Skip to main content
Top
Published in: BMC Infectious Diseases 1/2022

Open Access 01-12-2022 | Septicemia | Research article

Performance of BioFire Blood Culture Identification 2 Panel (BCID2) for the detection of bloodstream pathogens and their associated resistance markers: a systematic review and meta-analysis of diagnostic test accuracy studies

Authors: Anna Maria Peri, Weiping Ling, Luis Furuya-Kanamori, Patrick N. A. Harris, David L. Paterson

Published in: BMC Infectious Diseases | Issue 1/2022

Login to get access

Abstract

Background

Early identification of bloodstream pathogens and their associated antimicrobial resistance may shorten time to optimal therapy in patients with sepsis. The BioFire Blood Culture Identification 2 Panel (BCID2) is a novel multiplex PCR detecting 43 targets directly from positive blood cultures, reducing turnaround times.

Methods

We have performed a systematic review and meta-analysis of diagnostic test accuracy studies to assess the BCID2 performance for pathogen identification and resistance markers detection compared to gold standard culture-based methods (including phenotypic and/or genotypic characterization).

Results

Nine studies were identified reporting data to build 2 × 2 tables for each BCID2 target, including 2005 blood cultures. The pooled specificity of the assay was excellent (> 97%) across most subgroups of targets investigated, with a slightly broader confidence interval for S. epidermidis (98.1%, 95% CI 93.1 to 99.5). Pooled sensitivity was also high for the major determinants of bloodstream infection, including Enterobacterales (98.2%, 95% CI 96.3 to 99.1), S. aureus (96.0%, 95% CI 90.4 to 98.4), Streptococcus spp. (96.7%, 95% CI 92.8 to 98.5), P. aeruginosa (92.7%, 95% CI 83.1 to 97.0), E. faecalis (92.3%, 95% CI 83.5 to 96.6), as well as blaCTX-M (94.9, 95% CI 85.7 to 98.3), carbapenemases (94.9%, 95% CI 83.4 to 98.6) and mecA/C & MREJ (93.9%, 95% CI 83.0 to 98.0). Sensitivity for less common targets was slightly lower, possibly due to their under-representation in the included studies.

Conclusions

BCID2 showed good performance for detecting major determinants of bloodstream infection and could support early antimicrobial treatment, especially for ESBL or carbapenemase-producing Gram-negative bacilli and methicillin-resistant S. aureus.
Appendix
Available only for authorised users
Literature
1.
go back to reference Ferrer R, Martin-Loeches I, Phillips G, Osborn TM, Townsend S, Dellinger RP, Artigas A, Schorr C, Levy MM. Empiric antibiotic treatment reduces mortality in severe sepsis and septic shock from the first hour: results from a guideline-based performance improvement program. Crit Care Med. 2014;42(8):1749–55.CrossRef Ferrer R, Martin-Loeches I, Phillips G, Osborn TM, Townsend S, Dellinger RP, Artigas A, Schorr C, Levy MM. Empiric antibiotic treatment reduces mortality in severe sepsis and septic shock from the first hour: results from a guideline-based performance improvement program. Crit Care Med. 2014;42(8):1749–55.CrossRef
2.
go back to reference Lamy B, Sundqvist M, Idelevich EA, Escmid Study Group for Bloodstream Infections E, Sepsis. Bloodstream infections—standard and progress in pathogen diagnostics. Clin Microbiol Infect. 2020;26(2):142–50.CrossRef Lamy B, Sundqvist M, Idelevich EA, Escmid Study Group for Bloodstream Infections E, Sepsis. Bloodstream infections—standard and progress in pathogen diagnostics. Clin Microbiol Infect. 2020;26(2):142–50.CrossRef
3.
go back to reference Opota O, Croxatto A, Prod’hom G, Greub G. Blood culture-based diagnosis of bacteraemia: state of the art. Clin Microbiol Infect. 2015;21(4):313–22.CrossRef Opota O, Croxatto A, Prod’hom G, Greub G. Blood culture-based diagnosis of bacteraemia: state of the art. Clin Microbiol Infect. 2015;21(4):313–22.CrossRef
4.
go back to reference Peker N, Couto N, Sinha B, Rossen JW. Diagnosis of bloodstream infections from positive blood cultures and directly from blood samples: recent developments in molecular approaches. Clin Microbiol Infect. 2018;24(9):944–55.CrossRef Peker N, Couto N, Sinha B, Rossen JW. Diagnosis of bloodstream infections from positive blood cultures and directly from blood samples: recent developments in molecular approaches. Clin Microbiol Infect. 2018;24(9):944–55.CrossRef
5.
go back to reference Banerjee R, Teng CB, Cunningham SA, Ihde SM, Steckelberg JM, Moriarty JP, Shah ND, Mandrekar JN, Patel R. Randomized trial of rapid multiplex polymerase chain reaction-based blood culture identification and susceptibility testing. Clin Infect Dis. 2015;61(7):1071–80.CrossRef Banerjee R, Teng CB, Cunningham SA, Ihde SM, Steckelberg JM, Moriarty JP, Shah ND, Mandrekar JN, Patel R. Randomized trial of rapid multiplex polymerase chain reaction-based blood culture identification and susceptibility testing. Clin Infect Dis. 2015;61(7):1071–80.CrossRef
6.
go back to reference Buss BA, Baures TJ, Yoo M, Hanson KE, Alexander DP, Benefield RJ, Spivak ES. Impact of a multiplex PCR assay for bloodstream infections with and without antimicrobial stewardship intervention at a cancer hospital. Open Forum Infect Dis. 2018;5(10):ofy258.CrossRef Buss BA, Baures TJ, Yoo M, Hanson KE, Alexander DP, Benefield RJ, Spivak ES. Impact of a multiplex PCR assay for bloodstream infections with and without antimicrobial stewardship intervention at a cancer hospital. Open Forum Infect Dis. 2018;5(10):ofy258.CrossRef
7.
go back to reference Ny P, Ozaki A, Pallares J, Nieberg P, Wong-Beringer A. Antimicrobial stewardship opportunities in patients with bacteremia not identified by BioFire FilmArray. J Clin Microbiol 2019; 57(5). Ny P, Ozaki A, Pallares J, Nieberg P, Wong-Beringer A. Antimicrobial stewardship opportunities in patients with bacteremia not identified by BioFire FilmArray. J Clin Microbiol 2019; 57(5).
9.
go back to reference Berinson B, Both A, Berneking L, Christner M, Lutgehetmann M, Aepfelbacher M, Rohde H. Usefulness of BioFire FilmArray BCID2 for Blood Culture Processing in Clinical Practice. J Clin Microbiol. 2021;59(8): e0054321.CrossRef Berinson B, Both A, Berneking L, Christner M, Lutgehetmann M, Aepfelbacher M, Rohde H. Usefulness of BioFire FilmArray BCID2 for Blood Culture Processing in Clinical Practice. J Clin Microbiol. 2021;59(8): e0054321.CrossRef
10.
go back to reference Graff KE, Palmer C, Anarestani T, Velasquez D, Hamilton S, Pretty K, Parker S, Dominguez SR. Clinical impact of the expanded BioFire blood culture identification 2 Panel in a U.S. Children’s Hospital. Microbiol Spectr. 2021;9(1):e0042921.CrossRef Graff KE, Palmer C, Anarestani T, Velasquez D, Hamilton S, Pretty K, Parker S, Dominguez SR. Clinical impact of the expanded BioFire blood culture identification 2 Panel in a U.S. Children’s Hospital. Microbiol Spectr. 2021;9(1):e0042921.CrossRef
11.
go back to reference Holma T, Torvikoski J, Friberg N, Nevalainen A, Tarkka E, Antikainen J, Martelin JJ. Rapid molecular detection of pathogenic microorganisms and antimicrobial resistance markers in blood cultures: evaluation and utility of the next-generation FilmArray Blood Culture Identification 2 panel. Eur J Clin Microbiol Infect Dis 2021. Holma T, Torvikoski J, Friberg N, Nevalainen A, Tarkka E, Antikainen J, Martelin JJ. Rapid molecular detection of pathogenic microorganisms and antimicrobial resistance markers in blood cultures: evaluation and utility of the next-generation FilmArray Blood Culture Identification 2 panel. Eur J Clin Microbiol Infect Dis 2021.
12.
go back to reference Sparks R, Balgahom R, Janto C, Polkinghorne A, Branley J. Evaluation of the BioFire Blood Culture Identification 2 panel and impact on patient management and antimicrobial stewardship. Pathology 2021. Sparks R, Balgahom R, Janto C, Polkinghorne A, Branley J. Evaluation of the BioFire Blood Culture Identification 2 panel and impact on patient management and antimicrobial stewardship. Pathology 2021.
13.
go back to reference Cortazzo V, D'Inzeo T, Giordano L, Menchinelli G, Liotti FM, Fiori B, De Maio F, Luzzaro F, Sanguinetti M, Posteraro B et al. Comparing BioFire FilmArray BCID2 and BCID panels for direct detection of bacterial pathogens and antimicrobial resistance genes from positive blood cultures. J Clin Microbiol. 2021; 59(4). Cortazzo V, D'Inzeo T, Giordano L, Menchinelli G, Liotti FM, Fiori B, De Maio F, Luzzaro F, Sanguinetti M, Posteraro B et al. Comparing BioFire FilmArray BCID2 and BCID panels for direct detection of bacterial pathogens and antimicrobial resistance genes from positive blood cultures. J Clin Microbiol. 2021; 59(4).
14.
go back to reference Sze DTT, Lau CCY, Chan TM, Ma ESK, Tang BSF. Comparison of novel rapid diagnostic of blood culture identification and antimicrobial susceptibility testing by Accelerate Pheno system and BioFire FilmArray Blood Culture Identification and BioFire FilmArray Blood Culture Identification 2 panels. BMC Microbiol. 2021;21(1):350.CrossRef Sze DTT, Lau CCY, Chan TM, Ma ESK, Tang BSF. Comparison of novel rapid diagnostic of blood culture identification and antimicrobial susceptibility testing by Accelerate Pheno system and BioFire FilmArray Blood Culture Identification and BioFire FilmArray Blood Culture Identification 2 panels. BMC Microbiol. 2021;21(1):350.CrossRef
15.
go back to reference McInnes MDF, Moher D, Thombs BD, McGrath TA, Bossuyt PM, Clifford T, Cohen JF, Deeks JJ, Gatsonis C, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA. 2018;319(4):388–96.CrossRef McInnes MDF, Moher D, Thombs BD, McGrath TA, Bossuyt PM, Clifford T, Cohen JF, Deeks JJ, Gatsonis C, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA. 2018;319(4):388–96.CrossRef
18.
go back to reference Team TE. EndNote. In., EndNote X9 edn. Philadelphia, PA: Clarivate; 2013. Team TE. EndNote. In., EndNote X9 edn. Philadelphia, PA: Clarivate; 2013.
19.
go back to reference Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):210.CrossRef Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):210.CrossRef
20.
go back to reference Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, Leeflang MM, Sterne JA, Bossuyt PM, Group Q-. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36.CrossRef Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, Leeflang MM, Sterne JA, Bossuyt PM, Group Q-. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36.CrossRef
21.
go back to reference Shah S, Davar N, Thakkar P, Sawant C, Jadhav L. Clinical utility of the FilmArray blood culture identification 2 panel in identification of microorganisms and resistance markers from positive blood culture bottles. Indian J Microbiol Res. 2022;9(1):28–33.CrossRef Shah S, Davar N, Thakkar P, Sawant C, Jadhav L. Clinical utility of the FilmArray blood culture identification 2 panel in identification of microorganisms and resistance markers from positive blood culture bottles. Indian J Microbiol Res. 2022;9(1):28–33.CrossRef
22.
go back to reference Furuya-Kanamori L, Kostoulas P, Doi SAR. A new method for synthesizing test accuracy data outperformed the bivariate method. J Clin Epidemiol. 2021;132:51–8.CrossRef Furuya-Kanamori L, Kostoulas P, Doi SAR. A new method for synthesizing test accuracy data outperformed the bivariate method. J Clin Epidemiol. 2021;132:51–8.CrossRef
23.
go back to reference Doi SA, Barendregt JJ, Khan S, Thalib L, Williams GM. Advances in the meta-analysis of heterogeneous clinical trials I: the inverse variance heterogeneity model. Contemp Clin Trials. 2015;45(Pt A):130–8.CrossRef Doi SA, Barendregt JJ, Khan S, Thalib L, Williams GM. Advances in the meta-analysis of heterogeneous clinical trials I: the inverse variance heterogeneity model. Contemp Clin Trials. 2015;45(Pt A):130–8.CrossRef
24.
go back to reference Doi SA, Barendregt JJ, Khan S, Thalib L, Williams GM. Advances in the meta-analysis of heterogeneous clinical trials II: The quality effects model. Contemp Clin Trials. 2015;45(Pt A):123–9.CrossRef Doi SA, Barendregt JJ, Khan S, Thalib L, Williams GM. Advances in the meta-analysis of heterogeneous clinical trials II: The quality effects model. Contemp Clin Trials. 2015;45(Pt A):123–9.CrossRef
25.
go back to reference Furuya-Kanamori L, Barendregt JJ, Doi SAR. A new improved graphical and quantitative method for detecting bias in meta-analysis. Int J Evid Based Healthc. 2018;16(4):195–203.CrossRef Furuya-Kanamori L, Barendregt JJ, Doi SAR. A new improved graphical and quantitative method for detecting bias in meta-analysis. Int J Evid Based Healthc. 2018;16(4):195–203.CrossRef
26.
go back to reference Deeks JJ, Macaskill P, Irwig L. The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol. 2005;58(9):882–93.CrossRef Deeks JJ, Macaskill P, Irwig L. The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol. 2005;58(9):882–93.CrossRef
27.
go back to reference Furuya-Kanamori L, Doi SAR, 2020. DIAGMA: Stata module for the split component synthesis method of diagnostic meta-analysis. Statistical Software Components S458815, Boston College Department of Economics, revised 16 Oct 2021. Furuya-Kanamori L, Doi SAR, 2020. DIAGMA: Stata module for the split component synthesis method of diagnostic meta-analysis. Statistical Software Components S458815, Boston College Department of Economics, revised 16 Oct 2021.
28.
go back to reference Furuya-Kanamori L, Doi SAR, 2020. LFK: Stata module to compute LFK index and Doi plot for detection of publication bias in meta-analysis. Statistical Software Components S458762, Boston College Department of Economics, revised 16 Oct 2021. Furuya-Kanamori L, Doi SAR, 2020. LFK: Stata module to compute LFK index and Doi plot for detection of publication bias in meta-analysis. Statistical Software Components S458762, Boston College Department of Economics, revised 16 Oct 2021.
29.
go back to reference Peri AM, Bauer MJ, Bergh H, Butkiewicz D, Paterson DL, Harris PN. Performance of the BioFire Blood culture identification 2 panel for the diagnosis of bloodstream infections on blood cultures from the intensive care unit and emergency department. SSRN Electronic J 2022. Peri AM, Bauer MJ, Bergh H, Butkiewicz D, Paterson DL, Harris PN. Performance of the BioFire Blood culture identification 2 panel for the diagnosis of bloodstream infections on blood cultures from the intensive care unit and emergency department. SSRN Electronic J 2022.
30.
go back to reference Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372: n71.CrossRef Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372: n71.CrossRef
31.
go back to reference Camelena F. Performances et impact thérapeutique du BioFire Blood Culture Identification 2 (BCID2) Panel au cours du sepsis. In: 23es Journées Nationales d'Infectiologie. Monpellier, France; 2021. Camelena F. Performances et impact thérapeutique du BioFire Blood Culture Identification 2 (BCID2) Panel au cours du sepsis. In: 23es Journées Nationales d'Infectiologie. Monpellier, France; 2021.
32.
go back to reference Lu Y, Hatch J, Holmberg K, Hurlock A, Drobysheva D, Spaulding U, Vourli S, Pournaras S, Everhart K, Leber A et al. P651. Multi-center Evaluation of the BioFire® FilmArray® Blood Culture Identification 2 Panel for the Detection of Microorganisms and Resistance Markers in Positive Blood Cultures. In: IDWeek. Washington DC, U.S.; 2019. Lu Y, Hatch J, Holmberg K, Hurlock A, Drobysheva D, Spaulding U, Vourli S, Pournaras S, Everhart K, Leber A et al. P651. Multi-center Evaluation of the BioFire® FilmArray® Blood Culture Identification 2 Panel for the Detection of Microorganisms and Resistance Markers in Positive Blood Cultures. In: IDWeek. Washington DC, U.S.; 2019.
34.
go back to reference Diekema DJ, Hsueh PR, Mendes RE, Pfaller MA, Rolston KV, Sader HS, Jones RN. The microbiology of bloodstream infection: 20-year trends from the SENTRY antimicrobial surveillance program. Antimicrob Agents Chemother. 2019; 63(7). Diekema DJ, Hsueh PR, Mendes RE, Pfaller MA, Rolston KV, Sader HS, Jones RN. The microbiology of bloodstream infection: 20-year trends from the SENTRY antimicrobial surveillance program. Antimicrob Agents Chemother. 2019; 63(7).
35.
go back to reference Douglas NM, Hennessy JN, Currie BJ, Baird RW. Trends in bacteremia over 2 decades in the top end of the northern territory of Australia. Open Forum Infect Dis. 2020;7(11):ofaa472.CrossRef Douglas NM, Hennessy JN, Currie BJ, Baird RW. Trends in bacteremia over 2 decades in the top end of the northern territory of Australia. Open Forum Infect Dis. 2020;7(11):ofaa472.CrossRef
36.
go back to reference Sherwin R, Winters ME, Vilke GM, Wardi G. Does early and appropriate antibiotic administration improve mortality in emergency department patients with severe sepsis or septic shock? J Emerg Med. 2017;53(4):588–95.CrossRef Sherwin R, Winters ME, Vilke GM, Wardi G. Does early and appropriate antibiotic administration improve mortality in emergency department patients with severe sepsis or septic shock? J Emerg Med. 2017;53(4):588–95.CrossRef
37.
go back to reference Timbrook TT, Morton JB, McConeghy KW, Caffrey AR, Mylonakis E, LaPlante KL. The effect of molecular rapid diagnostic testing on clinical outcomes in bloodstream infections: a systematic review and meta-analysis. Clin Infect Dis. 2017;64(1):15–23.CrossRef Timbrook TT, Morton JB, McConeghy KW, Caffrey AR, Mylonakis E, LaPlante KL. The effect of molecular rapid diagnostic testing on clinical outcomes in bloodstream infections: a systematic review and meta-analysis. Clin Infect Dis. 2017;64(1):15–23.CrossRef
38.
go back to reference EUCAST. To clinical colleagues: On recent changes in clinical microbiology susceptibility reports - new interpretation of susceptibility categories S, I and R. In.; 2021. EUCAST. To clinical colleagues: On recent changes in clinical microbiology susceptibility reports - new interpretation of susceptibility categories S, I and R. In.; 2021.
39.
go back to reference Hughes D, Andersson DI. Environmental and genetic modulation of the phenotypic expression of antibiotic resistance. FEMS Microbiol Rev. 2017;41(3):374–91.CrossRef Hughes D, Andersson DI. Environmental and genetic modulation of the phenotypic expression of antibiotic resistance. FEMS Microbiol Rev. 2017;41(3):374–91.CrossRef
40.
go back to reference Williams MC, Dominguez SR, Prinzi A, Lee K, Parker SK. Reliability of mecA in predicting phenotypic susceptibilities of coagulase-negative staphylococci and Staphylococcus aureus. Open Forum Infect Dis. 2020;7(12):ofaa553.CrossRef Williams MC, Dominguez SR, Prinzi A, Lee K, Parker SK. Reliability of mecA in predicting phenotypic susceptibilities of coagulase-negative staphylococci and Staphylococcus aureus. Open Forum Infect Dis. 2020;7(12):ofaa553.CrossRef
41.
go back to reference Stewart AG, Price EP, Schabacker K, Birikmen M, Harris PNA, Choong K, Subedi S, Sarovich DS. Molecular epidemiology of third-generation-cephalosporin-resistant enterobacteriaceae in Southeast Queensland, Australia. Antimicrob Agents Chemother. 2021;65(6):e00130-e221.CrossRef Stewart AG, Price EP, Schabacker K, Birikmen M, Harris PNA, Choong K, Subedi S, Sarovich DS. Molecular epidemiology of third-generation-cephalosporin-resistant enterobacteriaceae in Southeast Queensland, Australia. Antimicrob Agents Chemother. 2021;65(6):e00130-e221.CrossRef
Metadata
Title
Performance of BioFire Blood Culture Identification 2 Panel (BCID2) for the detection of bloodstream pathogens and their associated resistance markers: a systematic review and meta-analysis of diagnostic test accuracy studies
Authors
Anna Maria Peri
Weiping Ling
Luis Furuya-Kanamori
Patrick N. A. Harris
David L. Paterson
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2022
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-022-07772-x

Other articles of this Issue 1/2022

BMC Infectious Diseases 1/2022 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.