1. Denise Evans, Mhairi Maskew, Lynne McNamara, Patrick MacPhail, Christopher Mathews, Ian Sanne, Matthew Fox CD4 criteria improves the sensitivity of a clinical algorithm developed to identify viral failure in HIV-positive patients on first-line antiretroviral therapy This research has been supported by the President's Emergency Plan for AIDS Relief (PEPFAR) through South Africa Mission of the US Agency for International Development (USAID) under the terms of grant number 674-A-00-08-00007-00

2. Background Routine viral load monitoring is neither affordable nor available in most resource-limited settings –Previous attempts to identify low-cost surrogate markers of virologic failure have shown conflicting results (Lynen et al., 2009; Robbins et al., 2010; Meya et al., Johannessen et al., 2008; Lawn et al., 2006) –Need to develop simpler, cheaper monitoring strategies that can be administered by minimally trained clinic personnel Used data from a large South African clinic to try to develop an algorithm using accessible, inexpensive, routinely collected markers to identify virological failure

3. Human Research Ethics Committee of the University of the Witwatersrand (HREC M060623/M110140/M10418) Methods Study site and subjects –Themba Lethu Clinic, Johannesburg, South Africa, >20,000 patients on ART –Included non-pregnant, HIV+ ART naïve adults (≥18) –Initiated on public sector first-line regimen, April 2004 – February 2010 –Limited to those with ≥2 viral load and >6 months on ART Study data –Included inexpensive, routinely collected baseline and follow-up markers e.g. BMI, blood pressure, WHO staging, hemoglobin, albumin, mean cell volume, new conditions, CD4 count etc. WHO failure criteria: WHO stage III/IV, CD4 < baseline or < 100 cells/mm 3 –Matched virologic failures to comparison group (1:3) on person-time Outcomes –Virological failure: 2 HIV-RNA ≥400 copies/ml after suppression

4. Cox PH model to identify important predictors of viral failure to create risk score –Univariate p < 0.1 included (age and gender) –Risk score calculated by assigning rounded aHR for each predictor* E.g. if low BMI has aHR 1.75 = +2 –For each subject, total score is sum of risk scores –Low risk (0-4), Medium/High risk (≥ 4)** Assessed diagnostic accuracy of risk groups with virologic failure as gold standard –Se, Sp, PPV, NPV –Model with and without CD4 criteria Themba Lethu Clinic, Johannesburg Statistical analysis *Spiegelhalter and Knill-Jones method; Berkley et al., 2003; Lynen et al., 2009 **Robbins et al., 2010

5. Baseline characteristicsVirologic failure (n = 919) No virologic failure (n = 2756) Male342 (39.7%)1095 (39.0%) Age [Median (IQR)]34.7 (30.2 – 41.4)36.2 (31.1 – 42.8) Body mass index (kg/m 2 )21.4 (18.9 – 24.6)21.3 (18.8 – 24.3) <18.5 kg/m 2 177/856 (20.7%) 544/2515 (21.6%) CD4 cell count (cells/mm 3 )65 (23 – 130)89 (34 – 154) CD4 <100 cells/mm 3 548/831 (65.9%) 1374/2530 (54.3%) Hemoglobin (g/dl)11.4 (10.0 – 12.9)11.5 (10.0 – 13.0) Viral load >100 000 copies/ml98/194 (50.5%)280/687 (40.8%) WHO stage III/IV385/830 (46.4%)1030/2493(41.3%) First regimen d4T-3TC-EFV 778 (84.7%)2408 (87.4%) d4T-3TC -NVP94 (10.2%)185 (6.7%) Other47 (5.1%)163 (5.9%) Tuberculosis at ART initiation171 (18.6%)438 (15.9%) Time on ART (months) [Median (IQR)]26.4 (15.4 – 42.2)26.2 (15.4 – 42.1) Matched Results (n=3675)

6. Baseline characteristicsVirologic failure (n = 919) No virologic failure (n = 2756) Male342 (39.7%)1095 (39.0%) Age [Median (IQR)]34.7 (30.2 – 41.4)36.2 (31.1 – 42.8) Body mass index (kg/m 2 )21.4 (18.9 – 24.6)21.3 (18.8 – 24.3) <18.5 kg/m 2 177/856 (20.7%) 544/2515 (21.6%) CD4 cell count (cells/mm 3 )65 (23 – 130)89 (34 – 154) CD4 <100 cells/mm 3 548/831 (65.9%) 1374/2530 (54.3%) Hemoglobin (g/dl)11.4 (10.0 – 12.9)11.5 (10.0 – 13.0) Viral load >100 000 copies/ml98/194 (50.5%)280/687 (40.8%) WHO stage III/IV385/830 (46.4%)1030/2493(41.3%) First regimen d4T-3TC-EFV 778 (84.7%)2408 (87.4%) d4T-3TC -NVP94 (10.2%)185 (6.7%) Other47 (5.1%)163 (5.9%) Tuberculosis at ART initiation171 (18.6%)438 (15.9%) Time on ART (months) [Median (IQR)]26.4 (15.4 – 42.2)26.2 (15.4 – 42.1) Matched Results (n=3675)

7. Risk factorCrude HR 95% CIAdjusted HR 95% CIScore Gender - Male0.97 (0.85 – 1.11)0.95 (0.77 – 1.15)+ 0 Age > 40 years1.16 (1.03 – 1.33)1.30 (1.06 – 1.60)+ 1 Albumin <25 g/l1.20 (1.01 – 1.42)1.15 (0.95 – 1.45)+ 1 CD4 cell count <100 cells/mm 3 1.35 (1.17 – 1.56)1.20 (1.09 – 1.48)+ 1 WHO stage III/IV1.16 (1.01 – 1.33)1.26 (1.02 – 1.57)+ 1 Baseline Multivariate risks scores (HRs)

8. Risk factorCrude HR 95% CIAdjusted HR 95% CIScore Gender - Male0.97 (0.85 – 1.11)0.95 (0.77 – 1.15)+ 0 Age > 40 years1.16 (1.03 – 1.33)1.30 (1.06 – 1.60)+ 1 Albumin <25 g/l1.20 (1.01 – 1.42)1.15 (0.95 – 1.45)+ 1 CD4 cell count <100 cells/mm 3 1.35 (1.17 – 1.56)1.20 (1.09 – 1.48)+ 1 WHO stage III/IV1.16 (1.01 – 1.33)1.26 (1.02 – 1.57)+ 1 New condition/diagnosis1.34 (1.16 – 1.55)1.14 (0.97 – 2.07)+ 1 Worsening of WHO stage1.24 (1.04 – 1.48)1.17 (0.98 – 1.41)+ 1 Mean cell volume (MCV) <100 fl1.29 (1.12 – 1.49)1.23 (1.02 – 1.49)+ 1 CD4 cell count <200 cells/mm 3 1.37 (1.19 – 1.59)1.28 (1.02 – 1.60)+ 1 Hemoglobin drop >20%1.60 (1.05 – 2.45)1.38 (0.97 – 2.77)+ 1 WHO stage III/IV1.52 (1.08 – 2.13)1.58 (1.03 – 2.46)+ 2 Baseline 6-12 months before failure Multivariate risks scores (HRs)

9. Virologic failure by risk score Risk category Virological failure No Virologic Failure ≥ 4 (51.4%)5251364 < 4 (48.6%)3941392 CriteriaSeSpPPVNPV Clinical & immunological WHO criteria* √ 25.2 (22.8 – 27.8) 70.6 (69.8 – 71.5) 22.3 (20.1 – 24.6) 73.9 (73.1 – 74.8) *Lynen et al., 2009; Meya et al., 2009 √ WHO stage III/IV, CD4 < baseline or CD4 < 100cells/mm 3

10. Virologic failure by risk score CriteriaSeSpPPVNPV Clinical & immunological WHO criteria* √ 25.2 (22.8 – 27.8) 70.6 (69.8 – 71.5) 22.3 (20.1 – 24.6) 73.9 (73.1 – 74.8) WHO stage III/IV* 20.9 (18.4 – 23.6) 73.7 (72.8 – 74.6) 21.7 (19.1 – 24.4) 72.8 (72.0 – 73.7) *Lynen et al., 2009; Meya et al., 2009 √ WHO stage III/IV, CD4 < baseline or CD4 < 100cells/mm 3 Risk category Virological failure No Virologic Failure ≥ 4 (51.4%)5251364 < 4 (48.6%)3941392

11. Virologic failure by risk score CriteriaSeSpPPVNPV Clinical & immunological WHO criteria* √ 25.2 (22.8 – 27.8) 70.6 (69.8 – 71.5) 22.3 (20.1 – 24.6) 73.9 (73.1 – 74.8) WHO stage III/IV* 20.9 (18.4 – 23.6) 73.7 (72.8 – 74.6) 21.7 (19.1 – 24.4) 72.8 (72.0 – 73.7) Score without CD4 criteria (≥4 v. <4) 38.0 (34.8 – 41.2) 65.4 (63.6 – 67.2) 26.8 (24.4 – 29.3) 76.0 (74.2 – 77.7) *Lynen et al., 2009; Meya et al., 2009 √ WHO stage III/IV, CD4 < baseline or CD4 < 100cells/mm 3 Risk category Virological failure No Virologic Failure ≥ 4 (51.4%)5251364 < 4 (48.6%)3941392

12. Virologic failure by risk score CriteriaSeSpPPVNPV Clinical & immunological WHO criteria* √ 25.2 (22.8 – 27.8) 70.6 (69.8 – 71.5) 22.3 (20.1 – 24.6) 73.9 (73.1 – 74.8) WHO stage III/IV* 20.9 (18.4 – 23.6) 73.7 (72.8 – 74.6) 21.7 (19.1 – 24.4) 72.8 (72.0 – 73.7) Score without CD4 criteria (≥4 v. <4) 38.0 (34.8 – 41.2) 65.4 (63.6 – 67.2) 26.8 (24.4 – 29.3) 76.0 (74.2 – 77.7) Score with CD4 criteria (≥4 v. <4) 57.1 (53.9 – 60.4) 50.5 (48.6 – 52.4) 27.8 (25.8 – 29.9) 77.9 (75.9– 79.8) *Lynen et al., 2009; Meya et al., 2009 √ WHO stage III/IV, CD4 < baseline or CD4 < 100cells/mm 3 Risk category Virological failure No Virologic Failure ≥ 4 (51.4%)5251364 < 4 (48.6%)3941392

13. Conclusions Average sensitivity and poor specificity of virologic failure Similar to previous scoring systems –Total score without CD4 criteria improved Se over WHO criteria or WHO stage III/IV –CD4 criteria further improves Sensitivity Limitations –Missing values (20-25%) –Data from a single site (validate) –Could only evaluate what actually happened, not whether method could predict future events Looking at further refinements of the model Could be useful to screen for risk of virologic failure –Absence of routine viral load testing, targeted laboratory testing

14. Acknowledgements NIH and USAID HE 2 RO/CHRU – WITS Health Consortium Hazel Molefe Daphne Radebe Bontle Mahlatsi Desiree Louw Keagile Komane Frank Phakathi University of California – San Diego Right to Care Patients and staff at Themba Lethu Clinic – Helen Joseph Hospital This research has been supported by the President's Emergency Plan for AIDS Relief (PEPFAR) through South Africa Mission of the US Agency for International Development (USAID) under the terms of grant number 674-A-00-08-00007-00

15. % n=3675 SeSpPPVNPVOR Male gender100%37.2 (34.5-40.0)60.3 (59.4-61.2)23.8 (22.0-25.6)74.2 (73.1-75.4)0.90 (0.77-1.05) Age > 40 years100%70.2 (67.5-72.8)34.8 (33.9-35.7)26.4 (25.4-27.4)77.8 (75.8-79.7)1.26 (1.07-1.48) CD4 cell count <100 cells/mm 3 91.5%65.9 (63.0-68.8)45.7 (44.7-46.6)28.5 (27.2-29.7)80.3 (78.6-82.0)1.63 (1.38-1.93) WHO stage III/IV 90.4%46.4 (43.4-49.4)58.7 (57.7-59.7)27.2 (25.5-29.0)76.7 (75.4-78.0)1.23 (1.05-1.44) Albumin <25 g/l 87.4%21.7 (19.2-24.3)80.6 (79.8-81.4)26.6 (23.6-29.8)76.0 (75.2-76.8)1.15 (0.94-1.41) Hemoglobin drop >20% 77.2%2.7 (1.8-3.6)98.2 (97.9-98.6)37.9 (25.9-51.5)71.2 (70.9-71.5)1.51 (0.85-2.66) BMI drop >10% 83.4%2.1 (1.3-3.1)98.3 (98.0-98.7)30.9 (19.6-44.8)73.9 (73.7-74.2)1.27 (0.68-2.33) Mean cell volume (MCV) <100 fl 72.4%50.2 (47.2-53.2)52.3 (51.1-53.6)30.2 (28.4-32.0)71.9 (70.2-73.6)1.11 (0.93-1.31 CD4 cell count <200 cells/mm 3 76.4%34.7 (31.9-37.6)58.2 (57.1-59.4)25.6 (23.5-27.7)68.3 (67.0-69.7)1.35 (1.14-1.61) Missed medical visit >7days 90.4%8.3 (6.8-10.0)93.5 (93.0-94.1)31.0 (25.4-37.2)74.4 (74.0-74.9)1.31 (0.97-1.76) Worsening of WHO stage 77.3%4.7 (3.5-6.2)95.4 (94.9-95.9)26.5 (19.5-34.8)74.1 (73.7-74.5)1.03 (0.68-1.56) New condition/diagnosis 100%26.6 (24.1-29.1)71.4 (70.6-72.3)23.7 (21.5-26.0)74.5 (73.6-75.4)0.90 (0.76-1.07) Sub-optimal adherence 54.2%11.8 (9.4-14.5)88.3 (87.5-89.2)25.2 (20.1-30.9)75.0 (74.3-75.7)1.01 (0.73-1.40) Regimen change/substitution 100%24.0 (21.7-26.5)82.1 (81.3-82.9)30.9 (27.9-34.0)76.4 (75.7-77.2)1.45 (1.21-1.74) Missed ARV visit current/previous 85.3%6.9 (5.4-8.5)93.3 (92.8-93.8)26.4 (20.9-32.7)74.0 (73.6-74.4)1.02 (0.73-1.42) WHO stage III/IV 81.2%20.9 (18.4-23.6)73.7 (72.8-74.6)21.7 (19.1-24.4)72.8 (72.0-73.7)0.74 (0.61-0.91) Individual Se/Sp of variables

16. ReferenceSeSpPPVNPV Lynen et al., JAIDS 2009 (score 4) 12.6 (6.8 – 22.3) 99.7 (99.3 – 99.9) 68.8 (41.7 – 87.1) 95.7 (94.4 – 96.8) Meya et al., JIAS 2009 (CD4, VL, missed visits) 67.0 (63.0 – 71.0) 82.0 (79.0 – 85.0) 24.0 (20.0 – 28.0) 97.0 (96.0 – 99.0) Robbins et al., CID 2010 Derivation Validation 30.6% 28.6% 94.6% 92.3% Mee et al., AIDS 2008 CD4 criteria Clinical criteria 21.2% 15.2% 95.8% 88.1% 36.8% 12.8% Badhi et al., BMC 2008 CD4 criteria 53.0%63.6%10.9% Se/Sp of algorithms in literature

17. Se/Sp of each score Criteria (Med/High v. Low) SeSpPPVNPV ≥ 1 vs. < 1 98.8 (97.9 – 99.4) 2.6 (2.0 – 3.3) 25.3 (23.9 – 26.7) 86.7 (77.5 – 93.2) ≥ 2 vs. < 291.1 (89.0 – 92.8) 14.8 (13.5 – 16.2) 26.3 (24.8 – 27.8) 83.3 (79.7 – 86.5) ≥ 3 vs. < 3 75.7 (72.8 – 78.5) 32.9 (31.1 – 34.7) 27.3 (25.6 – 29.1) 80.2 (77.8 – 82.5) ≥ 4 vs. < 4 57.1 (53.9 – 60.4) 50.5 (48.6 – 52.4) 27.8 (25.8 – 29.9) 77.9 (75.9– 79.8) ≥ 5 vs. < 5 37.3 (34.2 – 40.5) 66.3 (64.5 – 68.1) 27.0 (24.5 – 29.5) 76.0 (73.1 – 74.8) ≥ 6 vs. < 6 23.2 (20.5 – 26.0) 78.4 (76.8 – 79.9) 26.3 (23.3 – 29.5) 75.4 (73.7 – 76.9) ≥ 7 vs. < 7 12.9 (10.8 – 15.3) 87.8 (86.5 – 89.0) 26.1 (22.1 – 30.4) 75.1 (73.6 – 76.6)

18. Se/Sp of each score excluding variables with < 80% of the data Criteria (Med/High v. Low) SeSpPPVNPV ≥ 1 vs. < 1 97.3 (96.0 – 98.2) 4.5 (3.7 – 5.3) 25.3 (23.9 – 26.8) 83.1 (76.1 – 88.8) ≥ 2 vs. < 284.3 (81.8 – 86.6) 21.9 (20.4 – 23.5) 26.5 (24.9 – 28.1) 80.7 (77.7 – 83.5) ≥ 3 vs. < 3 64.1 (60.9 – 67.2) 44.3 (42.5 – 46.2) 27.7 (25.8 – 29.7) 78.7 (76.6 – 80.7) ≥ 4 vs. < 4 41.3 (38.1 – 44.6) 62.0 (60.1 – 63.8) 26.6 (24.3 – 29.0) 76.0 (74.2 – 77.8) ≥ 5 vs. < 5 22.3 (19.7 – 25.1) 77.0 (75.4 – 78.6) 24.5 (21.6 – 27.5) 74.8 (73.2 – 76.4) ≥ 6 vs. < 6 11.0 (9.0 – 13.2) 87.9 (86.6 – 89.1) 23.2 (19.3 – 27.5) 74.8 (73.2 – 76.2) ≥ 7 vs. < 7 4.5 (3.2 – 6.0) 94.7 (93.8 – 95.5) 21.9 (16.2 – 28.5) 74.8 (73.4 – 76.3)

19. Se/Sp of each score – Lynen et al., 2009

20. Se/Sp of each score – Meya et al., 2009

21. Se/Sp of each score – Robbins et al., 2010