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COMPARISON BETWEEN TRANSIENT ELASTOGRAPHY AND POINT-SHEAR WAVE IN NON-ALCOHOLIC STEATOHEPATITS PATIENTS: A PROSPECTIVE STUDY

Giuseppe Losurdo 1, Antonio Continisio 1, MARGHERITA DE BELLIS 1, Ilaria Ditonno 1, Domenico Novielli 1, Maria Rendina 1, Antonino Castellaneta 1, Alfredo Di Leo 1, Michele Barone 1

Affiliations

1 University of Bari, Bari, Italy

Summary

AI Generated

Point-shear wave elastography and transient elastography show comparable liver stiffness measurements in NASH patients, with concordance influenced by the degree of hepatic steatosis.

In 77 NASH patients, overall correlation between pSWE and transient elastography was moderate (r=0.63, p<0.001), with linear regression coefficient of 0.99 ± 0.033 and Bland-Altman bias of -0.52.
Correlation between the two methods was strongest in patients with moderate steatosis (S2, r=0.90) and strong in mild steatosis (S1, r=0.81), but low in severe steatosis (S3, r=0.42).
A pSWE cut-off of 11.15 kPa achieved 87.50% sensitivity and 97.10% specificity for detecting relevant fibrosis, with AUC=0.98 compared to transient elastography.
The study suggests good concordance between pSWE and transient elastography in mild to moderate steatosis, but weaker agreement in severe steatosis, relevant for clinicians selecting non-invasive fibrosis assessment methods in NASH.

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Abstract

Introduction

Transient elastography (TE) by Fibroscan® is a widespread method for non-invasive evaluation of liver stiffness measurement (LSM). Point-shear wave elastography (pSWE) is an alternative non-invasive method for this type of assessment. Transient elastography is also able to evaluate hepatic steatosis by the function Controlled Attenuation Parameter (CAP).

Aims & Methods

We aimed to compare the results of TE and pSWE for fibrosis assessment in patients with non-alcoholic steatohepatitis (NASH), stratified by the degree of steatosis.
Consecutive patients with established diagnosis of NASH attending our Gaastroenterology Unit underwent liver stiffness measurement (LSM) by both TE and pSWE. Liver steatosis was measured by CAP and the severity was graded into S0-S3. At least 10 measurements were performed and results were expressed as median with interquartile range. Statistical analysis was conducted by Pearson’s test for correlation and linear regression. Bland-Altman graphs with bias and ROC curves with estimation of sensitivity, specificity, and area under the curve (AUC) were drawn.

Results

Seventy-seven patients were recruited (17 females, 60 males, aging 54.1 ± 13.9). The overall correlation between TE and pSWE was moderate (r=0,63, p < 0.001). Linear regression showed a “b” coefficient of 0.99 ± 0.033. The Bland-Altman plot found a bias of -0,52 and only six valued exceeded the 95% CI limits. When considering patients with mild steatosis (S1), we found a strong correlation (r=0.81, 95% CI 0.39-0.95, p=0.003). The highest correlation between TE and pSWE was recorded for S2 subjects: r=0.90 (95% CI, 0.64-0.98, p<0.001). The correlation was low in S3 patients (r=0.42, 95% CI, 0.09-0.67, p=0.001). A cut-off of 11.15 kPa of pSWE had sensitivity=87,50 % and specificity=97,10% to detect relevant fibrosis, with an AUC=0.98 compared to TE.

Conclusion

pSWE and TE showed comparable LSM in NASH. A good concordance was observed in patients with mild or moderate liver steatosis, while in S3 patients we observed a weaker agreement between the two techniques.

Conference

UEG Week Copenhagen 2023

Topics

Hepatobiliary

Submission format

Abstract

Session

PP 07 Liver & biliary (Posters)

Citation

United European Gastroenterology Journal 2023; 11 (Supplement 8)

Published

2023

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Iris Lansdorp-Vogelaar

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DEEP LEARNING-BASED ENDOSCOPIC ULTRASOUND DIAGNOSIS OF FATTY PANCREAS: AGREEMENT WITH MRI AND PERFORMANCE OF AI MODELS

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DEEP LEARNING-BASED ENDOSCOPIC ULTRASOUND DIAGNOSIS OF FATTY PANCREAS: AGREEMENT WITH MRI AND PERFORMANCE OF AI MODELS

Matteo Tacelli 1, Alberta De monti 2, Maria Chiara Petrone 1, Piera Zaccari 1, Gemma Rossi 1, Francesco Prato 1, Diego Palumbo 1, Francesco De Cobelli 1, Paolo Giorgio Arcidiacono 1

Affiliations

1 San Raffaele Scientific Institute IRCCS, Milano, Italy

2 Lecco Hospital, Milano, Italy

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Abstract

Introduction

Fatty pancreas is an increasingly recognized condition associated with metabolic abnormalities, but its diagnosis remains poorly standardized. In clinical practice, endoscopic ultrasound (EUS) is widely used to assess pancreatic parenchyma, yet its interpretation is mainly qualitative and operator-dependent, while magnetic resonance imaging (MRI) currently represents the most reliable non-invasive reference standard for pancreatic fat quantification.

Aims & Methods

This study aimed to assess the agreement between expert EUS-based diagnosis of fatty pancreas and MRI, and to develop deep learning models for automated fatty pancreas detection on EUS images. A retrospective single-centre observational study was conducted at San Raffaele Hospital including consecutive patients who underwent diagnostic EUS between January 2023 and December 2025 and had abdominal MRI within 12 months. Fatty pancreas was defined on MRI by pancreatic fat fraction >6%. Agreement between EUS and MRI was assessed with Cohen’s kappa. Secondary analyses included operator-level performance and subgroup analyses. For the AI endpoint, convolutional neural network models were developed using three approaches: all available EUS images per patient, a single representative image per patient, and a segmentation-based strategy combined with an ensemble model.

Results

Among 2324 EUS procedures, 314 patients had MRI available and were included in the primary analysis; 150 had fatty pancreas and 164 did not. Patients with fatty pancreas were older than controls (65.8 ± 11.0 vs 58.7 ± 14.2 years, p<0.001), and dyslipidaemia was more frequent (41% vs 25%, p<0.001). Agreement between EUS and MRI was only fair (Cohen’s κ=0.31), with sensitivity 39.9%, specificity 91.5%, and overall accuracy 66.6%. Marked inter-operator variability was observed, with κ ranging from 0.06 to 0.82. Concordance tended to be higher in patients with BMI >25 kg/m² (κ=0.40 vs 0.20, p=0.05) and was significantly lower in chronic pancreatitis (κ=-0.16 vs 0.34, p=0.03). For deep learning, the model using all available images achieved an AUC of 0.70. The single-image model achieved an AUC of 0.713, with high sensitivity (0.86–0.95) but modest specificity (0.38–0.50). The best performance was obtained with the segmentation-based ensemble model, which reached an AUC of 0.724, accuracy 69.8%, sensitivity 90%, specificity 52%, and balanced accuracy 0.71 in the independent test set.

Conclusion

EUS shows limited agreement with MRI for fatty pancreas diagnosis and substantial inter-operator variability, supporting the need for more objective and standardized diagnostic criteria. Deep learning applied to EUS images demonstrated moderate discriminatory ability, with the segmentation-based ensemble approach providing the most promising results. These findings support further development of AI-assisted EUS tools to improve reproducibility and diagnostic performance in fatty pancreas assessment.

Event

UEG Week Barcelona 2026

Topics

Radiology & Imaging Hepatobiliary Endoscopy Pancreas

Submission format

Abstract

Session

Endoscopy: Taming the biliary tree

Citation

2026: United European Gastroenterology Journal 2026; 14 (S1)

Published

2026

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Edmond Atallah

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Iris Lansdorp-Vogelaar

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Let’s not forget about TIPS: Improving outcomes in portal hypertension

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Let’s not forget about TIPS: Improving outcomes in portal hypertension

Mattias Mandorfer 1

Affiliations

1 Medical University of Vienna, Vienna, Austria

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Abstract

Event

UEG Week Barcelona 2026

Topics

Mechanisms & Personalised Medicine Surgery Hepatobiliary

Session

How to manage cirrhosis in 2026

Citation

2026: United European Gastroenterology Journal 2026; 14 (S1)

Published

2026

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Iris Lansdorp-Vogelaar

UEG Presentation

New

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MULTI-OMICS BIOMARKERS FOR PREDICTING TREATMENT RESPONSE IN INFLAMMATORY BOWEL DISEASE

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MULTI-OMICS BIOMARKERS FOR PREDICTING TREATMENT RESPONSE IN INFLAMMATORY BOWEL DISEASE

Montse Baldan Martin 1, Mikel Azkargorta 2, Ana M. Aransay 3, Rubén Gil-Redondo 4, Isabel Moreno-Indias 5, Ibon Iloro 2, Paula J Martínez 1, Irene Soleto 1, Fabio Suarez-Trujillo 1, Cristina Ramírez 1, Alfredo J. Lucendo 6, Cristina Rodríguez Gutiérrez 7, Ana Gutiérrez-Casbas 8, Eduardo Martín Arranz 9, Luis Bujanda Fernández de Piérola 10, Iago Rodríguez-Lago 11, Ruth María de Francisco García 12, Eva Iglesias-Flores 13, Fernando Bermejo 14, Manuel Van Domselaar 15, María José García 16, Luis Fernández-Salazar 17, Francisco Javier Garcia-Alonso 18, Xavier Calvet Calvo 19, Leyanira Torrealba Medina 20, Iria Bastón-Rey 21, Hector Pallares Manrique 22, Yolanda Ber Nieto 23, Eduardo Leo Carnerero 24, María José Casanova 1, Oscar Millet 4, Felix Elortza 2, Jose Mato 4, Francisco J Tinahones 5, María Chaparro 1, Javier P. Gisbert 1

Affiliations

1 Hospital Universitario de La Princesa- Instituto de Investigación Sanitaria Princesa IIS-Princesa and Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas CIBEREHD, Gastroenterology Unit, Madrid, Spain

2 CIC bioGUNE- Basque Research & Technology Alliance BRTA- CIBEREHD, Proteomics Platform, Derio, Spain

3 CIC bioGUNE- BRTA- CIBEREHD, Genome Analysis Platform, Derio, Spain

4 CIC bioGUNE, Precision Medicine and Metabolism Lab, Derio, Spain

5 Virgen de la Victoria University Hospital- Málaga- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición CIBEROBN- Instituto de Salud Carlos III, Department of Endocrinology and Nutrition, Malaga, Spain

6 Hospital General de Tomelloso- Instituto de Investigación Sanitaria de Castilla-La Mancha IDISCAM- CIBEREHD, Gastroenterology Department, Ciudad Real, Spain

7 Hospital Universitario de Navarra, Gastroenterology Department, Pamplona, Spain

8 Hospital General Universitario de Alicante- CIBEREHD and Instituto Investigación Sanitaria y Biomédica de Alicante, Gastroenterology Department, Alicante, Spain

9 Hospital Universitario La Paz and Instituto de Investigación Sanitaria La Paz IdiPaz, Gastroenterology Department, Madrid, Spain

10 Hospital Universitario Donostia and Instituto Biodonostia. Universidad del País Vasco UPV/EHU, Gastroenterology Department, Donostia, Spain

11 Hospital Universitario de Galdakao- Biocruces Bizkaia HRI, Gastroenterology Department, Vizcaya, Spain

12 Hospital Universitario Central de Asturias and Instituto de Investigación Sanitaria del Principado de Asturias ISPA, Gastroenterology Department, Oviedo, Spain

13 Hospital Universitario Reina Sofia, Gastroenterology Department, Cordoba, Spain

14 Hospital Universitario de Fuenlabrada, Gastroenterology Department, Madrid, Spain

15 Hospital Universitario de Torrejón, Gastroenterology Department, Madrid, Spain

16 Hospital Universitario Marqués de Valdecilla and IDIVAL, Gastroenterology Department, Santander, Spain

17 Hospital Clínico Universitario de Valladolid, Gastroenterology Department, Valladolid, Spain

18 Hospital Universitario Rio Hortega, Gastroenterology Department, Valladolid, Spain

19 Consorci Corporació Santitària Parc Taulí- CIBEREHD, Unitat de Malaties Digestives, Sabadell, Spain

20 Hospital Universitario Dr. Josep Trueta, Gastroenterology Department, Girona, Spain

21 Hospital Clínico Universitario de Santiago, Gastroenterology and Hepatology Department, Santiago de Compostela, Spain

22 Hospital Juan Ramón Jiménez, Gastroenterology Department, Huelva, Spain

23 Hospital San Jorge, Gastroenterology Department, Huesca, Spain

24 Hospital Universitario Virgen del Rocío, Gastroenterology Department, Sevilla, Spain

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Abstract

Introduction

Inflammatory bowel diseases (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), are chronic, immune-mediated disorders characterized by heterogeneous clinical courses and unpredictable therapeutic responses. Despite the availability of biologics and small molecules, treatment selection remains empirical, delaying remission, increasing exposure to ineffective drugs, and highlighting urgent need for biomarker-driven, precision-guided strategies.

Aims & Methods

A multi-omics analysis was performed integrating transcriptomics, proteomics, metabolomics, and metagenomics across intestinal tissue, serum, urine, serum-derived extracellular vesicles (EVs), and stool from 130 IBD patients treated with anti-TNFα, ustekinumab, vedolizumab, or tofacitinib.

Results

Clinical and demographic characteristics are summarised in Table 1. Analyses revealed distinct, therapy-specific molecular signatures capable of discriminating responders from non-responders, with all markers achieving a predictive performance of area under the curve > 0.9. In CD, PDIA1 and IGHV4-28 in serum EVs and intestinal tissue predicted anti-TNFα response, while LINC02802 and MIR567 distinguished ustekinumab responders. In UC, vedolizumab response was associated with SCIMP and CYP39A1 in intestinal tissue, and tofacitinib response with CAVN2 in serum EVs. Metabolomic profiling highlighted coordinated serum and urinary alterations in amino acids, organic acids, and lipid metabolism linked to therapeutic efficacy. Metagenomic analysis identified genera associated with response, including Prevotella and Anaerotruncus for anti-TNFα, Faecalibacterium for ustekinumab, Catenibacterium for vedolizumab, and Phascolarctobacterium for tofacitinib. Integration of multi-omics layers provided complementary insights, emphasising the central role of the intestinal microenvironment and host-microbiota interactions in mediating treatment outcomes.

Table 1. Clinical characteristics of patients with Crohn's disease and ulcerative colitis.

Clinical characteristic	CD (n=58)	UC (n=72)
Sex (M/F) n (%)	35/23 (60/40)	40/32 (56/44)
Age at biologic/tofacitinib start (mean ± SD)	45 ± 13	47 ± 16
Smoking (yes), n (%)	10 (17)	3 (4)
CD phenotype, n (%) B1 B2 B3	39 (67) 13 (23) 6 (10)
CD severity (SES-CD), n (%) 3-6 7-15 ≥16	18 (31) 44 (57) 7 (12)
UC location, n (%) E1 E2 E3		4 (6) 24 (33) 44 (61)
UC severity (Mayo), n (%) Moderate Severe		27 (38) 45 (62)
Anti-TNF, n (%) Ustekinumab, n (%)	31 (53) 27 (47)	29 (40) -
Vedolizumab, n (%) Tofacitinib, n (%)	- -	27 (38) 16 (22)

Conclusion

These findings establish a comprehensive framework for precision therapy in IBD, identifying predictive biomarkers with translational potential to optimize personalized therapy, minimize ineffective treatment, and reduce disease burden.

Disclosure

- Eduardo Martin Arranz. Personal fees: Olympus, Janssen; Non-financial support: Abbvie, Pfizer, Janssen
- María José García. Financial support for travel and education: Janssen, Pfizer, Abbvie, Takeda, Ferring
- Francisco Javier García Alonso. Speaker fees: Abbvie, Lilly, Johnson & Johnson
- Xavier Calvet Calvo. Research grants: Abbvie, Janssen, Kern, Vifor; Advisory board/lectures: Abbvie, MSD, Takeda, Vifor, Janssen
- Iria Bastón Rey. Travel/education support and advisory boards: Abbvie, Johnson & Johnson, Takeda, Pfizer, Alfasigma, Ferring, Faes Farma, Otsuka, Adacyte
- Eduardo Leo Carnerero. Grants/fees/advisory: MSD, Pfizer, Abbvie, Takeda, Janssen, Tillotts, Shire, Ferring, Dr. Falk, Lilly, Adacyte, Otsuka
- María José Casanova. Education funding: Pfizer, Takeda, Janssen, MSD, Dr. Falk, Shire, Ferring, Galápagos, Abbvie; Research funding: Lilly
- María Chaparro. Grants: Pfizer, Janssen, Biogen, Abbvie, Lilly; Personal fees: Pfizer, Faes, Lilly, Abbvie, Janssen
- Javier P. Gisbert. Grants, personal fees, and other support: MSD, Abbvie, Pfizer, Kern Pharma, Biogen, Mylan, Takeda, Janssen, Roche, Sandoz, Celgene/BMS, Gilead/Galápagos/Alfasigma, Lilly, Sanofi, STADA, Teva, Ferring, Faes Farma, Shire, Dr. Falk, Tillotts, Chiesi, Casen Fleet, Gebro Pharma, Otsuka, Norgine, Italfarmaco, Vifor Pharma

Event

UEG Week Barcelona 2026

Topics

Gut Microbiota Mechanisms & Personalised Medicine IBD

Submission format

Abstract

Session

One patient, multiple futures: Predicting outcomes in IBD

Citation

2026: United European Gastroenterology Journal 2026; 14 (S1)

Published

2026

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Paolo Giorgio Arcidiacono

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Mattias Mandorfer

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Javier P. Gisbert

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Ivo Boskoski

Drug-induced liver injury: new treatment strategies

Edmond Atallah

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Iris Lansdorp-Vogelaar

UEG Presentation

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Beyond surgery: The expanding role of bariatric and metabolic endoscopy

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Beyond surgery: The expanding role of bariatric and metabolic endoscopy

Ivo Boskoski 1

Affiliations

1 Catholic University of Rome Digestive Endoscopy Unit, Rome, Italy

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Abstract

Event

UEG Week Barcelona 2026

Topics

Surgery Mechanisms & Personalised Medicine Endoscopy

Session

A 360° multidisciplinary approach to obesity and metabolic health

Citation

2026: United European Gastroenterology Journal 2026; 14 (S1)

Published

2026

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Edmond Atallah

EFFECTIVENESS OF TAILORED SCREENING INTERVALS BASED ON PRIOR FECAL HEMOGLOBIN CONCENTRATION IN FIT-BASED COLORECTAL CANCER SCREENING: RESULTS OF THE RANDOMIZED CONTROLLED TRIAL PERFECT-FIT

Iris Lansdorp-Vogelaar

UEG Presentation

New

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Drug-induced liver injury: new treatment strategies

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Drug-induced liver injury: new treatment strategies

Edmond Atallah 1

Affiliations

1 NIHR Nottingham Biomedical Research Centre & Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom

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Abstract

Event

UEG Week Barcelona 2026

Topics

Mechanisms & Personalised Medicine Hepatobiliary

Session

What’s new in… Hepatitis and liver failure

Citation

2026: United European Gastroenterology Journal 2026; 14 (S1)

Published

2026

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DEEP LEARNING-BASED ENDOSCOPIC ULTRASOUND DIAGNOSIS OF FATTY PANCREAS: AGREEMENT WITH MRI AND PERFORMANCE OF AI MODELS

Paolo Giorgio Arcidiacono

Let’s not forget about TIPS: Improving outcomes in portal hypertension

Mattias Mandorfer

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Javier P. Gisbert

Beyond surgery: The expanding role of bariatric and metabolic endoscopy

Ivo Boskoski

Drug-induced liver injury: new treatment strategies

Edmond Atallah

EFFECTIVENESS OF TAILORED SCREENING INTERVALS BASED ON PRIOR FECAL HEMOGLOBIN CONCENTRATION IN FIT-BASED COLORECTAL CANCER SCREENING: RESULTS OF THE RANDOMIZED CONTROLLED TRIAL PERFECT-FIT

Iris Lansdorp-Vogelaar

UEG Presentation

New

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EFFECTIVENESS OF TAILORED SCREENING INTERVALS BASED ON PRIOR FECAL HEMOGLOBIN CONCENTRATION IN FIT-BASED COLORECTAL CANCER SCREENING: RESULTS OF THE RANDOMIZED CONTROLLED TRIAL PERFECT-FIT

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EFFECTIVENESS OF TAILORED SCREENING INTERVALS BASED ON PRIOR FECAL HEMOGLOBIN CONCENTRATION IN FIT-BASED COLORECTAL CANCER SCREENING: RESULTS OF THE RANDOMIZED CONTROLLED TRIAL PERFECT-FIT

Esther Toes-Zoutendijk 1, Lucie de Jonge 1, Emilie Breekveldt 1, Manon C.W. Spaander 1, Evelien Dekker 2, Folkert J. van Kemenade 1, Unknown Unknown 1, Iris Nagtegaal 3, Marc Thelen 4, Monique van leerdam 5, Iris Lansdorp-Vogelaar 6

Affiliations

1 Erasmus MC University Medical Center, Rotterdam, Netherlands

2 AMC, Amsterdam, Netherlands

3 Radboud University Nijmegen Medical Center Dept. of Pathology, Nijmegen, Netherlands

4 Radboud University Nijmegen Medical Center, Nijmegen, Netherlands

5 Netherlands Cancer Institute, Amstelveen, Netherlands

6 Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands

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Abstract

Introduction

Previous studies of fecal immunochemical test (FIT)-based colorectal cancer (CRC) screening programs have demonstrated that fecal hemoglobin (f-Hb) concentrations below the FIT positivity threshold, are associated with a higher risk of advanced neoplasia (AN) in subsequent screening rounds. These findings highlight the potential of risk-stratified CRC screening based on prior f-Hb concentrations. However, prospective evidence of this approach is lacking.

Aims & Methods

The aim of this randomized controlled trial (RCT) was to evaluate the of yield risk-tailored screening intervals based on prior f-Hb concentrations in a FIT-based CRC screening. The PERFECT‑FIT study (NCT05423886) recruited individuals aged 57 to 72 in 2022 and 2023 in the Netherlands. They were randomly assigned to either tailored screening intervals based on f-Hb concentrations measured in their prior negative FIT (1 year for >15 to <47 µg Hb/g feces, 2 years for >0 to ≤15 µg Hb/g feces, and 3 years for 0 µg Hb/g feces; intervention group) or the standard 2-year screening interval (control group). The primary outcome was the detection of AN (CRC and advanced adenomas) over one screening round.

Results

In total, 20,088 participants provided informed consent and were randomly assigned to either the control group (n = 10,211) or the intervention group (n=9,877). In the intervention group, 352 (3.6%) participants were assigned to a 1-year screening interval, 350 (3.5%) to a 2-year interval and 9,175 (92.9%) to a 3-year interval. 19,547 study participants returned their FIT (97.3%). The positivity rate of FIT was significantly higher in the intervention group (4.4%) than in the control group (3.7%; p=0.03). The detection rate of AN showed no significant difference between the intervention group (1.0%) and the control group (0.8%; p=0.21, Table 1). Within the intervention group, detection rate of AN for the extended 3-year interval (0.7%) was substantially lower than that of the 1-year (3.5%) and 2-year interval (5.0%). It was similar to that of the total control group, in which all individuals had received an uniform 2-year screening interval (Table 1).

Conclusion

In this nationwide RCT on risk-stratified CRC screening, the majority of individuals were classified as low risk based on undetectable f-Hb concentrations and were offered an extended screening interval. Risk-tailored screening intervals did not result in a higher detection rate of AN after one screening round for the total intervention group compared with the control arm. However, the yield among those assigned to an extended screening interval was comparable to that of the control group. These findings suggest that screening intervals can be safely extended for low-risk individuals, potentially improving screening efficiency without compromising screening yield.

Table 1: Detection rates of advanced neoplasia among participants in the control group and the intervention group in the PERFECT-FIT RCT, including the three intervention subgroups.

Group	Total participants	Advanced Neoplasia	Detection rate (%, 95%CI)	p value
Control	9963	79	0.8 (0.6-1.0)
Intervention	9584	93	1.0 (0.8-1.2)	0.21
1 year	347	12	3.5 (1.9-6.1)
2 year	341	17	5.0 (3.0-8.0)
3 year	8896	64	0.7 (0.6-0.9)

References

1. Meester RGS, van de Schootbrugge-Vandermeer HJ, Breekveldt ECH, de Jonge L, Toes-Zoutendijk E, Kooyker A, Nieboer D, Ramakers CR, Spaander MCW, van Vuuren AJ, Kuipers EJ, van Kemenade FJ, Nagtegaal ID, Dekker E, van Leerdam ME, Lansdorp-Vogelaar I; Dutch colorectal cancer screening working group. Faecal occult blood loss accurately predicts future detection of colorectal cancer. A prognostic model. Gut. 2023;72(1):101-108. doi: 10.1136/gutjnl-2022-327188.
2. van den Berg DMN, van den Puttelaar R, de Jonge L, Lansdorp-Vogelaar I, Toes-Zoutendijk E. Fecal Hemoglobin Levels in Prior Negative Screening and Detection of Colorectal Neoplasia: A Dose-Response Meta-Analysis. Gastroenterology. 2025;168(3):587-597. doi: 10.1053/j.gastro.2024.10.047.
3. Breekveldt ECH, Toes-Zoutendijk E, de Jonge L, Spaander MCW, Dekker E, van Kemenade FJ, van Vuuren AJ, Ramakers CRB, Nagtegaal ID, van Leerdam ME, Lansdorp-Vogelaar I. Personalized colorectal cancer screening: study protocol of a mixed-methods study on the effectiveness of tailored intervals based on prior f-Hb concentration in a fit-based colorectal cancer screening program (PERFECT-FIT). BMC Gastroenterol. 2023;23(1):45. doi: 10.1186/s12876-023-02670-1.

Disclosure

The authors have received research funding, unrelated to the present study, from Sentinel, Sysmex, Medtronic, and Norgine.

Event

UEG Week Barcelona 2026

Topics

Primary Care Oesophagus Hepatobiliary Endoscopy Digestive Oncology Colorectal

Submission format

Late-Breaking Abstract

Session

Late-Breaking: Advances in GI-endoscopy

Citation

2026: United European Gastroenterology Journal 2026; 14 (S1)

Published

2026

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