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Molecular diagnostics in the future July 14 - Prof. Bert Niesters

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Molecular diagnostics in the future July 14 - Prof. Bert Niesters

  1. 1. Molecular diagnostics in the future: How will it look like and what are the challenges! Bert Niesters Department of Medical Microbiology Division of Clinical of Virology University Medical Center Groningen The Netherlands
  2. 2. Point of Impact: From Classical PCR to Point-of-Care Systems. Division of Clinical Virology
  3. 3. Division of Clinical Virology Disclosures • Executive board member of QCMD. • Commercial developments on FlowG MiddleWare solutions. • Assessor for the Dutch Council of Accreditation. • Editor-in-Chief of Journal of Clinical Virology. • Advisory board Stratec on AURORA VigiLant.
  4. 4. Division of Clinical Virology What I will present • Introduction • How we are interlinked, networks, cross-border • Facts on molecular diagnostics • The diagnostic triangle • The €hr concept • The Extended Diagnostic Triangle • The AID-Stewardship Portfolio
  5. 5. Division of Clinical Virology
  6. 6. Division of Clinical Virology
  7. 7. Division of Clinical Virology What is the UMCG? The UMCG is a tertiary referral hospital providing care for both adults and children and has a large Solid Organ Transplant program. The large proportion of immune-compromised patients require isolation from patients with respiratory illness.
  8. 8. Division of Clinical Virology Introduction • The Influenza season of 2012-2013 was characterized by co-circulation of two Influenza A types. – H1N1 2009pdm09 – H3N2 • Due to the circulation of two Influenza viruses Influenza A-positive patients had to be admitted into single rooms. • A large number of different respiratory viruses were circulating during a long (5 months) period of time, with RSV and influenza viruses being present simultaneously.
  9. 9. Number of viruses identified Division of Clinical Virology December 2012-April 2013 300 200 100 0 December January February March April Influenza A Influenza B hMPV RSV Adeno Boca Corona Rhino Parainfl A total of 1259 respiratory samples were tested
  10. 10. Typing results of Influenza A positives Division of Clinical Virology 0 20 40 60 December January February March April H3N2 H1N1pdm09 NT 166 patients had Influenza A • 59 had H1N1pdm09 • 104 had H3N2 • 3 NT
  11. 11. Isolation regiment of patients admitted Division of Clinical Virology with a respiratory illness ? Neg Infl A Other virus No isolation Geno-type? H1N1 Care in cohort H3N2 isolation H1N1 H1N1 H1N1 H3N2 H3N2 H3N2 Care in cohort
  12. 12. The Challenges • In our setting, the validation of BINAX Now influenza test resulted in a negative outcome. Too insensitive. Did not pass the validation process. • Request for data on more viruses that circulated simultaneously. • Samples from patients received at the end of the day, on Friday Division of Clinical Virology (after 16.00 hr) and in the weekend, had a long TAT. • Lack of isolation rooms.
  13. 13. Patient Referral Network in the Netherlands Donker et al. Math Biol 2012 Prof Grundmann, UMCG University Hospitals Regional Centers Local Hospital
  14. 14. Connectivity between regional centers Labmicta, Enschede Izore, Leeuwarden UMCG Isala, Zwolle LvI Apeldoorn UMCG Regional Center Satellite Dr. Donker, Prof. Grundmann, UMCG (does not cross borders)
  15. 15. Intra-Hospital travel of potentially exposed patients KPNEU, esbl+ outbreak, UMCG 09-2012 Day-by-day patient transfer Start: 29.5.2012 <10 <50 >50 Mariano Ciccolini, MMB, UMCG
  16. 16. How patients are moved within UMCG Division of Clinical Virology Data analysed with UCINET 6 www.medicalmicrobiology.eu
  17. 17. Ems-Dollart Region
  18. 18. HealthCare Network EDR -Patient transfer 2011 - 5 healthcare clusters - Regional network building Dr. Rocker, Dr. Pulz (NLGA) & Dr. Ciccolini (UMCG)
  19. 19. From TypeNed to RegioType to UMCG Nosocomial Infections  Percentage of nosocomial infections in UMCG  12% for influenza A virus, 19% for influenza B virus  22-24% for rhinovirus and enterovirus 68  Around 50% for norovirus  Consequence is Infection Control  Focusing on patients  Less focusing on visitors  Sequence a select number of target viruses ASAP  Norovirus, rhinovirus Division of Clinical Virology
  20. 20. Division of Clinical Virology
  21. 21. The Facts on Molecular Diagnostics • Molecular diagnostics is an integrated, solid and important part Division of Clinical Virology within our diagnostic laboratory. • Investments over the years have been high, both equipment, reagents and consumables. • Equipment from different diagnostic companies. • Patient diagnostics, treatment and safety is important within our work. A short TAT time has impact on the use of antibiotics. • Limited availability of Point-of-Care (Impact) technologies.
  22. 22. Division ooff CClliinniiccaall VViirroollooggyy
  23. 23. Overview (virology) High throughput Sample in-result out Commercial Blood screening Commercial STD Commercial HPV Medium to low throughput In-house or LDT “Everything” Commercial Limited portfolio No sample in - result out Point-of-Care Point-of-Impact Commercial Short TAT Influenza virus Norovirus Respiratory viruses Sample in - result out Division of Clinical Virology
  24. 24. Alternatives for the LDT (in-house) PCR Point-of-Care/Point-of-Impact (respiratory targets) Cepheid GeneXpert Flu (too insensitive). Detects not enough clinical relevant respiratory targets. BioFire FilmArray Respiratory assay. 1 Sample per instrument. Broad panel. GenMark NexGen Respiratory Panel (Should be as sensitive as previous eSensor technology) Division of Clinical Virology
  25. 25. ‘QA & QC’ within the Microbiology Laboratory Certification Accreditation New method Establish Performance Perform Clinical tests ISO15189:2012 Characterised Quality reagents Verify method Validate Performance Method Equivalence Quality Improvements Report Results Implement method Assay Verification Assay Validation Assay Implementation Method Maintenance Quality Management System EQA (PT) Internal QC Internal QA Division of Clinical Virology
  26. 26. Division of Clinical Virology QCMD proficiency testing Stock dilution series Coronavirus NL63 Influenza A H1pdm09 Influenza H3 Influenza B Parainfluenza virus 1 RSV A RSV B Panels Adenovirus Influenza virus Parainfluenza virus Rhinovirus RSV Compared eSensor technology with our LDT assays Compare FilmArray with our LDT assays
  27. 27. Conclusions FilmArray eSensor Technology • FilmArray RP (Ct <31) is more sensitive than INF and RSV BinaxNOW (Ct < 21 en <24) • Detects 98% of the positive patient samples with Ct values < 31. Missed a rhinovirus positive sample • Specificity of the validated targets is 100%, with an exception for Rhinovirus 98.5% Division of Clinical Virology
  28. 28. Conclusions GenMark Technology • GenMark eSensor Technology (Ct <35-37) is more sensitive than Influenza and RSV BinaxNOW (Ct < 21 en <24). Similar sensitivity compared to LDT. • Initial results also indicate an improved sensitivity compared to BioFire FilmArray. • We have not yet validated all parameters. • A challenge for Proficiency Testing as well as for QCMD as a Proficiency Provider, is how to develop proficiency panels for multiplex system according to the ISO15189:2012 guidelines. Division of Clinical Virology
  29. 29. Performance of FilmArray versus LDT FilmArray RP Influenza A H1 Influenza A H3 Influenza A H1pdm09 Influenza B Human Metapneumovirus RSV Adenovirus Bocavirus Coronavirus HKU1 Coronavirus NL63 Coronavirus 229 E Coronavirus OC43 Rhinovirus/enterovirus Parainfluenza 1 Parainfluenza 2 Parainfluenza 3 Parainfluenza 4 Routine LDT PCR Influenza A Influenza B Human Metapneumovirus RSV Adenovirus Bocavirus Coronavirus NL63 Coronavirus 229 E Coronavirus OC43 Rhinovirus/enterovirus Parainfluenza 1 Parainfluenza 2 Parainfluenza 3 Parainfluenza 4 FilmArray RP (Ct <31-33) is more sensitive than Influenza and RSV BinaxNOW (Ct < 21 en <24). Division of Clinical Virology Influenza A H1 Influenza A H3 Influenza A H1pdm09 Influenza A N1 Influenza A N2 Negative or positive result Turnaround time 1.5 hours after the sample arrived in the laboratory Negative or positive result Turnaround time 1.25 days Influenza A with genotype Turnaround time 2 days
  30. 30. Division of Clinical Virology The Diagnostic Triangle Time to Result TAT Diagnostics Quality LI S
  31. 31. Division of Clinical Virology Dear Dr. Riezebos, FilmArray 2 detected Influenza A, Influenza A/H1 in sample E2013100465
  32. 32. Division of Clinical Virology
  33. 33. Division of Clinical Virology Norovirus II.4.Sydney
  34. 34. Division of Clinical Virology Norovirus II.4.2009
  35. 35. Is this affordable point-of-care? Division ooff CClliinniiccaall VViirroollooggyy IQuum The lab in a tube technology GeneXpert Infinity System Biocartis platform FilmArray, bioMerieux GenMark Dx Luminex Aries
  36. 36. Division of Clinical Virology The € hour concept (comparable with kWhr) • Time-to-result or turn-around-time (TAT) for critical care is important. • Time-to-result for decision making is important. • Start or stop treatment • Isolation of patient or not • Cohorting of patients (e.g. Influenza H1 infected patients in one room) • Combine time-to-result with costs of assay.
  37. 37. Division of Clinical Virology The € hour concept (comparable with kWhr) • Calculate the costs of stay in hospital and/or isolation of a patient • Assay 30 € but TAT is 24 hr: total 720 €hr (Plus 1 extra costs of bed). • Assay 100 € but TAT is 3 hr: total 300 €hr. • Cost –and earning- of bed (estimated between €1700 and €3200/day) • (example critical care at Friday late afternoon). • Calculate the costs for getting a hospital acquired infection. • We have to work more intensively with economists and mathematicians!
  38. 38. Modeling infection and transmission fHA due to delay and background transmission Model based on Rhinovirus data Model predicted impact of infection control (IC) on hospital acquired infections (fHA); the red circle represents UMCG data (74% under IC, 24% fHA).
  39. 39. Model predicted number of hospital acquired cases for five different infection control scenarios Rhinovirus as model Division of Clinical Virology
  40. 40. Nursing department Division of Clinical Virology The Ideal World Total turnaround time: ~3h Patient with respiratory ilness (or, Influenza like Ilness, ILI) Molecular diagnostic test application Sampling and sending to the laboratory Technician; Medical virologist Interpretation of test results Diagnosis ; Positioning; Treatment plan Nurse; Co-assistent Admission; Treatment Turnaround time : ~1 .5h Emergency Department Department of Medical Microbiology Technician Performing a Laboratory test (Clinical virology ) Turnaround time : ~1.5h Physician Increase of 288% in viral respiratoire diagnostics.
  41. 41. Respiratory season 2012-2013 0 20 40 60 Division of Clinical Virology 300 200 100 0 December January February March April Influenza A Influenza B hMPV RSV Adeno Boca Corona Rhino Parainfl ? Neg Infl A Other virus No isolation Geno-type? H1N1 December January February March April Care in cohort H3N2 isolation H1N1H1N1H1N1 H3N2H3N2H3N2 Care in cohort H3N2 H1N1pdm09 NT
  42. 42. The Extended Diagnostic Triangle Division of Clinical Virology Infection Control TAT Cost or €hr Quality Diagnostics Treatment LI S
  43. 43. The AID-Stewardship Portfolio Division of Clinical Virology • The Antibiotic/Antimicrobial Stewardship • The Infection Control Stewardship • The Diagnostic Stewardship • (Giving Antibiotics without Diagnostics should also be financially compensated to the laboratory) (For management, the Financial Stewardship portfolio)
  44. 44. E-health Current focus UMC’s Cure (and care) Patient oriented Based on Apple HealthKit Division of Clinical Virology (Near) Future Prevention Society oriented
  45. 45. The AID-Stewardship Portfolio • The Antibiotic/Antimicrobial Stewardship • The Infection Control Stewardship • The Diagnostic Stewardship Determine and communicate the value of molecular diagnostics! – Take the lead (use of POC/POI; E-health) – Cost effectiveness – Awareness (communicate) Division of Clinical Virology
  46. 46. Cost Effectiveness of AID-Stewardship Cost Benefit Division of Clinical Virology
  47. 47. Burden of infectious diseases • Nosocomial infections (HAI) • and Antibiotic resistance • (MRSA, VRE, ESBL et al.) • Pneumococci • HIV/AIDS • Viral Hepatitis • Pandemic flu • Diarrhea (v.a. Norovirus, Camplylobacter) • Emerging infections / Zoonosen (z.B. EHEC, MERS, H5N1) CDC-report 2005 ECDC-report 2009
  48. 48. The silver generation
  49. 49. Ageing Society
  50. 50. Division of Clinical Virology Improved Infectious Diseases Diagnostics • CID 2013:57 (Suppl 3) • S139
  51. 51. Division of Clinical Virology Who detects MERS in POC?
  52. 52. Division of Clinical Virology
  53. 53. Division of Clinical Virology
  54. 54. Division of Clinical Virology
  55. 55. “The only limitation is your imagination”.
  56. 56. Division of Clinical Virology Take home message • Increase in availability of Point-of-Care/Impact technologies. • Important is good sensitivity, however, less of a problem within the season. eSensor technology very promising. • Not all POC/POI assays detect all relevant targets. • Costs versus benefits. The €hr concept. • Consider the AID stewardship concept. • Value of a negative result is also very important!
  57. 57. Network-based Infection Control
  58. 58. Awareness Division of Clinical Virology
  59. 59. Division of Clinical Virology More info: www.FlowG.nl www.MedicalMicrobiology.eu
  60. 60. Division of Clinical Virology

Editor's Notes

  • 3 QCMD panels
    INFHT11H1N1pdm09 H1 en H3N2 tot Ct &amp;lt;32H7N7 kon niet getypeerd worden
    INFRNA11Core Panel1 Eq Ct 33 &amp;gt;Ct 33 m.u.v InfB ct 36
    RSV11RSV A en BCt &amp;lt;36geen onderscheid tussEN RSV A en B
  • De FilmArray RP detecteert gevoeliger dan de influenza en RSV BinaxNOW sneltesten. Deze testen detecteren positieve monsters respectievelijk bij Ct ≤ 21 en ≤ 24 (bijlage 5 en 6). De FilmArray RP is een kwalitatieve test die een positief of negatief resultaat geeft. De FilmArray RP detecteert 98% van de patiëntenmaterialen met Ct ≤ 31 en is daarmee minder gevoelig dan de in-house PCR. De adenovirus detectie is hierin niet meegenomen. Slechts 20% van het geteste positieve adenovirus patiëntenmateriaal werd positief bevonden in de FilmArray RP. Loeffelholz, M.J. et al 2011 heeft een sensitiviteit van de FilmArray RP voor het adenovirus gemeten van 54,5% met een panel van 192 samples (bijlage 7).
    De specificiteit van de gevalideerde targets is 100%, uitgezonderd het rhinovirus (98,5%). Loeffelholz, M.J. et al 2011 heeft een specificiteit van 85,1% van de FilmArray RP voor het rhinovirus gemeten met een panel van 192 samples (1). Rand, K.H., et al 2011 heeft echter een specificiteit van 100% van de FilmArray RP voor het rhinovirus gemeten met een panel van 200 samples (bijlage 8).
  • De FilmArray RP detecteert gevoeliger dan de influenza en RSV BinaxNOW sneltesten. Deze testen detecteren positieve monsters respectievelijk bij Ct ≤ 21 en ≤ 24 (bijlage 5 en 6). De FilmArray RP is een kwalitatieve test die een positief of negatief resultaat geeft. De FilmArray RP detecteert 98% van de patiëntenmaterialen met Ct ≤ 31 en is daarmee minder gevoelig dan de in-house PCR. De adenovirus detectie is hierin niet meegenomen. Slechts 20% van het geteste positieve adenovirus patiëntenmateriaal werd positief bevonden in de FilmArray RP. Loeffelholz, M.J. et al 2011 heeft een sensitiviteit van de FilmArray RP voor het adenovirus gemeten van 54,5% met een panel van 192 samples (bijlage 7).
    De specificiteit van de gevalideerde targets is 100%, uitgezonderd het rhinovirus (98,5%). Loeffelholz, M.J. et al 2011 heeft een specificiteit van 85,1% van de FilmArray RP voor het rhinovirus gemeten met een panel van 192 samples (1). Rand, K.H., et al 2011 heeft echter een specificiteit van 100% van de FilmArray RP voor het rhinovirus gemeten met een panel van 200 samples (bijlage 8).
  • Model predicted impact of infection control (IC) on hospital acquired infections (fHA); the red circle represents UMCG data (74% under IC, 24% fHA). No infection control in place doubles the amount of hospital acquired cases. If all infected patients are under infection control, hospital acquired infections can occur due to delay in implementation of IC measures and background transmission.
  • Figure 4. Model predicted number of hospital acquired cases for five different infection control scenarios as depicted in the method section of the paper (blue boxes). The contribution of patient-to-patient transmission (red boxes) and background transmission (green boxes) for the given number of hospital acquired cases is also given.
    No IC = no baseline infection control policies + no HRV specific measures
    Early = baseline infection control policies + no HRV specific measures
    Late = baseline infection control policies + HRV specific measures limited to specific wards and only when Ct value&amp;lt; 30
    All = baseline infection control policies + HRV specific measures for all HRV positive patients
  • Als uitstapje naar toekomstig denken, van cure en care naar prevention, overigens gestimuleerd door zorgverzekeraars.
  • POCT Point of Care tests POIT point of impact tests
  • Concrete cijfers of effecten van een nw beleid nog niet altijd bekend, maar prototyping (in de vorm van een business case oid) is van belang om ‘ergens’ te komen.

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