# Risk factors for persistent candidemia and prognostic implications: Results from the ECMM Candida III study

Sarah Sedik, Matthias Egger, Stella Wolfgruber, Jon Salmanton-García, Matteo Bassetti, Malgorzata Mikulska, Volkan Özenci, Sevtap Arikan-Akdagli, Murat Akova, Jean-Pierre Gangneux, et al.

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## To cite this version:

Sarah Sedik, Matthias Egger, Stella Wolfgruber, Jon Salmanton-García, Matteo Bassetti, et al. Risk factors for persistent candidemia and prognostic implications: Results from the ECMM Candida III study. Journal of Infection, 2025, 91 (5), pp.106629. 10.1016/j.jinf.2025.106629. hal-05345745

HAL Id: hal-05345745

https://univ-rennes.hal.science/hal-05345745v1

Submitted on 20 Nov 2025

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Fungi and Fungal Diseases

Risk factors for persistent candidemia and prognostic implications:
Results from the ECMM *Candida* III study

<figure><img src="image_3.png" /></figure>

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Sarah Sedik a,*,¹, Matthias Egger a,¹, Stella Wolfgruber a, Jon Salmanton-García b,c,d, Matteo Bassetti e,f, Malgorzata Mikulska e,f, Volkan Özenci g,h, Sevtap Arikan-Akdagli i, Murat Akova j, Jean-Pierre Gangneux k, Alessandra Bandera l,m, Ana Alastruey-Izquierdo n,o, Aleksandra Barac p, Riina Rautemaa-Richardson q, Nick A. de Jonge r, Laura Loughlin s, Ola Blennow t, Fanny Lanternier u, Eelco F.J. Meijer v,w,x, Nina Khanna y, Carolina Garcia-Vidal z, Julio Dávila-Valls aa, Nikolai Klimko ab, Sophia N. Khostelidi ab, P. Lewis White ac, Halis Akalin ad, Benedict Rogers ae,af, Maite Ruiz ag, Julio García-Rodríguez ah, Deniz Akyol ai, Thomas Longval aj, François Danion ak, Juergen Prattes a, Robert Krause a,al, Subhra K. Biswas am, Maiken Cavling Arendrup an,ao,ap, Philipp Koehler aq,ar, Oliver A. Cornely b,c,d,as,2, Martin Hoenigl a,al,*,2, on behalf of the ECMM Candida III study group 3

<footnote>ª Division of Infectious Diseases, Translational Medical Mycology Research Unit, European Confederation of Medical Mycology Excellence Center for Medical Mycology, Department of Internal Medicine, Medical University of Graz, Graz, Austria</footnote>

<footnote>ᵇ University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Translational Research, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany</footnote>

<footnote>ᶜ University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Division of Infectious Diseases, Excellence Center for Medical Mycology (ECMM), and Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Cologne, Germany</footnote>

<footnote>d German Centre for Infection Research (DZIF), partner site Bonn-Cologne, Cologne, Germany</footnote>

<footnote>e Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy</footnote>

<footnote>f Infectious Diseases Unit, IRCCS Ospedale Policlinico San Martino, L.go R. Benzi 10, 16132 Genoa, Italy</footnote>

<footnote>g Division of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet, Sweden</footnote>

<footnote>h Department of Clinical Microbiology, Karolinska University Hospital, Huddinge, Stockholm, Sweden</footnote>

<footnote>i Department of Medical Microbiology, Hacettepe University Medical School, Ankara, Turkey</footnote>

<footnote>j Hacettepe University School of Medicine, Department of Infectious Diseases, Ankara, Turkey</footnote>

<footnote>k Univ Rennes, CHU de Rennes, INSERM, Institut de Recherche en Santé, Environnement et Travail, (UMR_S 1085), National Reference Center on Chronic Aspergillosis, Excellence Center of Medical Mycology (ECMM), Rennes, France</footnote>

<footnote>l Department of Pathophysiology and Transplantation, University of Milano, Milan, Italy</footnote>

<footnote>m Infectious Diseases Unit, IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation, Milan, Italy</footnote>

<footnote>n Mycology Reference Laboratory, Spanish National Centre for Microbiology, Instituto de Salud Carlos III, Madrid, Spain</footnote>

<footnote>o Centro de Investigación Biomedica en Red en Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain</footnote>

<footnote>p Clinic for Infectious and Tropical Diseases, University Clinical Center of Serbia, Belgrade, Serbia</footnote>

<footnote>q Mycology Reference Centre Manchester and Department of Infectious Diseases, Manchester Academic Health Science Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust and Division of Evolution, Infection and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom</footnote>

<footnote>r Department of Hematology, Amsterdam UMC, Amsterdam, the Netherlands</footnote>

<footnote>s Belfast Health and Social Care Trust, Belfast, United Kingdom</footnote>

<footnote>t Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden</footnote>

<footnote>u Paris Cité Université, Necker Hospital, APHP, Paris, France</footnote>

<footnote>v Department of Medical Microbiology and Immunology, Canisius-Wilhelmina Hospital (CWZ)/Dicon, Nijmegen, the Netherlands</footnote>

<footnote>w Radboudumc-CWZ Center of Expertise for Mycology, Nijmegen, the Netherlands</footnote>

<footnote>x Department of Medical Microbiology, Radboud University Medical Center, Nijmegen, the Netherlands</footnote>

<footnote>y Division of Infectious Diseases and Hospital Epidemiology, University Hospital of Basel, Basel, Switzerland</footnote>

<footnote>Original data of this manuscript have been presented at TIMM 2025, Bilbao, Spain (poster presentation number P167).</footnote>

<footnote>* Correspondence to: Division of Infectious Diseases, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria.
E-mail addresses: sarah.sedik@medunigraz.at (S. Sedik),
hoeniglmartin@gmail.com (M. Hoenigl).</footnote>
## ARTICLE INFO

**Article history:**

Accepted 6 October 2025

Available online 15 October 2025

**Keywords:**

ECMM

Blood culture

Candidemia

Follow-up blood culture

Candida

Europe

Mortality

## SUMMARY

**Objectives:** Candidemia is a severe complication in critically ill and immunocompromised patients, and is associated with high morbidity and mortality. While early fungal clearance may improve outcomes, the association between follow-up blood culture (FUBCs) results and clinical outcomes remains insufficiently explored. This sub-analysis of the ECMM Candida III study investigates predictors of persistent candidemia and the impact of positive FUBC results on clinical outcomes.

**Methods:** The multicenter ECMM Candida III study enrolled adults with culture-proven candidemia from 60 European centers (2018–2019). This sub-analysis included patients with at least one FUBC result reported (n = 258; 40.8%). Statistical analysis used SPSS 29 and R. Binary logistic regression was used to identify predictors of persistent candidemia. To assess mortality risk factors, Cox proportional hazards regression models were constructed.

**Results:** Of 258 patients, 52 (20.2%) had persistent candidemia based on positive FUBCs (median duration of candidemia 6 days). Utilization of echinocandins as first line treatment was less frequent (61.5% vs. 78.2%; p=0.014) in those with positive FUBCs. Mortality was significantly higher in the FUBC-positive group (50% vs. 32%; p=0.016). In the multivariable logistic regression model, lower EQUAL Candida Scores, reflecting reduced adherence to guideline-recommended management, were independently associated with persistent candidemia (OR 0.003, 95% CI 0.0002–0.07; p < 0.001). Univariable Cox regression identified persistent candidemia ≥5 days (HR 2.16; 95% CI 1.33–3.53; p= 0.002) as a significant predictor of mortality. In the multivariable Cox regression model, intensive care unit (ICU) admission (HR 1.59, 95% CI 1.02–2.50; p= 0.039) and persistent candidemia ≥5 days (HR 2.06, 95% CI 1.26–3.37; p= 0.004) remained independent predictors of mortality.

**Conclusion:** Persistent candidemia was predicted by poor adherence to treatment guidelines, as shown by low EQUAL Candida Scores, particularly due to the lack of initial echinocandin use. After controlling immortal time bias, persistent candidemia ≥5 days and ICU admission remained independent predictors of mortality in the multivariable model.

© 2025 The Author(s). Published by Elsevier Ltd on behalf of The British Infection Association. This is an open access article under the CC BY license ([http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/)).

## Introduction

Candidemia remains a significant clinical challenge, especially in critically ill and immunocompromised patients.<fnref n="1" /> Despite advances in antifungal therapies, the morbidity and mortality associated with candidemia remain high, with reported mortality rates reaching up to 47% in certain populations.<fnref n="2" />⁻⁷

Early and adequate antifungal treatment has been shown to predict survival,<fnref n="1" />,⁸ further reducing length of hospital stays, and treatment costs.<fnref n="2" />,⁹ These observations have led to the paradigm that

early mycological clearance—the rapid elimination of *Candida* species from the bloodstream after starting antifungal therapy—may be an important target when managing candidemia.<fnref n="2" />,¹⁰,¹¹ Early clearance of candidemia, within 3 to 5 days from treatment initiation, may be associated with improved survival, reduced duration of antifungal therapy and shorter hospital stays,<fnref n="2" />,¹² while patients with persistent candidemia may experience worse outcomes, prolonged hospitalization and higher mortality.<fnref n="2" />,⁹⁻¹¹ However, evidence from clinical studies is to date very limited. Therefore, further research is needed to elucidate the role of follow-up blood cultures (FUBC) in guiding treatment decisions and investigate the interplay between mycological clearance and clinical outcomes.

To investigate the predictors of persistent candidemia, and the impact of positive FUBC results on treatment outcomes, we

<footnote>z Department of Infectious Diseases, Hospital Clínic de Barcelona, IDIBAPS, University of Barcelona, Barcelona, Spain</footnote>

<footnote>aa Department of Hematology, Hospital Nuestra Señora de Sonsoles, Ávila, Spain</footnote>

<footnote>ab Department of Clinical Mycology, Allergy and Immunology, North-Western State Medical University, St Petersburg, Russia</footnote>

<footnote>ac Public Health Wales Mycology Reference Laboratory and Cardiff University Centre for Trials Research, Cardiff, United Kingdom</footnote>

<footnote>ad Bursa Uludag University, Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Bursa, Turkey</footnote>

<footnote>ae University Hospitals of Leicester, Department of Microbiology, Leicester, United Kingdom</footnote>

<footnote>af Hampshire Hospitals NHS Trust, United Kingdom</footnote>

<footnote>ag University Hospital Virgen del Rocío, Seville, Spain</footnote>

<footnote>ah Microbiology Department, La Paz University Hospital, Madrid, Spain</footnote>

<footnote>ai Faculty of Medicine, Ege University, Izmir, Turkey</footnote>

<footnote>aj Centre Hospitalier de Versailles, Hematology, Le Chesnay, France</footnote>

<footnote>ak Department of Infectious Diseases, CHU de Strasbourg, Université de Strasbourg, Strasbourg, France</footnote>

<footnote>al BioTechMed-Graz, Graz, Austria</footnote>

<footnote>am The Ignaz Semmelweis Institute and Division of Infectious Diseases, Host-Fungal Pathogen Interaction Group, Translational Medical Mycology Research Unit, European Confederation of Medical Mycology Excellence Center for Medical Mycology, Medical University of Graz, Graz, Austria</footnote>

<footnote>an Unit of Mycology, Statens Serum Institut, Copenhagen, Denmark</footnote>

<footnote>ao Department of Clinical Microbiology, Rigshospitalet, Copenhagen, Denmark</footnote>

<footnote>ap Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark</footnote>

<footnote>aq Institute of Translational Research, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany</footnote>

<footnote>ar Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf and Excellence Center for Medical Mycology and Division of Clinical Immunology, Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany</footnote>

<footnote>as University of Cologne, Faculty of Medicine and University Hospital Cologne, Clinical Trials Centre Cologne (ZKS Köln), Cologne, Germany</footnote>

<footnote n="1">¹ Authors contributed equally.</footnote>

<footnote n="2">² Shared Senior Authors.</footnote>

<footnote n="3">³ See Appendix A for the ECMM Candida III study group details.</footnote>
compared patients with candidemia and positive FUBCs with patients with candidemia and negative FUBC enrolled in the ECMM *Candida* III study, a multinational European registry.

## Methods

The ECMM *Candida* III study was a European, multicenter, observational cohort study, including 632 adult culture-confirmed candidemia patients from 60 centers across 20 European countries (with the number of participating hospitals per country proportional to population).¹³ Each participating hospital recruited up to 10 consecutive patients with candidemia occurring after July 2018 and reported these cases to the ECMM *Candida* Registry (FungiScope CandiReg; NCT01731353).¹⁴ To evaluate the quality of candidemia management, the EQUAL *Candida* Score—developed by the ECMM in 2018¹⁵—was applied as a validated measure of adherence to key recommendations from major clinical guidelines.¹⁶ Central ethical approval was obtained from the University of Cologne (approval number EK 17–485), and additional local ethical approvals were secured at each study site according to local regulatory requirements. Detailed methods were described before.⁴

This sub-analysis focused on those ECMM *Candida* III participants (n = 258; 40.8%) who had at least one FUBC result reported after diagnosis of candidemia.

### Statistical analysis

Statistical analyses were performed using IBM SPSS Statistics version 29 (SPSS Inc., Chicago, IL, USA) and R version 2025.05.0+496. Descriptive statistics were used to summarize patient characteristics, including the distribution of *Candida* species and hospital stay duration. Categorical variables were presented as frequencies and percentages, while continuous variables were summarized as medians with interquartile ranges (IQR). For comparisons between groups, categorical data were analyzed using the chi-square test for data with more than 10 observations, while Fisher's exact test was used for data with fewer than 10 observations, both two-tailed. For non-normally distributed variables, the Mann-Whitney U test (two groups) was applied. A two-sided p-value of less than 0.05 was considered statistically significant. Predictors of positive FUBC compared to negative FUBC were evaluated using univariable and multivariable binary logistic regression models. Clinical, microbiological, and management-related variables—including presence of a central venous catheter (CVC), ICU admission, *Candida* species, and initial antifungal therapy. The EQUAL *Candida* Score was calculated as a proportion of the maximum achievable score (19 for patients without a CVC and 22 for those with a CVC).¹⁵ Variables with a p-value < 0.2 in univariable analysis, as well as those deemed clinically relevant based on prior literature, were considered for inclusion in the multivariable model. A backward stepwise selection method was applied to identify independent predictors of persistent candidemia.

Similarly, predictors of all-cause mortality among patients with available FUBC results were analyzed using univariable and multivariable Cox proportional hazards regression models. Candidate variables included demographic characteristics, comorbidities, infection-related parameters (e.g., positive FUBCs, disseminated and duration of FUBC positivity), and quality-of-care indicators (e.g., initial echinocandin therapy, treatment consultation and Equal *Candida* Score relative to maximum). Variables with a p-value < 0.2 in univariable analysis and those considered clinically relevant were selected for inclusion in multivariable models. Two separate multivariable models were constructed: one including the EQUAL *Candida* Score and one excluding it, to explore the influence of this score on model performance and to address potential immortal time and indication bias. Backward elimination was applied in both models to

identify independent predictors of mortality. Model comparison was performed using the Akaike information criterion (AIC) to compare the relative quality of multivariable Cox models for baseline risk factors.

## Results

### Patient characteristics

In total, 258 participants had at least one FUBC result and were included in the analysis. These patients were treated at 51 centers across 18 European countries (Fig. 1). Of these 258 patients, 52 patients (20%) had at least one positive FUBC, while 206 (80%) had exclusively negative FUBC.

The median age was comparable between the two groups (63 years [IQR 55–72] in positive FUBC vs. 62 years [IQR range 52–70] in negative FUBC; p=0.459), as was sex distribution (63.5% males [33/52] in positive FUBC vs. 58.7% [121/206] in negative FUBC; p=0.536). Regarding underlying conditions, haemato-oncological diseases were equally prevalent in both groups (44.2% [23/52 vs. 91/206]; p=0.994), as was the rate of admission to the intensive care unit (ICU) (36.5% [19/52] in positive FUBC vs. 40.8% [84/206]; p=0.578). The Charlson Comorbidity Index was similar between FUBC-positive (median 5 [IQR 3–7]) and FUBC-negative patients (median 5 [IQR 3–7]; p=0.995). Detailed results on demographics and underlying diseases are displayed in Table 1.

### Microbiological findings

The median duration of continued blood culture positivity in the FUBC-positive cohort was 6 days (range 1–104 days). Notably, 82.7% (43/52) of patients remained positive for at least 3 days, and 69.2% (36/52) remained positive for at least 5 days. A detailed breakdown of *Candida* species isolated from blood cultures across countries is provided in Supplementary Table 1.

The overall distribution of *Candida* species did not differ between patients with positive and negative FUBC results (p=0.212). Among patients with positive FUBC, *Candida* species (Table 2) were distributed as follows: *C. albicans* was the most frequently detected species (44.2% [23/52]), followed by *C. glabrata* (*Nakaseomyces glabratus*) (25.0% [13/52]), *C. parapsilosis* (15.4% [9/52]), *C. kefyr* (*Kluyveromyces marxianus*; 3.8% [2/52]), *C. tropicalis* (3.8% [2/52]), *C. auris* (5.8% [3/52]), and *C. lusitaniae* (*Clavispora lusitaniae*; 1.9% [1/52]). Details are displayed in Table 2. For geographic distribution, see Supplementary Table 1.

### Clinical management of candidemia

Detailed results are depicted in Table 3. Echocardiography and ophthalmoscopy were performed less frequently in the FUBC-positive cohort (50.0% [26/52] and 40.4% [21/52]) than in the FUBC-negative cohort (60.7% [125/206] and 52.9% [109/206], respectively), although the differences were not statistically significant (p = 0.163 and 0.107). Country-level data on the frequency of echocardiography and ophthalmoscopy are presented in Supplementary Table 2.

The rate of first-line treatment with echinocandins was significantly lower in those with positive FUBC versus those with negative FUBC (61.5% (32/52) vs. 78.2% (161/206); p=0.014). Among those who survived ≥14 days, patients with positive FUBC were less likely to have received ≥14 days of therapy after the first negative blood culture compared to those with negative FUBC (71.1% [27/38] vs. 85.8% [151/176]; p = 0.028). In terms of timing of initiation of initial antifungal treatment, there was no difference between those with and without positive FUBC for early initiation one day or more before the first positive blood culture result (30.6% [11/36] vs. 21.6% [36/167]; p = 0.246), or delayed initiation one day or more after the
<figure><img src="image_4.png" /><figcaption>Fig. 1. Participating countries reporting cases with follow-up blood culture (FUBC) in Europe.</figcaption></figure>

<table><caption>**Table 1**
Study cohort characteristics positive and negative follow-up blood cultures (FUBC).</caption><thead><tr><th>Baseline characteristic</th><th>Positive FUBC-cohort n=52</th><th>negative FUBC-cohort n=206</th><th>p-value</th></tr></thead><tbody><tr><td><strong>Sex, n (%)</strong></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>33 (63.5)</td><td>121 (58.7)</td><td>0.536</td></tr><tr><td>Female</td><td>19 (36.5)</td><td>85 (41.3)</td><td></td></tr><tr><td><strong>Age</strong></td><td></td><td></td><td></td></tr><tr><td>Age in years (median, IQR range)</td><td>63 (55-72)</td><td>62 (52-70)</td><td>0.459</td></tr><tr><td><strong>*Underlying diseases/conditions, n (%)</strong></td><td></td><td></td><td></td></tr><tr><td>Hematological oncological disease</td><td>23 (44.2)</td><td>91 (44.2)</td><td>0.994</td></tr><tr><td>Other disorders requiring or causing immunosuppression</td><td>1 (1.9)</td><td>10 (4.9)</td><td>0.700</td></tr><tr><td>Chronic cardiovascular disease</td><td>17 (32.7)</td><td>53 (25.7)</td><td>0.314</td></tr><tr><td>Chronic pulmonary disease</td><td>8 (15.4)</td><td>17 (8.3)</td><td>0.123</td></tr><tr><td>Acute or renal disease</td><td>9 (17.3)</td><td>46 (22.3)</td><td>0.570</td></tr><tr><td>Rheumatic disease/ Autoimmune disease</td><td>1 (1.9)</td><td>9 (4.4)</td><td>0.692</td></tr><tr><td>Viral pneumonia</td><td>1 (1.9)</td><td>11 (5.3)</td><td>0.469</td></tr><tr><td>Low albumin level</td><td>26 (50.0)</td><td>90 (43.7)</td><td>0.415</td></tr><tr><td>Urinary catheter</td><td>23 (44.2)</td><td>75 (36.4)</td><td>0.300</td></tr><tr><td>Total parenteral nutrition</td><td>15 (28.8)</td><td>43 (20.9)</td><td>0.219</td></tr><tr><td>Admission to the ICU</td><td>19 (36.5)</td><td>84 (40.8)</td><td>0.578</td></tr><tr><td>Major surgery</td><td>16 (30.8)</td><td>54 (26.2)</td><td>0.510</td></tr><tr><td>Diabetes mellitus</td><td>11 (21.2)</td><td>48 (23.3)</td><td>0.742</td></tr><tr><td>Obesity</td><td>10 (19.2)</td><td>36 (17.5)</td><td>0.768</td></tr><tr><td>CVC</td><td>37 (71.2)</td><td>136 (66.0)</td><td>0.482</td></tr><tr><td><strong>Charlson Comorbidity Index</strong></td><td></td><td></td><td></td></tr><tr><td>Median (IQR range)</td><td>5 (3-7)</td><td>5 (3-7)</td><td>0.995</td></tr></tbody></table>

Abbreviations: IQR, interquartile range; ICU, intensive care unit; CVC, central venous catheter.

first positive blood culture result was received (13.9% [5/36] vs. 11.4% [19/167]; p = 0.179), while in the remaining majority in both groups antifungal therapy was initiated on exactly the day of the first positive blood culture result. Supplementary Table 3 summarizes the Candida species identified in patients who were not started on echinocandin therapy.

Patients with positive FUBC had lower **EQUAL Candida Scores**, **indicating lower adherence to guideline recommendations**, compared to patients with negative FUBC cultures (median score relative to maximum score **0.75** (IQR 0.59–0.86) vs. median 0.82 (IQR 0.73–0.91; p < 0.001). Also among patients who survived ≥14 days, the Equal Candida Score remained lower in those with positive FUBCs (0.79 [IQR 0.634–0.86]) compared to those with negative FUBCs (0.84 [IQR 0.77–0.95]; p > 0.001).

## Predictors of positive follow-up blood cultures

We assessed 19 clinical and microbiological variables in univariable logistic regression modeling (Table 4), to identify predictors of persistent candidemia.

Initial echinocandin use (OR 0.45; 95% CI 0.23–0.86; p= 0.015), and higher EQUAL Candida Scores (OR 0.01; 95% CI 0.001–0.07; p < 0.001) were significantly associated with a lower likelihood of persistent candidemia in the univariate model. In the multivariable model, lower EQUAL Candida Scores (adjusted OR 0.003; 95% CI 0.0002–0.07; p < 0.001) remained independently associated with persistent candidemia.
<table><caption>**Table 2**
Causative *Candida* spp. in those with positive versus negative follow-up blood cultures (FUBC).</caption><thead><tr><th>Candida spp.</th><th>Positive FUBC-cohort (n=52)</th><th>Negative FUBC-cohort (n=206)</th><th>p-value</th></tr></thead><tbody><tr><td>C. albicans</td><td>23</td><td>103</td><td>0.458</td></tr><tr><td>C. glabrata (Nakaseomyces glabratus)</td><td>13</td><td>35</td><td>0.186</td></tr><tr><td>C. kefyr (Kluyveromyces marxianus)</td><td>2</td><td>1</td><td>0.104</td></tr><tr><td>C. krusei (Pichia kudriavzevii)</td><td>0</td><td>6</td><td>0.604</td></tr><tr><td>C. parapsilosis</td><td>8</td><td>29</td><td>0.826</td></tr><tr><td>C. auris</td><td>3</td><td>5</td><td>0.204</td></tr><tr><td>C. dubliniensis</td><td>0</td><td>4</td><td>0.586</td></tr><tr><td>C. famata (Debaryomyces hansenii)</td><td>0</td><td>1</td><td>1.000</td></tr><tr><td>C. guilliermondii (Meyerozyma guilliermondii)</td><td>0</td><td>2</td><td>1.000</td></tr><tr><td>C. inconspicua (Pichia cactophila)</td><td>0</td><td>1</td><td>1.000</td></tr><tr><td>C. lusitaniae (Clavispora lusitaniae)</td><td>1</td><td>0</td><td>0.202</td></tr><tr><td>C. rugosa (Diatina rugosa)</td><td>0</td><td>1</td><td>1.000</td></tr><tr><td>C. tropicalis</td><td>2</td><td>13</td><td>0.742</td></tr><tr><td>Candida spp. not specified</td><td>0</td><td>5</td><td>0.586</td></tr></tbody></table>

Analyzing components of the EQUAL Candida Score separately, positive FUBC (Table 5) were significantly more frequent in those without initial blood cultures > 40 ml (p=0.002), without Candida species identification (p=0.027), without echinocandin treatment initiation (p=0.014) and without treatment duration of ≥14 days after the first negative culture (p=0.002).

### Clinical outcomes and mortality

Duration of hospitalization did not differ between those with positive and negative FUBC (median 21 days, IQR 9.5–35 days in positive FUBC vs. median 20 days, IQR 13–34 days in negative FUBC; p=0.453).

Overall mortality (Table 3) was significantly higher in the positive FUBC group (50.0% [26/52] vs. 32.0% [66/206]; p=0.016). Among patients FUBC-positive for at least 3 days, 55.8% (24/43) died and among those positive for at least 5 days, 58.3% (21/36) died (=0.907). Mortality at day 28 was significantly higher in patients with positive FUBC (36.5%) compared to those with negative FUBC (21.8%; p=0.029). The median time from diagnosis of candidemia to death was numerically shorter in the positive FUBC group (13 days [range -3 to 105] vs. 16 days [range 0 to 1182] in negative FUBC; p=0.231). In the FUBC-positive cohort, mortality did not significantly differ between patients with C. albicans (11/23, 47.8%) and those with non-albicans Candida species (15/29, 51.7%; p=0.780).

Univariable Cox regression modeling (Table 6) identified positive FUBCs (HR 1.81, 95% CI 1.14–2.85; p=0.011), persistent candidemia for more than 3 days (HR 2.05, 95% CI 1.29–3.28; p=0.003), and persistent candidemia for more than 5 days (HR 2.16, 95% CI 1.33–3.53; p=0.002) as significant predictors of mortality. Other predictors were lower EQUAL Candida Scores (HR 0.03; 95% CI

<table><caption>**Table 4**
Univariable and multivariable binary logistic regression models for predictors of positive follow-up blood culture compared to patients with negative follow-up blood culture results from the Candida-III-cohort (n=258).</caption><thead><tr><th>Variable</th><th>Univariable<br>odds ratio</th><th>95% CI</th><th>p-value</th></tr></thead><tbody><tr><td>CVC presence</td><td>1.27</td><td>0.65–2.47</td><td>0.482</td></tr><tr><td>Charles comorbidity index</td><td>0.99</td><td>0.90–1.11</td><td>0.963</td></tr><tr><td>Age (per 10 years)</td><td>1.11</td><td>0.90–1.37</td><td>0.326</td></tr><tr><td>Male sex</td><td>1.20</td><td>0.64–2.24</td><td>0.577</td></tr><tr><td>Disseminated</td><td>1.42</td><td>0.73–2.78</td><td>0.302</td></tr><tr><td>ICU</td><td>0.84</td><td>0.45–1.57</td><td>0.577</td></tr><tr><td>Body mass index</td><td>1.53</td><td>0.79–2.98</td><td>0.205</td></tr><tr><td>Hematological or Oncological malignancy</td><td>1.00</td><td>0.54–1.85</td><td>0.994</td></tr><tr><td>Major surgery</td><td>1.25</td><td>0.64–2.43</td><td>0.510</td></tr><tr><td>Solid organ transplant</td><td>0.79</td><td>0.09–6.90</td><td>0.830</td></tr><tr><td>Diabetes mellitus</td><td>0.88</td><td>0.42–1.85</td><td>0.742</td></tr><tr><td>Total parenteral nutrition</td><td>1.54</td><td>0.77–3.06</td><td>0.221</td></tr><tr><td>Treatment consultation</td><td>1.20</td><td>0.91–1.60</td><td>0.201</td></tr><tr><td>Echocardiography</td><td>0.65</td><td>0.35–1.19</td><td>0.164</td></tr><tr><td>Ophthalmoscopy</td><td>0.60</td><td>0.33–1.12</td><td>0.108</td></tr><tr><td>Initial echinocandin</td><td>0.45</td><td>0.23–0.86</td><td><strong>0.015</strong></td></tr><tr><td>Equal Candida Score relative to max</td><td>0.01</td><td>0.001–0.07</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Prosthetic</td><td>1.11</td><td>0.47–2.60</td><td>0.81</td></tr><tr><td><strong>Multivariable model</strong></td><td><strong>Multivariable<br>Odds Ratio</strong></td><td></td><td></td></tr><tr><td>Ophthalmoscopy</td><td>1.43</td><td>0.66–3.08</td><td>0.363</td></tr><tr><td>Initial echinocandin</td><td>1.29</td><td>0.55–3.01</td><td>0.563</td></tr><tr><td>Equal Candida Score relative to max</td><td>0.003</td><td>0.0002–0.07</td><td><strong>&lt;0.001</strong></td></tr></tbody></table>

Abbreviations: CVC, central venous catheter; ICU, intensive care unit; ECMO, Extracorporeal Membrane Oxygenation.

0.01–0.08; p < 0.001), CVC presence (HR 2.33, 95% CI 1.37–3.94; p=0.002), omission of echocardiography (HR 0.62, 95% CI 0.41–0.93; p=0.021), and omission of ophthalmoscopy (HR 0.41, 95% CI

<table><caption>**Table 3**
Patient management and outcome in those positive and negative follow-up blood cultures (FUBC).</caption><thead><tr><th></th><th>positive FUBC-cohort (n=52, %)</th><th>negative FUBC-cohort (n=206, %)</th><th>p-value</th></tr></thead><tbody><tr><td><strong>Management</strong></td><td></td><td></td><td></td></tr><tr><td>Ophthalmoscopy performed</td><td>21 (40.4)</td><td>109 (52.9)</td><td>0.107</td></tr><tr><td>Endocarditis - Signs of IC</td><td>2 (3.8)</td><td>11 (5.3)</td><td>1.000</td></tr><tr><td>Echocardiography performed</td><td>26 (50)</td><td>125 (60.7)</td><td>0.163</td></tr><tr><td>Echocardiography- Signs of IC</td><td>0</td><td>10 (4.9)</td><td>0.220</td></tr><tr><td><strong>Antifungal therapy</strong></td><td></td><td></td><td></td></tr><tr><td>Echinocandin as first line treatment</td><td>32 (61.5)</td><td>161 (78.2)</td><td><strong>0.014</strong></td></tr><tr><td>Equal Candida Score relative to max (≥14-day survivors), Median (IQR range)</td><td>0.79 (0.634–0.86)</td><td>0.84 (0.77–0.95)</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Equal Candida Score relative to max, Median (IQR range)</td><td>0.75 (0.59–0.86)</td><td>0.82 (0.72–0.90)</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Length of hospitalization after diagnosis (days; IQR range)</td><td>21 (9.5–35)</td><td>20 (13–34)</td><td>0.453</td></tr><tr><td>Hospital stay prolonged for completion of iv antifungal treatment</td><td>6 (13)</td><td>38 (18.4)</td><td>0.304</td></tr><tr><td><strong>Mortality</strong></td><td></td><td></td><td></td></tr><tr><td>Overall All-cause Mortality</td><td>26 (50)</td><td>66 (32)</td><td><strong>0.016</strong></td></tr><tr><td>Day 28 All-cause Mortality</td><td>19 (36.5)</td><td>45 (21.8)</td><td><strong>0.029</strong></td></tr></tbody></table>

Abbreviations: IC, invasive candidiasis; IQE, interquartile range.

<footnote>* Mortality in FUBC-positive cohort: C. albicans (11/23) vs. non-C. albicans (15/29); p = 0.780.</footnote>
<table><caption>**Table 5**
Rates of positive follow-up blood cultures among populations with diagnostic and therapeutic components of the EQUAL Candida Score.</caption><thead><tr><th>Rate of positive FUBC</th><th>Diagnostic measures</th><th>p-value</th></tr></thead><tbody><tr><td><strong>Initial blood cultures of 40 ml</strong></td><td>N (%)</td><td>0.002</td></tr><tr><td>Performed</td><td>47/250 (18.8)</td><td></td></tr><tr><td>Not performed</td><td>5/8 (62.5)</td><td></td></tr><tr><td><strong>Candida identified down to species level</strong></td><td></td><td>0.027</td></tr><tr><td>Performed</td><td>49/254 (19.3)</td><td></td></tr><tr><td>Not performed</td><td>3/4 (75)</td><td></td></tr><tr><td><strong>Susceptibility testing</strong></td><td></td><td>0.212</td></tr><tr><td>Performed</td><td>51/244 (20.9)</td><td></td></tr><tr><td>Not performed</td><td>1/14 (7.1)</td><td></td></tr><tr><td><strong>Echocardiography</strong></td><td></td><td>0.162</td></tr><tr><td>Performed</td><td>26/151 (17.2)</td><td></td></tr><tr><td>Not performed</td><td>26/107 (24.3)</td><td></td></tr><tr><td><strong>Ophthalmoscopy</strong></td><td></td><td>0.106</td></tr><tr><td>Performed</td><td>21/52 (40.3)</td><td></td></tr><tr><td>Not performed</td><td>31/52 (59.6)</td><td></td></tr><tr><td><strong>Treatment measures</strong></td><td></td><td></td></tr><tr><td><strong>Initial echinocandin treatment</strong></td><td></td><td>0.014</td></tr><tr><td>Performed</td><td>32/193 (16.6)</td><td></td></tr><tr><td>Not performed</td><td>20/65 (30.8)</td><td></td></tr><tr><td><strong>Step-down therapy to fluconazole</strong></td><td></td><td>0.236</td></tr><tr><td>Performed</td><td>18/108 (16.7)</td><td></td></tr><tr><td>Not performed</td><td>34/150 (22.7)</td><td></td></tr><tr><td><strong>Treatment for ≥14 days after the first negative blood culture</strong></td><td></td><td>0.002</td></tr><tr><td>Performed</td><td>29/188 (15.4)</td><td></td></tr><tr><td>Not performed</td><td>23/70 (32.9)</td><td></td></tr><tr><td><strong>Central venous catheter removal ≤24 h</strong></td><td></td><td>0.667</td></tr><tr><td>Performed</td><td>22/116 (19.0)</td><td></td></tr><tr><td>Not performed</td><td>30/142 (21.1)</td><td></td></tr><tr><td><strong>Central venous catheter removal > 24 h but < 72 h</strong></td><td></td><td>0.145</td></tr><tr><td>Performed</td><td>12/42 (28.6)</td><td></td></tr><tr><td>Not performed</td><td>40/216 (4.6)</td><td></td></tr></tbody></table>

0.26–0.62; p < 0.001). ICU admission also showed a significant association with increased mortality (HR 1.99, 95% CI 1.32–2.99; p=0.001).

In the first multivariable Cox regression model (Table 6), which included the EQUAL Candida Score, the score remained an independent predictor of survival (adjusted HR 0.03, 95% CI 0.01–0.14; p < 0.001), while ICU admission was also independently associated with increased mortality (adjusted HR 1.74, 95% CI 1.10–2.74; p=0.018). In contrast, persistent candidemia ≥5 days did not retain statistical significance in this model (adjusted HR 1.41, 95% CI 0.83–2.39; p=0.203).

Addressing potential immortal time and indication bias and therefore excluding the EQUAL Candida Score in a second model (Table 6), persistent candidemia ≥5 days emerged as an independent predictor of death (adjusted HR 2.06, 95% CI 1.26–3.37; p=0.004), along with ICU admission (adjusted HR 1.59, 95% CI 1.02–2.50; p=0.039).

## Discussion

We analyzed predictors of persistent candidemia and the association of positive FUBCs with treatment outcomes within the multicenter European ECMM Candida III observational study cohort. Two major findings emerged. First, persistent candidemia was independently predicted by poor adherence to evidence-based clinical guidelines, including inadequate first-line treatment, as reflected by low EQUAL Candida Scores. Second, persistent candidemia lasting ≥5 days was independently associated with increased mortality.

Our analysis identified low EQUAL Candida Scores, reflecting deviations from recommended management practices, as a strong

<table><caption>**Table 6**
Univariable and multivariable Cox regression model for predictors of mortality in patients with available follow-up blood cultures (FUBC) from the Candida-III-comort (n=258).</caption><thead><tr><th></th><th>Univariable hazard ratio</th><th>95% CI</th><th>p-value</th></tr></thead><tbody><tr><td><strong>CVC presence</strong></td><td>2.33</td><td>1.37–3.94</td><td>0.002</td></tr><tr><td>Charles comorbidity index</td><td>1.06</td><td>0.99–1.13</td><td>0.099</td></tr><tr><td>Age (per 10 years)</td><td>1.10</td><td>0.96–1.27</td><td>0.163</td></tr><tr><td>Male sex</td><td>1.11</td><td>0.72–1.69</td><td>0.644</td></tr><tr><td>Positive FUBC</td><td>1.81</td><td>1.14–2.85</td><td>0.011</td></tr><tr><td>FUBC positive ≥ 3 days</td><td>2.05</td><td>1.29–3.28</td><td>0.003</td></tr><tr><td>FUBC positive ≥ 5 days</td><td>2.16</td><td>1.33–3.53</td><td>0.002</td></tr><tr><td>Disseminated</td><td>1.13</td><td>0.71–1.80</td><td>0.618</td></tr><tr><td>ICU admission</td><td>1.99</td><td>1.32–2.99</td><td>0.001</td></tr><tr><td>Body mass index</td><td>1.01</td><td>0.66–1.54</td><td>0.974</td></tr><tr><td>Hematological or Oncological malignancy</td><td>1.46</td><td>0.97–2.21</td><td>0.072</td></tr><tr><td>Major surgery</td><td>1.06</td><td>0.67–1.67</td><td>0.817</td></tr><tr><td>Solid organ transplant</td><td>0.35</td><td>0.05–2.50</td><td>0.294</td></tr><tr><td>Diabetes</td><td>1.06</td><td>0.66–1.71</td><td>0.797</td></tr><tr><td>ECMO</td><td>0.99</td><td>0.24–4.01</td><td>0.987</td></tr><tr><td>Total parental nutrition</td><td>0.99</td><td>0.61–1.62</td><td>0.992</td></tr><tr><td>Treatment consultation</td><td>1.18</td><td>0.97–1.42</td><td>0.093</td></tr><tr><td>Echocardiography</td><td>0.62</td><td>0.41–0.93</td><td>0.021</td></tr><tr><td>Ophthalmoscopy</td><td>0.41</td><td>0.26–0.62</td><td>&lt; 0.001</td></tr><tr><td>Initial echinocandin</td><td>0.80</td><td>0.50–1.27</td><td>0.34</td></tr><tr><td>Equal Candida Score relative to max</td><td>0.03</td><td>0.01–0.08</td><td>&lt; 0.001</td></tr><tr><td>Prosthetic</td><td>1.11</td><td>0.63–1.94</td><td>0.705</td></tr><tr><td><strong>Model #1 (AIC = 890.12)</strong></td><td><strong>Multivariable hazard ratios</strong></td><td></td><td></td></tr><tr><td>CVC presence</td><td>1.56</td><td>0.87–2.83</td><td>0.138</td></tr><tr><td>Charles comorbidity index</td><td>1.04</td><td>0.96–1.12</td><td>0.358</td></tr><tr><td>ICU admission</td><td>1.74</td><td>1.10–2.74</td><td>0.018</td></tr><tr><td>FUBC positive ≥ 5 days</td><td>1.41</td><td>0.83–2.39</td><td>0.203</td></tr><tr><td>Hematological or Oncological malignancy</td><td>1.28</td><td>0.83–1.98</td><td>0.263</td></tr><tr><td>Treatment consultation</td><td>0.89</td><td>0.72–1.11</td><td>0.303</td></tr><tr><td>Echocardiography</td><td>1.06</td><td>0.66–1.69</td><td>0.818</td></tr><tr><td>Equal Candida Score relative to max</td><td>0.03</td><td>0.01–0.14</td><td>&lt; 0.001</td></tr><tr><td><strong>Model #2 (AIC = 908.86)</strong></td><td><strong>Multivariable hazard ratios</strong></td><td></td><td></td></tr><tr><td>CVC presence</td><td>1.71</td><td>0.96–3.06</td><td>0.070</td></tr><tr><td>Charles comorbidity index</td><td>1.05</td><td>0.98–1.13</td><td>0.168</td></tr><tr><td>ICU admission</td><td>1.59</td><td>1.02–2.50</td><td>0.039</td></tr><tr><td>FUBC positive ≥ 5 days</td><td>2.06</td><td>1.26–3.37</td><td>0.004</td></tr><tr><td>Hematological or Oncological malignancy</td><td>1.31</td><td>0.85–2.01</td><td>0.226</td></tr><tr><td>Treatment consultation</td><td>1.07</td><td>0.88–1.30</td><td>0.496</td></tr><tr><td>Echocardiography</td><td>0.68</td><td>0.45–1.03</td><td>0.071</td></tr></tbody></table>

Abbreviations: CVC, central venous catheter; ICU, intensive care unit; ECMO, Extracorporeal Membrane Oxygenation; AIC, AIC, Akaike information criterion.

and independent predictor of persistent candidemia. The score represents a multicomponent analysis, incorporating many variables that demonstrated significance during univariable analysis and its cumulative nature likely underpins significance during multivariate analysis. The lower adherence to guideline-recommended practices observed in the prolonged candidemia group may be a reflection of limited clinical resources in some European healthcare settings, as outlined before,¹⁷ but may also reflect differences in provider experience or familiarity with current international recommendations, or divergence of local guidance that is followed instead. This finding may therefore also highlight the importance of targeted educational initiatives and implementation strategies to improve adherence to evidence-based guidelines. Ensuring that clinicians are aware of and have the resources to apply recommended diagnostic and therapeutic practices may help reduce the duration of candidemia, optimize antifungal therapy, and ultimately improve patient outcomes.

Among the individual components of guideline adherence, insufficient blood culture volume and inappropriate first-line antifungal therapy emerged as particularly relevant factors predicting persistent candidemia. A low initial blood culture volume (≤40 ml; p=0.002) was significantly associated with positive FUBCs. This finding emphasizes the importance of obtaining adequate sampling volumes at the time of diagnosis, as insufficient volumes may reduce
sensitivity for detecting candidemia and thereby contribute to late diagnosis and persistent bloodstream infection. While there was no difference in the timing of initiation of antifungal therapy, patients with positive FUBCs who survived 2 weeks or more were less likely to receive ≥14 days of therapy after the first negative blood culture (71.1% vs. 85.8%; p = 0.028).

Patients with positive FUBC were also significantly less likely to have received echinocandins as first-line treatment compared to those with negative FUBC (61.5% vs. 78.2%; OR 0.45, 95%CI 0.23–0.86; p=0.015). This supports current recommendations that favor echinocandins as initial therapy, including those by the recent ECMM/ISHAM 2025 guideline recommending timely initiation of echinocandin therapy as first-line treatment for patients with candidemia.¹⁸ Treatment challenges in candidemia have been discussed in earlier work,¹⁹ informed by associations between delayed echinocandin therapy and worse outcomes reported from retrospective studies.²⁰,²¹ One of those, a multicenter study, found that empirical use of echinocandins reduced 30-day mortality (31.9% vs. 37.4% with fluconazole). That study concluded that echinocandin therapy was a protective factor for both 30-day and 90-day mortality in critically ill patients with candidemia.²¹ This benefit may relate to the fungicidal activity of echinocandins against most *Candida* species, in contrast to the fungistatic nature of azoles, which may result in slower or incomplete clearance of bloodstream infections.²²,²³ Echinocandins inhibit 1,3-β-D-glucan synthase, disrupting fungal cell wall synthesis and leading to cell lysis, thereby achieving more rapid fungal clearance. This mechanism has been associated with higher early therapeutic success and reduced persistence of infection compared to azoles.²⁴,²⁵ These findings can be at least partly explained by the capacity of *Candida* to form biofilms and the good activity of echinocandins against these whilst azole antifungals have poor in vitro and in vivo anti-biofilm activity independent of the planktonic minimum inhibitory concentrations.²⁶ Our results are in keeping with the results by Tumbarello et al. showing that the 30-day survival of patients with proven candidaemia was significantly better when an antifungal with anti-biofilm activity (echinocandin or amphotericin B) was used instead of a non-anti-biofilm active drug (e.g., fluconazole).²⁶,²⁷

To our knowledge, this is one of the first multicenter European studies to systematically investigate predictors of persistent candidemia using standardized adherence metrics like the EQUAL *Candida* Score.¹⁵ While earlier studies have identified individual risk factors such as CVC retention, neutropenia, or infection with *C. parapsilosis*²²,²⁸,²⁹ as predictors of persistent candidemia, few have quantitatively assessed the impact of antifungal treatment adequacy on persistence.

Several important findings were observed regarding the clinical outcomes of patients with candidemia and FUBCs. In our cohort, persistent candidemia was associated with a significantly higher mortality rate (50% vs. 32%, p= 0.016), with a median duration of persistent bloodstream infection of six days, highlighting the prognostic significance of prolonged candidemia. One study reported crude mortality rates ranging from 43% to 61% among ICU patients with candidemia, highlighting the severity of persistent candidemia.³⁰ Although the difference in mortality rates between *C. albicans* and non-albicans *Candida* species was not statistically significant in our cohort, another study revealed that patients with persistent candidemia by non-*albicans* *Candida* species or resistant strains had higher mortality rates, underscoring the need for careful management in these cases.³¹ Other studies also confirm that persistent candidemia is linked to an elevated mortality rate.²,³²,³³ Importantly, we evaluated mortality predictors using two multivariable Cox regression models. The EQUAL *Candida* Score remained a very strong independent predictor of mortality in the first model, but the score includes post-diagnostic and downstream interventions (e.g., ophthalmoscopy, step-down therapy, treatment for more than 14 days) that can only be performed if patients survive long

enough—potentially introducing immortal time bias.³⁴,³⁵ Its inclusion in causal models of mortality may therefore be misleading, as the score may reflect treatment opportunity rather than outcome determinants, and the same may apply in part also for ophthalmoscopy which is often performed later after diagnosis of candidemia. In the revised model excluding the EQUAL *Candida* Score and ophthalmoscopy, we found that persistent candidemia ≥5 days remained an independent predictor of mortality (adjusted HR 2.06, 95% CI 1.26–3.37; p=0.004), along with ICU admission (adjusted HR 1.59, 95% CI 1.02–2.50; p=0.039). This highlights the clinical relevance of persistent candidemia as a negative prognostic marker and as a potential target for interventions to improve outcomes of candidemia.

Several important limitations should be considered. First, there were no predefined fungal diagnostic strategies or antifungal treatment protocols, which may have delayed diagnosis and therapy, potentially impacting outcomes.

A survival bias may also have been introduced, as early deaths could have influenced the EQUAL Candida Score assessments and treatment duration analyses, given those patients who died early may not have received full diagnostics or complete treatments; however results remained significant after exclusion of those who have died within 14 days of diagnosis. Furthermore, this is a real world study and the absence of predefined diagnostic strategies and antifungal treatment protocols, including definition of blood volume for culture diagnostic represent a significant limitation and may have affected the outcomes. The rate of FUBC was also relatively low and the timing of FUBC was not standardized, which could have influenced assessments of microbiological clearance and treatment response. In addition, global variability in access to fungal diagnostics, infectious disease consultations, and antifungal drugs, particularly between high- and low-income countries,¹⁷ limits the generalizability of the findings. Finally, the study population was drawn predominantly European, with a likely over-representation of high-resource centers, further restricting the applicability of the results to lower-resource settings.

In conclusion, this study emphasizes the prognostic relevance of persistent candidemia and the importance of early, appropriate diagnostic and therapeutic management including antifungal therapy with echinocandins to avoid positive FUBC in patients with candidemia. Future studies should assess the impact of antifungal combination therapy and novel antifungal agents, such as rezafungin, which features a high loading dose and an extended half-life with high initial plasma concentrations,³⁶⁻³⁸ on microbiological clearance, rates of infectious complications, and mortality in patients with candidemia.

## Funding

Investigator Initiated Research Grant from Scynexis and Mundipharma was obtained to support the study.

## Data availability

Deidentified participant data at the case level, along with the data dictionary, can be requested from the corresponding author (hoe-niglmartin@gmail.com) starting from the time of publication. Access will be granted upon approval of study proposals by the ECMM *Candida* III steering committee, ensuring that the proposed analyses do not overlap with other ongoing subanalyses of the dataset.

## Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing
interests: **JS-G** has served on advisory boards for Pfizer, received speaker honoraria from Gilead Sciences, Menarini, and Pfizer, and received travel grants from AstraZeneca; all outside the submitted work. **PK** reports grants or contracts from German Federal Ministry of Research and Education (BMBF) B-FAST (Bundesweites Forschungsnetz Angewandte Surveillance und Testung) and NAPKON (Nationales Pandemie Kohorten Netz, German National Pandemic Cohort Network) of the Network University Medicine (NUM), the State of North Rhine-Westphalia and the Dr.Heinz Lux-Stiftung; Consulting fees Ambu GmbH, Gilead Sciences, infill healthcare communication GmbH, Mundipharma Research Limited, Noxxon N.V. and Pfizer Pharma; Honoraria for lectures from Akademie für Infektionsmedizin e.V., Ambu GmbH, Astellas Pharma, BioRad Laboratories Inc., Datamed GmbH, European Confederation of Medical Mycology, Gilead Sciences, GPR Academy Ruesselsheim, HELIOS Kliniken GmbH, Jazz Pharmaceuticals Germany GmbH, Lahn-Dill-Kliniken GmbH, medupdate GmbH, MedMedia GmbH, MSD Sharp & Dohme GmbH, Pfizer Pharma GmbH, Sanofi-Aventis Deutschland GmbH, Scilink Comunicación Científica SC, streamedup! GmbH, University Hospital and LMU Munich and VITIS GmbH; Participation on an Advisory Board from Ambu GmbH, Gilead Sciences, Mundipharma Research Limited and Pfizer Pharma; A filed patent at the German Patent and Trade Mark Office (DE 10 2021 113 007.7); Other non-financial interests from Elsevier, Wiley and Taylor & Francis online outside the submitted work. **MB** reports personal fees from Bayer, bioMérieux, Cidara Therapeutics, Cipla, Gilead Sciences, Menarini, MSD, Pfizer, and Shionogi, and research grants from Pfizer and MSD, all outside the submitted work. **MM** received lecture fees and board meeting fees from Allovir, Astra-Zeneca, bioMerieux, Gilead, Janssen, Moderna, Mundipharma, Pfizer; Shionogi, and grant to institution from Gilead, all unrelated to the submitted work. **SA-A** received research grant from Cidara and lecture honoraria from Gilead in the last five years, all unrelated to the submitted work. **MA** declares no conflict of interest. **J-PG** received consulting fees from Gilead, Mundipharma, Pfizer, and Shionogi. **AB** received speaker's honoraria and fees for attending advisory boards from Astra-Zeneca, Biomerieux, Gilead, Janssen-Cilag, Nordic Pharma, Pfizer, Qiagen, SOBI, Takeda, VIIIV, and received research grants from Gilead. **AA-I** received a research grant from Scynexis, consultancy fees from WHO, lecture honoraria from Gilead and Pfizer, travel support from Gilead, served on an advisory board for Basilea, and held unpaid positions with JPIAMR, the Spanish Society for Mycology, and Women for Mycology, all unrelated to the submitted work. **AB** declares no conflict of interest. **RR-R** reports receiving research funding from Scynexis and F2G as principal and co-investigator for clinical trials, honoraria for lectures from Pfizer, Mundipharma, and Gilead, and holding honorary roles as Chair of the UK SMI Bacteriology Working Group, member of the Royal College of Pathologists' Special Advisory Committee for Medical Microbiology and Virology, and lead for the ESCMID Academy. **EF.JM** received research grants from Mundiparma and Scynexis, is on the scientific advisory board for Pfizer and has received speaker fees from Gilead Sciences, all unrelated to the submitted work. **NK** reports receiving consultancy fees and serving on advisory boards and data safety monitoring boards for Gilead Sciences, Novartis, MSD, Pfizer, Idorsia, and Pulmocide, all outside the submitted work. **CG-V** [FIS PI24/01776] has received research grants from the Ministerio de Sanidad y Consumo, Instituto de Salud Carlos III. Project PI24/01776 has been funded by the Instituto de Salud Carlos III (ISCIII) and co-funded by the European Union. She also received a research grant (SGR 01324 Q5856414G) from the AGAUR (Agencia de Gestión de Ayudas Universitarias y de Investigación) of Catalunya. **CG-V** has received honoraria for talks on behalf of Gilead Science, MSD, Pfizer, Janssen, Novartis, Basilea, GSK, Shionogi, AbbVie, and Advanz Pharma, as well as grant support from Gilead Science, Pfizer, GSK, MSD, and Pharmamar **P.LW** has performed diagnostic evaluations

and received meeting sponsorship from Associates of Cape Cod, Bruker, Dynamiker, and Launch Diagnostics; speaker fees, expert advice fees, and meeting sponsorship from Gilead and Mundipharma; speaker and expert advice fees from Pfizer and expert advice fees from F2G. All unrelated to the submitted work. **HA** declares no conflict of interest. **BR** received conference sponsorship from Mundiparma and has been a paid speaker for MSD, all unrelated to the submitted work. **JP** holds the position of President at the Austrian Society of Medical Mycology, received speaker fees from Gilead, Pfizer, Swedish Orphan BioVitrum, Associates of Cape Cod and is stockholder of AbbVie Inc. and Novo Nordisk – all outside of the submitted work. **SKB** is supported by start-up core funds from the Medical University of Graz and The Ignaz Semmelweis Institute, Austria. **MCA** has, over the past 5 years, received research grants/ contract work (paid to the SSI) from Cidara/Mundiparma, F2G/ Shionogi, Pfizer and Scynexis, and speaker honoraria (personal fee) from Chiesi, Gilead and F2G/Shionogi. She is the current chair of the EUCAST-AFST. **PK** reports grants or contracts from German Federal Ministry of Research and Education (BMBF) B-FAST (Bundesweites Forschungsnetz Angewandte Surveillance und Testung) and NAPKON (Nationales Pandemie Kohorten Netz, German National Pandemic Cohort Network) of the Network University Medicine (NUM), the State of North Rhine-Westphalia and the Dr.Heinz Lux-Stiftung; Consulting fees Ambu GmbH, Gilead Sciences, infill healthcare communication GmbH, Mundiparma Research Limited, Noxxon N.V. and Pfizer Pharma; Honoraria for lectures from Akademie für Infektionsmedizin e.V., Ambu GmbH, Astellas Pharma, BioRad Laboratories Inc., Datamed GmbH, European Confederation of Medical Mycology, Gilead Sciences, GPR Academy Ruesselsheim, HELIOS Kliniken GmbH, Jazz Pharmaceuticals Germany GmbH, Lahn-Dill-Kliniken GmbH, medupdate GmbH, MedMedia GmbH, MSD Sharp & Dohme GmbH, Pfizer Pharma GmbH, Sanofi-Aventis Deutschland GmbH, Scilink Comunicación Científica SC, streamedup! GmbH, University Hospital and LMU Munich and VITIS GmbH; Participation on an Advisory Board from Ambu GmbH, Gilead Sciences, Mundiparma Research Limited and Pfizer Pharma; A filed patent at the German Patent and Trade Mark Office (DE 10 2021 113 007.7); Other non-financial interests from Elsevier, Wiley and Taylor & Francis online outside the submitted work. **OAC** reports grants or contracts from iMi, iHi, DFG, BMBF, Cidara, DZIF, EU-DG RTD, F2G, Gilead, MedPace, MSD, Mundiparma, Octapharma, Pfizer, Scynexis; Consulting fees from Abbvie, AiCuris, Basilea, Biocon, Boston Strategic Partners, Cidara, Elion Therapeutics, Gilead, GSK, IQVIA, Janssen, Matinas, MedPace, Menarini, Melinta, Molecular Partners, MSG-ERC, Mundiparma, Noxxon, Octapharma, Pardes, Partner Therapeutics, Pfizer, PSI, Scynexis, Seres, Seqirus, Shionogi, The Prime Meridian Group; Speaker and lecture honoraria from Abbott, Abbvie, Akademie für Infektionsmedizin, Al-Jazeera Pharmaceuticals/Hikma, amedes, AstraZeneca, Deutscher Ärzteverlag, Gilead, GSK, Grupo Biotoscana/United Medical/Knight, InfectoPharm, Ipsen Pharma, Medscape/WebMD, MedUpdate, MSD, Moderna, Mundiparma, Noscendo, Paul-Martini-Stiftung, Pfizer, Sandoz, Seqirus, Shionogi, streamedup!, Touch Independent, Vitis; Payment for expert testimony Cidara; Participation on a DRC, DSMB, DMC, Advisory Board for AstraZeneca, Cidara, IQVIA, Janssen, MedPace, Melinta, PSI, Pulmocide, Vedanta Biosciences. **MH** received research funding from Gilead, Astellas, MSD, IMMY, Pulmocide, Shionogi, Melinta, Mundiparma, Scynexis, F2G and Pfizer, all unrelated to the submitted work. All other authors declare no conflict of interest.

Acknowledgments

This study received partial funding through Investigator Initiated Research Grants from Scynexis (principal investigators MH and OAC) and Mundiparma, with the remaining funding provided
independently, without additional external support. Additionally, this work was in part-funded by the National Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre grant (NIHR203308).

## Appendix A

ECMM Candida III Study Group contributors: Birgit Willinger (Division of Clinical Microbiology, Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria), Deborah E. A. Lockhart (Department of Medical Microbiology, Aberdeen Royal Infirmary, Foresterhill, Aberdeen, United Kingdom), Sonia Martín-Pérez (Hospital Nuestra Señora de Sonsoles, Ávila Spain), Janina Trauth (Department of Medicine II, Section of Infectious Diseases, Justus-Liebig-University Giessen, Giessen, Germany), Jens Van Praet (Department of Nephrology and Infectious Diseases, AZ Sint-Jan Brugge AV, Brugge, Belgium), Alida Fe Talento (Beaumont Hospital Dublin - Dublin, Ireland), Cristina Toscano (Laboratory of Clinical Microbiology and Molecular Biology, Centro Hospitalar de Lisboa Ocidental, Lisboa, Portugal), Guillaume Desoubeaux (CHRU de Tours, Tours, France), Mario Tumbarello (Fondazione Policlinico A. Gemelli IRCCS, Rome, Italy), Anna L. Goodman (Department of Infection, Guy's and St Thomas' NHS Foundation Trust) but if space/capacity please add a secondary one- which is MRC Clinical Trials Unit at University College London), Tadeja Matos (Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia), Helena Hammarstroem (Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden), Ulrike Scharmann (Institut of Medical Microbiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany), Joerg Steinmann (Institut of Medical Microbiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany); Institute for Clinical Hygiene, Medical Microbiology and Infectiology, Paracelsus Medical University, Klinikum Nürnberg, Nuremberg, Germany), Michael Samarkos (1st Department of Medicine, Laikon General Hospital, Medical School, National & Kapodistrian University of Athens, Greece), Manjusha Narayanan (Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom), Tihana Bicanic (Institute of Infection and Immunity, St George's University of London, London, UK), Alena Siváková (Department of Microbiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic), Petr Hamal (Department of Microbiology, Faculty of Medicine and Dentistry, Palacky University, Olomouc, Czech Republic), Diane Poscarme (Hospital Saint Louis Paris, France), Alba C. Ruiz (Universitäre and Polytechnic Hospital La Fe, Valencia, Spain).

## Appendix B. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.jinf.2025.106629.

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