CRP as a potential TB triage or screening test: considerations for modelers

Transcription

1 CRP as a potential TB triage or screening test: considerations for modelers TB MAC Diagnostics Meeting September 14, 2018 Christina Yoon, MD, MAS, MPH Assistant Professor, UCSF

2 Triage vs. Screening tests Triage test used to reduce the proportion of individuals with suspected disease requiring confirmatory TB testing Can be used in both PCF and ACF (as a 2 screening test) Screening test used to identify individuals undergoing screening who require confirmatory TB testing (ACF) Good triage tests may be good screening tests, Caution: screening tests sometimes described as a triage and vice versa tests Same goal: limit (costly) confirmatory TB testing to a smaller subset of high-risk individuals Same desired test characteristics: low-cost, simple, sensitivity prioritized over specificity

3 Who should be screened for active TB? Recommendations 1-3 Should be done: Household contacts PLHIV Silica-exposed workers Recommendations 4-7 Should be considered: Prisons Untreated fibrotic CXR lesions Healthcare settings (prevalence >100/100,000) Communities (prevalence 1%)

4 How to screen? Current options for TB screening: 1. Symptoms 2. CXR TPP for a good TB screening (and triage) test: 1. Test characteristics (minimum): Sensitivity 90%; Specificity 70% 2. Operational characteristics: Low-cost (<$2 per test), rapid, nonsputum-based, simple

5 C-reactive protein (CRP) Inflammatory marker; levels rise (>10 mg/l) with active TB Prior studies (patients with presumptive TB): High (>90%) sensitivity, low (<50%) specificity (how would it perform in a healthier pop?) Available as a simple, low-cost, and rapid point-ofcare (POC) test + = Results in 3 min Capillary blood $2 per assay

6 CRP studies 1. Systematic review/meta-analysis (SR/MA) to evaluate the accuracy of CRP for identifying active pulmonary TB (IJTLD 2017) 2. Prospective evaluation of CRP in PLHIV a. Diagnostic accuracy of CRP-based TB screening (Lancet ID 2017) b. Yield and efficiency of CRP-based ICF algorithms (AJRCCM 2018)

7 SR/MA Objective: To assess the diagnostic accuracy of CRP for active PTB, by clinical setting (clinic vs. hospital) Methods: Population: Patients being screened for or undergoing evaluation for active PTB Intervention/ Index test: CRP (cut-point 10 mg/l) Outcome: Diagnostic accuracy for pulmonary TB Reference standard: 1 positive sputum culture (solid or liquid) result

8 Outpatient studies (5) Study Country Setting Lawn, 2013 Yoon, 2014 Drain, 2014 Wilson, 2006 Wilson, 2011 S. Africa Uganda S. Africa S. Africa S. Africa ARTinitiation ARTinitiation Smearnegative Smearnegative Smearnegative N (% HIV) 496 (100) 271 (100) TB n (%) CRP assay Culture 81 (16) Lab-based MGIT 27 (10) POC MGIT 76 (100) 30 (39) POC 74 (100) 59 (80) Lab-based LJ and MGIT LJ and MGIT 204 (44) 116 (57) Lab-based MGIT Adapted from Yoon et al, IJTLD 2017

9 Outpatient studies: diagnostic accuracy & heterogeneity Pooled sensitivity: 93% (95% CI: 88-98) I 2 = 53%, p=0.07 Pooled specificity: 60% (95% CI: 44-75) I 2 = 93%, p<0.001 Yoon et al, IJTLD 2017

10 Sub-group analyses Outpatient 5 # of studies Pooled sensitivity Pooled specificity 93% (95% CI: 88-98) 60% (95% CI: 44-75) Screening 2 Range: 81-85% Range: 58-81% Diagnosisseeking HIV-positive 5 3 Range: 96-97% Range: 33-73% 93% (95% CI: 88-98) 61% (95% CI: 45-77) HIV-negative 1 100% 85% Inpatient 5 Pooled estimates calculated if 4 studies. 78% (95% CI: 58-90) 21% (95% CI: 6-52) Adapted from Yoon et al, IJTLD 2017

11 Conclusion CRP shows promise as a potential TB screening and/or triage test

12 CRP studies 1. Systematic review/meta-analysis (SR/MA) to evaluate the accuracy of CRP for identifying active pulmonary TB (IJTLD 2017) 2. Prospective evaluation of CRP in PLHIV a. Diagnostic accuracy of CRP-based TB screening (Lancet ID 2017) b. Yield and efficiency of CRP-based ICF algorithms (AJRCCM 2018)

13 Methods Participants: Consecutive HIV-infected adults with CD4 350 initiating ART from 2 HIV clinics in Kampala, Uganda Procedures: TB screening: symptom screen assessment, POC CRP testing (cut-point 10 mg/l) TB evaluation: Xpert MTB/RIF (x1) and liquid culture (x2) Analysis: sensitivity, specificity in reference to 1) culture and 2) Xpert MTB/RIF

14 Patient flow diagram Patients enrolled N = 1246 N=69, incomplete results and/ or contaminated cultures Included in analysis N = 1177 No TB N = 1014 TB N = % TB prevalence N=84, Xpert-positive N=79, culture-positive only

15 Demographics and clinical characteristics Characteristic, N (%) Total (N=1177) Age (years) 33 (27-40) Female 626 (53%) CD4 count (cells/µl) 165 (75-271) WHO symptom screen positive 1025 (87%) Elevated POC CRP ( 10 mg/l) 428 (36%) POC CRP (mg/l) 4.6 ( ) Yoon et al, Lancet ID 2017

16 Diagnostic accuracy of POC CRP (in ref to culture) & alternate cut-points Sensitivity, % (95% CI) Specificity, % (95% CI) PPV, % (95% CI) NPV, % (95% CI) 3 mg/l 93 9% ( ) 46 5% ( ) 22 0% ( ) 97 9% ( ) 4 mg/l 93 3% ( ) 53 2% ( ) 24 2% ( ) 98 0% ( ) 7 mg/l 91 4% ( ) 67 6% ( ) 5 mg/l 92 6% ( ) 59 7% ( ) 27 0% ( ) 98 1% ( ) 6 mg/l 92 0% ( ) 63 9% ( ) 29 1% ( ) 98 0% ( ) 8 mg/l 90 2% ( ) 69 6% ( ) 7 mg/l 91 4% ( ) 67 6% ( ) 31 2% ( ) 98 0% ( ) 8 mg/l 90 2% ( ) 69 6% ( ) 32 3% ( ) 97 8% ( ) 9 mg/l 89 6% ( ) 71 5% ( ) 9 mg/l 89 6% ( ) 71 5% ( ) 33 6% ( ) 97 7% ( ) 10 mg/l 89 0% ( ) 72 1% ( ) 10 mg/l 89 0% ( ) 72 1% ( ) 33 9% ( ) 97 6% ( ) 11 mg/l 87 1% ( ) 74 6% ( ) 35 5% ( ) 97 3% ( ) 12 mg/l 85 3% ( ) 75 3% ( ) 35 7% ( ) 97 0% ( ) PPV=positive predictive value. NPV=negative predictive value. Table 3: Effect of varying point-of-care C-reactive protein threshold on diagnostic accuracy Yoon et al, Lancet ID 2017

17 Sensitivity, stratified by CD4 strata POC CRP WHO symptom screen Sensitivity (%) In reference to culture ( 89%) In reference to culture 120% 110% 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% p=0.65 for trend p= for difference in sensitivity < CD4 cell-count (cells/ul) PO WH 120% 110% 100% m screen 90% 80% Sensitivity (%) In reference to Xpert to Xpert ( 94%) p=0.56 for trend 70% 60% 50% 40% 30% 20% 10% 0% < CD4 cell-count (cells/ul) POC CR WHO sy Yoon et al, Lancet ID 2017

18 Specificity, stratified by CD4 strata Specificity (%) 120% 110% 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% p=0.73 for trend p< for difference in specificity p<0.001 for trend < CD cell-count (cells/ul) POC CRP POC CRP WHO symptom screen WHO symptom screen Yoon et al, Lancet ID 2017

19 Conclusion 1 POC CRP meets the minimum TPP for a TB screening test among PLHIV with CD4 350 initiating ART POC CRP-based TB screening could improve ICF efficiency and scale-up of TB preventive therapy

20 Diagnostic and incremental ICF yield ICF algorithm Dx yield (# and %, 95% CI) TB cases detected WHO symptom screen + Xpert 119 (59%, 52-65) # add l TB cases detected Incremental yield % add l TB cases detected (95% CI) # false pos REF REF 7 POC CRP ( 8 mg/l) +... Xpert 114 (56%, 49-63) -5-2% (-5 to +1) 4 Xpert + culture 157 (78%, 71-83) % (+12 to +26) 4 Adapted from Yoon et al, AJRCCM 2018

21 Number of confirmatory tests used and NNT to detect 1 case of active TB ICF algorithm (N=1245) # of confirmatory tests used NNT to detect 1 TB case Xpert Culture Xpert Culture WHO symptom screen + Xpert POC CRP ( 8 mg/l) +... Xpert Xpert + culture Adapted from Yoon et al, AJRCCM 2018

22 Individual test costs, ICF test costs, and costs per TB case detected ICF algorithm Individual test costs (USD) POC CRP ($2) Xpert ($11) Culture ($17) ICF test costs Costs per TB case detected WHO symptom screen + Xpert -- $12, $12,000 $102 POC CRP ( 8 mg/l) +... Xpert $2,490 $5, $7,968 $70 Xpert + culture $2,490 $5,478 $6,069 $14,037 $89 Adapted from Yoon et al, AJRCCM 2018

23 Conclusion 2 Without compromising yield, POC CRP could: 1. Improve ICF efficiency 2. Reduce ICF test costs 3. Improve scale-up of TB preventive therapy Costs saved from using POC CRP-based ICF, could be re-allocated to culture to substantially improve ICF yield

24 Considerations for modelers Diagnostic accuracy of CRP (and any test) depends on key POPULATION characteristics: 1. Clinical TB disease severity (sensitivity) Ex: clinic vs. community; PCF vs. ACF 2. Prevalence of TB mimickers (specificity) Ex: CD4 strata; ART status 3. Degree of prior TB testing (sensitivity) Ex: serial screening

25 Considerations for modelers (con t) Modeling the impact of screening/triage tests should also include consideration of: 1. Frequency of testing One-off testing (PCF) vs. serial screening (PLHIV) 2. How test results are used Case detection +/- selection of patients for preventive therapy 3. How the test is used with other tests Accuracy and cost of up- and down-stream tests 4. Different rates of implementation

26 Acknowledgements UCSF Adithya Cattamanchi 1, 2 Laurence Huang 1 Sweta Patel 2 I. Elaine Allen 2 Johns Hopkins University Derek Armstrong 1 David Dowdy 1 Lelia Chaisson 2 Yale University 1 J. Luke Davis UW 2 Paul Drain Makerere University 1 Fred Semitala Moses Kamya Lucy Asege Sandra Mwebe Jane Katende Martha Nakaye Alfred Andama Elly Atuhumuza University of KwaZulu-Natal 2 Doug Wilson 1 Prospective studies; 2 SR/MA Funding: NIAID; CFAR; UCSF Nina Ireland Program in Lung Health