antibiotic Use on Outcomes in Cancer Patients Treated Using Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis[END_REF][START_REF] Petrelli | Survival of Patients Treated with Antibiotics and Immunotherapy for Cancer: A Systematic Review and Meta-Analysis[END_REF][START_REF] Wilson | The effect of antibiotics on clinical outcomes in immune-checkpoint blockade: a systematic review and meta-analysis of observational studies[END_REF][START_REF] Xu | The association between antibiotics use and outcome of cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis[END_REF][START_REF] Tsikala-Vafea | Use of antibiotics is associated with worse clinical outcomes in patients with cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis[END_REF] In addition, the exhaustiveness of the database, with no loss to follow-up, protected from selection and attrition bias. Fourth, as there is no underlying rationale for antibiotics to impact the efficacy of targeted therapy, using the targeted therapy cohort as a negative control was an original and relevant approach to address our question. Fifth, TTD corresponds to the time during which the disease is under control for a given treatment line, and was therefore used to reflect the impact of antibiotics on the first anti-melanoma treatment, irrespective of subsequent treatment lines.

Our study has limitations. First, prognostic factors like LDH levels, performance status or socioeconomic status were lacking in our database and could therefore not be used in the propensity score. Second, we used drug dispensations as a proxy for drug intake, but we could not ascertain the completion of antibiotic courses. However, even short antibiotic courses could have a prolonged effect on gut microbiota. [START_REF] Abeles | Microbial diversity in individuals and their household contacts following typical antibiotic courses[END_REF][START_REF] Elvers | Antibiotic-induced changes in the human gut microbiota for the most commonly prescribed antibiotics in primary care in the UK: a systematic review[END_REF] Third, antibiotics administered during hospital stays are not recorded in our database. Therefore, in a sensitivity analysis we excluded patients who had been hospitalized for infection during the timeframe of exposure, as they could have been misclassified. In addition, infections requiring hospitalization often correspond to severe infections, [START_REF] Sahli | Positive predictive values of selected hospital discharge diagnoses to identify infections responsible for hospitalization in the French national hospital database[END_REF] and patients could have a competing risk of death, which justified excluding them.

Fourth, participation in a clinical trial could not be identified in our database, because clinical trials entail no billing to the National Health Insurance. Fifth, strictly speaking, our results apply only to metastatic melanoma and one could be reluctant to extrapolate to other cancers. However, the two hypotheses discussed (antibiotic-induced gut dysbiosis impairing ICI efficacy and confounding by indication) concern general phenomena and should apply across other cancers treated with ICI.

Our results bring a robust contribution to the question of the impact of antibiotics on ICI efficacy and overall prognosis among cancer patients. Unlike previous findings, we show that antibiotic treatment before anti-PD-1 antibody initiation is not associated with decreased efficacy of anti-PD-1 antibody among metastatic melanoma patients. While some may consider that the jury is still out, we argue that strong and reasonable doubt exists for confounding by indication as the culprit accounting for a so-called antibiotic-induced detrimental effect on ICI efficacy. As a consequence, from a clinical point of view, we suggest that physicians should not delay ICI for patients who have recently received antibiotics on the grounds of a risk of lack of efficacy. In addition, no data exist to substantiate what would be an appropriate and safe time-lag. Avoiding delaying immunotherapy is certainly a widely-shared attitude in metastatic settings, but it should also be recalled when administering ICI in adjuvant settings.

Tables

Figure 1 .

 1 Figure 1. Evolution of antibiotic use according to the progression of melanoma disease over

Figure 2 .

 2 Figure 2. Kaplan Meier curves for overall survival and time-to-treatment discontinuation

Figure 3 .

 3 Figure 3. Forest plot summarizing the analyses performed in both cohorts of patients

Figure 2 -

 2 Figure 2--FINAL Click here to access/download;Figure;21-1391R1 Dupuy Figure 2_011822.pdf

Table 1 . Characteristics of patients receiving anti-PD-1 antibody as a first-line treatment for metastatic melanoma and standardized mean differences according to antibiotic exposure

 1

	Characteristic

Sanofi and UCB Pharma, and personal fees from Sanofi, outside the submitted work. The other authors have no disclosures.

Funding

This work was supported by the Ligue Contre le Cancer (French Cancer League) (PhD grant to [FP]).

Notes

Role of the funder: The funding source had no role in the study design, the conduct or the management for the study; in the collection, analysis, or the interpretation of the data; in the writing of the manuscript; nor in the decision to submit the manuscript for publication.

Disclosures: VC reports reimbursement for travel and/or accommodation expenses for attending congresses from bioMérieux, Menarini and Pfizer, and personal fees for expertise and/conferences from Accelerate Diagnostics, bioMérieux, Correvio, Eumedica, Menarini and Mylan, outside the submitted work. TL reports personal fees from BMS, MSD, Novartis and Pierre Fabre Oncology, outside the submitted work. MD reports reimbursement for travel and/or accommodation expenses for attending medical meetings from BMS, MSD, Novartis and Pierre Fabre Oncology and personal fees from Sanofi, outside the submitted work. AD reports reimbursement for travel and/or accommodation expenses for attending medical meetings from

Data Availability

The protocol and the statistical code are available on justified request. Under French law and regulations, databases extracted from the Systeme National des Données de Santé cannot be made available.


domain: chim phys

text:
Adam P Pikul
email: a.pikul@intibs.pl

Rafał Idczak

Piotr Sobota

Wojciech Nowak

Mathieu Pasturel

Vinh Hung Tran

S S Saxena

P Agarwal

K Ahilan

F M Grosche

R K W Hasel- 347 Wimmer

M J Steiner

E Pugh

I R Walker

S R Julian

P Monthoux

M Szlawska

H Noël

D Kaczorowski

: Ineestnatong

Ineestnatong Vinh

Hunn Tran

Ferromagnetic Ordering in UFe 0.40 Ge 2 Studied by 57 Fe Mössbauer Spectroscopy

Keywords: A. Uranium intermetallics, A. Uranium germanides, D. Ferromagnetic ordering, E. X-ray powder diffraction, E. Magnetization measurements, E. Mössbauer spectroscopy Conceptualization, Formal analysis, Writing - Conceptualizatonn Formal analysisn Writnn --Orininal Drafn eeiew

A polycrystalline 57 Fe-isotope-enriched sample of UFe 0.40 Ge 2 was investigated by X-ray powder diffraction, magnetization and Mössbauer spectra measurements. The compound was confirmed to crystallize with the orthorhombic CeNiSi 2 -type structure (space group Cmcm) and with the lattice parameters a = 4.0759(2) Å, b = 15.8107(7) Å, and c = 4.0379(2) Å, being close to those reported previously for a very similar composition. Magnetic properties measurements showed that UFe 0.40 Ge 2 orders ferromagnetically at T C = 37 K with the effective magnetic moment of 2.57(3) µ B and the ordered magnetic moment at 70 kOe of about 0.64(1) µ B , being fully consistent with the earlier report on physical properties of UFe 0.39 Ge 2 . 57 Fe Mössbauer spectra measurements performed both in the field-cooled and zero-field-cooled regimes rulled out the formation of ferromagnetic cluster-glass or spin-glass state, and confirmed that the ferromagnetism in the studied system is purely long-range in nature. A small contribution of about 0.24-0.36 µ B to the total magnetic moment from the iron atoms was observed.

Introduction

Uranium germanides have attracted much attention from the scientific community, following the discovery of unconventional superconductivity in the ferromagnetically ordered compound UGe 2 [1], which crystallizes in the orthorhombic ZrGa 2type structure (space group Cmmm) [2, 3]. As a result of intense search for other compounds exhibiting the coexistence of ferromagnetism and superconductivity, which so far were considered to be mutually exclusive, two ternary uranium germanides, namely URhGe and UCoGe, have been reported to be superconducting ferromagnets [4,5]. They crystallize with the orthorhombic unit cell of the TiNiSi type (space group Pnma), and their common feature with UGe 2 is the presence of uranium zig-zag chains within the uranium layers.

Very similar uranium zig-zag chains have also been found in another group of uranium germanides, namely the compounds UT 1-x Ge 2 (where T = Ru, Os, Ni and Fe), which all crystallize in certain derivatives of the same orthorhombic type of crystal structure. In particular, URu 0.29 Ge 2 and UOs 0.25 Ge 2 form with a monoclinically distorted CeNiSi 2 -type unit cell (space group C2/c) [6, 7]), while UNi 0.45 Ge 2 and UFe 0.39 Ge 2 crystallize in a Ni-deficient CeNiSi 2 structure type (space group Cmcm) [START_REF] Pasturel | An-376 tiferromagnetic ordering in the ternary uranium germanide UNi 1-x Ge 2 : 377 Neutron diffraction and physical properties studies[END_REF][START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF].

The compounds with Ru, Os and Fe order ferromagnetically at 63 K [6], 45 K [7] and 37 K [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF], respectively, and only the Nibearing phase was found to order antiferromagnetically at 47 K [START_REF] Pasturel | An-376 tiferromagnetic ordering in the ternary uranium germanide UNi 1-x Ge 2 : 377 Neutron diffraction and physical properties studies[END_REF].

The ferromagnetic order in UFe 0.39 Ge 2 at T C = 37 K oc-27 curs in the presence of significant crystallographic disorder.

28

That disorder strongly influences the low-temperature physical 29 properties of the compound (especially its transport properties), 30 suggesting the formation of a ferromagnetic cluster glass [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF].

31

To verify the latter hypothesis, we have investigated that com-32 pound by measuring its 57 Fe Mössbauer spectra at various tem-33 peratures from the magnetically ordered range and in two dif-34 ferent cooling regimes. In the following, we present the results

35

of those experiments along with their analysis for the formation 36 of glassy states.

37

Material and Methods

38

A polycrystalline sample with a nominal composition of 39 UFe 0.40 Ge 2 (that is, to the nearest 0.3%, identical to the pre-40 vious composition) was prepared by conventional arc melting 41 the elemental components (with purity higher than 99.5% in 42 each case) with about 5 at.% iron substitution by the 57 Fe iso-

Results and Discussion

Crystal structure

The experimental XRD pattern of the 57 Fe-isotope-enriched UFe 0.40 Ge 2 sample (Fig. 1) was readily indexed within the Fedeficient orthorhombic CeNiSi 2 -type structure, already solved for that germanide [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF], with a small addition of the tetragonal paramagnetic U 9 Fe 7 Ge 24 phase [START_REF] Henriques | Structural and physical properties of the U 9 Fe 7 Ge 24 uranium 389 germanide[END_REF]. (The presence of that secondary phase was deliberately allowed, as discussed in

Ref. [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF]). The Rietveld refinement of those two crystal structures, performed using the crystallographic data reported in

Refs. [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF] and [START_REF] Henriques | Structural and physical properties of the U 9 Fe 7 Ge 24 uranium 389 germanide[END_REF], gave relative amounts of the two phases of phases (if present at all), but their amount would still be less 86 than 1 -2 wt%. Fig. 2 shows results of the magnetic properties measurements carried out for UFe 0.40 Ge 2 . As can be seen, above about 130 K the inverse magnetic susceptibility exhibits featureless and slightly curvilinear behavior characteristic of paramagnets. The experimental data can be easily described by the modified Curie-Weiss law:

χ(T ) = 1 8 µ 2 eff T -θ p + χ 0 , (1)
where µ eff is the effective magnetic moment, θ p stands for the Journal Pre-proof µ eff is lower than that expected for free U 3+ and U 4+ ions (3.62 and 3.58 µ B , respectively), but it is large enough to be attributed mainly to the uranium ions. The observed discrepancy may be due to partial delocalization of 5f electrons, magnetocrystalline anisotropy or crystal field effects. The large and positive value of θ p indicates the presence of predominantly ferromagnetic interactions between the magnetic moments.

The pronounced Brillouin-like-shaped anomaly that is visible in the temperature variation of the magnetization, σ(T ), at about 37 K (see the upper inset to Fig. 2) manifests ferromagnetic ordering of UFe 0.40 Ge 2 , being in full agreement with our previous finding [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF]. The field dependence of the magnetization, σ(H), measured at the lowest temperature studied, i.e.

1.8 K (see the lower inset to Fig. 2) confirms the ferromagnetic character of the ordering. In the highest field σ reaches a value of 8.83 emu/g, which corresponds to the ordered magnetic moment of about 0.64 µ B . It is close to the value reported for UNi 0.39 Ge 2 [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF] and is within the range of values observed for uranium intermetallics.

The above findings show that the magnetic properties of the sample used in the present study are well defined, and the UFe 1-x Ge 2 system under study exhibits reproducible magnetic properties.

TMS results

Selected TMS spectra measured for the UFe 0.40 Ge 2 sample are presented in Figs. 3 and4. As can be seen, the spectra measured at T ⩾ 35 K (Fig. 3), corresponding approximately to the paramagnetic region of the studied compound, can be described using two paramagnetic components. The major one, with the relative intensity of about 95%, is a well-resolved symmetric doublet. Given the XRD results described in Sec.3.1 as well as in Ref. [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF], this component can be ascribed to the compound UFe 0.40 Ge 2 , in which Fe atoms occupy a single crystallographic site with symmetry lower than cubic. Deep in the magnetically ordered region (Fig. 4), i.e. at T ⩽ 30 K, this component can no longer be described by the doublet, and it must be described by a magnetic sextet with a small hyperfine field B hf = 2.10(3) T, 3.39(1) T and 3.55(2) T for the spectra measured at 30 K, 10 K and 4.3 K, respectively.

The second, minor component of the deconvoluted TMS spectra, with relative intensity being close to 5%, can be described by a single line component (a singlet) with IS = 0.06(5) mm/s at 300 K. As can be seen in Figs. 3 and4 U 34 Fe 4-x Ge 33 is -0.03 mm/s [START_REF] Henriques | Unusual 5f magnetism 398 in the U 2 Fe 3 Ge ternary laves phase: a single crystal study[END_REF] and 0.13 mm/s [START_REF] Henriques | A novel ternary uranium-based intermetal-403 lic U 34 Fe 4-x Ge 33 : Structure and physical properties[END_REF], respec-164 tively.

165

The TMS spectra shown in Figs. 3 and4 the isomer shift is dependent on the s-electrons density and is given by the relation [START_REF] Gütlich | Mössbauer Spectroscopy and Tran-407 sition Metal Chemistry: Fundamentals and Applications[END_REF]:

IS = 4π 5 Ze 2 R 2 δR R |Ψ A (0)| 2 -|Ψ S (0)| 2 , ( 2
)
where Z is the nuclear charge of the Mössbauer absorber, e is the elementary charge, R is the radius of the probe nucleus, δR is the difference between the radii in the ground and excited states, and |Ψ S (0)| 2 and |Ψ A (0)| 2 are the s-electrons densities at the probe nuclei in the source and absorber, respectively. At 300 K, the IS parameter determined for the UFe 0.40 Ge 2 compound is equal to 0.238(4) mm/s. This value lies between that reported earlier for U 3 Fe 2 Ge 7 (0.21(2) mm/s) [START_REF] Henriques | Synthe-414 sis and Structural/Physical Properties of U 3 Fe 2 Ge 7 : A Single-Crystal 415 Study[END_REF] and that found for U 3 Fe 4 Ge 4 (0.27(2) mm/s) [START_REF] Berthebaud | Crystal structure and electronic properties of 419 the new compound U 3 Fe 4 Ge 4[END_REF], indicating a very similar electron density at the iron nuclei in these three systems.

As expected from the second-order Doppler (SOD) effect, the IS values obtained for UFe 0.40 Ge 2 increase concavely with decreasing temperature. Since the second-order Doppler shift depends on the lattice vibrations of the Fe atoms, the IS (T ) dependence can be expressed in terms of the Debye approximation of the lattice vibrations as [START_REF] Gütlich | Mössbauer Spectroscopy and Tran-407 sition Metal Chemistry: Fundamentals and Applications[END_REF]:

IS (T ) = IS (0) + IS SOD (T ) = = IS (0) - 9 2 k B T Mc T Θ D 3 Θ D /T 0 x 3 dx e x -1 , (3)
where IS (0) denotes the temperature-independent isomer shift, M is the mass of the nuclei of the absorber (here: 57 Fe), k B eter at 300 K is equal to 0.342(2) mm/s, which is comparable 214 to QS = 0.32(2) mm/s reported previously for U 3 Fe 2 Ge 7 [START_REF] Henriques | Synthe-414 sis and Structural/Physical Properties of U 3 Fe 2 Ge 7 : A Single-Crystal 415 Study[END_REF].

Since the structure of U 3 Fe 2 Ge 7 can be seen as stacking of the UFeGe 2 and UGe 3 layers along the b-axis, the charge distribution around the Fe nuclei in the U 3 Fe 2 Ge 7 system should indeed be similar to that observed in UFe 0.40 Ge 2 .

In many intermetallic systems, the QS (T ) dependence can be described by the empirical formula [START_REF] Stadnik | Mag-422 netic ordering in TlFe 1.3 Se 2 studied by Mössbauer spectroscopy[END_REF][START_REF] Albedah | 57 Fe Möss-426 bauer spectroscopy and magnetic study of Al 13 Fe 4[END_REF]:

QS (T ) = QS (0)(1 -AT 3/2 ), (4)
where QS (0) is the value of QS at 0 K and A is a constant. Fitting Eq. 4 to the experimental data yields QS (0) = 0.353(2) mm/s and A = 6(1)×10 -6 K -3/2 . The determined fitting parameters can be treated as material constants, since their physical meaning is not clearly defined.

According to the results of our magnetic properties measurements (see Sec. 3.2 and Ref. [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF]), the observed magnetic properties of the UFe 0.40 Ge 2 compound can be ascribed mainly to the uranium ions. However, the appearance of the Zeeman sextets in the TMS spectra measured at T ⩽ 30 K may suggest that the Fe sublattice establishes long-range magnetic correlations below T C . This behavior is similar to that observed in other uranium-iron ferromagnets, e.g. UFe 2 [START_REF] Tsutsui | 430 238 U and 57 Fe Mössbauer Spectroscopic Study of UFe 2[END_REF], U 2 Fe 3 Ge [START_REF] Dhar | Structure and 434 magnetic properties of U 2 Fe 3 Ge[END_REF] and U 3 Fe 2 Ge 7 [START_REF] Henriques | Synthe-414 sis and Structural/Physical Properties of U 3 Fe 2 Ge 7 : A Single-Crystal 415 Study[END_REF]. In all of them, the Mössbauer spectra collected below their magnetic ordering temperatures indicate the presence of small hyperfine field (B hf < 5 T) at the 57 Fe nuclei.

On the other hand, the magnetic 57 Fe spectra observed be- is comparable with µ Fe ≈ 0.2 µ B inferred from the Mössbauer spectra measurements carried out for U 3 Fe 2 Ge 7 [START_REF] Henriques | Synthe-414 sis and Structural/Physical Properties of U 3 Fe 2 Ge 7 : A Single-Crystal 415 Study[END_REF], and is small compared to the effective magnetic moment found for UFe 0.40 Ge 2 . Thus, it does not change our conclusions about the origin of magnetism in the latter compound (see Sec. 3.2 and Ref. [START_REF] Szlawska | Ferromagnetism in 381 structurally disordered UFe 0.39 Ge 2[END_REF]).

The values of the QS and ϵ parameters obtained for the paramagnetic and magnetically ordered states of UFe 0.40 Ge 2 , respectively, can be used to determine the angle φ between B hf and the principal axis V zz of the main electrical field gradient 269 (EFG). Using the commonly used formula [START_REF] Henriques | Synthe-414 sis and Structural/Physical Properties of U 3 Fe 2 Ge 7 : A Single-Crystal 415 Study[END_REF][START_REF] Filoti | Mössbauer study of the hyperfine 440 interactions and spin dynamics in α-iron(ii) phthalocyanine[END_REF]:

270 ϵ = 1 2 QS (3cos 2 φ -1), (5)
and taking QS = 0.353 mm/s and ϵ = 0.08 mm/s, the angle The first measurement (denoted as ZFC in Fig. 4) was carried

43Figure 1 :

 1 Figure1: Powder X-ray diffraction pattern of UFe 0.40 Ge 2 (red circles) plotted along with results of the Rietveld refinement of its crystal structure (black curve). Upper and lower green ticks indicate Bragg positions for the major (UFe 0.40 Ge 2 ) and the impurity (U 9 Fe 7 Ge 24 ) phases, respectively. Blue curve shows the difference between the experimental and the theoretical patterns.

Figure 2 :

 2 Figure 2: Temperature dependence of inverse magnetic susceptibility χ -1 of UFe 0.40 Ge 2 ; solid line is a fit of the modified Curie-Weiss law to the experimental data (for details see the text). Upper inset: low temperature variation of mass magnetization σ measured in field-cooling regime; an arrow marks the ferromagnetic ordering temperature T C . Lower inset: σ as a function of increasing (open symbols) and decreasing (closed symbols) applied magnetic field H.

87

  The refined cell parameters for UFe 0.40 Ge 2 are 88 a = 4.0759(2) Å, b = 15.8107(7) Å, and c = 4.0379(2) Å. These 89 values are somewhat closer to those reported by Henriques 90 et al. for a similar chemical composition (a = 4.083(5) Å, 91 b = 15.805(5) Å, and c = 4.030(5) Å[12]) than our previous 92 results reported for a polycrystalline sample with the initial 93 composition 'UFe 0.45 Ge 2 ' (a = 4.0886(1) Å, b = 15.8339(3) Å, 94 and c = 4.0505(1) Å), suggesting the existence of a small 95 homogeneity domain for the studied phase. Nevertheless, 96 the results show that the sample synthesized for the study 97 described in this paper is essentially identical to the previous 98 sample described in Ref. [9].99 3.2. Magnetic properties 100

101Curie-

  Weiss temperature, and χ 0 denotes temperature indepen-102 dent Pauli-like contribution to the total magnetic susceptibility. 103 The least-squares fitting of Eq. (1) to the experimental data re-104 sulted in the parameter values: µ eff = 2.57(3) µ B , θ p = 23(2) K, 105 and χ 0 = 8.6(5)×10 -4 emu/mol, being fully consistent with 106 those obtained previously for UFe 0.39 Ge 2 (µ eff = 2.59µ B , 107 θ p = 30 K, and χ 0 = 1× 10 -4 [9]). The so-estimated value of J o u r n a l P r e -p r o o f

Figure 3 :

 3 Figure3: TMS spectra of UFe 0.40 Ge 2 measured at several temperatures from the range 35 -300 K and in zero applied magnetic field, fitted by a sum (black curve) of one doublet and one singlet component (blue and red lines, respectively). For details of the fits see the text.

Figure 4 :

 4 Fig. 3 consist of two components rather than one doublet with 184

Figure 5 :Figure 6 :

 56 Figure 5: Temperature variations of the IS (a) and QS (b) parameters derived from the TMS spectra of UFe 0.40 Ge 2 . Black curves are fits of Eqs. (3) and (4) to the experimental data shown in panels (a) and (b), respectively (for details see the text).

  Fig.6, the collected spectrum reveals the presence of two Zeeman components that consist of four lines, since in such a configuration the observed line intensity ratio for the sextet should be 3:0:1:1:0:3[START_REF] Greenwood | Mössbauer Spectroscopy[END_REF]. The first component, with a relative intensity of 7(2)%, IS = 0.13(2) mm/s and effective hyperfine magnetic field B eff = 2.8(2) T, can be attributed to the impurity phase. The second, major component corresponds to UFe 0.40 Ge 2 and can be described by the Zeeman sextet with B eff = 3.78(2) T, IS = 0.333(7) mm/s and ϵ = 0.01(4) mm/s. Since B eff = B hf + B ext , the determined B eff = 3.78(2) T confirms that the iron atoms in UFe 0.40 Ge 2 have a small magnetic moment. Assuming that the hyperfine coupling constant for intermetallic compounds is in the range from 10 T/µ B to 15 T/µ B[START_REF] Henriques | Synthe-414 sis and Structural/Physical Properties of U 3 Fe 2 Ge 7 : A Single-Crystal 415 Study[END_REF][START_REF] Dhar | Structure and 434 magnetic properties of U 2 Fe 3 Ge[END_REF][START_REF] Dubiel | Relationship between the magnetic hyperfine field and the 437 magnetic moment[END_REF], the hyperfine magnetic field B hf = 0.78(2) T, obtained from the TMS spectrum measured for UFe 0.40 Ge 2 at 40 K and in B ext = 3 T, corresponds to the magnetic moment of iron µ Fe of about 0.05 -0.08 µ B . This estimated value of µ Fe

271φ

  = 45.3 • was obtained. 272 Finally, the TMS technique can be used to confirm or rule 273 out the formation of a ferromagnetic cluster-glass state in the 274 UFe 0.40 Ge 2 system [9]. For this purpose, we measured the 275 Mössbauer spectra of the compound at 4.3 K, that is, deep in 276 the magnetically ordered region, and in two different regimes.

  277

278315

  out in zero applied magnetic field and after cooling the sam-279 ple in zero external magnetic field. The second one (labelled 280 as FC in Fig.4) was also performed in zero magnetic field, but 281 after cooling the sample in the external field of 3 T, i.e. in the 282 nearly-saturated magnetization range. 283 For the ZFC spectrum, the sextet attributed to UFe 0.40 Ge 2 284 could be described by IS = 0.353(4) mm/s, ϵ = 0.08(1) mm/s 285 and B hf = 3.55(2) T while for FC, the hyperfine parameters 286 are IS = 0.349(2) mm/s, ϵ = 0.08(1) mm/s and B hf = 3.52(2) T. 287 Comparing these two sets of values, it can be seen that the two 288 spectra are virtually identical. Moreover, the line intensity ra-289 tio estimated for both Zeeman sextets is close to 3:2:1:1:2:3. 290 This means that the magnetic domains in the sample cooled in 291 both the ZFC and FC regimes are randomly oriented, which is 292 expected for the TMS measurements performed on polycrys-293 talline or powdered samples in the absence of an external mag-294 netic field [16]. 295 Let us now consider the expected response from the hypo-296 thetical cluster-glass formation. In the FC regime, the sam-297 ple was cooled down to 4.3 K in magnetic field applied par-298 allel to the γ-ray beam propagation. Again, in this configura-299 tion, the observed line intensity ratio for the sextet should be 300 3:0:1:1:0:3 [16]. If we assume that below T rmc a ferromagnetic 301 cluster-glass state really forms, then in the FC regime the mag-302 netic moments should be frozen at 4.3 K and aligned parallel 303 to the applied field. And then also the line intensity ratio for 304 the magnetic sextet in the FC spectrum should be close to the 305 3:0:1:1:0:3 mentioned above, not 3:2:1:1:2:3 as inferred from 306 the experimental spectrum. This means that the magnetic mo-307 ments are already magnetically ordered within randomly ori-308 ented domains, so the external magnetic field does not affect 309 their local arrangement. Thus, it can be concluded that no 310 behavior indicating the freezing of the magnetic moments (as 311 should be the case in cluster glass or spin glass) is observed, 312 and the compound UFe 0.40 Ge 2 orders purely ferromagnetically We have measured the transmission Mössbauer spectra on 316 a polycrystalline, 57 Fe-isotope-enriched sample of UFe 0.40 Ge 2 , 317 which has been positively verified for the crystal structure and 318

The work in Poland and France was co-financed by 341 the Polish National Agency for Academic Exchange

J o u r n a l P r e -p r o o f

Journal Pre-proof

The authors declare that they have no known competnn fnancial interests or personal relatonships that could have appeared to infuence the work reported in this paperh


Maëva Daoud

Ricardo Salvador

Nada El Youssef

Alexane Fierain

Elodie Garnier

Maria Chiara Biagi

Samuel Medina Villalon

Fabrice Wendling

Christian G Bénar

Giulio Ruffini

Nada El

Alexane Fierain²

Christian Benar

Fabrice Bartolomei
email: fabrice.bartolomei@ap-hm.fr

Prof Fabrice Bartolomei

Stereo-EEG based personalized multichannel transcranial direct current stimulation in drug-resistant epilepsy

Keywords: Drug-resistant epilepsy, Multichannel transcranial direct current stimulation (tDCS), Patient-specific approach, functional connectivity, Electroencephalography tDCS: Transcranial Direct Current Stimulation. SEEG: Stereoelectrocencephalography. EEG: Electroencephalography. DRE: Drug-resistant Epilepsy. SF: Seizure Frequency. Fc: Functional connectivity. R: Responder. NR: Non-responder. MRI: Magnetic Resonance Imaging. IQ: Intelligence Quotient. AEs: Adverse events. ICA: Independent Component Analysis. EMG: Electromyography. LMM: Linear Mixed Models. REML: Restricted Maximum Likelihood. LSM: Least Squares Means. SOZ: Seizure Onset Zone. VNS: Vagus Nerve Stimulation. SMA: Supplementary motor area. SZs: Seizures. FCD: Focal cortical dysplasia. SGTC: Seizure generalized tonico-clonic. ASM: antiseizure medication Cycle 1. C2: Cycle 2. C3: Cycle 3. Strength D5-D1: Strength Day 5 -Strength Day

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

Introduction

One-third of patients with epilepsy have seizures refractory to pharmacotherapy [START_REF] Brodie | Staged approach to epilepsy management[END_REF][START_REF] Devinsky | Epilepsy[END_REF]. The only curative treatment is surgery and in this context stereoelectroencephalography (SEEG) is increasingly used in presurgical assessment [START_REF] Baud | European trends in epilepsy surgery[END_REF][START_REF] Jehi | The evolution of epilepsy surgery between 1991 and 2011 in nine major epilepsy centers across the United States, Germany, and Australia[END_REF]. However, epilepsy surgery is only possible in a limited number of cases (15-20%) and is associated with a relatively high number of failures [START_REF] Baud | European trends in epilepsy surgery[END_REF]. Consequently, alternative treatments based on non-invasive brain stimulation methods aiming at decreasing cortical excitability represent a promising therapeutic. Transcranial direct current stimulation (tDCS) is an emerging noninvasive method of brain stimulation involving passing a weak current (1-2 mA) across the head tissue (scalp, skull, cortex) using scalp electrodes positioned on the head [START_REF] San-Juan | Transcranial Direct Current Stimulation in Epilepsy[END_REF]. This neuromodulatory technique could modulate brain excitability by subthreshold membrane depolarization or hyperpolarization. As the electric field under the anode is predominantly excitatory, and the one under the cathode is predominantly inhibitory [START_REF] Nitsche | Pharmacological Modulation of Cortical Excitability Shifts Induced by Transcranial Direct Current Stimulation in Humans[END_REF][START_REF] Nitsche | Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation[END_REF], in epilepsy, the target region must be in the field of a cathode to achieve cerebral inhibition. tDCS effects depend on several factors including stimulation duration, current intensity, number of repetitions, duration of the interval between stimulation sessions, number, and localization of electrodes. Indeed, conventional tDCS montage employs only two large electrodes (one anode and one cathode) whereas multichannel tDCS, uses several smaller pairs of electrodes that potentially enhance and optimize stimulation focality [START_REF] Villamar | Technique and Considerations in the Use of 4x1 Ring High-definition Transcranial Direct Current Stimulation (HD-tDCS)[END_REF]. Furthermore, the current values and electrode positions can be determined from computational head models and account for the geometry and conductive properties of the head tissues in order to accurately calculate the induced electric field, making it possible to target brain regions with more accuracy [START_REF] Sadleir | Target Optimization in Transcranial Direct Current Stimulation[END_REF].

In this way, several human and animal studies have shown the efficacy of cathodal stimulation for decreasing the number of epileptiform discharges [START_REF] Fregni | A Controlled Clinical Trial of Cathodal DC Polarization in Patients with Refractory Epilepsy[END_REF][START_REF] Lian | Local Suppression of Epileptiform Activity by Electrical Stimulation in Rat Hippocampus In Vitro[END_REF][START_REF] Yook | Suppression of Seizure by Cathodal Transcranial Direct Current Stimulation in an Epileptic Patient-A Case Report[END_REF]. However, the majority of previous studies employed generic bipolar montages with large sponges applied during one or a few treatment sessions and without personalization. Recently, a study involving drug resistant epilepsy patients employed multielectrode montages that were designed using a realistic head model-driven approach to drive an inhibitory electric field to the target cortical epileptic region [START_REF] Kaye | Personalized, Multisession, Multichannel Transcranial Direct Current Stimulation in Medication-Refractory Focal Epilepsy: An Open-Label Study[END_REF]. This study used a generic head model and a definition of the epileptogenic zone based solely on non-invasive recordings. Since tDCS electric-fields are affected by individual brain anatomy, a patient-specific approach is more suited to properly engage the targeted brain region [START_REF] Laakso | Inter-subject Variability in Electric Fields of Motor Cortical tDCS[END_REF][START_REF] Miranda | The electric field in the cortex during transcranial current stimulation[END_REF][START_REF] Ruffini | Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields[END_REF].

We report here a pilot study investigating the efficacy of an individualized multichannel tDCS protocol based on the patient's anatomy and epileptogenic network. We selected a population of patients with focal epilepsy considered as inoperable (or failing after surgery) and whose epileptogenic zone was clearly identified by prior SEEG recordings. This specific population was selected because the patients have severe epilepsy with no other therapeutic resources and they had SEEG procedure favoring optimal targeting for multichannel cathodal tDCS, especially for epilepsies with normal MRI or a complex epileptogenic zone exceeding lesion boundaries. Moreover, the neuromodulatory mechanisms associated with the application of a low-frequency electric field remain poorly understood. Drugresistant focal epilepsies are associated with interictal alterations in Fc, characterized in particular by increased neural synchrony in most epileptogenic regions [START_REF] Bartolomei | Defining epileptogenic networks : Contribution of SEEG and signal analysis[END_REF][START_REF] Bettus | Enhanced EEG functional connectivity in mesial temporal lobe epilepsy[END_REF][START_REF] Lagarde | Interictal stereotactic-EEG functional connectivity in refractory focal epilepsies[END_REF]. Thus, we sought to correlate the clinical efficacy of our tDCS protocol with changes in functional connectivity (Fc) measured from scalp EEG recordings. We hypothesized that the efficacy of multichannel tDCS is associated with Fc-specific changes.

Methods

Patients

Ten patients with drug-resistant focal epilepsy were enrolled in this study (7 male, 3 female); mean age 29.9 years; range 12-60 years).

Inclusion criteria were the following: (1) ≥12 years of age; (2) diagnosed with focal drug-resistant epilepsy not operable or presenting a failure of previous epilepsy surgery with at least 3 seizures per month during the baseline (before the first session of tDCS treatment) for at least 3 months; (3) SEEG previously performed before inclusion with an adequate definition of unifocal epileptogenic zone; (4) have stable medications for epilepsy for the whole study duration (5) Total IQ > 55; (6) be able to understand, speak and write in French.

Exclusion criteria were the following: (1) skin conditions (e.g., eczema, lesions) on the scalp;(2) any cranial metal implant; (3) or implanted devices (i.e. cardiac pacemaker, deep brain stimulator, cochlear implant, medication infusion pump); (4) previous surgeries opening the skull leaving skull defects with a radius ≥ to 5mm; (5) persons protected by articles L1121-5, L1121-6 and L1121-8 of Public Health Code (pregnant or breastfeeding woman, deprived of liberty by judicial decision, situations of social fragility, adults unable to express their consent).

The general characteristics of the patients are summarized in Table 1. This study was approved by the local ethics committee. Written informed consent was obtained from each patient or his or her legal representative before inclusion in the study.

Experimental design

This is a prospective, open labelled, monocentric pilot study in patients with medically refractory epilepsy followed during 8 months with patients acting as their own internal control For each patient, after a baseline period of at least two months, the study started with a 1-hour EEG exam (Electroencephalography) on day 1 of the week (before stimulation) in order to collect electrophysiological brain state right before stimulation treatment at the end of the baseline period. Then, each day of each stimulation cycle period (a cycle consisted of 5 consecutive days of stimulation), patients received tDCS treatment with a mean total injected current of 1.99 mA. The daily treatment was organized in two periods of 20 minutes of stimulation (a bi-session) each separated by 20 minutes off (i.e., with 40 minutes of cathodal stimulation in total). At the end of each cycle (on the 5th day), another EEG exam of 1 hour was performed for comparison with the one obtained before tDCS treatment at the first day of the cycle. Each cycle was repeated every two months, for a total of 3 times (six months in total)(see figure 1).

Personalized multichannel cathodal tDCS

The electrode montage was determined individually based on a montage optimization pipeline. Biophysical head models were created from structural images of each patient (T1-weighted MRIs), using the methods described in [START_REF] Fischer | Multifocal tDCS targeting the resting state motor network increases cortical excitability beyond traditional tDCS targeting unilateral motor cortex[END_REF]. We used MRI acquisitions performed before the SEEG.

These models included lesions such as previous corticectomies. Montage optimization was performed with the Stimweaver algorithm [START_REF] Ruffini | Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields[END_REF]. In short, this method takes as input a target E-field map, defined on the personalized cortical surface of the head model created for each patient. This target map contained information about the areas to inhibit (identified by SEEG recording previously acquired Fig. 2) and of areas to leave unaffected by stimulation. The latter corresponded to silent areas, defined as the cortical areas with normal EEG activity or with the smallest amount of epileptogenic activity.

The region to be inhibited (target) was defined according to the definition of the epileptogenic zone obtained from SEEG. It was based on visual analysis according to classical rules of interpretation [START_REF] Bartolomei | Epileptogenicity of brain structures in human temporal lobe epilepsy : A quantified study from intracerebral EEG[END_REF] and quantification using epileptogenicity index (EI). The EI combines analysis of both spectral and temporal features of SEEG signals, respectively, related to the propensity of a brain area to generate fast discharges , and to the earliness of involvement of this area in the seizure (see details in [START_REF] Bartolomei | Epileptogenicity of brain structures in human temporal lobe epilepsy : A quantified study from intracerebral EEG[END_REF].

The algorithm then automatically identified the positions of electrodes and associated currents that resulted in the E-field distribution that better approximates the target. This solution was constrained to a maximum number of electrodes (8), maximum current per electrode (1.884 mA, in absolute value) and maximum total injected current (2.0 mA). The electrode positions were constrained to a subset of positions of the 10-10 EEG system. Typical montages involved cathodes over the areas to inhibit and anodes over the silent areas. Stimulation was applied via a multichannel tDCS system (Starstim8, Neuroelectrics Barcelona). The stimulation protocol was created and monitored using the NIC 2.0 software (www.neuroelectrics.com/products/software/nic2/). The electrodes (NG PiStim electrodes, 1 cm radius, cylindrical Ag/AgCl electrodes with a layer of conductive SIGMA gel underneath) were positioned in a neoprene cap with the 39 positions used in the montage optimization (Neuroelectric's Standard Cap). The current was gradually ramped-up over a period of 15 seconds until reaching an intensity up to 2.0 mA and delivered in two periods of 20 min separated by 20 min off. The break between sessions of tDCS may be crucial for optimizing cumulative effects and for prolongating the inhibitory neuroplastic effects of cathodal stimulation [START_REF] Kuo | Shaping the Optimal Repetition Interval for Cathodal Transcranial Direct Current Stimulation (tDCS)[END_REF]. A recent study [START_REF] Yang | Transcranial direct current stimulation reduces seizure frequency in patients with refractory focal epilepsy : A randomized, double-blind, sham-controlled, and three-arm parallel multicenter study[END_REF] has found a superior significant effect using a protocol of 2x20 min stimulation per day with a 20 min interval, compared with a protocol using 40 min stimulation only (without interval).

At the end of each period, the currents ramped-down for a period of 15 seconds. These parameters have previously been shown to be well tolerated in healthy subjects and in other clinical conditions [START_REF] Borckardt | A Pilot Study of the Tolerability and Effects of High-Definition Transcranial Direct Current Stimulation (HD-tDCS) on Pain Perception[END_REF][START_REF] Yang | Transcranial direct current stimulation reduces seizure frequency in patients with refractory focal epilepsy : A randomized, double-blind, sham-controlled, and three-arm parallel multicenter study[END_REF].

Electroencephalogram recordings

EEG was performed using 21 channels EEG cap using a Natus apparatus (Natus, France, sampling rate 256 Hz). Signals were acquired during one hour with at least 10 min eyes-closed resting state, and at distance from seizures or post-ictal state (at least 3h). EEG recording was obtained before the start of stimulations (baseline), before each cycle of personalized multichannel tDCS and at the last day of each cycle, immediately following the last stimulation period. The electrodes were arranged based on the international 10-20 system.

Clinical outcome

The patients or their relatives were instructed to record the number and type of seizures in a calendar (seizure diary) two months before (the baseline) the beginning of the study until two months after the last stimulation-period of multichannel tDCS. The records were evaluated each month to count the number of seizures for each period (before, during, shortly after and a long-time period after each cycle of tDCS). Reduction and increase in the number of seizures were represented as a percentage compared to the baseline. Patients whose seizures were reduced by at least 50% in frequency after tDCS cycles were qualified as ''responders''. Others were qualified as ''non-responders''. Furthermore, patients were asked to notify any perceived adverse effect of tDCS, during and after each bi-session of 20-minutes stimulation. All adverse events (AEs) were recorded.

Data analysis and functional connectivity

EEG recordings were analysed using AnyWave software [START_REF] Colombet | AnyWave : A cross-platform and modular software for visualizing and processing electrophysiological signals[END_REF]. A post recording bandpass filter (notch) was applied to signals to remove 50 Hz noise (powerline frequency band in Europe), frequencies below 0.5 Hz and above 70 Hz. The sampling frequency was 256 Hz. We first removed artifacts using independent component analysis (ICA) [START_REF] Barbati | Optimization of an independent component analysis approach for artifact identification and removal in magnetoencephalographic signals[END_REF]. Then, the EEG recording was inspected visually, and all segments containing artifacts not identified by the ICA analysis were rejected (cardiac, muscles, and eye movement artefacts were eliminated). Interictal spikes were automatically quantified in AnyWave using Delphos (Detector of ElectroPhysiological Oscillations and Spikes) [START_REF] Roehri | Time-Frequency Strategies for Increasing High-Frequency Oscillation Detectability in Intracerebral EEG[END_REF].

Then, we estimated the functional connectivity in the theta (4-8 Hz), alpha (8-13 Hz) and beta (13-30 Hz) frequency bands. We did not include gamma activity in this analysis because fast electrical rhythms recorded in the scalp (30-100 Hz) are predominantly due to electromyographic (EMG) activity [START_REF] Goncharova | EMG contamination of EEG : Spectral and topographical characteristics[END_REF]. Then, Fc was computed on bipolar channels in such a way that there was no common electrode between all pairs of electrodes in order to avoid massive biases for the functional connectivity analysis (Fp2-F8, F4-C4, P4-O2, T8-P8, Fz-Pz, Fp1-F7, F3-C3, P3-O1, T7-P7).

Functional connectivity was estimated using linear regression analysis which quantifies the dependency of a signal x on a signal y, from signal samples only and independently of the type of relation between the two signals [START_REF] Pijn | Propagation of Electrical Activity : Nonlinear Associations and Time Delays between EEG Signals[END_REF]. The level of dependency can be characterized by the linear cross-correlation coefficient r 2 xy .

𝑟² 𝑥𝑦 = 𝑚𝑎𝑥 𝜏 𝑐𝑜𝑣²(𝑥(𝑡), 𝑦(𝑡 + 𝜏)) (𝜎 𝑥(𝑡) 𝜎 𝑦(𝑡 + 𝜏) )²
Where σ and cov denote the standard deviation and the covariance, respectively, and τ the delay between signals x and y. r 2 xy will be simply denoted by r 2 in the following.

Correlation values are contained between 0 (y is uncorrelated of x) and 1 (x and y are fully linearly dependent). The estimation of this parameter is performed on a temporal window of fixed duration and sliding in time in order to follow the temporal evolution of the linear statistical relationship between both signals (fixed window of 2s, 1s overlap, max lag of 100 ms). This statistical coupling between signals was recorded on each pair of the 21 electrodes over the selected resting-state period. In the present study, we summarised coupling at each bipolar electrode pair (node) by the sum of all values containing this node (this is the "node strength" in graph theory terminology). The strength values were computed on signals filtered in the EEG frequency sub-bands followed: theta (4-8 Hz), alpha (8-13 Hz)

and beta (13-30 Hz).

Statistical analysis

Changes in functional connectivity between the first and the last day of each cycle were assessed by linear mixed models (LMM) using the "lme4" package (version 1.1-26, [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF]) of the statistical software R version 4.0.3 (R Core Team, 2020). One LMM was computed for each frequency band with the responsiveness to the tDCS treatment (R or NR) and cycle as fixed effects. The by-subject intercept was included as a random factor as well as the effect of cycle. Restricted Maximum Likelihood (REML) was used to fit the LMM and Satterthwaite's method was used to estimate the degrees of freedom. Post-hoc pairwise comparisons were performed with the Least Squares Means (LSM) method.

In addition, the difference in seizure onset zones (temporal or extratemporal) and in gender between responder and not-responder patients were tested with Fisher's exact test. Differences with p-values <0.05 (two-sided) were considered as significant.

Results

Subjects

Ten patients with various forms of focal refractory epilepsy were included in this study between December 2019 and April 2021. Their clinical characteristics are summarized in Table 1.

Clinical outcome

All patients regularly completed their seizure diary. The results are shown in Figure 3. The mean number (±SD) of seizures, in the two months before stimulation, was 44±91. After the first cycle of tDCS, the average seizure frequency had decreased by -32% (±44%) compared with baseline. After the second cycle of five days of stimulation, the average seizure frequency had decreased by -57% (±31) compared with baseline. Finally, after the last cycle (C3) of stimulation, the average seizure frequency had decreased by -48% (±39%). At this point, five patients (50%) had more than 50% decrease in their seizure frequency compared with baseline (R group mean of decrease: -74% ± 14%) and were considered as "responders" for the connectivity analysis (see below). The non-responder group (5/10) presented a mean seizure frequency reduction of -16% (±36%) compared to the baseline SF.

No significant difference in responsiveness to the stimulation protocol was found between patients suffering from temporal lobe epilepsy (5/10) and those suffering from extra-temporal lobe epilepsy

(5/10) (Odd Ratio=0.5; p=1). No significant effect of gender was found on the responsiveness to the treatment (Odd Ratio=0.4; p=1). We found no significant difference in the rate of interictal spikes per minute between cycles and the day of stimulation (before the first stimulation of the cycle: "pre" condition and after the last stimulation day of the cycle: "post" condition) (F1,44.084=0.1012, p=0.75)

and between responder and non-responder patients (F1,8.051=0.2326, p=0.6424).

Safety and tolerability

Overall, all participants tolerated well tDCS treatment. A slight itching sensation under the stimulation electrodes was described by 7/10 of all patients during stimulation. A sensation of slight dizziness at the beginning of the stimulation was reported by two patients. None of the participants reported moderate nor severe side effects during or after the procedure. Two patients had an increase in seizures: one patient (P8) showed an increase in SF after the first cycle of stimulation (50% increase from baseline) but by the second five-days cycle of stimulation, SF had dropped dramatically from baseline and P8 was considered a responder. Another patient in the non-responder group (P4) showed a moderate and transient increase in SF in the first month following the cycles 2 and 3 (25-50%).

Functional connectivity

Functional connectivity, estimated by r 2 strength, was first analysed in EEG broadband signal (4-30 Hz). Results did not show a significant change for the cycles (F 2,7.1 =0.9, p=0.46) and for responder and non-responder patients (F 1,8.1 =0.7, p=0.43) (Fig. 4A). For the theta band (4-8 Hz) analysis, we did not find a significant change for the cycles (F 2,5.9 =1.6, p=0.28) and the responsiveness to the tDCS treatment (F 1,8.02 =0.2, p=0.65). However, we clearly identified a tendency to a decrease in the r 2 strength, between the cycles 1 and 3 for the responder patients (Fig. 4B). The alpha band (8-13Hz) analysis revealed no main effect (cycle: F 2,5.9 =3.8, p=0.09; response F 1,8.3 =0.1, p=0.72) but an interaction effect was present significantly (F 2,5.9 =5.9, p=0.04). Post-hoc tests have shown a significant difference between cycles 1 and 2 (t=2.7, p=0.04) and between 1 and 3 (t=4.3, p=0.009) for the responder group. The mean strength in responders for the cycle 1 was 0.08±0.09, in cycle two 0.00±0.07 and -0.06±0.08 for the third cycle (Fig. 4C). The beta band (13-30 Hz) analysis revealed no main effect (cycle: F 2,6.8 =0.9, p=0.5; response F 1,8.1 =0.05) but an interaction effect was present significantly (F 2,6.8 =6.4, p=0.03). Post-hoc tests have shown a significant difference between cycles 1 and 3 for responder patients (t=3.4, p=0.01) (Fig. 4D).

Although there was no significant difference, we also observed a trend to a decrease in SF between cycles 1 and 2 for responder patients. Interestingly for the non-responder group, we observed a trend for an increase in functional connectivity at the end of the study compared to cycle 1 (non-significant).

Finally, comparing Fc at baseline (before any tDCS stimulation), we have found significant difference between responders and non-responders with higher value of r 2 strength in beta band in non-responder patients (p<0.001).

Discussion

In this open pilot study, we used for the first time a personalized multichannel tDCS protocol targeting the epileptogenic zone as defined on SEEG in a population of patients with drug-resistant focal epilepsy involving different anatomical regions.

Efficacy of multichannel tDCS

Our study confirms that tDCS can lead to a significant reduction in seizures with a responder rate of about 50% and an average seizure reduction of 48% after the third treatment cycle. In responders, the reduction in seizure frequency was 74% (min -58.5%, max -92%). Importantly, and contrary to previous studies, the duration of patient follow-up (6 months) was longer, and we performed three cycles of tDCS, whereas in previous studies, only short-term results were reported [START_REF] Auvichayapat | Transcranial Direct Current Stimulation for Treatment of Refractory Childhood Focal Epilepsy[END_REF][START_REF] Fregni | A Controlled Clinical Trial of Cathodal DC Polarization in Patients with Refractory Epilepsy[END_REF][START_REF] Tecchio | Brain Functional Connectivity Changes After Transcranial Direct Current Stimulation in Epileptic Patients[END_REF] [START_REF] Auvichayapat | Transcranial Direct Current Stimulation for Treatment of Refractory Childhood Focal Epilepsy[END_REF][START_REF] San-Juan | Transcranial Direct Current Stimulation in Mesial Temporal Lobe Epilepsy and Hippocampal Sclerosis[END_REF][START_REF] Tekturk | Transcranial direct current stimulation improves seizure control in patients with Rasmussen encephalitis[END_REF]. Another clinical report showed the importance of repeating the DCS session to achieve a cumulative and longterm decrease in seizure frequency [START_REF] San-Juan | Successful Treatment of a Drug-Resistant Epilepsy by Long-term Transcranial Direct Current Stimulation : A Case Report[END_REF]. Then, the study by Yang et al., 2019 used a 14-days stimulation protocol versus sham stimulation [START_REF] Yang | Transcranial direct current stimulation reduces seizure frequency in patients with refractory focal epilepsy : A randomized, double-blind, sham-controlled, and three-arm parallel multicenter study[END_REF]. They found a median seizure frequency reduction of 50% and 50% (the first 4-weeks of follow-up), as well as 25% and 45% (the second 4-weeks of follow-up), respectively, for patients who received 20-min of tDCS (group 2) and for patients from the group receiving 2x20-min of tDCS (group 3) as compared to a -12.50% change in the sham group (group 1).

Recently, Kaye et al reported a study using a methodology similar to the present study with regard to optimization [START_REF] Kaye | Personalized, Multisession, Multichannel Transcranial Direct Current Stimulation in Medication-Refractory Focal Epilepsy: An Open-Label Study[END_REF]. There were important differences with our study, however: they used a single cycle of ten days and a 20-minute single simulation session per day, defining the target area without SEEG, and without using an MRI-personalized brain model in all patients. In our study, we achieved a comparable result in terms of reduction in mean frequency (48% vs. 44%) but with a demonstrated effect over a longer term, using a multi-cycle approach.

Furthermore, the beneficial clinical effect in our study, lasted at least 8 weeks after a 5-days cycle of tDCS. This could be explained by several new factors in our protocol. In addition to SEEG target identification and model personalization, previous studies have shown that the duration of the clinical benefit depends on the repetition, duration, pause between stimulation sessions and current intensity [START_REF] Kuo | Shaping the Optimal Repetition Interval for Cathodal Transcranial Direct Current Stimulation (tDCS)[END_REF][START_REF] Yang | Transcranial direct current stimulation reduces seizure frequency in patients with refractory focal epilepsy : A randomized, double-blind, sham-controlled, and three-arm parallel multicenter study[END_REF]. [START_REF] Yang | Transcranial direct current stimulation reduces seizure frequency in patients with refractory focal epilepsy : A randomized, double-blind, sham-controlled, and three-arm parallel multicenter study[END_REF] have found a greater effect in reducing seizure frequency using a protocol of 2x20 min stimulation per day with a 20 min interval, compared with a protocol using 40 min stimulation only (no interval) [START_REF] Yang | Transcranial direct current stimulation reduces seizure frequency in patients with refractory focal epilepsy : A randomized, double-blind, sham-controlled, and three-arm parallel multicenter study[END_REF].

Personalized tDCS protocol

In the present work, we used an individualized montage targeting the epileptogenic focus identified by the SEEG recordings, which allowed for a more precise delineation of the patient-specific epileptogenic network. Thus, we sought to optimize current levels and orientation such that induced currents maximized inhibitory stimulation of the while minimizing excitatory anodal feedback in other potentially epileptogenic regions from return currents.

Safety

This long-term study allowed us to confirm the safety of long-term multichannel inhibitory tDCS treatment for epilepsy (6 months). Only mild side effects were reported in most of the participants, such as mild itching and dizziness at the beginning of the stimulation. However, we reported an increase in seizure frequency for one patient in the NR group (25-50%) but who returned to baseline at the end of the study. In addition, one patient in the responder group showed a transient increase in seizure frequency after the first cycle (50%) before a dramatic reduction of seizures after the second and third cycles.

Functional connectivity

Despite the growing number of studies supporting the clinical interest of applying low-level electric fields using tDCS in epilepsy, the underlying neurophysiological mechanisms remain elusive. Some recent studies have suggested its role regarding transient and long-term effects on cortical excitability [START_REF] Antal | Low intensity transcranial electric stimulation : Safety, ethical, legal regulatory and application guidelines[END_REF][START_REF] Cirillo | Neurobiological after-effects of non-invasive brain stimulation[END_REF][START_REF] Lefaucheur | Mechanisms of action of tDCS : A brief and practical overview[END_REF][START_REF] Stagg | Physiology of Transcranial Direct Current Stimulation[END_REF]. Here, we performed a non-invasive measure of functional connectivity to characterize changes induced by several cycles of stimulation. The study of functional connectivity is justified because it is a classic measure of network brain activity and because several publications have shown that regions generating seizures are characterized by an increased Fc compared to non-epileptic regions [START_REF] Bettus | Enhanced EEG functional connectivity in mesial temporal lobe epilepsy[END_REF][START_REF] Lagarde | Interictal stereotactic-EEG functional connectivity in refractory focal epilepsies[END_REF][START_REF] Schevon | Cortical abnormalities in epilepsy revealed by local EEG synchrony[END_REF]. In the present study, the 6-month period of stimulation had induced a decrease in EEG Fc in responder patients compared to their first cycle of tDCS. This profile of cumulative decrease observed in responders across cycles was not observed for non-responder patients.

Conversely, for the latest, we observed a tendency to an increase of Fc at the end of the study. In line with these findings, a recent study has used Fc with fMRI as a quantitative measure of tDCS effects on brain activity in patients with epilepsy [START_REF] Hao | Functional Network Alterations as Markers for Predicting the Treatment Outcome of Cathodal Transcranial Direct Current Stimulation in Focal Epilepsy[END_REF]. This study showed that the response to the cathodal tDCS was linked to functional network alterations with a decreasing Fc in patients responding to the active cathodal tDCS.

Here, we observed a general tendency to a decrease in Fc in the broad frequency band in the responder group, but this decrease was only significantly observed for the alpha and the beta bands. In line with our results, Lin and colleagues have shown that seizure reduction due to repeated application of cathodal tDCS was associated with a decrease in phase lag index synchrony measure in the alpha band without altering the number of epileptiform discharges [START_REF] Lin | Cumulative effect of transcranial direct current stimulation in patients with partial refractory epilepsy and its association with phase lag index-A preliminary study[END_REF]. The reduction of Fc in epilepsy could be a general mechanism for the action of neuromodulation techniques in epilepsy. A decrease in Fc in responding patients has been shown for example after vagus nerve stimulation (VNS) [START_REF] Bodin | Responders to vagus nerve stimulation (VNS) in refractory epilepsy have reduced interictal cortical synchronicity on scalp EEG[END_REF]) [START_REF] Sangare | The Effectiveness of Vagus Nerve Stimulation in Drug-Resistant Epilepsy Correlates with Vagus Nerve Stimulation-Induced Electroencephalography Desynchronization[END_REF] in delta, after biofeedback [START_REF] Ferri | Is beta band desynchronization related to skin conductance biofeedback effectiveness in drug resistant focal epilepsy?[END_REF], or thalamic stimulation [START_REF] Deutschová | Ictal connectivity changes induced by pulvinar stimulation correlate with improvement of awareness[END_REF]. The same trend has been also observed after epilepsy surgery [START_REF] Ueda | Improvement of brain function after surgery in infants with posterior quadrant cortical dysplasia[END_REF].

On the contrary, Tecchio et al have shown that cathodal tDCS was able to increase Fc in six patients suffering from epilepsy in the theta band most specifically [START_REF] Tecchio | Brain Functional Connectivity Changes After Transcranial Direct Current Stimulation in Epileptic Patients[END_REF]. These discrepancies between studies may be partially explained by the repetition of tDCS cycles and the use of different Fc analysis methods.

Limitations

This study has some limitations. First, our small sample size makes it difficult to generalize results regarding tDCS efficiency for all types of epilepsy disease. Another limitation is related to its openended design. We showed that it was possible to obtain a significant response both in terms of seizure frequency and in terms of number of responders (50% of patients with a mean response of -74%) but without comparison with a control group. However, neuromodulation studies, particularly in tDCS, have shown a response to placebo about 13-27% in terms of seizure frequency [START_REF] Goldenholz | Placebo in epilepsy[END_REF]) and our results are much higher than this figure. Moreover, we have shown that the therapeutic response is linked to an objective marker of functional connectivity. Our estimation of Fc was quite simple based on EEG scalp measurement with a limited number of electrodes. This did not allow us to study more precisely the brain changes induced by the stimulation. One of the emerging issues that remains to be demonstrated is the superiority of a customized multichannel tDCS protocol. Again, a specific study comparing conventional bipolar tDCS and multichannel tDCS could be interesting in the future.

From the modelling perspective there are also several limitations. In this population of patients with scar tissue in the skull due to prior SEEG implantation and, sometimes, surgery, there can be significant changes in the E-field distribution in the brain when compared to a healthy case. This has been shown

previously [START_REF] Datta | Transcranial direct current stimulation in patients with skull defects and skull plates: High-resolution computational FEM study of factors altering cortical current flow[END_REF] and confirmed with our own results (see Supplementary Material).

However, in none of these studies have these changes in the modeled induced E-field values exceeded those reported in the literature as inducing lesions in animal model [START_REF] Bikson | Safety of Transcranial Direct Current Stimulation: Evidence Based Update 2016[END_REF]. Our own results

(see again Supplementary Material) show that when these factors are correctly modelled, the montage optimization algorithm can adjust the currents and electrode positions to account in part for the local increases of E-field under the skull defects. Such models can also be extended to include the effects of implants such as Ti plates (Mercadal et al, 2021a[START_REF] Mercadal | Modeling implanted metals in electrical stimulation applications[END_REF]. It should be noticed, however, that it is hard to accurately segment accurately the scar tissue with MRI data alone, and the incorporation of CT data with robust segmentation algorithms for scar tissue would improve the models. That uncertainty, allied with the uncertainty on the dielectric properties of the tissues in the scar region remains as a source of uncertainty when predicting the E-field distribution in this population of subjects.

Conclusions

This pilot study shows the feasibility, clinical efficiency and safety of a long-term (>6 months) multichannel cathodal tDCS with a personalized stimulation protocol in patients with drug-resistant epilepsy. We observed a substantial reduction in seizure frequency after three cycles of 5-days stimulation every two months. Half of the patients were responders with a mean seizure reduction of 74%. This clinical improvement for these difficult cases is cumulative with the stimulation cycles and was associated with a decrease in functional connectivity in alpha and beta bands.

Fig. 1 .

 1 Fig. 1. Study timeline. For each patient, the information of the seizure diary was collected at each

Fig. 2 .Fig. 3 .

 23 Fig. 2. Example of epileptogenic zone identification using SEEG recordings for tDCS targeting

Fig. 4 .

 4 Fig. 4. Multichannel cathodal tDCS induced a decrease in functional connectivity for responder

  . The decrease in seizure frequency observed in our study agrees with previous trials in the field. Most previous studies of tDCS in epilepsy, making use of a generic set-up with a single pair of sponge electrodes, have highlighted the safety and the potential clinical benefit of this neuromodulation technique despite the heterogeneity of patient populations and methods. Three studies byAuvichayapat et al., Tekturk et al., and San-Juan et al. have found a significant reduction in seizure frequency of at least 50% after cathodal tDCS, respectively in patients with epilepsy compared with sham stimulation

Table and Figure legends Table 1 :

 andlegends1 Patient data. Abbrevations: SOZ: Seizure onset zone; SEEG: Stereoelectroencephalography;

	SMA: Supplementary motor area; SZs: Seizures; FCD: Focal cortical dysplasia; SGTC: Seizure
	generalized tonico-clonic; ASM: Antiseizure medication; R: responder; NR: Non-responder.

Funding

This study is supported by the European Research Council: Galvani project, ERC-SyG 2019, grant agreement No 855109.

Declaration of Competing Interest

The non-invasive brain stimulation device used in this study was produced by Neuroelectrics Corp. and Starlab Neuroscience. Dr. Giulio Ruffini is a co-founder of these companies, Dr. Ricardo Salvador and Dr Maria Chiara Biagi works for this company. All the other authors state there is no conflict of interest.