Meta-Analysis Open Access
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Feb 14, 2024; 30(6): 579-598
Published online Feb 14, 2024. doi: 10.3748/wjg.v30.i6.579
Urea breath test for Helicobacter pylori infection in adult dyspeptic patients: A meta-analysis of diagnostic test accuracy
Fabian Fellipe Bueno Lemos, Marcel Silva Luz, Gabriel Reis Rocha, Gabriel Lima Correa Santos, Luís Guilherme de Oliveira Silva, Mariana Santos Calmon, Cláudio Lima Souza, Fabrício Freire de Melo, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
Caroline Tianeze de Castro, Instituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador 40110040, Bahia, Brazil
Ana Carla Zarpelon-Schutz, Kádima Nayara Teixeira, Campus Toledo, Universidade Federal do Paraná, Toledo 85919-899, Paraná, Brazil
Dulciene Maria de Magalhães Queiroz, Laboratory of Research in Bacteriology, UFMG, Belo Horizonte 30130-100, Minas Gerais, Brazil
ORCID number: Fabian Fellipe Bueno Lemos (0000-0002-4686-7086); Caroline Tianeze de Castro (0000-0002-9445-8842); Marcel Silva Luz (0000-0003-1650-5807); Gabriel Reis Rocha (0000-0002-3090-0726); Gabriel Lima Correa Santos (0000-0003-3673-9889); Luís Guilherme de Oliveira Silva (0000-0001-7275-7182); Mariana Santos Calmon (0000-0002-3871-7408); Cláudio Lima Souza (0000-0002-8094-8357); Ana Carla Zarpelon-Schutz (0000-0002-8320-3633); Kádima Nayara Teixeira (0000-0002-2928-9181); Dulciene Maria de Magalhães Queiroz (0000-0003-1334-9423); Fabrício Freire de Melo (0000-0002-5680-2753).
Author contributions: Lemos FFB, Castro CT, Silva Luz M, Queiroz DMM, and Freire de Melo F contributed to the conceptualization of the manuscript; Lemos FFB, Castro CT, Queiroz DMM and Freire de Melo F designed the study methodology; Lemos FFB, Castro CT, Calmon MS, Silva Luz M, Rocha GR, Correa Santos GL, de Oliveira Silva LG, Calmon MS were responsible for manuscript visualization; Lemos FFB, Castro CT, Calmon MS, Silva Luz M, Rocha GR, Correa Santos GL, de Oliveira Silva LG, Calmon MS contributed to the investigation; Lemos FFB, Castro CT, Calmon MS, Silva Luz M, Rocha GR, Correa Santos GL, de Oliveira Silva LG, Calmon MS performed formal analysis; Lemos FFB and Castro CT wrote the original draft; Castro CT and Queiroz DMM were responsible for manuscript editing; Castro CT, Teixeira KN, Souza CL, and Queiroz DMM were responsible for manuscript writing and review; Freire de Melo F supervised the writing of the original draft.
Supported by Scientific Initiation Scholarship Programme (PIBIC) of the Bahia State Research Support Foundation; the Doctorate Scholarship Program of the Coordination of Improvement of Higher Education Personnel; the Scientific Initiation Scholarship Programme (PIBIC) of the National Council for Scientific and Technological Development; and the CNPq Research Productivity Fellowship.
Conflict-of-interest statement: The authors declare no conflict of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Fabrício Freire de Melo, PhD, Professor, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Estrada do Bem Querer, No. 3293-3391- Candeias, Vitória da Conquista 45029-094, Bahia, Brazil. freiremeloufba@gmail.com
Received: November 14, 2023
Peer-review started: November 14, 2023
First decision: December 5, 2023
Revised: December 16, 2023
Accepted: January 16, 2024
Article in press: January 16, 2024
Published online: February 14, 2024

Abstract
BACKGROUND

Helicobacter pylori (H. pylori) infection has been well-established as a significant risk factor for several gastrointestinal disorders. The urea breath test (UBT) has emerged as a leading non-invasive method for detecting H. pylori. Despite numerous studies confirming its substantial accuracy, the reliability of UBT results is often compromised by inherent limitations. These findings underscore the need for a rigorous statistical synthesis to clarify and reconcile the diagnostic accuracy of the UBT for the diagnosis of H. pylori infection.

AIM

To determine and compare the diagnostic accuracy of 13C-UBT and 14C-UBT for H. pylori infection in adult patients with dyspepsia.

METHODS

We conducted an independent search of the PubMed/MEDLINE, EMBASE, and Cochrane Central databases until April 2022. Our search included diagnostic accuracy studies that evaluated at least one of the index tests (13C-UBT or 14C-UBT) against a reference standard. We used the QUADAS-2 tool to assess the methodological quality of the studies. We utilized the bivariate random-effects model to calculate sensitivity, specificity, positive and negative test likelihood ratios (LR+ and LR-), as well as the diagnostic odds ratio (DOR), and their 95% confidence intervals. We conducted subgroup analyses based on urea dosing, time after urea administration, and assessment technique. To investigate a possible threshold effect, we conducted Spearman correlation analysis, and we generated summary receiver operating characteristic (SROC) curves to assess heterogeneity. Finally, we visually inspected a funnel plot and used Egger’s test to evaluate publication bias.

RESULTS

The titles and abstracts of 4621 studies were screened; 79 articles were retrieved and selected for full-text reading. Finally, 60 studies were included in the diagnostic test accuracy meta-analysis. Our analysis demonstrates superior diagnostic accuracy of 13C-UBT over 14C-UBT, indicated by higher sensitivity (96.60% vs 96.15%), specificity (96.93% vs 89.84%), likelihood ratios (LR+ 22.00 vs 10.10; LR- 0.05 vs 0.06), and area under the curve (AUC; 0.979 vs 0.968). Notably, 13C-UBT's DOR (586.47) significantly outperforms 14C-UBT (DOR 226.50), making it the preferred diagnostic tool for dyspeptic individuals with H. pylori infection. Correlation analysis revealed no threshold effect (13C-UBT: r = 0.48; 14C-UBT: r = -0.01), and SROC curves showed consistent accuracy. Both 13C-UBT and 14C-UBT showed high AUC values (13C-UBT 0.979; 14C-UBT 0.968) near 1.00, reinforcing their excellent accuracy and endorsing both as reliable diagnostic tools in clinical practice.

CONCLUSION

In summary, our study has demonstrated that 13C-UBT has been found to outperform the 14C-UBT, making it the preferred diagnostic approach. Additionally, our results emphasize the significance of carefully considering urea dosage, assessment timing, and measurement techniques for both tests to enhance diagnostic precision. Nevertheless, it is crucial for researchers and clinicians to evaluate the strengths and limitations of our findings before implementing them in practice.

Key Words: Helicobacter pylori, Urea breath test, Diagnosis, Diagnostic test accuracy, Meta-analysis

Core Tip: The urea breath test (UBT) is a pivotal noninvasive method for detecting Helicobacter pylori (H. pylori); however, its reliability is challenging. This meta-analysis aimed to compare the precision of the 13C-UBT and 14C-UBT in diagnosing H. pylori among adults with dyspepsia, providing insights to enhance clinical strategies.



INTRODUCTION

Helicobacter pylori (H. pylori) is a spiral-shaped, gram-negative microaerophilic bacterium that infects approximately 43% of the global population[1]. While the majority of infected individuals remain asymptomatic, chronic gastritis inevitably ensues, leading to a significant burden of morbidity and mortality[2,3]. Adults who are infected with H. pylori are at increased risk of developing peptic ulcer disease, gastric cancer, and mucosa-associated lymphoid tissue lymphoma[4-6]. To address this, current guidelines advocate for either a test-and-treat or a scope-and-treat approach in managing uninvestigated dyspepsia, underscoring the importance of timely diagnosis and intervention[7,8].

Diagnostic testing for H. pylori infection typically involves two primary categories: Invasive (endoscopic) and non-invasive testing, depending on the application of upper endoscopy[9]. For individuals aged 50 years or older or those with alarm features, the recommended standard diagnostic approach involves upper endoscopy, followed by histopathological examination (HE) or rapid urease test (RUT), and occasionally, culture[8]. In contrast, in dyspeptic patients under 50 years without specific risk factors or alarm symptoms, non-invasive methods such as urea breath testing (UBT), stool antigen testing, and serology are preferred[8,10].

Among non-invasive diagnostic techniques, the UBT has emerged as a prominent method. This approach capitalizes on the urease activity of H. pylori, initiating the hydrolysis of ingested urea and consequent release of labeled carbon dioxide[11]. Two commonly utilized isotopic variants, 13C-UBT and 14C-UBT, offer distinctive features. In 13C-UBT, a stable isotope (carbon-13) is employed, and breath samples are collected and analyzed for labeled carbon dioxide using various methods such as mass spectrometry and infrared spectrometry[12]. This method presents important advantages, notably the absence of ionizing radiation, rendering it suitable for repeated application and applicable in vulnerable populations, including pregnant women and children[11,13]. In contrast, 14C-UBT utilizes a radioactive isotope (carbon-14) and primarily relies on scintillation counting for detection[14,15]. Despite its historical use, concerns regarding radiation exposure have diminished its preference in contemporary clinical practice.

In a prior meta-analysis, Ferwana et al[16] assessed the diagnostic accuracy of the UBT, encompassing both 13C-UBT and 14C-UBT, for detecting H. pylori infection in adult dyspeptic patients. Despite its high accuracy, the reliability of UBT results was constrained by significant unexplained heterogeneity, persisting even after subgroup analysis[16]. This pattern persisted in subsequent studies, with Zhou et al[17] finding analogous challenges in calculating pooled estimates of diagnostic accuracy for 14C-UBT. Moreover, a subsequent systematic review emphasized that the variability in thresholds and reference standards across studies limited the data available for pooling accuracy measures at specific UBT thresholds[18].

These findings underscore the need for a rigorous statistical synthesis to clarify and reconcile the diagnostic accuracy of the UBT for the diagnosis of H. pylori infection, addressing challenges identified in prior research. To address this gap in the evidence, we conducted a systematic review and meta-analysis to determine the diagnostic accuracy of the UBT for H. pylori infection in adult patients with dyspepsia.

MATERIALS AND METHODS

This study adhered to the guidelines outlined in the PRISMA-DTA[19]. These guidelines encompass a 27-item checklist and a 3-phase flowchart, both designed to enhance the transparency of systematic review reporting. Accordingly, our study protocol has been officially registered in the PROSPERO database under the registration number CRD42023449854.

Literature search

This search strategy was designed following the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy (Version 2.0, 2022)[20]. We performed independent, computer-assisted searches of the: (1) PubMed/MEDLINE; (2) EMBASE; and (3) Cochrane Library databases. MeSH (Medical Subject Headings) and Emtree (EMBASE Subject Headings) index terms and free-text words were combined. Search terms included "urea breath test," "breath test," "13C-urea breath test," "14C-urea breath test," "13C-UBT," "14C-UBT," "Helicobacter pylori," "H. pylori," and "dyspepsia." Boolean operators (AND, OR) were also used to narrow or broaden the search as required. No language restriction was applied. To identify additional studies, reference lists were also scanned. Finally, we conducted a “citing reference” search (by searching articles which cited the included studies) in PubMed/MEDLINE and EMBASE. Following the search, all identified citations were collated and uploaded into the Rayyan (https://www.rayyan.ai/) tool, and all duplicates were removed.

Selection of studies

Two independent reviewers, Lemos FFB and Calmon MS, screened the references against predefined eligibility criteria. In the case of disagreement, a 3rd researcher, Silva Luz M, was consulted. Full-text papers were obtained for references considered relevant. If any study was not retrieved, the authors were contacted. Two authors, Lemos FFB and Correa Santos GL, independently screened the full-text papers against the eligibility criteria. In the case of disagreement, consensus was reached.

We included diagnostic accuracy studies that evaluated at least one of the index tests (13C- or 14C-UBTs) against a reference standard (biopsy fragments followed by culture or HE or RUT and/or not serology/stool antigen-based tests in adult dyspeptic patients. Exclusion criteria were as follows: (1) Studies that enrolled children or adolescents under 18 years of age; (2) studies that included only patients with acute upper gastrointestinal bleeding; (3) studies that enrolled subjects who presented for reasons other than dyspeptic symptoms, complicated dyspeptic cases that need surgery, those who received previous therapy for H. pylori within the last 3 months, or long-term use of corticosteroids and immunosuppressant drugs; (4) screening studies; (5) studies that did not report true positive, false positive, false negative, and true negative data and the threshold used for the index tests; (6) case-control studies because these are prone to bias[21]; and (7) full-text articles not available or articles not available in English, Spanish, or Portuguese.

Data extraction and management

Two review authors, Rocha GR and Correa Santos GL, independently extracted data from each included study using a pre-piloted data extraction form. In case of discrepancies, a 3rd researcher, Lemos FFB, was consulted. The extracted data included: (1) Information about the studies, such as the first author, publication year, and country; (2) details about the study design, including the type of study (prospective and retrospective cohort studies, cross-sectional studies, or randomized clinical trials), the reference standards used, blinding of the index test and reference standard, and the flow and timing (retrospective/prospective); (3) participant information, i.e., the total number of participants and population characteristics (age, mean ± SD, sex, and disease prevalence); (4) reference standard details, including the time interval between the index test and the reference standard; index test information, including the model (13C- or 14C-UBT), cut-off values, urea dosing, time for measurement after urea administration (min), and measurement technique; and (5) diagnostic accuracy data, including the number of true positives, false positives, false negatives, and true negatives.

Assessment of methodological quality

Two independent reviewers, Silva Luz M and de Oliveira Silva LG, conducted critical appraisal using the QUADAS-2 tool. In cases of disagreement, they consulted a 3rd researcher, Lemos FFB. The QUADAS-2 tool is applied in four phases[21]: Summarizing the review question, tailoring the tool and producing review-specific guidance, constructing a flow diagram for the primary study, and evaluating bias and applicability. This tool comprises four domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed for the risk of bias, and the first three domains are also evaluated for concerns regarding applicability. It's important to note that "risk of bias" refers to internal validity, i.e., whether there are systematic errors in conducting the study with respect to the specific domain, while "applicability concern" pertains to external validity, i.e., whether there are concerns that the population, index test, or reference standard used in the studies align with the review question. Signaling questions were also included to assist in assessing the risk of bias.

Statistical analysis and data synthesis

Eligible studies were subjected to data extraction, and we organized the data into 2 × 2 tables. In our analysis, we selected only the optimal threshold values for H. pylori positivity in cases where multiple thresholds were presented. We added 0.5 to values equal to zero to ensure computational stability and prevent potential issues[22].

To address the anticipated diversity in meta-analyses of diagnostic accuracy studies, we utilized the random-effects model to calculate sensitivity, specificity, positive and negative test likelihood ratios (LR+ and LR-), as well as the diagnostic odds ratio (DOR)[23]. We also determined the corresponding 95% confidence intervals (95%CIs). The results of the 13C- and 14C-UBT are presented separately. Subgroup analyses were conducted with a focus on urea dosing, time for measurement after urea administration (in minutes), and the assessment technique employed. To investigate the possibility of a threshold effect in the analysis, we conducted Spearman correlation analysis. A substantial threshold effect was recognized when the correlation coefficient reached or exceeded 0.6[24].

We performed a bivariate random-effects meta-analysis and generated summary receiver operating characteristic (SROC) curves to visually assess heterogeneity. Furthermore, these curves allowed us to predict accuracy by summarizing diagnostic performance as the area under the curve (AUC)[25]. We categorized accuracy levels as follows: fail (0.50-0.60), poor (0.61-0.70), fair (0.71-0.80), good (0.81-0.90), and excellent (0.91-1.00)[22].

To evaluate publication bias, we conducted a visual inspection of a funnel plot and employed Egger’s tests for statistical assessment. The creation of this plot and the assessment of the risk of data due to missing data required a minimum of ten studies.

All analyses were performed using R version 4.2.1, an environment for statistical computing in Vienna, Austria, utilizing the “meta” package (version 6.5-0), “dmetar” package (version 0.1.0), and the “mada” package (version 0.5.11).

RESULTS
Study selection

Database searches initially yielded 10902 reports, from which duplicates were removed. No additional references were discovered through alternative search methods. Subsequently, the titles and abstracts of 4621 studies underwent screening, resulting in the retrieval and selection of 79 articles for full-text examination. Ultimately, 60 studies fulfilled the inclusion criteria. The reasons for exclusion were as follows: Incorrect population (n = 8), unsuitable reference standard (n = 4), insufficient accuracy measures (n = 2), missing threshold information (n = 2), failure to compare against the reference standard (n = 1), writing in a foreign language (n = 1), and involvement of the same sample (n = 1). Figure 1 illustrates the flow of information through various phases of the systematic review.

Figure 1
Figure 1 PRISMA 2020 flow diagram. This flowchart delineates the progression of information throughout various phases of the systematic review, illustrating the quantities of records identified, included, and excluded, along with the rationales for study exclusion.
General characteristics of included studies

Among all the studies, 39 (comprising 65%) employed the 13C-UBT as their primary diagnostic test, featuring a median population size of 200 individuals (lower to upper quartile: 84.5-254). Cross-sectional study design was predominant, making up 97.5% of the total, while only one study (2.5%) adopted a randomized controlled trial approach. For the 13C-UBT, the median pre-test probability was 51.2% (lower to upper quartile: 47.8-67.6). Various reference standards were used, with the most common being "H. pylori culture (HpC) or (HE and RUT)," accounting for 22.5% of cases. Other reference standards included "HE and RUT" (17.5%), "HE" (12.5%), "HE or HpC" (12.5%), "HE or (RUT and serology)" (5%), "RUT" (5%), "HE, HpC, and RUT" (5%), and "HpC" (2.5%). Some studies also combined reference standards, such as "RUT or HE" and “(HE, HpC, RUT) at least two positives," each constituting 2.5% of the sample, as shown in Table 1.

Table 1 Characteristics of the included studies that assessed the diagnostic test accuracy of the 13C-urea breath test.
Ref.
Country
Design
Population, n
Prevalence (%)
Reference standard
Index test (model)
Optimal cut-off
Urea dosing (mg)
Time after administration (min)
Measurement tecnique
TP
FP
TN
FN
Wang et al[29], 2021ChinaCross-sectional21765.9HE13C-UBT10.4‰ DOB5030IS120146023
Alzoubi et al[33], 2020JordanCross-sectional3056.7RUT or HE13C-UBT4‰ DOB7530IS163101
Nawacki et al[34], 2018PolandCross-sectional5036.0RUT13C-UBT9.5‰ DOBNR30IS160322
Som et al[27], 2014IndiaCross-sectional8359.0RUT13C-UBT1.47‰75Multiple timesICOS490340
Bruden et al[35], 2011United StatesCross-sectional28053.2HE or (HpC and RUT)13C-UBT7 DOBNRNRNR1391611510
Peng et al [36], 2009TaiwanCross-sectional10053.0HpC or (HE and RUT)13C-UBT4.8‰ DOB10015IS537400
Jordaan et al[37], 2008South AfricaCross-sectional10358.3HE13C-UBT4.5‰ DOB75NRGCMS553405
Gatta et al[26], 2006ItalyRCT10043.0HE and RUT13C-UBT4.40‰-6.26‰ DOB2530IRMS430570
Peng et al[38], 2005TaiwanCross-sectional5036.0HpC or (HE and RUT)13C-UBT5‰ DOB10015IRMS180320
Kato et al[39], 2004JapanCross-sectional25451.1HpC or (HE and RUT)13C-UBT2.5‰ DOB10020IRMS25252426
Ohara et al[40], 2004JapanCross-sectional25451.2HpC or (HE and RUT)13C-UBT2.5‰ DOB100Multiple timesIRMS12721223
Chen et al[41], 2003TaiwanCross-sectional55466.6HpC or (HE and RUT)13C-UBT3.5‰ DOB10020IS36161798
Valdepérez et al[42], 2003SpainCross-sectional8576.8HE and RUT13C-UBTNR10030NR610192
Gatta et al[43], 2003ItalyCross-sectional20056.5HpC or (HE and RUT)13C-UBT3.11‰-6.84‰ DOB7530IRMS1130870
Wong et al[44], 2003ChinaCross-sectional20049.5HE and RUT13C-UBT2.1‰ DOB5020IRMS9901010
Ng et al[45], 2002ChinaCross-sectional21354.9HE and RUT13C-UBT4.0‰-6.5‰ DOB7530IRMS1122945
Wong et al[46], 2001ChinaCross-sectional10148.1HE and RUT13C-UBT7.0-8.0‰ DOB5020IRMS9941030
Wong et al[47], 2001ChinaCross-sectional29455.4HE, HpC, CLO (RUT), in-house RUT, PCR, UBT (at least four positive)13C-UBT5‰ DOB7530IRMS151412712
Shirin et al[48], 2001United StatesCross-sectional9747.4HE and RUT13C-UBTPositive: > 6‰ DOB (> 2 points)/negative: < 3‰ DOB (> 2 points)755MCS452491
Pilotto et al[49], 2000ItalyCross-sectional9651.0HE, HpC, and RUT13C-UBT5‰ DOB10030IRMS492450
Sheu et al[50], 2000TaiwanCross-sectional17747.5HE or HpC13C-UBT3.5 DOB5015IS811923
Wong et al[51], 2000ChinaCross-sectional20256.4HE and RUT13C-UBT4.5‰ DOB7530IRMS1082866
Hahn et al[52], 2000United StatesCross-sectional676.0HE and at least two positives of (definitive presence of H. pylori organisms in HE, UBT, Serology)13C-UBT2.4‰ DOB12530IRMS49540
Chen et al[53], 2000JapanCross-sectional16283.3HE and Serology13C-UBT2.5‰ DOB10020IRMS1351260
Peng et al[54], 2000TaiwanCross-sectional13659.6HpC or (HE and RUT)13C-UBT4.8‰ DOB10015IRMS766495
Riepl et al[55], 2000GermanyCross-sectional8435.7HE, HpC, and RUT13C-UBT6.5‰ DOB7515IS300540
D'Elios et al[56], 2000ItalyCross-sectional25645.3HE13C-UBT4‰ DOB7530IRMS11321383
van der Hulst et al[57], 1999ItalyCross-sectional54452.2HE or HpC13C-UBT7.5‰ DOB ± 0.810030LOGES2602123924
Leodolter et al[58], 1999GermanyCross-sectional32048.1HpC or (HE and RUT)13C-UBT4‰ DOB7530IRMS142216412
Mock et al[59], 1999CanadaCross-sectional9819.8HE or (RUT and Serology)13C-UBT3‰ DOB7530IRMS172752
Mock et al[59], 1999KoreaCross-sectional10768.2HE or (RUT and Serology)13C-UBT3‰ DOB7530IRMS691334
Perri et al[60], 1998BelgiumCross-sectional17273.3HE or HpC13C-UBT1.15‰ DOB7560IRMS1211455
Ohara et al[61], 1998JapanCross-sectional21377.5HpC or at least two positives of (HE, RUT, Serology)13C-UBT2.5‰ DOB10020IRMS1621473
Leodolter et al[62], 1998GermanyCross-sectional4050.0HpC or (HE and RUT)13C-UBT4‰ DOB7510IRMS200200
Andersen et al[63], 1998DenmarkCross-sectional9754.6HE or HpC13C-UBT5‰ DOB100Multiple timesIRMS464407
Ellenrieder et al[64], 1997GermanyCross-sectional13243.2(HE, HpC, RUT) at least two positives13C-UBT3.5‰ DOBNR30IS528675
Epple et al[65], 1997GermanyCross-sectional12661.1HE13C-UBT1.3‰ DOB7530IRMS747423
Labenz et al[66], 1996GermanyCross-sectional7067.1HE or HpC13C-UBT4‰ DOB7530IRMS460231
Logan et al[67], 1991EnglandCross-sectional5668.0HE13C-UBT4.5‰ DOB125Multiple timesIRMS321152
Dill et al[68], 1990ScotlandCross-sectional6949.3HpC13C-UBT3‰ c-PDR25020IRMS330351

On the other hand, the 14C-UBT accounted for 35% of the total (21 studies) with a median population size of 108.5 (lower to upper quartile: 63.5-125.5). For the 14C-UBT, the median pre-test probability was 64.9% (lower to upper quartile: 43.6-73.1). Various reference standards were employed in these studies, with "HE" being the most prevalent, accounting for 38.1% of cases. Other reference standards included "HE and RUT" (14.3%) and "HpC or HE" (9.5%). Some studies also used combinations of reference standards, such as "HE, RUT, Serology (at least two positive)" and "HpC or [HE and (RUT or Gram staining)]," each comprising 4.8% of the sample, as detailed in Table 2.

Table 2 Characteristics of the included studies that assessed the diagnostic test accuracy of the 14C-urea breath test.
Ref.
Country
Design
Population, n
Prevalence (%)
Reference standard
Index test (model)
Optimal cut-off
Urea dosing (μCi)
Time after administration (min)
Measurement tecnique
TP
TN
FP
FN
Han et al[30], 2023ChinaCross-sectional20542.4HE and RUT14C-UBT100 dpm0.7520SC8331154
Wang et al[29], 2021ChinaCross-sectional26771.9HE14C-UBT238 dpm0.7525NR158126334
Miftahussurur[69], 2021IndonesiaCross-sectional5523.6HE14C-UBT57 cpm110HA121411
Cosgun et al[70], 2016TurkeyCross-sectional12692.1HpC or HE14C-UBTNR110HA112734
Atli et al[71], 2012TurkeyCross-sectional10035.0HE14C-UBTPositive: > 50 cpm/suspicious: 25-50 cpm /negative: < 25 dpm110HA324613
Alarcón-Rivera et al[72], 2011MexicoCross-sectional8470.2HE14C-UBTPositive: > 50 ppm/indeterminate: 25-50 ppm/negative: < 25 ppm110-15HA561243
Mansour-Ghanaei et al[73], 2011IranCross-sectional12556.8HE, RUT, Serology (at least two positive)14C-UBT50 cpm115HA670544
Ozdemir et al[74], 2008TurkeyCross-sectional8966.3HE, RUT, PCR (at least two positive)14C-UBTPositive: > 50 cpm/equivocal: 25-50 cpm; negative: < 25 dpm110HA570302
Rasool et al[75], 2007PakistanCross-sectional9464.9RUT14C-UBT50 cpm110β-SC603301
Gurbuz et al[76], 2005TurkeyCross-sectional6544.6HE14C-UBTPositive: > 50 cpm/suspicious: 25-50 cpm /negative: < 25 dpm110HA268283
Gatta et al[31], 2003ItalyCross-sectional11765.0HpC or (HE and RUT)14C-UBT130-136 dpm (dpm at sample-dpm at T0)112.5LSC732393
González et al[77], 2003ChileCross-sectionalNR71.9Two or more positives14C-UBT200 dpm110LSC6114113
Oztürk et al[78], 2009TurkeyCross-sectional7565.8HE14C-UBT100 dpm110LSC485200
Gomes et al[79], 2002BrazilCross-sectional13783.9HE and RUT14C-UBT1000 cpm515LSC1141211
Desroches et al[80], 1997CanadaCross-sectional5680.4HE or HpC14C-UBT0.33‰ AS (14CO2 specific activity)520LSC440111
Allardyce et al[81], 1997New ZealandCross-sectional6334.9HE and RUT14C-UBT49 dpm130β-SC222390
Faigel et al[82], 1996United StatesCross-sectional5042.6HE or RUT14C-UBTPositive: > 200 dpm in any sample/borderline: 100-200 dpm (as the peak count)/negative: < 100 dpm (in all samples)1Multiple timesLSC181262
Goh et al[83], 1995MalaysiaCross-sectional6350.8HpC or [HE and (RUT or Gram staining)]14C-UBT1275 dpm515LSC320310
Kao et al[84], 1993ChinaCross-sectional18453.8HpC or RUT14C-UBT150‰510LSC9914710
Vivas et al[85], 1993VenezuelaCross-sectional1553.3HE14C-UBT100 dpm120β-SC8160
Novis et al[28], 1991IsraelCross-sectional6480.3HE14C-UBT4,7‰10Multiple timesLSC593122
Methodological quality assessment

Supplementary Figure 1 and Figure 2 provide a visual representation of the comprehensive methodological quality assessment of the included studies. In the patient selection domain, 22 studies (35.5%) were categorized as having a low risk of bias, 36 studies (58.1%) were associated with a high risk of bias, and 2 studies (3.2%) were considered to have an unclear risk of bias. In terms of patient selection applicability, 40 studies (64.5%) exhibited low concern, 17 studies (27.4%) showed high concern, and 3 studies (4.8%) had unclear concern.

Figure 2
Figure 2 QUADAS-2 methodological quality graph. The QUADAS-2 methodological quality graph consists of four sections, each representing one of the key domains assessed.

Within the index test selection domain, 33 studies (53.2%) were rated as having a low risk of bias, 26 studies (41.9%) were identified with a high risk, and 1 study (1.6%) had an unclear risk of bias. Concerning index test applicability, 57 studies (91.9%) displayed low concern, while 3 studies (4.8%) raised high concern.

In the reference standard domain, 47 studies (75.8%) demonstrated a low risk of bias, 12 studies (19.4%) showed a high risk of bias, and 1 study (1.6%) had an unclear risk of bias. Notably, none of the studies raised concerns about the applicability of the reference standard.

Lastly, in the flow and timing domain, 23 studies (37.1%) were associated with a low risk of bias, 23 studies (37.1%) exhibited a high risk of bias, and 7 studies (11.3%) had an unclear risk of bias.

Overall accuracy of the 13C-UBT

The 13C-UBT test was evaluated for its diagnostic accuracy in 39 studies via a comprehensive meta-analysis The results demonstrated a high sensitivity of 96.60% (95%CI: 95.64-97.56; P value < 0.01; I2 = 65.0%) and an equally impressive specificity of 96.93% (95%CI: 96.04-97.82; P value < 0.01; I2 = 58.0%) for this test (Figure 3). Additionally, the DOR was calculated at 586.47 (95%CI: 340.03-1011.51), with a positive likelihood ratio (LR+) of 22.00 (95%CI: 15.60-30.10) and a negative likelihood ratio (LR-) of 0.05 (95%CI: 0.04-0.06) as presented in Supplementary Table 1.

Figure 3
Figure 3 Forest plot for studies based on the 13C-urea breath test for Helicobacter pylori infection in dyspeptic patients. A: Forest plot for overall sensitivity; B: Forest plot for overall specificity. 95%CI: 95% confidence interval.
Subgroup analysis of the 13C-UBT - Urea dosing

Among the thirty-six studies that documented the urea dosage, a 25 mg urea dose demonstrated notably high sensitivity (98.85%; 95%CI: 95.68-100.00) and specificity (99.13%; 95%CI: 96.73-100.00), as illustrated in Supplementary Figure 2. Increasing the urea dose to 50 mg across four studies resulted in a sensitivity of 95.28% (95%CI: 88.51-100.00) and a specificity of 94.91% (95%CI: 87.67-100.00). Seventeen studies explored the use of 75 mg of urea in the 13C-UBT, revealing a sensitivity of 96.47% (95%CI: 95.14-97.79) and a specificity of 98.33% (95%CI: 97.59-99.07). In cases where 100 mg of urea was used (in 12 studies), the 13C-UBT demonstrated a sensitivity of 97.31% (95%CI: 95.92-98.70) and a specificity of 96.08% (95%CI: 94.34-97.82). Two studies employing 125 mg of urea showed a sensitivity of 93.76% (95%CI: 86.13-100.00) and a specificity of 88.66% (95%CI: 81.07-96.25). Lastly, in a single study using 250 mg of urea, the 13C-UBT exhibited a sensitivity of 97.06% (95%CI: 91.38-100.00) and a specificity of 98.59% (95%CI: 94.72-100.00).

Subgroup analysis of the 13C-UBT - Time for assessment after urea administration

Among the 36 studies that provided information on the time after urea administration, optimal sensitivity (98.87%; 95%CI: 98.14-99.60) and specificity (98.14%; 95%CI: 96.98-99.30) were achieved when the assessment was conducted 20 min after urea administration [in 7 studies (Supplementary Figure 3)]. Notably, there were variations in sensitivity and specificity for different time intervals following urea administration.

For tests conducted 5 min post-urea administration (in one study), sensitivity was 97.83% (95%CI: 93.61-100.0), and specificity was 96.08% (95%CI: 90.75-100.00). Tests performed 10 min after urea administration (based on one study) yielded a sensitivity of 97.56% (95%CI: 90.88-100.0) and a specificity of 97.56% (95%CI: 90.88-100.00).

Similarly, in the case of tests carried out at 15 min post-urea administration (as reported in five studies), sensitivity averaged at 97.61% (95%CI: 95.68-99.55), with specificity at 95.85% (95%CI: 91.33-100.00). Longer intervals, such as 30 min and 60 min, as well as tests conducted at multiple time points after urea administration, displayed some variability. For instance, tests performed 30 min after urea administration (in 19 studies) had a sensitivity of 95.15% (95%CI: 93.30-96.92) and a specificity of 96.18% (95%CI: 94.48-97.87). A single study conducting tests 60 min post-urea administration reported a sensitivity of 96.03% (95%CI: 92.62-99.44) and a specificity of 97.83% (95%CI: 93.61-100.00). In the case of four studies investigating multiple time points after urea administration, the sensitivity was 96.13% (95%CI: 92.13-100.0), and the specificity was 97.95% (95%CI: 96.08-99.81).

Subgroup analysis of the 13C-UBT - Assessment technique

In our analysis of 38 studies that included data on the 13C-UBT assessment technique, Integrated Cavity Output Spectrometry (ICOS) for measuring CO2 Isotope Ratios exhibited exceptional performance. ICOS demonstrated a sensitivity of 98.99% (95%CI: 96.20-100.00) and a specificity of 98.55% (95%CI: 94.56-100.00), as visualized in Supplementary Figure 4. In contrast, Infrared spectrometry, assessed in 8 studies, displayed a sensitivity of 94.72% (95%CI: 90.91-98.54) and a specificity of 98.55% (95%CI: 88.17-98.22).

Gas chromatography-mass spectrometry, investigated in a single study, yielded a sensitivity of 91.67% (95%CI: 84.67-98.66) and a specificity of 93.02% (95%CI: 85.41-100.00). Isotope-ratio mass spectrometry, scrutinized in 17 studies, demonstrated a sensitivity of 97.37% (95%CI: 96.45-98.28) and a specificity of 98.38% (95%CI: 84.67-98.66). Molecular correlation spectrometry, examined in a solitary study, exhibited a sensitivity of 97.83% (95%CI: 93.61-100.00) and a specificity of 96.08% (95%CI: 90.75-100.00). Similarly, Laser opto-galvanic effect spectroscopy, reported in one study, recorded a sensitivity of 91.65% (95%CI: 88.31-94.78) and a specificity of 91.92% (95%CI: 88.61-98.21).

Overall accuracy of the 14C-UBT

A total of 21 studies investigated the diagnostic accuracy of the 14C-UBT, revealing a combined sensitivity of 96.15% (95%CI: 94.47-97.82; P value < 0.01; I2 = 62.0%) and specificity of 89.84% (95%CI: 84.90-94.77; P value < 0.01; I2 = 78.0%), as depicted in Figure 4. Within this dataset, a DOR of 226.50 (95%CI: 102.57-500.15), a positive likelihood ratio (LR+) of 10.10 (95%CI: 5.74-16.90), and a negative likelihood ratio (LR-) of 0.06 (95%CI: 0.04-0.08) were observed, as summarized in Supplementary Table 1.

Figure 4
Figure 4 Forest plot for studies based on the 14C-urea breath test for Helicobacter pylori infection in dyspeptic patients by time after urea administration. A: Forest plot for overall sensitivity; B: Forest plot for overall specificity. 95%CI: 95% confidence interval.
Subgroup analysis of the 14C-UBT - Urea dosing

Twenty-one studies investigated varying urea dosages in the context of the 14C-UBT. Among these, the use of a 5 µCi marked urea dose, as examined in four studies, demonstrated exceptional sensitivity (99.21%; 95%CI: 98.20-100.00) and specificity (93.43%; 95%CI 86.45-100.00), as depicted in Supplementary Figure 5. Elevating the urea dose to 10 µCi, as explored in a single study, resulted in a sensitivity of 96.72% (95%CI: 92.15-100.00) and a specificity of 80.00% (95%CI: 56.76-100.00). Conversely, when employing 1 µCi of marked urea (in 14 studies), the 14C-UBT exhibited a sensitivity of 96.78% (95%CI: 95.46-98.09) and a specificity of 87.19% (95%CI: 59.76-95.81). Lastly, two studies using 0.75 µCi of urea reported a sensitivity of 88.94% (95%CI: 76.10-100.00) and a specificity of 91.32% (95%CI: 78.18-100.00).

Subgroup analysis of the 14C-UBT - Time for measurement after marked urea administration

When considering the time for measurement after urea administration, an analysis of all included studies consistently revealed the highest sensitivity (98.39%; 95%CI: 96.36-100.00) and specificity (98.71%; 95%CI: 96.58-100.00) when the tests were conducted 15 minutes after urea administration, as illustrated in Supplementary Figure 6.

In studies conducted shortly after urea administration (within 10 minutes, n = 9), the sensitivity was consistently high at 97.83% (95%CI: 96.34-99.33), while specificity was somewhat lower at 79.90% (95%CI: 66.15-93.65). A single study, conducted at 12.5 minutes post-administration, reported a sensitivity of 96.05% (95%CI: 91.67-100.00) and a specificity of 95.12% (95%CI: 88.53-100.00). Studies conducted between 10- and 15-minutes post-urea administration (n = 3) showed a sensitivity of 94.92% (95%CI: 89.31-100.00) and a specificity of 96.00% (95%CI: 88.32-100.00).

However, longer intervals (20, 25, and 30 min), as well as tests conducted at various time points after urea administration, exhibited more variability. For instance, studies conducted at 20 min post-administration (n = 3) showed a sensitivity of 96.52% (95%CI: 93.50-97.55) and a specificity of 97.23% (95%CI: 94.48-99.97). A single study conducted at 25 min post-urea administration reported a sensitivity of 82.29% (95%CI: 76.89-87.69) and a specificity of 84.00% (95%CI: 75.70-92.30). A study conducted at 30 minutes post-administration yielded a sensitivity of 97.78% (95%CI: 91.69-100.00) and a specificity of 95.12% (95%CI: 88.53-100.00). In the case of two studies that investigated multiple time points after urea administration, the sensitivity was 96.03% (95%CI: 91.79-100.00), and the specificity was 91.02% (95%CI: 76.07-100.00).

Subgroup analysis of the 14C-UBT - Assessment technique

In the assessment of 20 studies with available data on the assessment technique, it was observed that liquid scintillation counting yielded a higher sensitivity of 98.79% (95%CI: 97.90-99.69) while maintaining a specificity of 87.24% (95%CI: 77.69-96.79). Conversely, Solid Scintillation UBT (scintillation counting) demonstrated higher specificity, reaching 97.46% (95%CI: 94.62-100.00), with a sensitivity of 95.40% (95%CI: 91.00-99.80), as illustrated in Supplementary Figure 7.

In contrast, the Heliprobe Analyser, assessed in 7 studies, displayed a sensitivity of 95.41% (95%CI: 93.32-97.50) and a specificity of 88.10% (95%CI: 74.43-100.00). Ultimately, the use of Beta-scintillation counter for the assessment of 14C-UBT resulted in a sensitivity of 98.11% (95%CI: 95.33-100.00) and a specificity of 93.47% (95%CI: 88.11-98.82).

Threshold effect and SROC curve

Spearman’s correlation analysis for studies evaluating 13C-UBT revealed a correlation coefficient (r) of 0.48, indicating the absence of a threshold effect. Similarly, 14C-UBT studies exhibited a negligible correlation (r = -0.01), also suggesting the absence of a threshold effect. Visual inspection of the SROC curves did not reveal any significant heterogeneity. Both the 13C-UBT (AUC = 0.979; Figure 5A) and the 14C-UBT (AUC = 0.968; Figure 5B) displayed excellent diagnostic accuracy.

Figure 5
Figure 5 Summary operating characteristics curve curves for studies based on the 13C-urea breath test and the 14C-urea breath test for Helicobacter pylori infection in dyspeptic patients. The summary operating characteristics curve (SROC) curve is a graphical representation that combines sensitivity and specificity data from multiple studies or diagnostic tests. It illustrates how these measures change with different threshold settings or study parameters. The curve is accompanied by the area under the curve (AUC), which provides a quantitative assessment of the test's overall performance. A higher AUC value indicates better discriminatory ability across tested thresholds. Furthermore, the diagnostic odds ratio (DOR) is derived from the ROC curve and offers an evaluation of the test's diagnostic precision. A higher DOR signifies stronger discriminatory power, reflecting the odds of a positive test result in individuals with the condition compared to those without it. A: SROC curve for studies based on the 13C-urea breath test (UBT) for Helicobacter pylori (H. pylori) infection in dyspeptic patients; B: SROC curve for studies based on the 14C-UBT for H. pylori infection in dyspeptic patients. SROC: Summary operating characteristics curve; AUC: Area under the curve; DOR: Diagnostic odds ratio.
Publication bias

The funnel plot visualization exposed asymmetry in both the 13C-UBT (Figure 6A) and 14C-UBT (Figure 6B) models. Additionally, Egger's test confirmed the presence of publication bias in both tests. The intercept was 2.54 with a P value < 0.001 for 13C-UBT and 3.04 with a P value < 0.001 for 14C-UBT.

Figure 6
Figure 6 Funnel plots for studies based on 13C-urea breath test and 14C-urea breath test for Helicobacter pylori infection in dyspeptic patients. A: Funnel plot for studies based on 13C-urea breath test (UBT); B: Funnel plot for studies based on 14C-UBT.
DISCUSSION
Insights from 13C- and 14C-UBT performance analysis

Our analysis has revealed that the 13C-UBT outperforms the 14C-UBT in terms of diagnostic accuracy, as evidenced by the following values: DOR, Likelihood Ratios (LR+ and LR-), and AUC values. Specifically, the 13C-UBT has sensitivity and specificity values of 96.60% (95%CI: 95.64-97.56; P value < 0.01; I2 = 65.0%) and 96.93% (95%CI: 96.04-97.82; P value < 0.01; I2 = 58.0%), respectively. In contrast, the 14C-UBT has sensitivity and specificity values of 96.15% (95%CI: 94.47-97.82; P value < 0.01; I2 = 62.0%) and 89.84% (95%CI: 84.90-94.77; P value < 0.01; I2 = 78.0%). The LR+ values for the 13C-UBT and 14C-UBT are 22.00 and 10.10, respectively, indicating the likelihood of positive results in individuals with H. pylori infection. Conversely, the LR- values, suggesting a reduced likelihood of negative test results for individuals with the infection, are 0.05 for the 13C-UBT and 0.06 for the 14C-UBT.

Furthermore, the DOR values show a substantial difference between the two tests. The 13C-UBT yields a significantly higher DOR of 586.47 compared to the 14C-UBT's DOR of 226.50. These results indicate that the 13C-UBT is statistically superior at distinguishing dyspeptic individuals with and without H. pylori infection, making it the preferred diagnostic tool in this clinical context.

Finally, it is essential to emphasize that our correlation analysis, utilizing both the 13C-UBT (r = 0.48) and the 14C-UBT (r = -0.01), yielded no evidence of a threshold effect. Visual examination of the SROC curves revealed no heterogeneity, indicating consistent accuracy assessments across the studies. Additionally, both the 13C-UBT and the 14C-UBT displayed remarkably high AUC values: 0.979 for the 13C-UBT and 0.968 for the 14C-UBT, which approaching 1.00 reinforces the excellent accuracy of these tests in detecting H. pylori infection in individuals with dyspepsia. These findings strongly support the reliability of the 13C-UBT and the 14C-UBT as valuable diagnostic tools in clinical practice.

13C-UBT performance: Urea dose, assessment timing, and measurement technique selection

Our analysis highlights the critical importance of selecting the appropriate urea dose when conducting the 13C-UBT for diagnosing H. pylori infection. While the 25 mg urea dose displays the highest sensitivity (98.85%) and specificity (99.13%), concerns regarding the generalizability of these results arise due to the fact that these findings are primarily based on a single study[26]. In contrast, the use of 75 mg and 100 mg doses is supported by a larger body of evidence, maintaining excellent diagnostic accuracy with sensitivity and specificity exceeding 96%. Conversely, higher doses, such as 125 mg or 250 mg, exhibit a modest reduction in accuracy, particularly in terms of specificity. These findings strongly advocate for the consideration of 75 mg and 100 mg doses when aiming to optimize both sensitivity and specificity.

A crucial factor affecting the performance of the 13C-UBT is the timing of the assessment following urea administration. Our observations reveal that the optimal sensitivity and specificity, both exceeding 98%, are achieved at the 20-minute mark post-urea administration. Tests conducted at shorter intervals, such as 5 min and 10 min, also demonstrate high sensitivity and specificity, albeit slightly lower than the 20-min assessment. Conversely, assessments at 15 min maintain excellent accuracy, with sensitivity close to 98% and specificity around 95%. However, assessments at longer intervals, such as 30 min, 60 min, and multiple time points, exhibit some variability, with sensitivity and specificity values slightly lower than the 20-min assessment. These results highlight the 20-min assessment as the most reliable time point, offering a balance between high sensitivity and specificity. Nevertheless, the test remains accurate when conducted at shorter intervals.

The choice of assessment technique is also crucial for test accuracy. ICOS is the most accurate technique, with a sensitivity of 98.99% and a specificity of 98.55%. However, it is important to note that ICOS was evaluated in a single study[27], potentially limiting the generalizability of these results. To address this limitation, Isotope-ratio mass spectrometry is a more advisable option. In contrast, Infrared spectrometry, gas chromatography-mass spectrometry, isotope-ratio mass spectrometry, molecular correlation spectrometry, and Laser opto-galvanic effect spectroscopy yield varying levels of sensitivity and specificity. These findings underscore the significance of selecting the right assessment technique. While ICOS may be preferred when available due to its exceptional accuracy, other factors such as cost, availability, and local expertise should also be considered when making this choice.

14C-UBT performance: Urea dose, assessment timing, and measurement technique selection

Our research indicates that the urea dosage utilized in the 14C-UBT can also impact test accuracy. Specifically, a urea dose of 5 µCi was examined in four studies and was found to possess exceptional sensitivity (99.21%) and specificity (93.43%). These findings underscore the potential benefits of employing a 5 µCi dose for the 14C-UBT, as it offers a high level of accuracy in detecting H. pylori infection. However, increasing the urea dose to 10 µCi, as investigated in a single study[28], resulted in a slightly lower sensitivity (96.72%) and a specificity of 80.00%. This suggests that while higher urea dosages may still provide reliable results, they may be associated with a decrease in specificity, which could lead to more false-positive results.

On the other hand, the use of 1 µCi of marked urea, which was the most commonly used dosage in 14 studies, resulted in a sensitivity of 96.78% and a specificity of 87.19%. This indicates that a 1 µCi dose remains a viable option for the 14C-UBT, offering a good balance between sensitivity and specificity. Two recent studies using 0.75 µCi of urea reported a sensitivity of 88.94% and a specificity of 91.32%, suggesting that even lower urea doses can provide reasonable diagnostic accuracy[29,30].

Regarding the time for measurement, tests conducted 15 min after urea administration consistently exhibited the highest sensitivity (98.39%) and specificity (98.71%). This indicates that the 15-min time point is optimal for maximizing test accuracy. Tests conducted within 10 min post-administration maintained high sensitivity (97.83%) but had a somewhat lower specificity (79.90%). A single study conducted at 12.5 min post-administration reported favorable sensitivity (96.05%) and specificity (95.12%)[31]. In contrast, longer intervals (20, 25, and 30 min) showed more variability, with varying levels of sensitivity and specificity. This suggests that measurements taken beyond 15 min may not be as reliable for H. pylori detection. Clinicians should carefully consider the timing of the 14C-UBT to ensure accurate results, with a preference for the 15-min mark when feasible.

Lastly, our analysis of assessment techniques uncovered differences in sensitivity and specificity. Liquid scintillation counting demonstrated the highest sensitivity (98.79%) but had a specificity of 87.24%. In contrast, Solid Scintillation UBT (scintillation counting) showed higher specificity (97.46%) at the expense of sensitivity (95.40%). The Heliprobe Analyser and Beta-scintillation counter also demonstrated moderate sensitivity and specificity. When choosing the assessment technique, the trade-off between sensitivity and specificity should be considered in relation to the clinical context. For instance, if high sensitivity is paramount to avoid missing positive cases, liquid scintillation counting may be the preferred method. Conversely, if high specificity is crucial to minimize false positives, solid scintillation counting could be a better choice.

Strengths and limitations

This meta-analysis adhered to established guidelines and rigorous methodological principles, enhancing the validity and reliability of our findings. We used a bivariate random-effects model to calculate sensitivity, specificity, likelihood ratios, and the DOR, alongside generating SROC curves for a comprehensive statistical analysis of the included studies. Subgroup analyses based on urea dosing, measurement timing, and assessment technique were conducted to explore potential sources of variation, while Spearman correlation analysis was used to assess the threshold effect's impact on diagnostic accuracy. Additionally, we assessed publication bias through visual inspections of funnel plots and Egger's tests.

However, it's important to acknowledge inherent limitations in our analysis. These include potential language bias, reliance on available data, and challenges associated with the inherent heterogeneity in diagnostic accuracy studies. Although we did not impose language restrictions in our search, the inclusion of studies conducted in English, Spanish, or Portuguese may introduce language bias[32]. The exclusion of studies due to unavailability of full-text articles or articles not in these specified languages could potentially lead to the omission of essential data.

Furthermore, the quality of our meta-analysis is closely tied to the quality of the primary studies we included. Biases within these primary studies can affect our analysis outcomes. In particular, we have concerns regarding the inclusion of patients, as there was no reported consecutive patient inclusion in some studies, and the index test was not always performed using a pre-specified threshold. Moreover, the diversity in diagnostic accuracy studies can present challenges when consolidating results, and despite subgroup analyses, residual heterogeneity may impact the broad applicability of our findings. Encouragingly, the visual examination of the SROC curves indicates consistent accuracy assessments across the included studies. Nevertheless, it is imperative to underscore that the reliability of our meta-analysis hinges on the data provided in these included studies. The absence or inconsistency of critical data points can significantly affect the precision of our analysis. Researchers and clinicians should consider these strengths and limitations when applying our findings in their practice.

CONCLUSION

In summary, our study offers crucial insights for selecting optimal diagnostic methods to detect H. pylori infection in clinical settings. We found that the 13C-UBT outperforms the 14C-UBT in terms of diagnostic accuracy, making it the preferred diagnostic approach. Furthermore, our findings highlight the significance of precise considerations when choosing urea dosage, assessment timing, and measurement techniques for both the 13C-UBT and 14C-UBT, thus enhancing diagnostic precision. These insights provide practical guidance to healthcare practitioners when choosing the most suitable diagnostic method for H. pylori infection, tailored to their specific clinical context. Factors like diagnostic accuracy, cost, and availability should be carefully weighed in this decision-making process. Our findings also have the potential to contribute significantly to the standardization of testing procedures, ensuring consistent and reliable results, especially for patients with dyspepsia or suspected H. pylori infection. Nevertheless, it's essential for researchers and clinicians to consider the strengths and limitations when applying our findings in their practice.

ARTICLE HIGHLIGHTS
Research background

The urea breath test (UBT) has become a widely accepted non-invasive method for detecting Helicobacter pylori (H. pylori). While numerous studies have confirmed its high accuracy, its reliability is often hindered by inherent limitations.

Research motivation

In a previous investigation, the diagnostic accuracy of the UBT, which encompasses both 13C-UBT and 14C-UBT, was evaluated in adult patients with dyspepsia to determine the presence of H. pylori infection. Although the test demonstrated a high degree of precision, its reliability was compromised by significant and unexplained heterogeneity, which persisted even after conducting subgroup analyses. This trend continued in subsequent studies, with similar challenges encountered in determining pooled estimates of diagnostic accuracy for 14C-UBT. Furthermore, a subsequent systematic review revealed that the variability in thresholds and reference standards across studies limited the available data for pooling accuracy measures at specific UBT thresholds. These findings underscore the need for a rigorous statistical synthesis to clarify and reconcile the diagnostic accuracy of the UBT for the diagnosis of H. pylori infection, addressing challenges identified in prior research.

Research objectives

To evaluate and contrast the diagnostic accuracy of 13C-UBT and 14C-UBT for H. pylori infection in adult patients with dyspepsia.

Research methods

We conducted independent searches of PubMed/MEDLINE, EMBASE, and Cochrane Central databases until April 2022, focusing on diagnostic accuracy studies that evaluated at least one of the index tests (13C-UBT or 14C-UBT) against a reference standard. We utilized the QUADAS-2 tool to assess the methodological quality of the studies, and we calculated sensitivity, specificity, positive and negative test likelihood ratios (LR+ and LR-), as well as the diagnostic odds ratio (DOR) and their 95% confidence intervals using the bivariate random-effects model. We conducted subgroup analyses based on urea dosing, time after urea administration, and assessment technique. To investigate a possible threshold effect, we conducted Spearman correlation analysis, and we generated summary receiver operating characteristic (SROC) curves to assess heterogeneity. Lastly, we visually inspected a funnel plot and used Egger’s test to evaluate publication bias.

Research results

A screening of 4621 studies led to the selection of 60 articles for inclusion in a diagnostic test accuracy meta-analysis after full-text reading. Our analysis highlights the superior diagnostic accuracy of 13C-UBT compared to 14C-UBT, as evidenced by higher sensitivity (96.60% vs 96.15%), specificity (96.93% vs 89.84%), likelihood ratios (LR+ 22.00 vs 10.10; LR- 0.05 vs 0.06), and AUC values (0.979 vs 0.968). Particularly noteworthy is the significantly higher DOR of 13C-UBT (586.47) compared to 14C-UBT (DOR 226.50), establishing 13C-UBT as the preferred diagnostic tool for individuals with dyspepsia and H. pylori infection. Correlation analysis indicated no threshold effect for both 13C-UBT (r = 0.48) and 14C-UBT (r = -0.01), and the SROC curves consistently demonstrated accurate performance for both tests. The high AUC values (13C-UBT: 0.979; 14C-UBT: 0.968), nearing 1.00, further affirm the excellent accuracy of both UBT variants, solidifying their reliability as diagnostic tools in clinical practice.

Research conclusions

Our study establishes 13C-UBT as the superior diagnostic approach over 14C-UBT. Furthermore, our findings underscore the critical importance of meticulously considering factors such as urea dosage, assessment timing, and measurement techniques for both tests to optimize diagnostic accuracy. However, it is paramount for researchers and clinicians to thoroughly evaluate the strengths and limitations of our conclusions before integrating them into clinical practice.

Research perspectives

Future research should focus on improving the comprehension, practicality, and dependability of UBTs for H. pylori infection. This endeavor involves refining techniques, examining sources of variability, exploring threshold effects, conducting longitudinal and comparative investigations, addressing biases, and assessing cost-effectiveness.

Footnotes

Provenance and peer review: Invited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Gastroenterology and hepatology

Country/Territory of origin: Brazil

Peer-review report’s scientific quality classification

Grade A (Excellent): 0

Grade B (Very good): B

Grade C (Good): 0

Grade D (Fair): 0

Grade E (Poor): 0

P-Reviewer: Huang YQ, China S-Editor: Lin C L-Editor: A P-Editor: Zhao YQ

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